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| 2025 | 3D StreetUnveiler with Semantic-aware 2DGS - a simple baseline. Jingwei Xu, Yikai Wang, Yiqun Zhao, Yanwei Fu, Shenghua Gao |
| 2025 | 3D Vision-Language Gaussian Splatting. Qucheng Peng, Benjamin Planche, Zhongpai Gao, Meng Zheng, Anwesa Choudhuri, Terrence Chen, Chen Chen, Ziyan Wu |
| 2025 | 3D-AffordanceLLM: Harnessing Large Language Models for Open-Vocabulary Affordance Detection in 3D Worlds. Hengshuo Chu, Xiang Deng, Qi Lv, Xiaoyang Chen, Yinchuan Li, Jianye Hao, Liqiang Nie |
| 2025 | 3D-MolT5: Leveraging Discrete Structural Information for Molecule-Text Modeling. Qizhi Pei, Rui Yan, Kaiyuan Gao, Jinhua Zhu, Lijun Wu |
| 2025 | 3D-Properties: Identifying Challenges in DPO and Charting a Path Forward. Yuzi Yan, Yibo Miao, Jialian Li, Yipin Zhang, Jian Xie, Zhijie Deng, Dong Yan |
| 2025 | 3D-Spatial Multimodal Memory. Xueyan Zou, Yuchen Song, Ri-Zhao Qiu, Xuanbin Peng, Jianglong Ye, Sifei Liu, Xiaolong Wang |
| 2025 | 3DGS-Drag: Dragging Gaussians for Intuitive Point-Based 3D Editing. Jiahua Dong, Yu-Xiong Wang |
| 2025 | 3DIS: Depth-Driven Decoupled Image Synthesis for Universal Multi-Instance Generation. Dewei Zhou, Ji Xie, Zongxin Yang, Yi Yang |
| 2025 | 3DMolFormer: A Dual-channel Framework for Structure-based Drug Discovery. Xiuyuan Hu, Guoqing Liu, Can Chen, Yang Zhao, Hao Zhang, Xue Liu |
| 2025 | 3DTrajMaster: Mastering 3D Trajectory for Multi-Entity Motion in Video Generation. Xiao Fu, Xian Liu, Xintao Wang, Sida Peng, Menghan Xia, Xiaoyu Shi, Ziyang Yuan, Pengfei Wan, Di Zhang, Dahua Lin |
| 2025 | 3DitScene: Editing Any Scene via Language-guided Disentangled Gaussian Splatting. Qihang Zhang, Yinghao Xu, Chaoyang Wang, Hsin-Ying Lee, Gordon Wetzstein, Bolei Zhou, Ceyuan Yang |
| 2025 | 4K4DGen: Panoramic 4D Generation at 4K Resolution. Renjie Li, Panwang Pan, Bangbang Yang, Dejia Xu, Shijie Zhou, Xuanyang Zhang, Zeming Li, Achuta Kadambi, Zhangyang Wang, Zhengzhong Tu, Zhiwen Fan |
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| 2025 | 6DGS: Enhanced Direction-Aware Gaussian Splatting for Volumetric Rendering. Zhongpai Gao, Benjamin Planche, Meng Zheng, Anwesa Choudhuri, Terrence Chen, Ziyan Wu |
| 2025 | A Benchmark for Semantic Sensitive Information in LLMs Outputs. Qingjie Zhang, Han Qiu, Di Wang, Yiming Li, Tianwei Zhang, Wenyu Zhu, Haiqin Weng, Liu Yan, Chao Zhang |
| 2025 | A Black Swan Hypothesis: The Role of Human Irrationality in AI Safety. Hyunin Lee, Chanwoo Park, David Abel, Ming Jin |
| 2025 | A CLIP-Powered Framework for Robust and Generalizable Data Selection. Suorong Yang, Peng Ye, Wanli Ouyang, Dongzhan Zhou, Furao Shen |
| 2025 | A Causal Lens for Learning Long-term Fair Policies. Jacob Lear, Lu Zhang |
| 2025 | A Closer Look at Machine Unlearning for Large Language Models. Xiaojian Yuan, Tianyu Pang, Chao Du, Kejiang Chen, Weiming Zhang, Min Lin |
| 2025 | A Coefficient Makes SVRG Effective. Yida Yin, Zhiqiu Xu, Zhiyuan Li, Trevor Darrell, Zhuang Liu |
| 2025 | A Common Pitfall of Margin-based Language Model Alignment: Gradient Entanglement. Hui Yuan, Yifan Zeng, Yue Wu, Huazheng Wang, Mengdi Wang, Liu Leqi |
| 2025 | A Computational Framework for Modeling Emergence of Color Vision in the Human Brain. Atsunobu Kotani, Ren Ng |
| 2025 | A Conditional Independence Test in the Presence of Discretization. Boyang Sun, Yu Yao, Guang-Yuan Hao, Yumou Qiu, Kun Zhang |
| 2025 | A Decade's Battle on Dataset Bias: Are We There Yet? Zhuang Liu, Kaiming He |
| 2025 | A Deep Generative Learning Approach for Two-stage Adaptive Robust Optimization. Aron Brenner, Rahman Khorramfar, Jennifer Z. Sun, Saurabh Amin |
| 2025 | A Differentiable Rank-Based Objective for Better Feature Learning. Krunoslav Lehman Pavasovic, Giulio Biroli, Levent Sagun |
| 2025 | A Distributional Approach to Uncertainty-Aware Preference Alignment Using Offline Demonstrations. Sheng Xu, Bo Yue, Hongyuan Zha, Guiliang Liu |
| 2025 | A Formal Framework for Understanding Length Generalization in Transformers. Xinting Huang, Andy Yang, Satwik Bhattamishra, Yash Raj Sarrof, Andreas Krebs, Hattie Zhou, Preetum Nakkiran, Michael Hahn |
| 2025 | A General Framework for Off-Policy Learning with Partially-Observed Reward. Rikiya Takehi, Masahiro Asami, Kosuke Kawakami, Yuta Saito |
| 2025 | A General Framework for Producing Interpretable Semantic Text Embeddings. Yiqun Sun, Qiang Huang, Yixuan Tang, Anthony Kum Hoe Tung, Jun Yu |
| 2025 | A Generalist Hanabi Agent. Arjun Vaithilingam Sudhakar, Hadi Nekoei, Mathieu Reymond, Miao Liu, Janarthanan Rajendran, Sarath Chandar |
| 2025 | A Generic Framework for Conformal Fairness. Aditya T. Vadlamani, Anutam Srinivasan, Pranav Maneriker, Ali Payani, Srinivasan Parthasarathy |
| 2025 | A Geometric Framework for Understanding Memorization in Generative Models. Brendan Leigh Ross, Hamidreza Kamkari, Tongzi Wu, Rasa Hosseinzadeh, Zhaoyan Liu, George Stein, Jesse C. Cresswell, Gabriel Loaiza-Ganem |
| 2025 | A Graph Enhanced Symbolic Discovery Framework For Efficient Logic Optimization. Yinqi Bai, Jie Wang, Lei Chen, Zhihai Wang, Yufei Kuang, Mingxuan Yuan, Jianye Hao, Feng Wu |
| 2025 | A Large-scale Dataset and Benchmark for Commuting Origin-Destination Flow Generation. Can Rong, Jingtao Ding, Yan Liu, Yong Li |
| 2025 | A Large-scale Training Paradigm for Graph Generative Models. Yu Wang, Ryan A. Rossi, Namyong Park, Huiyuan Chen, Nesreen K. Ahmed, Puja Trivedi, Franck Dernoncourt, Danai Koutra, Tyler Derr |
| 2025 | A Little Goes a Long Way: Efficient Long Context Training and Inference with Partial Contexts. Suyu Ge, Xihui Lin, Yunan Zhang, Jiawei Han, Hao Peng |
| 2025 | A Meta-Learning Approach to Bayesian Causal Discovery. Anish Dhir, Matthew Ashman, James Requeima, Mark van der Wilk |
| 2025 | A Multi-Power Law for Loss Curve Prediction Across Learning Rate Schedules. Kairong Luo, Haodong Wen, Shengding Hu, Zhenbo Sun, Zhiyuan Liu, Maosong Sun, Kaifeng Lyu, Wenguang Chen |
| 2025 | A Multiscale Frequency Domain Causal Framework for Enhanced Pathological Analysis. Xiaoyu Cui, Weixing Chen, Jiandong Su |
| 2025 | A New Perspective on Shampoo's Preconditioner. Depen Morwani, Itai Shapira, Nikhil Vyas, Eran Malach, Sham M. Kakade, Lucas Janson |
| 2025 | A Non-Contrastive Learning Framework for Sequential Recommendation with Preference-Preserving Profile Generation. Huimin Zeng, Xiaojie Wang, Anoop Jain, Zhicheng Dou, Dong Wang |
| 2025 | A Percolation Model of Emergence: Analyzing Transformers Trained on a Formal Language. Ekdeep Singh Lubana, Kyogo Kawaguchi, Robert P. Dick, Hidenori Tanaka |
| 2025 | A Periodic Bayesian Flow for Material Generation. Hanlin Wu, Yuxuan Song, Jingjing Gong, Ziyao Cao, Yawen Ouyang, Jianbing Zhang, Hao Zhou, Wei-Ying Ma, Jingjing Liu |
| 2025 | A Policy-Gradient Approach to Solving Imperfect-Information Games with Best-Iterate Convergence. Mingyang Liu, Gabriele Farina, Asuman E. Ozdaglar |
| 2025 | A Probabilistic Perspective on Unlearning and Alignment for Large Language Models. Yan Scholten, Stephan Günnemann, Leo Schwinn |
| 2025 | A Quantum Circuit-Based Compression Perspective for Parameter-Efficient Learning. Chen-Yu Liu, Chao-Han Huck Yang, Hsi-Sheng Goan, Min-Hsiu Hsieh |
| 2025 | A Riemannian Framework for Learning Reduced-order Lagrangian Dynamics. Katharina Friedl, Noémie Jaquier, Jens Lundell, Tamim Asfour, Danica Kragic |
| 2025 | A Robust Method to Discover Causal or Anticausal Relation. Yu Yao, Yang Zhou, Bo Han, Mingming Gong, Kun Zhang, Tongliang Liu |
| 2025 | A Sanity Check for AI-generated Image Detection. Shilin Yan, Ouxiang Li, Jiayin Cai, Yanbin Hao, Xiaolong Jiang, Yao Hu, Weidi Xie |
| 2025 | A Second-Order Perspective on Model Compositionality and Incremental Learning. Angelo Porrello, Lorenzo Bonicelli, Pietro Buzzega, Monica Millunzi, Simone Calderara, Rita Cucchiara |
| 2025 | A Simple Approach to Unifying Diffusion-based Conditional Generation. Xirui Li, Charles Herrmann, Kelvin C. K. Chan, Yinxiao Li, Deqing Sun, Chao Ma, Ming-Hsuan Yang |
| 2025 | A Simple Framework for Open-Vocabulary Zero-Shot Segmentation. Thomas Stegmüller, Tim Lebailly, Nikola Dukic, Behzad Bozorgtabar, Tinne Tuytelaars, Jean-Philippe Thiran |
| 2025 | A Simple yet Effective ΔΔG Predictor is An Unsupervised Antibody Optimizer and Explainer. Lirong Wu, Yunfan Liu, Haitao Lin, Yufei Huang, Guojiang Zhao, Zhifeng Gao, Stan Z. Li |
| 2025 | A Single Goal is All You Need: Skills and Exploration Emerge from Contrastive RL without Rewards, Demonstrations, or Subgoals. Grace Liu, Michael Tang, Benjamin Eysenbach |
| 2025 | A Skewness-Based Criterion for Addressing Heteroscedastic Noise in Causal Discovery. Yingyu Lin, Yuxing Huang, Wenqin Liu, Haoran Deng, Ignavier Ng, Kun Zhang, Mingming Gong, Yian Ma, Biwei Huang |
| 2025 | A Solvable Attention for Neural Scaling Laws. Bochen Lyu, Di Wang, Zhanxing Zhu |
| 2025 | A Spark of Vision-Language Intelligence: 2-Dimensional Autoregressive Transformer for Efficient Finegrained Image Generation. Liang Chen, Sinan Tan, Zefan Cai, Weichu Xie, Haozhe Zhao, Yichi Zhang, Junyang Lin, Jinze Bai, Tianyu Liu, Baobao Chang |
| 2025 | A Statistical Approach for Controlled Training Data Detection. Zirui Hu, Yingjie Wang, Zheng Zhang, Hong Chen, Dacheng Tao |
| 2025 | A Statistical Framework for Ranking LLM-based Chatbots. Siavash Ameli, Siyuan Zhuang, Ion Stoica, Michael W. Mahoney |
| 2025 | A Stochastic Approach to the Subset Selection Problem via Mirror Descent. Dan Greenstein, Elazar Gershuni, Ilan Ben-Bassat, Yaroslav Fyodorov, Ran Moshe, Fiana Raiber, Alex Shtoff, Oren Somekh, Nadav Hallak |
| 2025 | A Theoretical Analysis of Self-Supervised Learning for Vision Transformers. Yu Huang, Zixin Wen, Yuejie Chi, Yingbin Liang |
| 2025 | A Theoretical Framework for Partially-Observed Reward States in RLHF. Chinmaya Kausik, Mirco Mutti, Aldo Pacchiano, Ambuj Tewari |
| 2025 | A Theoretical Perspective: How to Prevent Model Collapse in Self-consuming Training Loops. Shi Fu, Yingjie Wang, Yuzhu Chen, Xinmei Tian, Dacheng Tao |
| 2025 | A Theoretically-Principled Sparse, Connected, and Rigid Graph Representation of Molecules. Shih-Hsin Wang, Yuhao Huang, Justin M. Baker, Yuan-En Sun, Qi Tang, Bao Wang |
| 2025 | A Theory for Token-Level Harmonization in Retrieval-Augmented Generation. Shicheng Xu, Liang Pang, Huawei Shen, Xueqi Cheng |
| 2025 | A Theory of Initialisation's Impact on Specialisation. Devon Jarvis, Sebastian Lee, Clémentine Carla Juliette Dominé, Andrew M. Saxe, Stefano Sarao Mannelli |
| 2025 | A Tight Convergence Analysis of Inexact Stochastic Proximal Point Algorithm for Stochastic Composite Optimization Problems. Shulan Zhu, Chenglong Bao, Defeng Sun, Yancheng Yuan |
| 2025 | A Training-Free Sub-quadratic Cost Transformer Model Serving Framework with Hierarchically Pruned Attention. Heejun Lee, Geon Park, Youngwan Lee, Jaduk Suh, Jina Kim, Wonyong Jeong, Bumsik Kim, Hyemin Lee, Myeongjae Jeon, Sung Ju Hwang |
| 2025 | A Transfer Attack to Image Watermarks. Yuepeng Hu, Zhengyuan Jiang, Moyang Guo, Neil Zhenqiang Gong |
| 2025 | A Truncated Newton Method for Optimal Transport. Mete Kemertas, Amir-massoud Farahmand, Allan Douglas Jepson |
| 2025 | A Unified Framework for Forward and Inverse Problems in Subsurface Imaging using Latent Space Translations. Naveen Gupta, Medha Sawhney, Arka Daw, Youzuo Lin, Anuj Karpatne |
| 2025 | A Unified Theory of Quantum Neural Network Loss Landscapes. Eric R. Anschuetz |
| 2025 | A Watermark for Order-Agnostic Language Models. Ruibo Chen, Yihan Wu, Yanshuo Chen, Chenxi Liu, Junfeng Guo, Heng Huang |
| 2025 | A deep inverse-mapping model for a flapping robotic wing. Hadar Sharvit, Raz Karl, Tsevi Beatus |
| 2025 | A new framework for evaluating model out-of-distribution generalisation for the biochemical domain. Raúl Fernández-Díaz, Hoang Thanh Lam, Vanessa López, Denis C. Shields |
| 2025 | A transfer learning framework for weak to strong generalization. Seamus Somerstep, Felipe Maia Polo, Moulinath Banerjee, Yaacov Ritov, Mikhail Yurochkin, Yuekai Sun |
| 2025 | A-Bench: Are LMMs Masters at Evaluating AI-generated Images? Zicheng Zhang, Haoning Wu, Chunyi Li, Yingjie Zhou, Wei Sun, Xiongkuo Min, Zijian Chen, Xiaohong Liu, Weisi Lin, Guangtao Zhai |
| 2025 | A3D: Does Diffusion Dream about 3D Alignment? Savva Victorovich Ignatyev, Nina Konovalova, Daniil Selikhanovych, Oleg Voynov, Nikolay Patakin, Ilya Olkov, Dmitry Senushkin, Alexey Artemov, Anton Konushin, Alexander Filippov, Peter Wonka, Evgeny Burnaev |
| 2025 | ACC-Collab: An Actor-Critic Approach to Multi-Agent LLM Collaboration. Andrew Estornell, Jean-Francois Ton, Yuanshun Yao, Yang Liu |
| 2025 | ACE: All-round Creator and Editor Following Instructions via Diffusion Transformer. Zhen Han, Zeyinzi Jiang, Yulin Pan, Jingfeng Zhang, Chaojie Mao, Chen-Wei Xie, Yu Liu, Jingren Zhou |
| 2025 | ACES: Automatic Cohort Extraction System for Event-Stream Datasets. Justin Xu, Jack Gallifant, Alistair E. W. Johnson, Matthew B. A. McDermott |
| 2025 | ACTIVE: Offline Reinforcement Learning via Adaptive Imitation and In-sample V-Ensemble. Tianyuan Chen, Ronglong Cai, Faguo Wu, Xiao Zhang |
| 2025 | ADAM Optimization with Adaptive Batch Selection. Gyu-Yeol Kim, Min-hwan Oh |
| 2025 | ADAM: An Embodied Causal Agent in Open-World Environments. Shu Yu, Chaochao Lu |
| 2025 | ADAPT: Attentive Self-Distillation and Dual-Decoder Prediction Fusion for Continual Panoptic Segmentation. Ze Yang, Shichao Dong, Ruibo Li, Nan Song, Guosheng Lin |
| 2025 | ADBM: Adversarial Diffusion Bridge Model for Reliable Adversarial Purification. Xiao Li, Wenxuan Sun, Huanran Chen, Qiongxiu Li, Yingzhe He, Jie Shi, Xiaolin Hu |
| 2025 | ADIFF: Explaining audio difference using natural language. Soham Deshmukh, Shuo Han, Rita Singh, Bhiksha Raj |
| 2025 | ADMM for Nonconvex Optimization under Minimal Continuity Assumption. Ganzhao Yuan |
| 2025 | ADMM for Structured Fractional Minimization. Ganzhao Yuan |
| 2025 | ADePT: Adaptive Decomposed Prompt Tuning for Parameter-Efficient Fine-tuning. Pengwei Tang, Xiaolin Hu, Yong Liu |
| 2025 | AFlow: Automating Agentic Workflow Generation. Jiayi Zhang, Jinyu Xiang, Zhaoyang Yu, Fengwei Teng, Xionghui Chen, Jiaqi Chen, Mingchen Zhuge, Xin Cheng, Sirui Hong, Jinlin Wang, Bingnan Zheng, Bang Liu, Yuyu Luo, Chenglin Wu |
| 2025 | AHA: A Vision-Language-Model for Detecting and Reasoning Over Failures in Robotic Manipulation. Jiafei Duan, Wilbert Pumacay, Nishanth Kumar, Yi Ru Wang, Shulin Tian, Wentao Yuan, Ranjay Krishna, Dieter Fox, Ajay Mandlekar, Yijie Guo |
| 2025 | AI Sandbagging: Language Models can Strategically Underperform on Evaluations. Teun van der Weij, Felix Hofstätter, Oliver Jaffe, Samuel F. Brown, Francis Rhys Ward |
| 2025 | AI as Humanity's Salieri: Quantifying Linguistic Creativity of Language Models via Systematic Attribution of Machine Text against Web Text. Ximing Lu, Melanie Sclar, Skyler Hallinan, Niloofar Mireshghallah, Jiacheng Liu, Seungju Han, Allyson Ettinger, Liwei Jiang, Khyathi Raghavi Chandu, Nouha Dziri, Yejin Choi |
| 2025 | AI2TALE: An Innovative Information Theory-based Approach for Learning to Localize Phishing Attacks. Van Nguyen, Tingmin Wu, Xingliang Yuan, Marthie Grobler, Surya Nepal, Carsten Rudolph |
| 2025 | AIMS.au: A Dataset for the Analysis of Modern Slavery Countermeasures in Corporate Statements. Adriana Eufrosina Bora, Pierre-Luc St-Charles, Mirko Bronzi, Arsène Fansi Tchango, Bruno Rousseau, Kerrie L. Mengersen |
| 2025 | AIR-BENCH 2024: A Safety Benchmark based on Regulation and Policies Specified Risk Categories. Yi Zeng, Yu Yang, Andy Zhou, Jeffrey Ziwei Tan, Yuheng Tu, Yifan Mai, Kevin Klyman, Minzhou Pan, Ruoxi Jia, Dawn Song, Percy Liang, Bo Li |
| 2025 | ALBAR: Adversarial Learning approach to mitigate Biases in Action Recognition. Joseph Fioresi, Ishan Rajendrakumar Dave, Mubarak Shah |
| 2025 | ALLaM: Large Language Models for Arabic and English. M. Saiful Bari, Yazeed Alnumay, Norah A. Alzahrani, Nouf M. Alotaibi, Hisham Abdullah Alyahya, Sultan AlRashed, Faisal Abdulrahman Mirza, Shaykhah Z. Alsubaie, Hassan A. Alahmed, Ghadah Alabduljabbar, Raghad Alkhathran, Yousef Almushayqih, Raneem Alnajim, Salman Alsubaihi, Maryam Al Mansour, Saad Amin Hassan, Majed Alrubaian, Ali Alammari, Zaki Alawami, Abdulmohsen Al-Thubaity, et al. |
| 2025 | ANaGRAM: A Natural Gradient Relative to Adapted Model for efficient PINNs learning. Nilo Schwencke, Cyril Furtlehner |
| 2025 | APE: Faster and Longer Context-Augmented Generation via Adaptive Parallel Encoding. Xinyu Yang, Tianqi Chen, Beidi Chen |
| 2025 | API Pack: A Massive Multi-Programming Language Dataset for API Call Generation. Zhen Guo, Adriana Meza Soria, Wei Sun, Yikang Shen, Rameswar Panda |
| 2025 | ARB-LLM: Alternating Refined Binarizations for Large Language Models. Zhiteng Li, Xianglong Yan, Tianao Zhang, Haotong Qin, Dong Xie, Jiang Tian, Zhongchao Shi, Linghe Kong, Yulun Zhang, Xiaokang Yang |
| 2025 | ARLON: Boosting Diffusion Transformers with Autoregressive Models for Long Video Generation. Zongyi Li, Shujie Hu, Shujie Liu, Long Zhou, Jeongsoo Choi, Lingwei Meng, Xun Guo, Jinyu Li, Hefei Ling, Furu Wei |
| 2025 | ASTrA: Adversarial Self-supervised Training with Adaptive-Attacks. Prakash Chandra Chhipa, Gautam Vashishtha, Settur Jithamanyu, Rajkumar Saini, Mubarak Shah, Marcus Liwicki |
| 2025 | AVHBench: A Cross-Modal Hallucination Benchmark for Audio-Visual Large Language Models. Sung-Bin Kim, Oh Hyun-Bin, JungMok Lee, Arda Senocak, Joon Son Chung, Tae-Hyun Oh |
| 2025 | Accelerated Over-Relaxation Heavy-Ball Method: Achieving Global Accelerated Convergence with Broad Generalization. Jingrong Wei, Long Chen |
| 2025 | Accelerated training through iterative gradient propagation along the residual path. Erwan Fagnou, Paul Caillon, Blaise Delattre, Alexandre Allauzen |
| 2025 | Accelerating 3D Molecule Generation via Jointly Geometric Optimal Transport. Haokai Hong, Wanyu Lin, Kc Tan |
| 2025 | Accelerating Auto-regressive Text-to-Image Generation with Training-free Speculative Jacobi Decoding. Yao Teng, Han Shi, Xian Liu, Xuefei Ning, Guohao Dai, Yu Wang, Zhenguo Li, Xihui Liu |
| 2025 | Accelerating Diffusion Transformers with Token-wise Feature Caching. Chang Zou, Xuyang Liu, Ting Liu, Siteng Huang, Linfeng Zhang |
| 2025 | Accelerating Goal-Conditioned Reinforcement Learning Algorithms and Research. Michal Bortkiewicz, Wladyslaw Palucki, Vivek Myers, Tadeusz Dziarmaga, Tomasz Arczewski, Lukasz Kucinski, Benjamin Eysenbach |
| 2025 | Accelerating Inference of Retrieval-Augmented Generation via Sparse Context Selection. Yun Zhu, Jia-Chen Gu, Caitlin Sikora, Ho Ko, Yinxiao Liu, Chu-Cheng Lin, Lei Shu, Liangchen Luo, Lei Meng, Bang Liu, Jindong Chen |
| 2025 | Accelerating Neural ODEs: A Variational Formulation-based Approach. Hongjue Zhao, Yuchen Wang, Hairong Qi, Zijie Huang, Han Zhao, Lui Sha, Huajie Shao |
| 2025 | Accelerating Task Generalisation with Multi-Level Skill Hierarchies. Thomas P. Cannon, Özgür Simsek |
| 2025 | Accelerating Training with Neuron Interaction and Nowcasting Networks. Boris Knyazev, Abhinav Moudgil, Guillaume Lajoie, Eugene Belilovsky, Simon Lacoste-Julien |
| 2025 | Accelerating neural network training: An analysis of the AlgoPerf competition. Priya Kasimbeg, Frank Schneider, Runa Eschenhagen, Juhan Bae, Chandramouli Shama Sastry, Mark Saroufim, Boyuan Feng, Less Wright, Edward Z. Yang, Zachary Nado, Sourabh Medapati, Philipp Hennig, Michael Rabbat, George E. Dahl |
| 2025 | Accessing Vision Foundation Models via ImageNet-1K. Yitian Zhang, Xu Ma, Yue Bai, Huan Wang, Yun Fu |
| 2025 | Accurate and Scalable Graph Neural Networks via Message Invariance. Zhihao Shi, Jie Wang, Zhiwei Zhuang, Xize Liang, Bin Li, Feng Wu |
| 2025 | Achieving Dimension-Free Communication in Federated Learning via Zeroth-Order Optimization. Zhe Li, Bicheng Ying, Zidong Liu, Chaosheng Dong, Haibo Yang |
| 2025 | ActSafe: Active Exploration with Safety Constraints for Reinforcement Learning. Yarden As, Bhavya Sukhija, Lenart Treven, Carmelo Sferrazza, Stelian Coros, Andreas Krause |
| 2025 | Action Sequence Augmentation for Action Anticipation. Yihui Qiu, Deepu Rajan |
| 2025 | Action abstractions for amortized sampling. Oussama Boussif, Léna Néhale Ezzine, Joseph D. Viviano, Michal Koziarski, Moksh Jain, Nikolay Malkin, Emmanuel Bengio, Rim Assouel, Yoshua Bengio |
| 2025 | ActionReasoningBench: Reasoning about Actions with and without Ramification Constraints. Divij Handa, Pavel Dolin, Shrinidhi Kumbhar, Tran Cao Son, Chitta Baral |
| 2025 | Actions Speak Louder Than Words: Rate-Reward Trade-off in Markov Decision Processes. Haotian Wu, Gongpu Chen, Deniz Gündüz |
| 2025 | Activation Gradient based Poisoned Sample Detection Against Backdoor Attacks. Danni Yuan, Mingda Zhang, Shaokui Wei, Li Liu, Baoyuan Wu |
| 2025 | Active Learning for Continual Learning: Keeping the Past Alive in the Present. Jaehyun Park, Dongmin Park, Jae-Gil Lee |
| 2025 | Active Learning for Neural PDE Solvers. Daniel Musekamp, Marimuthu Kalimuthu, David Holzmüller, Makoto Takamoto, Mathias Niepert |
| 2025 | Active Task Disambiguation with LLMs. Kasia Kobalczyk, Nicolás Astorga, Tennison Liu, Mihaela van der Schaar |
| 2025 | Ada-K Routing: Boosting the Efficiency of MoE-based LLMs. Tongtian Yue, Longteng Guo, Jie Cheng, Xuange Gao, Hua Huang, Jing Liu |
| 2025 | AdaFisher: Adaptive Second Order Optimization via Fisher Information. Damien Martins Gomes, Yanlei Zhang, Eugene Belilovsky, Guy Wolf, Mahdi S. Hosseini |
| 2025 | AdaGrad under Anisotropic Smoothness. Yuxing Liu, Rui Pan, Tong Zhang |
| 2025 | AdaIR: Adaptive All-in-One Image Restoration via Frequency Mining and Modulation. Yuning Cui, Syed Waqas Zamir, Salman H. Khan, Alois Knoll, Mubarak Shah, Fahad Shahbaz Khan |
| 2025 | AdaManip: Adaptive Articulated Object Manipulation Environments and Policy Learning. Yuanfei Wang, Xiaojie Zhang, Ruihai Wu, Yu Li, Yan Shen, Mingdong Wu, Zhaofeng He, Yizhou Wang, Hao Dong |
| 2025 | AdaRankGrad: Adaptive Gradient Rank and Moments for Memory-Efficient LLMs Training and Fine-Tuning. Yehonathan Refael, Jonathan Svirsky, Boris Shustin, Wasim Huleihel, Ofir Lindenbaum |
| 2025 | AdaWM: Adaptive World Model based Planning for Autonomous Driving. Hang Wang, Xin Ye, Feng Tao, Chenbin Pan, Abhirup Mallik, Burhaneddin Yaman, Liu Ren, Junshan Zhang |
| 2025 | Adam Exploits ℓ∞-geometry of Loss Landscape via Coordinate-wise Adaptivity. Shuo Xie, Mohamad Amin Mohamadi, Zhiyuan Li |
| 2025 | Adam-mini: Use Fewer Learning Rates To Gain More. Yushun Zhang, Congliang Chen, Ziniu Li, Tian Ding, Chenwei Wu, Diederik P. Kingma, Yinyu Ye, Zhi-Quan Luo, Ruoyu Sun |
| 2025 | Adapt-∞: Scalable Continual Multimodal Instruction Tuning via Dynamic Data Selection. Adyasha Maharana, Jaehong Yoon, Tianlong Chen, Mohit Bansal |
| 2025 | Adapters for Altering LLM Vocabularies: What Languages Benefit the Most? HyoJung Han, Akiko Eriguchi, Haoran Xu, Hieu Hoang, Marine Carpuat, Huda Khayrallah |
| 2025 | Adapting Multi-modal Large Language Model to Concept Drift From Pre-training Onwards. Xiaoyu Yang, Jie Lu, En Yu |
| 2025 | Adaptive Batch Size for Privately Finding Second-Order Stationary Points. Daogao Liu, Kunal Talwar |
| 2025 | Adaptive Camera Sensor for Vision Models. Eunsu Baek, Sunghwan Han, Taesik Gong, Hyung-Sin Kim |
| 2025 | Adaptive Data Optimization: Dynamic Sample Selection with Scaling Laws. Yiding Jiang, Allan Zhou, Zhili Feng, Sadhika Malladi, J. Zico Kolter |
| 2025 | Adaptive Deployment of Untrusted LLMs Reduces Distributed Threats. Jiaxin Wen, Vivek Hebbar, Caleb Larson, Aryan Bhatt, Ansh Radhakrishnan, Mrinank Sharma, Henry Sleight, Shi Feng, He He, Ethan Perez, Buck Shlegeris, Akbir Khan |
| 2025 | Adaptive Energy Alignment for Accelerating Test-Time Adaptation. Wonjeong Choi, Do-Yeon Kim, Jungwuk Park, Jungmoon Lee, Younghyun Park, Dong-Jun Han, Jaekyun Moon |
| 2025 | Adaptive Gradient Clipping for Robust Federated Learning. Youssef Allouah, Rachid Guerraoui, Nirupam Gupta, Ahmed Jellouli, Geovani Rizk, John Stephan |
| 2025 | Adaptive Length Image Tokenization via Recurrent Allocation. Shivam Duggal, Phillip Isola, Antonio Torralba, William T. Freeman |
| 2025 | Adaptive Methods through the Lens of SDEs: Theoretical Insights on the Role of Noise. Enea Monzio Compagnoni, Tianlin Liu, Rustem Islamov, Frank Norbert Proske, Antonio Orvieto, Aurélien Lucchi |
| 2025 | Adaptive Pruning of Pretrained Transformer via Differential Inclusions. Yizhuo Ding, Ke Fan, Yikai Wang, Xinwei Sun, Yanwei Fu |
| 2025 | Adaptive Q-Network: On-the-fly Target Selection for Deep Reinforcement Learning. Théo Vincent, Fabian Wahren, Jan Peters, Boris Belousov, Carlo D'Eramo |
| 2025 | Adaptive Rank Allocation: Speeding Up Modern Transformers with RaNA Adapters. Roberto Garcia, Jerry Weihong Liu, Daniel Sorvisto, Sabri Eyuboglu |
| 2025 | Adaptive Retention & Correction: Test-Time Training for Continual Learning. Haoran Chen, Micah Goldblum, Zuxuan Wu, Yu-Gang Jiang |
| 2025 | Adaptive Shrinkage Estimation for Personalized Deep Kernel Regression in Modeling Brain Trajectories. Vasiliki Tassopoulou, Haochang Shou, Christos Davatzikos |
| 2025 | Adaptive Transformer Programs: Bridging the Gap Between Performance and Interpretability in Transformers. Quoc-Vinh Lai-Dang, Taemin Kang, Seungah Son |
| 2025 | Adaptive backtracking line search. Joao V. Cavalcanti, Laurent Lessard, Ashia C. Wilson |
| 2025 | Adaptive teachers for amortized samplers. Minsu Kim, Sanghyeok Choi, Taeyoung Yun, Emmanuel Bengio, Leo Feng, Jarrid Rector-Brooks, Sungsoo Ahn, Jinkyoo Park, Nikolay Malkin, Yoshua Bengio |
| 2025 | Add-it: Training-Free Object Insertion in Images With Pretrained Diffusion Models. Yoad Tewel, Rinon Gal, Dvir Samuel, Yuval Atzmon, Lior Wolf, Gal Chechik |
| 2025 | Addax: Utilizing Zeroth-Order Gradients to Improve Memory Efficiency and Performance of SGD for Fine-Tuning Language Models. Zeman Li, Xinwei Zhang, Peilin Zhong, Yuan Deng, Meisam Razaviyayn, Vahab Mirrokni |
| 2025 | Adding Conditional Control to Diffusion Models with Reinforcement Learning. Yulai Zhao, Masatoshi Uehara, Gabriele Scalia, Sun-Yuan Kung, Tommaso Biancalani, Sergey Levine, Ehsan Hajiramezanali |
| 2025 | Addressing Label Shift in Distributed Learning via Entropy Regularization. Zhiyuan Wu, Changkyu Choi, Xiangcheng Cao, Volkan Cevher, Ali Ramezani-Kebrya |
| 2025 | Adjoint Matching: Fine-tuning Flow and Diffusion Generative Models with Memoryless Stochastic Optimal Control. Carles Domingo-Enrich, Michal Drozdzal, Brian Karrer, Ricky T. Q. Chen |
| 2025 | AdvPaint: Protecting Images from Inpainting Manipulation via Adversarial Attention Disruption. Joonsung Jeon, Woo Jae Kim, Suhyeon Ha, Sooel Son, Sung-Eui Yoon |
| 2025 | AdvWave: Stealthy Adversarial Jailbreak Attack against Large Audio-Language Models. Mintong Kang, Chejian Xu, Bo Li |
| 2025 | Advancing Graph Generation through Beta Diffusion. Xinyang Liu, Yilin He, Bo Chen, Mingyuan Zhou |
| 2025 | Advancing LLM Reasoning Generalists with Preference Trees. Lifan Yuan, Ganqu Cui, Hanbin Wang, Ning Ding, Xingyao Wang, Boji Shan, Zeyuan Liu, Jia Deng, Huimin Chen, Ruobing Xie, Yankai Lin, Zhenghao Liu, Bowen Zhou, Hao Peng, Zhiyuan Liu, Maosong Sun |
| 2025 | Advancing Mathematical Reasoning in Language Models: The Impact of Problem-Solving Data, Data Synthesis Methods, and Training Stages. Zui Chen, Tianqiao Liu, Tongqing, Mi Tian, Weiqi Luo, Zitao Liu |
| 2025 | Advancing Out-of-Distribution Detection via Local Neuroplasticity. Alessandro Canevaro, Julian Schmidt, Mohammad Sajad Marvi, Hang Yu, Georg Martius, Julian Jordan |
| 2025 | Advancing Prompt-Based Methods for Replay-Independent General Continual Learning. Zhiqi Kang, Liyuan Wang, Xingxing Zhang, Karteek Alahari |
| 2025 | Advantage Alignment Algorithms. Juan Agustin Duque, Milad Aghajohari, Tim Cooijmans, Razvan Ciuca, Tianyu Zhang, Gauthier Gidel, Aaron C. Courville |
| 2025 | Advantage-Guided Distillation for Preference Alignment in Small Language Models. Shiping Gao, Fanqi Wan, Jiajian Guo, Xiaojun Quan, Qifan Wang |
| 2025 | Adversarial Attacks on Data Attribution. Xinhe Wang, Pingbang Hu, Junwei Deng, Jiaqi W. Ma |
| 2025 | Adversarial Generative Flow Network for Solving Vehicle Routing Problems. Ni Zhang, Jingfeng Yang, Zhiguang Cao, Xu Chi |
| 2025 | Adversarial Latent Feature Augmentation for Fairness. Hoin Jung, Junyi Chai, Xiaoqian Wang |
| 2025 | Adversarial Machine Unlearning. Zonglin Di, Sixie Yu, Yevgeniy Vorobeychik, Yang Liu |
| 2025 | Adversarial Mixup Unlearning. Zhuoyi Peng, Yixuan Tang, Yi Yang |
| 2025 | Adversarial Perturbations Cannot Reliably Protect Artists From Generative AI. Robert Hönig, Javier Rando, Nicholas Carlini, Florian Tramèr |
| 2025 | Adversarial Policy Optimization for Offline Preference-based Reinforcement Learning. Hyungkyu Kang, Min-hwan Oh |
| 2025 | Adversarial Score identity Distillation: Rapidly Surpassing the Teacher in One Step. Mingyuan Zhou, Huangjie Zheng, Yi Gu, Zhendong Wang, Hai Huang |
| 2025 | Adversarial Search Engine Optimization for Large Language Models. Fredrik Nestaas, Edoardo Debenedetti, Florian Tramèr |
| 2025 | Adversarial Training Can Provably Improve Robustness: Theoretical Analysis of Feature Learning Process Under Structured Data. Binghui Li, Yuanzhi Li |
| 2025 | Adversarial Training for Defense Against Label Poisoning Attacks. Melis Ilayda Bal, Volkan Cevher, Michael Muehlebach |
| 2025 | Adversarially Robust Anomaly Detection through Spurious Negative Pair Mitigation. Hossein Mirzaei, Mojtaba Nafez, Jafar Habibi, Mohammad Sabokrou, Mohammad Hossein Rohban |
| 2025 | Adversarially Robust Out-of-Distribution Detection Using Lyapunov-Stabilized Embeddings. Hossein Mirzaei, Mackenzie W. Mathis |
| 2025 | Adversaries With Incentives: A Strategic Alternative to Adversarial Robustness. Maayan Ehrenberg, Roy Ganz, Nir Rosenfeld |
| 2025 | Affine Steerable Equivariant Layer for Canonicalization of Neural Networks. Yikang Li, Yeqing Qiu, Yuxuan Chen, Zhouchen Lin |
| 2025 | Agent S: An Open Agentic Framework that Uses Computers Like a Human. Saaket Agashe, Jiuzhou Han, Shuyu Gan, Jiachen Yang, Ang Li, Xin Eric Wang |
| 2025 | Agent Security Bench (ASB): Formalizing and Benchmarking Attacks and Defenses in LLM-based Agents. Hanrong Zhang, Jingyuan Huang, Kai Mei, Yifei Yao, Zhenting Wang, Chenlu Zhan, Hongwei Wang, Yongfeng Zhang |
| 2025 | Agent Skill Acquisition for Large Language Models via CycleQD. So Kuroki, Taishi Nakamura, Takuya Akiba, Yujin Tang |
| 2025 | Agent-Oriented Planning in Multi-Agent Systems. Ao Li, Yuexiang Xie, Songze Li, Fugee Tsung, Bolin Ding, Yaliang Li |
| 2025 | Agent-to-Sim: Learning Interactive Behavior Models from Casual Longitudinal Videos. Gengshan Yang, Andrea Bajcsy, Shunsuke Saito, Angjoo Kanazawa |
| 2025 | AgentHarm: A Benchmark for Measuring Harmfulness of LLM Agents. Maksym Andriushchenko, Alexandra Souly, Mateusz Dziemian, Derek Duenas, Maxwell Lin, Justin Wang, Dan Hendrycks, Andy Zou, J. Zico Kolter, Matt Fredrikson, Yarin Gal, Xander Davies |
| 2025 | AgentOccam: A Simple Yet Strong Baseline for LLM-Based Web Agents. Ke Yang, Yao Liu, Sapana Chaudhary, Rasool Fakoor, Pratik Chaudhari, George Karypis, Huzefa Rangwala |
| 2025 | AgentRefine: Enhancing Agent Generalization through Refinement Tuning. Dayuan Fu, Keqing He, Yejie Wang, Wentao Hong, Zhuoma Gongque, Weihao Zeng, Wei Wang, Jingang Wang, Xunliang Cai, Weiran Xu |
| 2025 | AgentSquare: Automatic LLM Agent Search in Modular Design Space. Yu Shang, Yu Li, Keyu Zhao, Likai Ma, Jiahe Liu, Fengli Xu, Yong Li |
| 2025 | AgentStudio: A Toolkit for Building General Virtual Agents. Longtao Zheng, Zhiyuan Huang, Zhenghai Xue, Xinrun Wang, Bo An, Shuicheng Yan |
| 2025 | AgentTrek: Agent Trajectory Synthesis via Guiding Replay with Web Tutorials. Yiheng Xu, Dunjie Lu, Zhennan Shen, Junli Wang, Zekun Wang, Yuchen Mao, Caiming Xiong, Tao Yu |
| 2025 | Agents' Room: Narrative Generation through Multi-step Collaboration. Fantine Huot, Reinald Kim Amplayo, Jennimaria Palomaki, Alice Shoshana Jakobovits, Elizabeth Clark, Mirella Lapata |
| 2025 | Agree to Disagree: Demystifying Homogeneous Deep Ensembles through Distributional Equivalence. Yipei Wang, Xiaoqian Wang |
| 2025 | Aioli: A Unified Optimization Framework for Language Model Data Mixing. Mayee F. Chen, Michael Y. Hu, Nicholas Lourie, Kyunghyun Cho, Christopher Ré |
| 2025 | Air Quality Prediction with Physics-Guided Dual Neural ODEs in Open Systems. Jindong Tian, Yuxuan Liang, Ronghui Xu, Peng Chen, Chenjuan Guo, Aoying Zhou, Lujia Pan, Zhongwen Rao, Bin Yang |
| 2025 | Alchemy: Amplifying Theorem-Proving Capability Through Symbolic Mutation. Shaonan Wu, Shuai Lu, Yeyun Gong, Nan Duan, Ping Wei |
| 2025 | Algorithmic Stability Based Generalization Bounds for Adversarial Training. Runzhi Tian, Yongyi Mao |
| 2025 | Aligned Better, Listen Better for Audio-Visual Large Language Models. Yuxin Guo, Shuailei Ma, Shijie Ma, Xiaoyi Bao, Chen-Wei Xie, Kecheng Zheng, Tingyu Weng, Siyang Sun, Yun Zheng, Wei Zou |
| 2025 | Aligned Datasets Improve Detection of Latent Diffusion-Generated Images. Anirudh Sundara Rajan, Utkarsh Ojha, Jedidiah Schloesser, Yong Jae Lee |
| 2025 | Aligned LLMs Are Not Aligned Browser Agents. Priyanshu Kumar, Elaine Lau, Saranya Vijayakumar, Tu Trinh, Elaine T. Chang, Vaughn Robinson, Shuyan Zhou, Matt Fredrikson, Sean M. Hendryx, Summer Yue, Zifan Wang |
| 2025 | Aligning Generative Denoising with Discriminative Objectives Unleashes Diffusion for Visual Perception. Ziqi Pang, Xin Xu, Yu-Xiong Wang |
| 2025 | Aligning Human Motion Generation with Human Perceptions. Haoru Wang, Wentao Zhu, Luyi Miao, Yishu Xu, Feng Gao, Qi Tian, Yizhou Wang |
| 2025 | Aligning Language Models with Demonstrated Feedback. Omar Shaikh, Michelle S. Lam, Joey Hejna, Yijia Shao, Hyundong Justin Cho, Michael S. Bernstein, Diyi Yang |
| 2025 | Aligning Visual Contrastive learning models via Preference Optimization. Amirabbas Afzali, Borna Khodabandeh, Ali Rasekh, Mahyar JafariNodeh, Sepehr Kazemi Ranjbar, Simon Gottschalk |
| 2025 | Almost Optimal Batch-Regret Tradeoff for Batch Linear Contextual Bandits. Zihan Zhang, Xiangyang Ji, Yuan Zhou |
| 2025 | AlphaEdit: Null-Space Constrained Knowledge Editing for Language Models. Junfeng Fang, Houcheng Jiang, Kun Wang, Yunshan Ma, Jie Shi, Xiang Wang, Xiangnan He, Tat-Seng Chua |
| 2025 | Ambient Diffusion Posterior Sampling: Solving Inverse Problems with Diffusion Models Trained on Corrupted Data. Asad Aali, Giannis Daras, Brett Levac, Sidharth Kumar, Alex Dimakis, Jonathan I. Tamir |
| 2025 | Amortized Control of Continuous State Space Feynman-Kac Model for Irregular Time Series. Byoungwoo Park, Hyungi Lee, Juho Lee |
| 2025 | Amulet: ReAlignment During Test Time for Personalized Preference Adaptation of LLMs. Zhaowei Zhang, Fengshuo Bai, Qizhi Chen, Chengdong Ma, Mingzhi Wang, Haoran Sun, Zilong Zheng, Yaodong Yang |
| 2025 | An Asynchronous Bundle Method for Distributed Learning Problems. Daniel Cederberg, Xuyang Wu, Stephen P. Boyd, Mikael Johansson |
| 2025 | An Auditing Test to Detect Behavioral Shift in Language Models. Leo Richter, Xuanli He, Pasquale Minervini, Matt J. Kusner |
| 2025 | An Effective Manifold-based Optimization Method for Distributionally Robust Classification. Jiawei Huang, Hu Ding |
| 2025 | An Effective Theory of Bias Amplification. Arjun Subramonian, Samuel J. Bell, Levent Sagun, Elvis Dohmatob |
| 2025 | An Efficient Framework for Crediting Data Contributors of Diffusion Models. Mingyu Lu, Chris Lin, Chanwoo Kim, Su-In Lee |
| 2025 | An Empirical Analysis of Uncertainty in Large Language Model Evaluations. Qiujie Xie, Qingqiu Li, Zhuohao Yu, Yuejie Zhang, Yue Zhang, Linyi Yang |
| 2025 | An Engorgio Prompt Makes Large Language Model Babble on. Jianshuo Dong, Ziyuan Zhang, Qingjie Zhang, Tianwei Zhang, Hao Wang, Hewu Li, Qi Li, Chao Zhang, Ke Xu, Han Qiu |
| 2025 | An Evolved Universal Transformer Memory. Edoardo Cetin, Qi Sun, Tianyu Zhao, Yujin Tang |
| 2025 | An Exploration with Entropy Constrained 3D Gaussians for 2D Video Compression. Xiang Liu, Bin Chen, Zimo Liu, Yaowei Wang, Shu-Tao Xia |
| 2025 | An Image is Worth More Than 16x16 Patches: Exploring Transformers on Individual Pixels. Duy-Kien Nguyen, Mido Assran, Unnat Jain, Martin R. Oswald, Cees G. M. Snoek, Xinlei Chen |
| 2025 | An Information Criterion for Controlled Disentanglement of Multimodal Data. Chenyu Wang, Sharut Gupta, Xinyi Zhang, Sana Tonekaboni, Stefanie Jegelka, Tommi S. Jaakkola, Caroline Uhler |
| 2025 | An Intelligent Agentic System for Complex Image Restoration Problems. Kaiwen Zhu, Jinjin Gu, Zhiyuan You, Yu Qiao, Chao Dong |
| 2025 | An Online Learning Theory of Trading-Volume Maximization. Tommaso Cesari, Roberto Colomboni |
| 2025 | An Optimal Discriminator Weighted Imitation Perspective for Reinforcement Learning. Haoran Xu, Shuozhe Li, Harshit Sikchi, Scott Niekum, Amy Zhang |
| 2025 | An Undetectable Watermark for Generative Image Models. Sam Gunn, Xuandong Zhao, Dawn Song |
| 2025 | AnalogGenie: A Generative Engine for Automatic Discovery of Analog Circuit Topologies. Jian Gao, Weidong Cao, Junyi Yang, Xuan Zhang |
| 2025 | Analysis of Linear Mode Connectivity via Permutation-Based Weight Matching: With Insights into Other Permutation Search Methods. Akira Ito, Masanori Yamada, Atsutoshi Kumagai |
| 2025 | Analytic DAG Constraints for Differentiable DAG Learning. Zhen Zhang, Ignavier Ng, Dong Gong, Yuhang Liu, Mingming Gong, Biwei Huang, Kun Zhang, Anton van den Hengel, Javen Qinfeng Shi |
| 2025 | Analyzing Neural Scaling Laws in Two-Layer Networks with Power-Law Data Spectra. Roman Worschech, Bernd Rosenow |
| 2025 | Analyzing and Boosting the Power of Fine-Grained Visual Recognition for Multi-modal Large Language Models. Hulingxiao He, Geng Li, Zijun Geng, Jinglin Xu, Yuxin Peng |
| 2025 | AndroidWorld: A Dynamic Benchmarking Environment for Autonomous Agents. Christopher Rawles, Sarah Clinckemaillie, Yifan Chang, Jonathan Waltz, Gabrielle Lau, Marybeth Fair, Alice Li, William E. Bishop, Wei Li, Folawiyo Campbell-Ajala, Daniel Kenji Toyama, Robert James Berry, Divya Tyamagundlu, Timothy P. Lillicrap, Oriana Riva |
| 2025 | AniSDF: Fused-Granularity Neural Surfaces with Anisotropic Encoding for High-Fidelity 3D Reconstruction. Jingnan Gao, Zhuo Chen, Xiaokang Yang, Yichao Yan |
| 2025 | Animate Your Thoughts: Reconstruction of Dynamic Natural Vision from Human Brain Activity. Yizhuo Lu, Changde Du, Chong Wang, Xuanliu Zhu, Liuyun Jiang, Xujin Li, Huiguang He |
| 2025 | Animate-X: Universal Character Image Animation with Enhanced Motion Representation. Shuai Tan, Biao Gong, Xiang Wang, Shiwei Zhang, Dandan Zheng, Ruobing Zheng, Kecheng Zheng, Jingdong Chen, Ming Yang |
| 2025 | AnoLLM: Large Language Models for Tabular Anomaly Detection. Che-Ping Tsai, Ganyu Teng, Phillip Wallis, Wei Ding |
| 2025 | Answer, Assemble, Ace: Understanding How LMs Answer Multiple Choice Questions. Sarah Wiegreffe, Oyvind Tafjord, Yonatan Belinkov, Hannaneh Hajishirzi, Ashish Sabharwal |
| 2025 | Anti-Exposure Bias in Diffusion Models. Junyu Zhang, Daochang Liu, Eunbyung Park, Shichao Zhang, Chang Xu |
| 2025 | Any-step Dynamics Model Improves Future Predictions for Online and Offline Reinforcement Learning. Haoxin Lin, Yu-Yan Xu, Yihao Sun, Zhilong Zhang, Yi-Chen Li, Chengxing Jia, Junyin Ye, Jiaji Zhang, Yang Yu |
| 2025 | AnyTouch: Learning Unified Static-Dynamic Representation across Multiple Visuo-tactile Sensors. Ruoxuan Feng, Jiangyu Hu, Wenke Xia, Tianci Gao, Ao Shen, Yuhao Sun, Bin Fang, Di Hu |
| 2025 | Anyprefer: An Agentic Framework for Preference Data Synthesis. Yiyang Zhou, Zhaoyang Wang, Tianle Wang, Shangyu Xing, Peng Xia, Bo Li, Kaiyuan Zheng, Zijian Zhang, Zhaorun Chen, Wenhao Zheng, Xuchao Zhang, Chetan Bansal, Weitong Zhang, Ying Wei, Mohit Bansal, Huaxiu Yao |
| 2025 | Apollo-MILP: An Alternating Prediction-Correction Neural Solving Framework for Mixed-Integer Linear Programming. Haoyang Liu, Jie Wang, Zijie Geng, Xijun Li, Yuxuan Zong, Fangzhou Zhu, Jianye Hao, Feng Wu |
| 2025 | Approaching Rate-Distortion Limits in Neural Compression with Lattice Transform Coding. Eric Lei, Hamed Hassani, Shirin Saeedi Bidokhti |
| 2025 | Approximating Full Conformal Prediction for Neural Network Regression with Gauss-Newton Influence. Dharmesh Tailor, Alvaro H. C. Correia, Eric T. Nalisnick, Christos Louizos |
| 2025 | Approximation algorithms for combinatorial optimization with predictions. Antonios Antoniadis, Marek Eliás, Adam Polak, Moritz Venzin |
| 2025 | Are Large Vision Language Models Good Game Players? Xinyu Wang, Bohan Zhuang, Qi Wu |
| 2025 | Are Transformers Able to Reason by Connecting Separated Knowledge in Training Data? Yutong Yin, Zhaoran Wang |
| 2025 | Aria-MIDI: A Dataset of Piano MIDI Files for Symbolic Music Modeling. Louis Bradshaw, Simon Colton |
| 2025 | Arithmetic Transformers Can Length-Generalize in Both Operand Length and Count. Hanseul Cho, Jaeyoung Cha, Srinadh Bhojanapalli, Chulhee Yun |
| 2025 | Arithmetic Without Algorithms: Language Models Solve Math with a Bag of Heuristics. Yaniv Nikankin, Anja Reusch, Aaron Mueller, Yonatan Belinkov |
| 2025 | Articulate-Anything: Automatic Modeling of Articulated Objects via a Vision-Language Foundation Model. Long Le, Jason Xie, William Liang, Hung-Ju Wang, Yue Yang, Yecheng Jason Ma, Kyle Vedder, Arjun Krishna, Dinesh Jayaraman, Eric Eaton |
| 2025 | Artificial Kuramoto Oscillatory Neurons. Takeru Miyato, Sindy Löwe, Andreas Geiger, Max Welling |
| 2025 | As Simple as Fine-tuning: LLM Alignment via Bidirectional Negative Feedback Loss. Xin Mao, Huimin Xu, Feng-Lin Li, Ziqi Jin, Wang Chen, Wei Zhang, Anh Tuan Luu |
| 2025 | Ask, and it shall be given: On the Turing completeness of prompting. Ruizhong Qiu, Zhe Xu, Wenxuan Bao, Hanghang Tong |
| 2025 | AssembleFlow: Rigid Flow Matching with Inertial Frames for Molecular Assembly. Hongyu Guo, Yoshua Bengio, Shengchao Liu |
| 2025 | Associative memory and dead neurons. Vladimir Fanaskov, Ivan V. Oseledets |
| 2025 | AstroCompress: A benchmark dataset for multi-purpose compression of astronomical data. Tuan Truong, Rithwik Sudharsan, Yibo Yang, Peter Xiangyuan Ma, Ruihan Yang, Stephan Mandt, Joshua S. Bloom |
| 2025 | Asymmetric Factorized Bilinear Operation for Vision Transformer. Junjie Wu, Qilong Wang, Jiangtao Xie, Pengfei Zhu, Qinghua Hu |
| 2025 | Asymptotic Analysis of Two-Layer Neural Networks after One Gradient Step under Gaussian Mixtures Data with Structure. Samet Demir, Zafer Dogan |
| 2025 | Asynchronous Federated Reinforcement Learning with Policy Gradient Updates: Algorithm Design and Convergence Analysis. Guangchen Lan, Dong-Jun Han, Abolfazl Hashemi, Vaneet Aggarwal, Christopher Brinton |
| 2025 | Asynchronous RLHF: Faster and More Efficient Off-Policy RL for Language Models. Michael Noukhovitch, Shengyi Huang, Sophie Xhonneux, Arian Hosseini, Rishabh Agarwal, Aaron C. Courville |
| 2025 | Atlas Gaussians Diffusion for 3D Generation. Haitao Yang, Yuan Dong, Hanwen Jiang, Dejia Xu, Georgios Pavlakos, Qixing Huang |
| 2025 | AtomSurf: Surface Representation for Learning on Protein Structures. Vincent Mallet, Yangyang Miao, Souhaib Attaiki, Bruno Correia, Maks Ovsjanikov |
| 2025 | Atomas: Hierarchical Adaptive Alignment on Molecule-Text for Unified Molecule Understanding and Generation. Yikun Zhang, Geyan Ye, Chaohao Yuan, Bo Han, Long-Kai Huang, Jianhua Yao, Wei Liu, Yu Rong |
| 2025 | Attention as a Hypernetwork. Simon Schug, Seijin Kobayashi, Yassir Akram, João Sacramento, Razvan Pascanu |
| 2025 | Attention in Large Language Models Yields Efficient Zero-Shot Re-Rankers. Shijie Chen, Bernal Jimenez Gutierrez, Yu Su |
| 2025 | Attention layers provably solve single-location regression. Pierre Marion, Raphaël Berthier, Gérard Biau, Claire Boyer |
| 2025 | Attention with Markov: A Curious Case of Single-layer Transformers. Ashok Vardhan Makkuva, Marco Bondaschi, Adway Girish, Alliot Nagle, Martin Jaggi, Hyeji Kim, Michael Gastpar |
| 2025 | AttriBoT: A Bag of Tricks for Efficiently Approximating Leave-One-Out Context Attribution. Fengyuan Liu, Nikhil Kandpal, Colin Raffel |
| 2025 | Attribute-based Visual Reprogramming for Vision-Language Models. Chengyi Cai, Zesheng Ye, Lei Feng, Jianzhong Qi, Feng Liu |
| 2025 | Attributing Culture-Conditioned Generations to Pretraining Corpora. Huihan Li, Arnav Goel, Keyu He, Xiang Ren |
| 2025 | Audio Large Language Models Can Be Descriptive Speech Quality Evaluators. Chen Chen, Yuchen Hu, Siyin Wang, Helin Wang, Zhehuai Chen, Chao Zhang, Chao-Han Huck Yang, Eng Siong Chng |
| 2025 | AugKD: Ingenious Augmentations Empower Knowledge Distillation for Image Super-Resolution. Yun Zhang, Wei Li, Simiao Li, Hanting Chen, Zhijun Tu, Bingyi Jing, Shaohui Lin, Jie Hu, Wenjia Wang |
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| 2025 | Auto-GDA: Automatic Domain Adaptation for Efficient Grounding Verification in Retrieval-Augmented Generation. Tobias Leemann, Periklis Petridis, Giuseppe Vietri, Dionysis Manousakas, Aaron Roth, Sergül Aydöre |
| 2025 | AutoBencher: Towards Declarative Benchmark Construction. Xiang Lisa Li, Farzaan Kaiyom, Evan Zheran Liu, Yifan Mai, Percy Liang, Tatsunori Hashimoto |
| 2025 | AutoCGP: Closed-Loop Concept-Guided Policies from Unlabeled Demonstrations. Pei Zhou, Ruizhe Liu, Qian Luo, Fan Wang, Yibing Song, Yanchao Yang |
| 2025 | AutoDAN-Turbo: A Lifelong Agent for Strategy Self-Exploration to Jailbreak LLMs. Xiaogeng Liu, Peiran Li, G. Edward Suh, Yevgeniy Vorobeychik, Zhuoqing Mao, Somesh Jha, Patrick McDaniel, Huan Sun, Bo Li, Chaowei Xiao |
| 2025 | AutoG: Towards automatic graph construction from tabular data. Zhikai Chen, Han Xie, Jian Zhang, Xiang Song, Jiliang Tang, Huzefa Rangwala, George Karypis |
| 2025 | AutoUAD: Hyper-parameter Optimization for Unsupervised Anomaly Detection. Wei Dai, Jicong Fan |
| 2025 | Autocorrelation Matters: Understanding the Role of Initialization Schemes for State Space Models. Fusheng Liu, Qianxiao Li |
| 2025 | Automated Design of Agentic Systems. Shengran Hu, Cong Lu, Jeff Clune |
| 2025 | Automated Filtering of Human Feedback Data for Aligning Text-to-Image Diffusion Models. Yongjin Yang, Sihyeon Kim, Hojung Jung, Sangmin Bae, Sangmook Kim, Se-Young Yun, Kimin Lee |
| 2025 | Automated Proof Generation for Rust Code via Self-Evolution. Tianyu Chen, Shuai Lu, Shan Lu, Yeyun Gong, Chenyuan Yang, Xuheng Li, Md Rakib Hossain Misu, Hao Yu, Nan Duan, Peng Cheng, Fan Yang, Shuvendu K. Lahiri, Tao Xie, Lidong Zhou |
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| 2025 | B-STaR: Monitoring and Balancing Exploration and Exploitation in Self-Taught Reasoners. Weihao Zeng, Yuzhen Huang, Lulu Zhao, Yijun Wang, Zifei Shan, Junxian He |
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| 2025 | BANGS: Game-theoretic Node Selection for Graph Self-Training. Fangxin Wang, Kay Liu, Sourav Medya, Philip S. Yu |
| 2025 | BEEM: Boosting Performance of Early Exit DNNs using Multi-Exit Classifiers as Experts. Divya Jyoti Bajpai, Manjesh Kumar Hanawal |
| 2025 | BIRD: A Trustworthy Bayesian Inference Framework for Large Language Models. Yu Feng, Ben Zhou, Weidong Lin, Dan Roth |
| 2025 | BLEND: Behavior-guided Neural Population Dynamics Modeling via Privileged Knowledge Distillation. Zhengrui Guo, Fangxu Zhou, Wei Wu, Qichen Sun, Lishuang Feng, Jinzhuo Wang, Hao Chen |
| 2025 | BOFormer: Learning to Solve Multi-Objective Bayesian Optimization via Non-Markovian RL. Yu-Heng Hung, Kai-Jie Lin, Yu-Heng Lin, Chien-Yi Wang, Cheng Sun, Ping-Chun Hsieh |
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| 2025 | BP-Modified Local Loss for Efficient Training of Deep Neural Networks. Lianhai Ren, Qianxiao Li |
| 2025 | BRAID: Input-driven Nonlinear Dynamical Modeling of Neural-Behavioral Data. Parsa Vahidi, Omid G. Sani, Maryam Shanechi |
| 2025 | BRIGHT: A Realistic and Challenging Benchmark for Reasoning-Intensive Retrieval. Hongjin Su, Howard Yen, Mengzhou Xia, Weijia Shi, Niklas Muennighoff, Han-yu Wang, Haisu Liu, Quan Shi, Zachary S. Siegel, Michael Tang, Ruoxi Sun, Jinsung Yoon, Sercan Ö. Arik, Danqi Chen, Tao Yu |
| 2025 | BTBS-LNS: Binarized-Tightening, Branch and Search on Learning LNS Policies for MIP. Hao Yuan, Wenli Ouyang, Changwen Zhang, Yong Sun, Liming Gong, Junchi Yan |
| 2025 | BaB-ND: Long-Horizon Motion Planning with Branch-and-Bound and Neural Dynamics. Keyi Shen, Jiangwei Yu, Jose A. Barreiros, Huan Zhang, Yunzhu Li |
| 2025 | Backdooring Vision-Language Models with Out-Of-Distribution Data. Weimin Lyu, Jiachen Yao, Saumya Gupta, Lu Pang, Tao Sun, Lingjie Yi, Lijie Hu, Haibin Ling, Chao Chen |
| 2025 | Backtracking Improves Generation Safety. Yiming Zhang, Jianfeng Chi, Hailey Nguyen, Kartikeya Upasani, Daniel M. Bikel, Jason E. Weston, Eric Michael Smith |
| 2025 | Bad-PFL: Exploiting Backdoor Attacks against Personalized Federated Learning. Mingyuan Fan, Zhanyi Hu, Fuyi Wang, Cen Chen |
| 2025 | BadJudge: Backdoor Vulnerabilities of LLM-As-A-Judge. Terry Tong, Fei Wang, Zhe Zhao, Muhao Chen |
| 2025 | BadRobot: Jailbreaking Embodied LLM Agents in the Physical World. Hangtao Zhang, Chenyu Zhu, Xianlong Wang, Ziqi Zhou, Changgan Yin, Minghui Li, Lulu Xue, Yichen Wang, Shengshan Hu, Aishan Liu, Peijin Guo, Leo Yu Zhang |
| 2025 | Balanced Neural ODEs: nonlinear model order reduction and Koopman operator approximations. Julius Aka, Johannes Brunnemann, Jörg Eiden, Arne Speerforck, Lars Mikelsons |
| 2025 | Balanced Ranking with Relative Centrality: A multi-core periphery perspective. Chandra Sekhar Mukherjee, Jiapeng Zhang |
| 2025 | Balancing Act: Diversity and Consistency in Large Language Model Ensembles. Ahmed Abdulaal, Chen Jin, Nina Montaña Brown, Aryo Pradipta Gema, Daniel C. Castro, Daniel C. Alexander, Philip Alexander Teare, Tom Diethe, Dino Oglic, Amrutha Saseendran |
| 2025 | Balancing Bias in Two-sided Markets for Fair Stable Matchings. Siyuan Wu, Leong Hou U, Panagiotis Karras |
| 2025 | Bandit Learning in Matching Markets with Indifference. Fang Kong, Jingqi Tang, Mingzhu Li, Pinyan Lu, John C. S. Lui, Shuai Li |
| 2025 | Basis Sharing: Cross-Layer Parameter Sharing for Large Language Model Compression. Jingcun Wang, Yu-Guang Chen, Ing-Chao Lin, Bing Li, Grace Li Zhang |
| 2025 | Bayesian Analysis of Combinatorial Gaussian Process Bandits. Jack Sandberg, Niklas Åkerblom, Morteza Haghir Chehreghani |
| 2025 | Bayesian Experimental Design Via Contrastive Diffusions. Jacopo Iollo, Christophe Heinkelé, Pierre Alliez, Florence Forbes |
| 2025 | Bayesian Image Regression with Soft-thresholded Conditional Autoregressive Prior. Yuliang Xu, Jian Kang |
| 2025 | Bayesian Optimization of Antibodies Informed by a Generative Model of Evolving Sequences. Alan Nawzad Amin, Nate Gruver, Yilun Kuang, Yucen Lily Li, Hunter Elliott, Calvin McCarter, Aniruddh Raghu, Peyton Greenside, Andrew Gordon Wilson |
| 2025 | Bayesian Optimization via Continual Variational Last Layer Training. Paul Brunzema, Mikkel Jordahn, John Willes, Sebastian Trimpe, Jasper Snoek, James Harrison |
| 2025 | Bayesian Regularization of Latent Representation. Chukwudi Paul Obite, Zhi Chang, Keyan Wu, Shiwei Lan |
| 2025 | Bayesian Treatment of the Spectrum of the Empirical Kernel in (Sub)Linear-Width Neural Networks. Ouns El Harzli, Bernardo Cuenca Grau |
| 2025 | Bayesian WeakS-to-Strong from Text Classification to Generation. Ziyun Cui, Ziyang Zhang, Guangzhi Sun, Wen Wu, Chao Zhang |
| 2025 | Be More Diverse than the Most Diverse: Optimal Mixtures of Generative Models via Mixture-UCB Bandit Algorithms. Parham Rezaei, Farzan Farnia, Cheuk Ting Li |
| 2025 | Behavioral Entropy-Guided Dataset Generation for Offline Reinforcement Learning. Wesley A. Suttle, Aamodh Suresh, Carlos Nieto-Granda |
| 2025 | BenTo: Benchmark Reduction with In-Context Transferability. Hongyu Zhao, Ming Li, Lichao Sun, Tianyi Zhou |
| 2025 | Benchmarking Agentic Workflow Generation. Shuofei Qiao, Runnan Fang, Zhisong Qiu, Xiaobin Wang, Ningyu Zhang, Yong Jiang, Pengjun Xie, Fei Huang, Huajun Chen |
| 2025 | Benchmarking LLMs' Judgments with No Gold Standard. Shengwei Xu, Yuxuan Lu, Grant Schoenebeck, Yuqing Kong |
| 2025 | Benchmarking Multimodal Retrieval Augmented Generation with Dynamic VQA Dataset and Self-adaptive Planning Agent. Yangning Li, Yinghui Li, Xinyu Wang, Yong Jiang, Zhen Zhang, Xinran Zheng, Hui Wang, Hai-Tao Zheng, Fei Huang, Jingren Zhou, Philip S. Yu |
| 2025 | Benchmarking Predictive Coding Networks - Made Simple. Luca Pinchetti, Chang Qi, Oleh Lokshyn, Cornelius Emde, Amine M'Charrak, Mufeng Tang, Simon Frieder, Bayar Menzat, Gaspard Oliviers, Rafal Bogacz, Thomas Lukasiewicz, Tommaso Salvatori |
| 2025 | Benchmarking Vision Language Model Unlearning via Fictitious Facial Identity Dataset. Yingzi Ma, Jiongxiao Wang, Fei Wang, Siyuan Ma, Jiazhao Li, Jinsheng Pan, Xiujun Li, Furong Huang, Lichao Sun, Bo Li, Yejin Choi, Muhao Chen, Chaowei Xiao |
| 2025 | Benign Overfitting in Out-of-Distribution Generalization of Linear Models. Shange Tang, Jiayun Wu, Jianqing Fan, Chi Jin |
| 2025 | Better Instruction-Following Through Minimum Bayes Risk. Ian Wu, Patrick Fernandes, Amanda Bertsch, Seungone Kim, Sina Khoshfetrat Pakazad, Graham Neubig |
| 2025 | Better autoregressive regression with LLMs via regression-aware fine-tuning. Michal Lukasik, Zhao Meng, Harikrishna Narasimhan, Yin-Wen Chang, Aditya Krishna Menon, Felix Yu, Sanjiv Kumar |
| 2025 | Better than Your Teacher: LLM Agents that learn from Privileged AI Feedback. Sanjiban Choudhury, Paloma Sodhi |
| 2025 | Beware of Calibration Data for Pruning Large Language Models. Yixin Ji, Yang Xiang, Juntao Li, Qingrong Xia, Ping Li, Xinyu Duan, Zhefeng Wang, Min Zhang |
| 2025 | Beyond Autoregression: Discrete Diffusion for Complex Reasoning and Planning. Jiacheng Ye, Jiahui Gao, Shansan Gong, Lin Zheng, Xin Jiang, Zhenguo Li, Lingpeng Kong |
| 2025 | Beyond Autoregression: Fast LLMs via Self-Distillation Through Time. Justin Deschenaux, Caglar Gulcehre |
| 2025 | Beyond Canonicalization: How Tensorial Messages Improve Equivariant Message Passing. Peter Lippmann, Gerrit Gerhartz, Roman Remme, Fred A. Hamprecht |
| 2025 | Beyond Circuit Connections: A Non-Message Passing Graph Transformer Approach for Quantum Error Mitigation. Tianyi Bao, Xinyu Ye, Hang Ruan, Chang Liu, Wenjie Wu, Junchi Yan |
| 2025 | Beyond Content Relevance: Evaluating Instruction Following in Retrieval Models. Jianqun Zhou, Yuanlei Zheng, Wei Chen, Qianqian Zheng, Zeyuan Shang, Wei Zhang, Rui Meng, Xiaoyu Shen |
| 2025 | Beyond FVD: An Enhanced Evaluation Metrics for Video Generation Distribution Quality. Ge Ya Luo, Gian Mario Favero, Zhi Hao Luo, Alexia Jolicoeur-Martineau, Christopher Pal |
| 2025 | Beyond Graphs: Can Large Language Models Comprehend Hypergraphs? Yifan Feng, Chengwu Yang, Xingliang Hou, Shaoyi Du, Shihui Ying, Zongze Wu, Yue Gao |
| 2025 | Beyond Interpretability: The Gains of Feature Monosemanticity on Model Robustness. Qi Zhang, Yifei Wang, Jingyi Cui, Xiang Pan, Qi Lei, Stefanie Jegelka, Yisen Wang |
| 2025 | Beyond Linear Approximations: A Novel Pruning Approach for Attention Matrix. Yingyu Liang, Jiangxuan Long, Zhenmei Shi, Zhao Song, Yufa Zhou |
| 2025 | Beyond Mere Token Analysis: A Hypergraph Metric Space Framework for Defending Against Socially Engineered LLM Attacks. Manohar Kaul, Aditya Saibewar, Sadbhavana Babar |
| 2025 | Beyond Model Collapse: Scaling Up with Synthesized Data Requires Verification. Yunzhen Feng, Elvis Dohmatob, Pu Yang, François Charton, Julia Kempe |
| 2025 | Beyond Next Token Prediction: Patch-Level Training for Large Language Models. Chenze Shao, Fandong Meng, Jie Zhou |
| 2025 | Beyond Random Augmentations: Pretraining with Hard Views. Fabio Ferreira, Ivo Rapant, Jörg K. H. Franke, Frank Hutter |
| 2025 | Beyond Random Masking: When Dropout meets Graph Convolutional Networks. Yuankai Luo, Xiao-Ming Wu, Hao Zhu |
| 2025 | Beyond Sequence: Impact of Geometric Context for RNA Property Prediction. Junjie Xu, Artem Moskalev, Tommaso Mansi, Mangal Prakash, Rui Liao |
| 2025 | Beyond Single Concept Vector: Modeling Concept Subspace in LLMs with Gaussian Distribution. Haiyan Zhao, Heng Zhao, Bo Shen, Ali Payani, Fan Yang, Mengnan Du |
| 2025 | Beyond Squared Error: Exploring Loss Design for Enhanced Training of Generative Flow Networks. Rui Hu, Yifan Zhang, Zhuoran Li, Longbo Huang |
| 2025 | Beyond Surface Structure: A Causal Assessment of LLMs' Comprehension ability. Yujin Han, Lei Xu, Sirui Chen, Difan Zou, Chaochao Lu |
| 2025 | Beyond Worst-Case Dimensionality Reduction for Sparse Vectors. Sandeep Silwal, David P. Woodruff, Qiuyi Zhang |
| 2025 | Beyond correlation: The impact of human uncertainty in measuring the effectiveness of automatic evaluation and LLM-as-a-judge. Aparna Elangovan, Lei Xu, Jongwoo Ko, Mahsa Elyasi, Ling Liu, Sravan Babu Bodapati, Dan Roth |
| 2025 | Beyond single neurons: population response geometry in digital twins of mouse visual cortex. Dario Liscai, Emanuele Luconi, Alessandro Marin Vargas, Alessandro Sanzeni |
| 2025 | Beyond the convexity assumption: Realistic tabular data generation under quantifier-free real linear constraints. Mihaela C. Stoian, Eleonora Giunchiglia |
| 2025 | Beyond-Expert Performance with Limited Demonstrations: Efficient Imitation Learning with Double Exploration. Heyang Zhao, Xingrui Yu, David Mark Bossens, Ivor W. Tsang, Quanquan Gu |
| 2025 | Bi-Factorial Preference Optimization: Balancing Safety-Helpfulness in Language Models. Wenxuan Zhang, Philip Torr, Mohamed Elhoseiny, Adel Bibi |
| 2025 | BiGR: Harnessing Binary Latent Codes for Image Generation and Improved Visual Representation Capabilities. Shaozhe Hao, Xuantong Liu, Xianbiao Qi, Shihao Zhao, Bojia Zi, Rong Xiao, Kai Han, Kwan-Yee K. Wong |
| 2025 | Bias Mitigation in Graph Diffusion Models. Meng Yu, Kun Zhang |
| 2025 | Bidirectional Decoding: Improving Action Chunking via Guided Test-Time Sampling. Yuejiang Liu, Jubayer Ibn Hamid, Annie Xie, Yoonho Lee, Max Du, Chelsea Finn |
| 2025 | BigCodeBench: Benchmarking Code Generation with Diverse Function Calls and Complex Instructions. Terry Yue Zhuo, Minh Chien Vu, Jenny Chim, Han Hu, Wenhao Yu, Ratnadira Widyasari, Imam Nur Bani Yusuf, Haolan Zhan, Junda He, Indraneil Paul, Simon Brunner, Chen Gong, James Hoang, Armel Randy Zebaze, Xiaoheng Hong, Wen-Ding Li, Jean Kaddour, Ming Xu, Zhihan Zhang, Prateek Yadav, et al. |
| 2025 | BigDocs: An Open Dataset for Training Multimodal Models on Document and Code Tasks. Juan A. Rodríguez, Xiangru Jian, Siba Smarak Panigrahi, Tianyu Zhang, Aarash Feizi, Abhay Puri, Akshay Kalkunte Suresh, François Savard, Ahmed Masry, Shravan Nayak, Rabiul Awal, Mahsa Massoud, Amirhossein Abaskohi, Zichao Li, Suyuchen Wang, Pierre-André Noël, Mats Leon Richter, Saverio Vadacchino, Shubham Agarwal, Sanket Biswas, et al. |
| 2025 | Bilinear MLPs enable weight-based mechanistic interpretability. Michael T. Pearce, Thomas Dooms, Alice Rigg, José Oramas, Lee Sharkey |
| 2025 | Binary Losses for Density Ratio Estimation. Werner Zellinger |
| 2025 | BinaryDM: Accurate Weight Binarization for Efficient Diffusion Models. Xingyu Zheng, Xianglong Liu, Haotong Qin, Xudong Ma, Mingyuan Zhang, Haojie Hao, Jiakai Wang, Zixiang Zhao, Jinyang Guo, Michele Magno |
| 2025 | BingoGuard: LLM Content Moderation Tools with Risk Levels. Fan Yin, Philippe Laban, Xiangyu Peng, Yilun Zhou, Yixin Mao, Vaibhav Vats, Linnea Ross, Divyansh Agarwal, Caiming Xiong, Chien-Sheng Wu |
| 2025 | Bio-xLSTM: Generative modeling, representation and in-context learning of biological and chemical sequences. Niklas Schmidinger, Lisa Schneckenreiter, Philipp Seidl, Johannes Schimunek, Pieter-Jan Hoedt, Johannes Brandstetter, Andreas Mayr, Sohvi Luukkonen, Sepp Hochreiter, Günter Klambauer |
| 2025 | BioDiscoveryAgent: An AI Agent for Designing Genetic Perturbation Experiments. Yusuf H. Roohani, Andrew H. Lee, Qian Huang, Jian Vora, Zachary Steinhart, Kexin Huang, Alexander Marson, Percy Liang, Jure Leskovec |
| 2025 | Biologically Constrained Barrel Cortex Model Integrates Whisker Inputs and Replicates Key Brain Network Dynamics. Tianfang Zhu, Dongli Hu, Jiandong Zhou, Kai Du, Anan Li |
| 2025 | Biologically Plausible Brain Graph Transformer. Ciyuan Peng, Yuelong Huang, Qichao Dong, Shuo Yu, Feng Xia, Chengqi Zhang, Yaochu Jin |
| 2025 | BirdSet: A Large-Scale Dataset for Audio Classification in Avian Bioacoustics. Lukas Rauch, Raphael Schwinger, Moritz Wirth, René Heinrich, Denis Huseljic, Marek Herde, Jonas Lange, Stefan Kahl, Bernhard Sick, Sven Tomforde, Christoph Scholz |
| 2025 | Bisimulation Metric for Model Predictive Control. Yutaka Shimizu, Masayoshi Tomizuka |
| 2025 | BitStack: Any-Size Compression of Large Language Models in Variable Memory Environments. Xinghao Wang, Pengyu Wang, Bo Wang, Dong Zhang, Yunhua Zhou, Xipeng Qiu |
| 2025 | Black Sheep in the Herd: Playing with Spuriously Correlated Attributes for Vision-Language Recognition. Xinyu Tian, Shu Zou, Zhaoyuan Yang, Mengqi He, Jing Zhang |
| 2025 | Black-Box Detection of Language Model Watermarks. Thibaud Gloaguen, Nikola Jovanovic, Robin Staab, Martin T. Vechev |
| 2025 | BlendRL: A Framework for Merging Symbolic and Neural Policy Learning. Hikaru Shindo, Quentin Delfosse, Devendra Singh Dhami, Kristian Kersting |
| 2025 | Block Diffusion: Interpolating Between Autoregressive and Diffusion Language Models. Marianne Arriola, Aaron Gokaslan, Justin T. Chiu, Zhihan Yang, Zhixuan Qi, Jiaqi Han, Subham Sekhar Sahoo, Volodymyr Kuleshov |
| 2025 | Block Verification Accelerates Speculative Decoding. Ziteng Sun, Uri Mendlovic, Yaniv Leviathan, Asaf Aharoni, Jae Hun Ro, Ahmad Beirami, Ananda Theertha Suresh |
| 2025 | Block-Attention for Efficient Prefilling. Dongyang Ma, Yan Wang, Tian Lan |
| 2025 | BlueSuffix: Reinforced Blue Teaming for Vision-Language Models Against Jailbreak Attacks. Yunhan Zhao, Xiang Zheng, Lin Luo, Yige Li, Xingjun Ma, Yu-Gang Jiang |
| 2025 | BodyGen: Advancing Towards Efficient Embodiment Co-Design. Haofei Lu, Zhe Wu, Junliang Xing, Jianshu Li, Ruoyu Li, Zhe Li, Yuanchun Shi |
| 2025 | Boltzmann Semantic Score: A Semantic Metric for Evaluating Large Vision Models Using Large Language Models. Ali Khajegili Mirabadi, Katherine Rich, Hossein Farahani, Ali Bashashati |
| 2025 | Boltzmann priors for Implicit Transfer Operators. Juan Viguera Diez, Mathias Jacob Schreiner, Ola Engkvist, Simon Olsson |
| 2025 | Boltzmann-Aligned Inverse Folding Model as a Predictor of Mutational Effects on Protein-Protein Interactions. Xiaoran Jiao, Weian Mao, Wengong Jin, Peiyuan Yang, Hao Chen, Chunhua Shen |
| 2025 | BoneMet: An Open Large-Scale Multi-Modal Murine Dataset for Breast Cancer Bone Metastasis Diagnosis and Prognosis. Tiankuo Chu, Fudong Lin, Shubo Wang, Jason Jiang, Wiley Jia-Wei Gong, Xu Yuan, Liyun Wang |
| 2025 | Bonsai: Gradient-free Graph Condensation for Node Classification. Mridul Gupta, Samyak Jain, Vansh Ramani, Hariprasad Kodamana, Sayan Ranu |
| 2025 | Boost Self-Supervised Dataset Distillation via Parameterization, Predefined Augmentation, and Approximation. Sheng-Feng Yu, Jia-Jiun Yao, Wei-Chen Chiu |
| 2025 | Booster: Tackling Harmful Fine-tuning for Large Language Models via Attenuating Harmful Perturbation. Tiansheng Huang, Sihao Hu, Fatih Ilhan, Selim Furkan Tekin, Ling Liu |
| 2025 | Boosting Latent Diffusion with Perceptual Objectives. Tariq Berrada, Pietro Astolfi, Melissa Hall, Marton Havasi, Yohann Benchetrit, Adriana Romero-Soriano, Karteek Alahari, Michal Drozdzal, Jakob Verbeek |
| 2025 | Boosting Methods for Interval-censored Data with Regression and Classification. Yuan Bian, Grace Y. Yi, Wenqing He |
| 2025 | Boosting Multiple Views for pretrained-based Continual Learning. Quyen Tran, Tung Lam Tran, Khanh Doan, Toan Tran, Dinh Q. Phung, Khoat Than, Trung Le |
| 2025 | Boosting Neural Combinatorial Optimization for Large-Scale Vehicle Routing Problems. Fu Luo, Xi Lin, Yaoxin Wu, Zhenkun Wang, Xialiang Tong, Mingxuan Yuan, Qingfu Zhang |
| 2025 | Boosting Perturbed Gradient Ascent for Last-Iterate Convergence in Games. Kenshi Abe, Mitsuki Sakamoto, Kaito Ariu, Atsushi Iwasaki |
| 2025 | Boosting Ray Search Procedure of Hard-label Attacks with Transfer-based Priors. Chen Ma, Xinjie Xu, Shuyu Cheng, Qi Xuan |
| 2025 | Boosting the visual interpretability of CLIP via adversarial fine-tuning. Shizhan Gong, Haoyu Lei, Qi Dou, Farzan Farnia |
| 2025 | Bootstrapped Model Predictive Control. Yuhang Wang, Hanwei Guo, Sizhe Wang, Long Qian, Xuguang Lan |
| 2025 | Bootstrapping Language Models with DPO Implicit Rewards. Changyu Chen, Zichen Liu, Chao Du, Tianyu Pang, Qian Liu, Arunesh Sinha, Pradeep Varakantham, Min Lin |
| 2025 | Bootstrapping Language-Guided Navigation Learning with Self-Refining Data Flywheel. Zun Wang, Jialu Li, Yicong Hong, Songze Li, Kunchang Li, Shoubin Yu, Yi Wang, Yu Qiao, Yali Wang, Mohit Bansal, Limin Wang |
| 2025 | Both Ears Wide Open: Towards Language-Driven Spatial Audio Generation. Peiwen Sun, Sitong Cheng, Xiangtai Li, Zhen Ye, Huadai Liu, Honggang Zhang, Wei Xue, Yike Guo |
| 2025 | Bounds on Lp Errors in Density Ratio Estimation via f-Divergence Loss Functions. Yoshiaki Kitazawa |
| 2025 | Brain Bandit: A Biologically Grounded Neural Network for Efficient Control of Exploration. Chen Jiang, Jiahui An, Yating Liu, Ni Ji |
| 2025 | Brain Mapping with Dense Features: Grounding Cortical Semantic Selectivity in Natural Images With Vision Transformers. Andrew F. Luo, Jacob Yeung, Rushikesh Zawar, Shaurya Dewan, Margaret M. Henderson, Leila Wehbe, Michael J. Tarr |
| 2025 | Brain-inspired Lp-Convolution benefits large kernels and aligns better with visual cortex. Jea Kwon, Sungjun Lim, Kyungwoo Song, C. Justin Lee |
| 2025 | BrainACTIV: Identifying visuo-semantic properties driving cortical selectivity using diffusion-based image manipulation. Diego Garcia Cerdas, Christina Sartzetaki, Magnus Petersen, Gemma Roig, Pascal Mettes, Iris I. A. Groen |
| 2025 | BrainOOD: Out-of-distribution Generalizable Brain Network Analysis. Jiaxing Xu, Yongqiang Chen, Xia Dong, Mengcheng Lan, Tiancheng Huang, Qingtian Bian, James Cheng, Yiping Ke |
| 2025 | BrainUICL: An Unsupervised Individual Continual Learning Framework for EEG Applications. Yangxuan Zhou, Sha Zhao, Jiquan Wang, Haiteng Jiang, Shijian Li, Tao Li, Gang Pan |
| 2025 | Breach By A Thousand Leaks: Unsafe Information Leakage in 'Safe' AI Responses. David Glukhov, Ziwen Han, Ilia Shumailov, Vardan Papyan, Nicolas Papernot |
| 2025 | Breaking Class Barriers: Efficient Dataset Distillation via Inter-Class Feature Compensator. Xin Zhang, Jiawei Du, Ping Liu, Joey Tianyi Zhou |
| 2025 | Breaking Free from MMI: A New Frontier in Rationalization by Probing Input Utilization. Wei Liu, Zhiying Deng, Zhongyu Niu, Jun Wang, Haozhao Wang, Zhigang Zeng, Ruixuan Li |
| 2025 | Breaking Mental Set to Improve Reasoning through Diverse Multi-Agent Debate. Yexiang Liu, Jie Cao, Zekun Li, Ran He, Tieniu Tan |
| 2025 | Breaking Neural Network Scaling Laws with Modularity. Akhilan Boopathy, Sunshine Jiang, William Yue, Jaedong Hwang, Abhiram Iyer, Ila R. Fiete |
| 2025 | Breaking the Reclustering Barrier in Centroid-based Deep Clustering. Lukas Miklautz, Timo Klein, Kevin Sidak, Collin Leiber, Thomas Lang, Andrii Shkabrii, Sebastian Tschiatschek, Claudia Plant |
| 2025 | Breaking the log(1/Δ2) Barrier: Better Batched Best Arm Identification with Adaptive Grids. Tianyuan Jin, Qin Zhang, Dongruo Zhou |
| 2025 | Bridging Compressed Image Latents and Multimodal Large Language Models. Chia-Hao Kao, Cheng Chien, Yu-Jen Tseng, Yi-Hsin Chen, Alessandro Gnutti, Shao-Yuan Lo, Wen-Hsiao Peng, Riccardo Leonardi |
| 2025 | Bridging Context Gaps: Leveraging Coreference Resolution for Long Contextual Understanding. Yanming Liu, Xinyue Peng, Jiannan Cao, Shi Bo, Yanxin Shen, Tianyu Du, Sheng Cheng, Xun Wang, Jianwei Yin, Xuhong Zhang |
| 2025 | Bridging Information Asymmetry in Text-video Retrieval: A Data-centric Approach. Zechen Bai, Tianjun Xiao, Tong He, Pichao Wang, Zheng Zhang, Thomas Brox, Mike Zheng Shou |
| 2025 | Bridging Jensen Gap for Max-Min Group Fairness Optimization in Recommendation. Chen Xu, Yuxin Li, Wenjie Wang, Liang Pang, Jun Xu, Tat-Seng Chua |
| 2025 | Bridging and Modeling Correlations in Pairwise Data for Direct Preference Optimization. Yuxin Jiang, Bo Huang, Yufei Wang, Xingshan Zeng, Liangyou Li, Yasheng Wang, Xin Jiang, Lifeng Shang, Ruiming Tang, Wei Wang |
| 2025 | Bridging the Data Provenance Gap Across Text, Speech, and Video. Shayne Longpre, Nikhil Singh, Manuel Cherep, Kushagra Tiwary, Joanna Materzynska, William Brannon, Robert Mahari, Naana Obeng-Marnu, Manan Dey, Mohammed Hamdy, Nayan Saxena, Ahmad Mustafa Anis, Emad A. Alghamdi, Vu Minh Chien, Da Yin, Kun Qian, Yizhi Li, Minnie Liang, An Dinh, Shrestha Mohanty, et al. |
| 2025 | Bridging the Gap Between f-divergences and Bayes Hilbert Spaces. Linus Lach, Alexander Willi Fottner, Yarema Okhrin |
| 2025 | Bridging the Gap between Database Search and De Novo Peptide Sequencing with SearchNovo. Jun Xia, Sizhe Liu, Jingbo Zhou, Shaorong Chen, Hongxin Xiang, Zicheng Liu, Yue Liu, Stan Z. Li |
| 2025 | Bridging the Gap between Variational Inference and Stochastic Gradient MCMC in Function Space. Mengjing Wu, Junyu Xuan, Jie Lu |
| 2025 | Bridging the Semantic Gap Between Text and Table: A Case Study on NL2SQL. Lin Long, Xijun Gu, Xinjie Sun, Wentao Ye, Haobo Wang, Sai Wu, Gang Chen, Junbo Zhao |
| 2025 | Bringing NeRFs to the Latent Space: Inverse Graphics Autoencoder. Antoine Schnepf, Karim Kassab, Jean-Yves Franceschi, Laurent Caraffa, Flavian Vasile, Jérémie Mary, Andrew I. Comport, Valérie Gouet-Brunet |
| 2025 | Broaden your SCOPE! Efficient Multi-turn Conversation Planning for LLMs with Semantic Space. Zhiliang Chen, Xinyuan Niu, Chuan-Sheng Foo, Bryan Kian Hsiang Low |
| 2025 | Broadening Target Distributions for Accelerated Diffusion Models via a Novel Analysis Approach. Yuchen Liang, Peizhong Ju, Yingbin Liang, Ness B. Shroff |
| 2025 | Budgeted Online Continual Learning by Adaptive Layer Freezing and Frequency-based Sampling. Minhyuk Seo, Hyunseo Koh, Jonghyun Choi |
| 2025 | Build-A-Scene: Interactive 3D Layout Control for Diffusion-Based Image Generation. Abdelrahman Eldesokey, Peter Wonka |
| 2025 | Building Interactable Replicas of Complex Articulated Objects via Gaussian Splatting. Yu Liu, Baoxiong Jia, Ruijie Lu, Junfeng Ni, Song-Chun Zhu, Siyuan Huang |
| 2025 | Building Math Agents with Multi-Turn Iterative Preference Learning. Wei Xiong, Chengshuai Shi, Jiaming Shen, Aviv Rosenberg, Zhen Qin, Daniele Calandriello, Misha Khalman, Rishabh Joshi, Bilal Piot, Mohammad Saleh, Chi Jin, Tong Zhang, Tianqi Liu |
| 2025 | Building, Reusing, and Generalizing Abstract Representations from Concrete Sequences. Shuchen Wu, Mirko Thalmann, Peter Dayan, Zeynep Akata, Eric Schulz |
| 2025 | Bundle Neural Network for message diffusion on graphs. Jacob Bamberger, Federico Barbero, Xiaowen Dong, Michael M. Bronstein |
| 2025 | C-CLIP: Multimodal Continual Learning for Vision-Language Model. Wenzhuo Liu, Fei Zhu, Longhui Wei, Qi Tian |
| 2025 | CAKE: Cascading and Adaptive KV Cache Eviction with Layer Preferences. Ziran Qin, Yuchen Cao, Mingbao Lin, Wen Hu, Shixuan Fan, Ke Cheng, Weiyao Lin, Jianguo Li |
| 2025 | CAMEx: Curvature-aware Merging of Experts. Viet Dung Nguyen, Minh Nguyen Hoang, Luc Q. Nguyen, Rachel S. Y. Teo, Tan Minh Nguyen, Linh Duy Tran |
| 2025 | CARTS: Advancing Neural Theorem Proving with Diversified Tactic Calibration and Bias-Resistant Tree Search. Xiao-Wen Yang, Zhi Zhou, Haiming Wang, Aoxue Li, Wen-Da Wei, Hui Jin, Zhenguo Li, Yu-Feng Li |
| 2025 | CAT-3DGS: A Context-Adaptive Triplane Approach to Rate-Distortion-Optimized 3DGS Compression. Yu-Ting Zhan, Cheng-Yuan Ho, Hebi Yang, Yi-Hsin Chen, Jui-Chiu Chiang, Yu-Lun Liu, Wen-Hsiao Peng |
| 2025 | CATCH: Channel-Aware Multivariate Time Series Anomaly Detection via Frequency Patching. Xingjian Wu, Xiangfei Qiu, Zhengyu Li, Yihang Wang, Jilin Hu, Chenjuan Guo, Hui Xiong, Bin Yang |
| 2025 | CAX: Cellular Automata Accelerated in JAX. Maxence Faldor, Antoine Cully |
| 2025 | CBGBench: Fill in the Blank of Protein-Molecule Complex Binding Graph. Haitao Lin, Guojiang Zhao, Odin Zhang, Yufei Huang, Lirong Wu, Cheng Tan, Zicheng Liu, Zhifeng Gao, Stan Z. Li |
| 2025 | CBMA: Improving Conformal Prediction through Bayesian Model Averaging. Pankaj Bhagwat, Linglong Kong, Bei Jiang |
| 2025 | CBQ: Cross-Block Quantization for Large Language Models. Xin Ding, Xiaoyu Liu, Zhijun Tu, Yun Zhang, Wei Li, Jie Hu, Hanting Chen, Yehui Tang, Zhiwei Xiong, Baoqun Yin, Yunhe Wang |
| 2025 | CBraMod: A Criss-Cross Brain Foundation Model for EEG Decoding. Jiquan Wang, Sha Zhao, Zhiling Luo, Yangxuan Zhou, Haiteng Jiang, Shijian Li, Tao Li, Gang Pan |
| 2025 | CEB: Compositional Evaluation Benchmark for Fairness in Large Language Models. Song Wang, Peng Wang, Tong Zhou, Yushun Dong, Zhen Tan, Jundong Li |
| 2025 | CFD: Learning Generalized Molecular Representation via Concept-Enhanced Feedback Disentanglement. Aming Wu, Cheng Deng |
| 2025 | CFG++: Manifold-constrained Classifier Free Guidance for Diffusion Models. Hyungjin Chung, Jeongsol Kim, Geon Yeong Park, Hyelin Nam, Jong Chul Ye |
| 2025 | CG-Bench: Clue-grounded Question Answering Benchmark for Long Video Understanding. Guo Chen, Yicheng Liu, Yifei Huang, Baoqi Pei, Jilan Xu, Yuping He, Tong Lu, Yali Wang, Limin Wang |
| 2025 | CHAMP: Conformalized 3D Human Multi-Hypothesis Pose Estimators. Harry Zhang, Luca Carlone |
| 2025 | CHASE-SQL: Multi-Path Reasoning and Preference Optimized Candidate Selection in Text-to-SQL. Mohammadreza Pourreza, Hailong Li, Ruoxi Sun, Yeounoh Chung, Shayan Talaei, Gaurav Tarlok Kakkar, Yu Gan, Amin Saberi, Fatma Ozcan, Sercan Ö. Arik |
| 2025 | CHiP: Cross-modal Hierarchical Direct Preference Optimization for Multimodal LLMs. Jinlan Fu, Shenzhen Huangfu, Hao Fei, Xiaoyu Shen, Bryan Hooi, Xipeng Qiu, See-Kiong Ng |
| 2025 | CL-DiffPhyCon: Closed-loop Diffusion Control of Complex Physical Systems. Long Wei, Haodong Feng, Yuchen Yang, Ruiqi Feng, Peiyan Hu, Xiang Zheng, Tao Zhang, Dixia Fan, Tailin Wu |
| 2025 | CL-MFAP: A Contrastive Learning-Based Multimodal Foundation Model for Molecular Property Prediction and Antibiotic Screening. Gen Zhou, Sugitha Janarthanan, Yutong Lu, Pingzhao Hu |
| 2025 | CLDyB: Towards Dynamic Benchmarking for Continual Learning with Pre-trained Models. Shengzhuang Chen, Yikai Liao, Xiaoxiao Sun, Kede Ma, Ying Wei |
| 2025 | CLIBD: Bridging Vision and Genomics for Biodiversity Monitoring at Scale. ZeMing Gong, Austin T. Wang, Xiaoliang Huo, Joakim Bruslund Haurum, Scott C. Lowe, Graham W. Taylor, Angel X. Chang |
| 2025 | CLIPDrag: Combining Text-based and Drag-based Instructions for Image Editing. Ziqi Jiang, Zhen Wang, Long Chen |
| 2025 | CLIPure: Purification in Latent Space via CLIP for Adversarially Robust Zero-Shot Classification. Mingkun Zhang, Keping Bi, Wei Chen, Jiafeng Guo, Xueqi Cheng |
| 2025 | CLoSD: Closing the Loop between Simulation and Diffusion for multi-task character control. Guy Tevet, Sigal Raab, Setareh Cohan, Daniele Reda, Zhengyi Luo, Xue Bin Peng, Amit Haim Bermano, Michiel van de Panne |
| 2025 | CO-MOT: Boosting End-to-end Transformer-based Multi-Object Tracking via Coopetition Label Assignment and Shadow Sets. Feng Yan, Weixin Luo, Yujie Zhong, Yiyang Gan, Lin Ma |
| 2025 | COAT: Compressing Optimizer states and Activations for Memory-Efficient FP8 Training. Haocheng Xi, Han Cai, Ligeng Zhu, Yao Lu, Kurt Keutzer, Jianfei Chen, Song Han |
| 2025 | COFlowNet: Conservative Constraints on Flows Enable High-Quality Candidate Generation. Yudong Zhang, Xuan Yu, Xu Wang, Zhaoyang Sun, Chen Zhang, Pengkun Wang, Yang Wang |
| 2025 | COMBO: Compositional World Models for Embodied Multi-Agent Cooperation. Hongxin Zhang, Zeyuan Wang, Qiushi Lyu, Zheyuan Zhang, Sunli Chen, Tianmin Shu, Behzad Dariush, Kwonjoon Lee, Yilun Du, Chuang Gan |
| 2025 | COME: Test-time Adaption by Conservatively Minimizing Entropy. Qingyang Zhang, Yatao Bian, Xinke Kong, Peilin Zhao, Changqing Zhang |
| 2025 | CONDA: Adaptive Concept Bottleneck for Foundation Models Under Distribution Shifts. Jihye Choi, Jayaram Raghuram, Yixuan Li, Somesh Jha |
| 2025 | CONGO: Compressive Online Gradient Optimization. Jeremy Carleton, Prathik Vijaykumar, Divyanshu Saxena, Dheeraj Narasimha, Srinivas Shakkottai, Aditya Akella |
| 2025 | CONTRA: Conformal Prediction Region via Normalizing Flow Transformation. Zhenhan Fang, Aixin Tan, Jian Huang |
| 2025 | COPER: Correlation-based Permutations for Multi-View Clustering. Ran Eisenberg, Jonathan Svirsky, Ofir Lindenbaum |
| 2025 | CPSample: Classifier Protected Sampling for Guarding Training Data During Diffusion. Joshua Kazdan, Hao Sun, Jiaqi Han, Felix Petersen, Frederick Vu, Stefano Ermon |
| 2025 | CR-CTC: Consistency regularization on CTC for improved speech recognition. Zengwei Yao, Wei Kang, Xiaoyu Yang, Fangjun Kuang, Liyong Guo, Han Zhu, Zengrui Jin, Zhaoqing Li, Long Lin, Daniel Povey |
| 2025 | CR2PQ: Continuous Relative Rotary Positional Query for Dense Visual Representation Learning. Shaofeng Zhang, Qiang Zhou, Sitong Wu, Haoru Tan, Zhibin Wang, Jinfa Huang, Junchi Yan |
| 2025 | CREAM: Consistency Regularized Self-Rewarding Language Models. Zhaoyang Wang, Weilei He, Zhiyuan Liang, Xuchao Zhang, Chetan Bansal, Ying Wei, Weitong Zhang, Huaxiu Yao |
| 2025 | CREIMBO: Cross-Regional Ensemble Interactions in Multi-view Brain Observations. Noga Mudrik, Ryan Ly, Oliver Rübel, Adam Shabti Charles |
| 2025 | CREMA: Generalizable and Efficient Video-Language Reasoning via Multimodal Modular Fusion. Shoubin Yu, Jaehong Yoon, Mohit Bansal |
| 2025 | CS-Bench: A Comprehensive Benchmark for Large Language Models towards Computer Science Mastery. Xiaoshuai Song, Muxi Diao, Guanting Dong, Zhengyang Wang, Yujia Fu, Runqi Qiao, Zhexu Wang, Dayuan Fu, Huangxuan Wu, Bin Liang, Weihao Zeng, Yejie Wang, Zhuoma Gongque, Jianing Yu, Qiuna Tan, Weiran Xu |
| 2025 | CSA: Data-efficient Mapping of Unimodal Features to Multimodal Features. Po-han Li, Sandeep P. Chinchali, Ufuk Topcu |
| 2025 | CTSyn: A Foundation Model for Cross Tabular Data Generation. Xiaofeng Lin, Chenheng Xu, Matthew Yang, Guang Cheng |
| 2025 | CURIE: Evaluating LLMs on Multitask Scientific Long-Context Understanding and Reasoning. Hao Cui, Zahra Shamsi, Gowoon Cheon, Xuejian Ma, Shutong Li, Maria Tikhanovskaya, Peter Christian Norgaard, Nayantara Mudur, Martyna Beata Plomecka, Paul Raccuglia, Yasaman Bahri, Victor V. Albert, Pranesh Srinivasan, Haining Pan, Philippe Faist, Brian Rohr, Michael J. Statt, Dan Morris, Drew Purves, Elise Kleeman, et al. |
| 2025 | CViT: Continuous Vision Transformer for Operator Learning. Sifan Wang, Jacob H. Seidman, Shyam Sankaran, Hanwen Wang, George J. Pappas, Paris Perdikaris |
| 2025 | CaPo: Cooperative Plan Optimization for Efficient Embodied Multi-Agent Cooperation. Jie Liu, Pan Zhou, Yingjun Du, Ah-Hwee Tan, Cees G. M. Snoek, Jan-Jakob Sonke, Efstratios Gavves |
| 2025 | Cached Multi-Lora Composition for Multi-Concept Image Generation. Xiandong Zou, Mingzhu Shen, Christos-Savvas Bouganis, Yiren Zhao |
| 2025 | Cafe-Talk: Generating 3D Talking Face Animation with Multimodal Coarse- and Fine-grained Control. Hejia Chen, Haoxian Zhang, Shoulong Zhang, Xiaoqiang Liu, Sisi Zhuang, Yuan Zhang, Pengfei Wan, Di Zhang, Shuai Li |
| 2025 | Calibrating Expressions of Certainty. Peiqi Wang, Barbara D. Lam, Yingcheng Liu, Ameneh Asgari-Targhi, Rameswar Panda, William M. Wells III, Tina Kapur, Polina Golland |
| 2025 | Calibrating LLMs with Information-Theoretic Evidential Deep Learning. Yawei Li, David Rügamer, Bernd Bischl, Mina Rezaei |
| 2025 | CameraCtrl: Enabling Camera Control for Video Diffusion Models. Hao He, Yinghao Xu, Yuwei Guo, Gordon Wetzstein, Bo Dai, Hongsheng Li, Ceyuan Yang |
| 2025 | Can Generative AI Solve Your In-Context Learning Problem? A Martingale Perspective. Andrew Jesson, Nicolas Beltran-Velez, David M. Blei |
| 2025 | Can In-context Learning Really Generalize to Out-of-distribution Tasks? Qixun Wang, Yifei Wang, Xianghua Ying, Yisen Wang |
| 2025 | Can Knowledge Editing Really Correct Hallucinations? Baixiang Huang, Canyu Chen, Xiongxiao Xu, Ali Payani, Kai Shu |
| 2025 | Can LLMs Generate Novel Research Ideas? A Large-Scale Human Study with 100+ NLP Researchers. Chenglei Si, Diyi Yang, Tatsunori Hashimoto |
| 2025 | Can LLMs Really Learn to Translate a Low-Resource Language from One Grammar Book? Seth Aycock, David Stap, Di Wu, Christof Monz, Khalil Sima'an |
| 2025 | Can LLMs Separate Instructions From Data? And What Do We Even Mean By That? Egor Zverev, Sahar Abdelnabi, Soroush Tabesh, Mario Fritz, Christoph H. Lampert |
| 2025 | Can LLMs Solve Longer Math Word Problems Better? Xin Xu, Tong Xiao, Zitong Chao, Zhenya Huang, Can Yang, Yang Wang |
| 2025 | Can LLMs Understand Time Series Anomalies? Zihao Zhou, Rose Yu |
| 2025 | Can Large Language Models Understand Symbolic Graphics Programs? Zeju Qiu, Weiyang Liu, Haiwen Feng, Zhen Liu, Tim Z. Xiao, Katherine M. Collins, Joshua B. Tenenbaum, Adrian Weller, Michael J. Black, Bernhard Schölkopf |
| 2025 | Can Neural Networks Achieve Optimal Computational-statistical Tradeoff? An Analysis on Single-Index Model. Siyu Chen, Beining Wu, Miao Lu, Zhuoran Yang, Tianhao Wang |
| 2025 | Can One Modality Model Synergize Training of Other Modality Models? Jae-Jun Lee, Sung Whan Yoon |
| 2025 | Can Reinforcement Learning Solve Asymmetric Combinatorial-Continuous Zero-Sum Games? Yuheng Li, Panpan Wang, Haipeng Chen |
| 2025 | Can Textual Gradient Work in Federated Learning? Minghui Chen, Ruinan Jin, Wenlong Deng, Yuanyuan Chen, Zhi Huang, Han Yu, Xiaoxiao Li |
| 2025 | Can Transformers Do Enumerative Geometry? Baran Hashemi, Roderic Guigo Corominas, Alessandro Giacchetto |
| 2025 | Can Video LLMs Refuse to Answer? Alignment for Answerability in Video Large Language Models. Eunseop Yoon, Hee Suk Yoon, Mark A. Hasegawa-Johnson, Chang D. Yoo |
| 2025 | Can Watermarked LLMs be Identified by Users via Crafted Prompts? Aiwei Liu, Sheng Guan, Yiming Liu, Leyi Pan, Yifei Zhang, Liancheng Fang, Lijie Wen, Philip S. Yu, Xuming Hu |
| 2025 | Can Watermarks be Used to Detect LLM IP Infringement For Free? Zhengyue Zhao, Xiaogeng Liu, Somesh Jha, Patrick McDaniel, Bo Li, Chaowei Xiao |
| 2025 | Can We Ignore Labels in Out of Distribution Detection? Hong Yang, Qi Yu, Travis Desell |
| 2025 | Can We Talk Models Into Seeing the World Differently? Paul Gavrikov, Jovita Lukasik, Steffen Jung, Robert Geirhos, Muhammad Jehanzeb Mirza, Margret Keuper, Janis Keuper |
| 2025 | Can We Trust Embodied Agents? Exploring Backdoor Attacks against Embodied LLM-Based Decision-Making Systems. Ruochen Jiao, Shaoyuan Xie, Justin Yue, Takami Sato, Lixu Wang, Yixuan Wang, Qi Alfred Chen, Qi Zhu |
| 2025 | Can a Large Language Model be a Gaslighter? Wei Li, Luyao Zhu, Yang Song, Ruixi Lin, Rui Mao, Yang You |
| 2025 | Can a MISL Fly? Analysis and Ingredients for Mutual Information Skill Learning. Chongyi Zheng, Jens Tuyls, Joanne Peng, Benjamin Eysenbach |
| 2025 | Capability Localization: Capabilities Can be Localized rather than Individual Knowledge. Xiusheng Huang, Jiaxiang Liu, Yequan Wang, Jun Zhao, Kang Liu |
| 2025 | CapeX: Category-Agnostic Pose Estimation from Textual Point Explanation. Matan Rusanovsky, Or Hirschorn, Shai Avidan |
| 2025 | Captured by Captions: On Memorization and its Mitigation in CLIP Models. Wenhao Wang, Adam Dziedzic, Grace C. Kim, Michael Backes, Franziska Boenisch |
| 2025 | Capturing the Temporal Dependence of Training Data Influence. Jiachen T. Wang, Dawn Song, James Zou, Prateek Mittal, Ruoxi Jia |
| 2025 | CarbonSense: A Multimodal Dataset and Baseline for Carbon Flux Modelling. Matthew Fortier, Mats Leon Richter, Oliver Sonnentag, Christopher Pal |
| 2025 | CatVTON: Concatenation Is All You Need for Virtual Try-On with Diffusion Models. Zheng Chong, Xiao Dong, Haoxiang Li, Shiyue Zhang, Wenqing Zhang, Hanqing Zhao, Xujie Zhang, Dongmei Jiang, Xiaodan Liang |
| 2025 | Catastrophic Failure of LLM Unlearning via Quantization. Zhiwei Zhang, Fali Wang, Xiaomin Li, Zongyu Wu, Xianfeng Tang, Hui Liu, Qi He, Wenpeng Yin, Suhang Wang |
| 2025 | Cauchy-Schwarz Regularizers. Sueda Taner, Ziyi Wang, Christoph Studer |
| 2025 | Causal Concept Graph Models: Beyond Causal Opacity in Deep Learning. Gabriele Dominici, Pietro Barbiero, Mateo Espinosa Zarlenga, Alberto Termine, Martin Gjoreski, Giuseppe Marra, Marc Langheinrich |
| 2025 | Causal Discovery via Bayesian Optimization. Bao Duong, Sunil Gupta, Thin Nguyen |
| 2025 | Causal Effect Estimation with Mixed Latent Confounders and Post-treatment Variables. Yaochen Zhu, Jing Ma, Liang Wu, Qi Guo, Liangjie Hong, Jundong Li |
| 2025 | Causal Graph Transformer for Treatment Effect Estimation Under Unknown Interference. Anpeng Wu, Haiyi Qiu, Zhengming Chen, Zijian Li, Ruoxuan Xiong, Fei Wu, Kun Zhang |
| 2025 | Causal Graphical Models for Vision-Language Compositional Understanding. Fiorenzo Parascandolo, Nicholas Moratelli, Enver Sangineto, Lorenzo Baraldi, Rita Cucchiara |
| 2025 | Causal Identification for Complex Functional Longitudinal Studies. Andrew Ying |
| 2025 | Causal Information Prioritization for Efficient Reinforcement Learning. Hongye Cao, Fan Feng, Tianpei Yang, Jing Huo, Yang Gao |
| 2025 | Causal Order: The Key to Leveraging Imperfect Experts in Causal Inference. Aniket Vashishtha, Abbavaram Gowtham Reddy, Abhinav Kumar, Saketh Bachu, Vineeth N. Balasubramanian, Amit Sharma |
| 2025 | Causal Representation Learning from Multimodal Biomedical Observations. Yuewen Sun, Lingjing Kong, Guangyi Chen, Loka Li, Gongxu Luo, Zijian Li, Yixuan Zhang, Yujia Zheng, Mengyue Yang, Petar Stojanov, Eran Segal, Eric P. Xing, Kun Zhang |
| 2025 | CausalRivers - Scaling up benchmarking of causal discovery for real-world time-series. Gideon Stein, Maha Shadaydeh, Jan Blunk, Niklas Penzel, Joachim Denzler |
| 2025 | Causally Motivated Sycophancy Mitigation for Large Language Models. Haoxi Li, Xueyang Tang, Jie Zhang, Song Guo, Sikai Bai, Peiran Dong, Yue Yu |
| 2025 | Centrality-guided Pre-training for Graph. Bin Liang, Shiwei Chen, Lin Gui, Hui Wang, Yue Yu, Ruifeng Xu, Kam-Fai Wong |
| 2025 | Century: A Framework and Dataset for Evaluating Historical Contextualisation of Sensitive Images. Canfer Akbulut, Kevin Robinson, Maribeth Rauh, Isabela Albuquerque, Olivia Wiles, Laura Weidinger, Verena Rieser, Yana Hasson, Nahema Marchal, Iason Gabriel, William Isaac, Lisa Anne Hendricks |
| 2025 | CertainlyUncertain: A Benchmark and Metric for Multimodal Epistemic and Aleatoric Awareness. Khyathi Raghavi Chandu, Linjie Li, Anas Awadalla, Ximing Lu, Jae Sung Park, Jack Hessel, Lijuan Wang, Yejin Choi |
| 2025 | Certified Robustness Under Bounded Levenshtein Distance. Elías Abad-Rocamora, Grigorios Chrysos, Volkan Cevher |
| 2025 | Certifying Counterfactual Bias in LLMs. Isha Chaudhary, Qian Hu, Manoj Kumar, Morteza Ziyadi, Rahul Gupta, Gagandeep Singh |
| 2025 | Certifying Language Model Robustness with Fuzzed Randomized Smoothing: An Efficient Defense Against Backdoor Attacks. Bowei He, Lihao Yin, Hui-Ling Zhen, Jianping Zhang, Lanqing Hong, Mingxuan Yuan, Chen Ma |
| 2025 | Chain-of-Action: Faithful and Multimodal Question Answering through Large Language Models. Zhenyu Pan, Haozheng Luo, Manling Li, Han Liu |
| 2025 | Chain-of-Focus Prompting: Leveraging Sequential Visual Cues to Prompt Large Autoregressive Vision Models. Jiyang Zheng, Jialiang Shen, Yu Yao, Min Wang, Yang Yang, Dadong Wang, Tongliang Liu |
| 2025 | Chain-of-Thought Provably Enables Learning the (Otherwise) Unlearnable. Chenxiao Yang, Zhiyuan Li, David Wipf |
| 2025 | Chain-of-region: Visual Language Models Need Details for Diagram Analysis. Xue Li, Yiyou Sun, Wei Cheng, Yinglun Zhu, Haifeng Chen |
| 2025 | ChartMimic: Evaluating LMM's Cross-Modal Reasoning Capability via Chart-to-Code Generation. Cheng Yang, Chufan Shi, Yaxin Liu, Bo Shui, Junjie Wang, Mohan Jing, Linran Xu, Xinyu Zhu, Siheng Li, Yuxiang Zhang, Gongye Liu, Xiaomei Nie, Deng Cai, Yujiu Yang |
| 2025 | ChartMoE: Mixture of Diversely Aligned Expert Connector for Chart Understanding. Zhengzhuo Xu, Bowen Qu, Yiyan Qi, Sinan Du, Chengjin Xu, Chun Yuan, Jian Guo |
| 2025 | Charting the Design Space of Neural Graph Representations for Subgraph Matching. Vaibhav Raj, Indradyumna Roy, Ashwin Ramachandran, Soumen Chakrabarti, Abir De |
| 2025 | ChatQA 2: Bridging the Gap to Proprietary LLMs in Long Context and RAG Capabilities. Peng Xu, Wei Ping, Xianchao Wu, Chejian Xu, Zihan Liu, Mohammad Shoeybi, Bryan Catanzaro |
| 2025 | CheapNet: Cross-attention on Hierarchical representations for Efficient protein-ligand binding Affinity Prediction. Hyukjun Lim, Sun Kim, Sangseon Lee |
| 2025 | Cheating Automatic LLM Benchmarks: Null Models Achieve High Win Rates. Xiaosen Zheng, Tianyu Pang, Chao Du, Qian Liu, Jing Jiang, Min Lin |
| 2025 | ChemAgent: Self-updating Memories in Large Language Models Improves Chemical Reasoning. Xiangru Tang, Tianyu Hu, Muyang Ye, Yanjun Shao, Xunjian Yin, Siru Ouyang, Wangchunshu Zhou, Pan Lu, Zhuosheng Zhang, Yilun Zhao, Arman Cohan, Mark Gerstein |
| 2025 | Chemistry-Inspired Diffusion with Non-Differentiable Guidance. Yuchen Shen, Chenhao Zhang, Sijie Fu, Chenghui Zhou, Newell Washburn, Barnabás Póczos |
| 2025 | ChroKnowledge: Unveiling Chronological Knowledge of Language Models in Multiple Domains. Yein Park, Chanwoong Yoon, Jungwoo Park, Donghyeon Lee, Minbyul Jeong, Jaewoo Kang |
| 2025 | Chunk-Distilled Language Modeling. Yanhong Li, Karen Livescu, Jiawei Zhou |
| 2025 | CipherPrune: Efficient and Scalable Private Transformer Inference. Yancheng Zhang, Jiaqi Xue, Mengxin Zheng, Mimi Xie, Mingzhe Zhang, Lei Jiang, Qian Lou |
| 2025 | CirT: Global Subseasonal-to-Seasonal Forecasting with Geometry-inspired Transformer. Yang Liu, Zinan Zheng, Jiashun Cheng, Fugee Tsung, Deli Zhao, Yu Rong, Jia Li |
| 2025 | Circuit Representation Learning with Masked Gate Modeling and Verilog-AIG Alignment. Haoyuan Wu, Haisheng Zheng, Yuan Pu, Bei Yu |
| 2025 | Circuit Transformer: A Transformer That Preserves Logical Equivalence. Xihan Li, Xing Li, Lei Chen, Xing Zhang, Mingxuan Yuan, Jun Wang |
| 2025 | CircuitFusion: Multimodal Circuit Representation Learning for Agile Chip Design. Wenji Fang, Shang Liu, Jing Wang, Zhiyao Xie |
| 2025 | CityAnchor: City-scale 3D Visual Grounding with Multi-modality LLMs. Jinpeng Li, Haiping Wang, Jiabin Chen, Yuan Liu, Zhiyang Dou, Yuexin Ma, Sibei Yang, Yuan Li, Wenping Wang, Zhen Dong, Bisheng Yang |
| 2025 | CityGaussianV2: Efficient and Geometrically Accurate Reconstruction for Large-Scale Scenes. Yang Liu, Chuanchen Luo, Zhongkai Mao, Junran Peng, Zhaoxiang Zhang |
| 2025 | Class Distribution-induced Attention Map for Open-vocabulary Semantic Segmentations. Dong Un Kang, Hayeon Kim, Se Young Chun |
| 2025 | ClassDiffusion: More Aligned Personalization Tuning with Explicit Class Guidance. Jiannan Huang, Jun Hao Liew, Hanshu Yan, YuYang Yin, Yao Zhao, Humphrey Shi, Yunchao Wei |
| 2025 | Classic but Everlasting: Traditional Gradient-Based Algorithms Converge Fast Even in Time-Varying Multi-Player Games. Yanzheng Chen, Jun Yu |
| 2025 | ClawMachine: Learning to Fetch Visual Tokens for Referential Comprehension. TianRen Ma, Lingxi Xie, Yunjie Tian, Boyu Yang, Qixiang Ye |
| 2025 | ClimaQA: An Automated Evaluation Framework for Climate Question Answering Models. Veeramakali Vignesh Manivannan, Yasaman Jafari, Srikar Eranky, Spencer Ho, Rose Yu, Duncan Watson-Parris, Yian Ma, Leon Bergen, Taylor Berg-Kirkpatrick |
| 2025 | Clique Number Estimation via Differentiable Functions of Adjacency Matrix Permutations. Indradyumna Roy, Eeshaan Jain, Soumen Chakrabarti, Abir De |
| 2025 | Closed-Form Merging of Parameter-Efficient Modules for Federated Continual Learning. Riccardo Salami, Pietro Buzzega, Matteo Mosconi, Jacopo Bonato, Luigi Sabetta, Simone Calderara |
| 2025 | Co3Gesture: Towards Coherent Concurrent Co-speech 3D Gesture Generation with Interactive Diffusion. Xingqun Qi, Yatian Wang, Hengyuan Zhang, Jiahao Pan, Wei Xue, Shanghang Zhang, Wenhan Luo, Qifeng Liu, Yike Guo |
| 2025 | CoInD: Enabling Logical Compositions in Diffusion Models. Sachit Gaudi, Gautam Sreekumar, Vishnu Boddeti |
| 2025 | CoMRes: Semi-Supervised Time Series Forecasting Utilizing Consensus Promotion of Multi-Resolution. Yunju Cho, Jay-Yoon Lee |
| 2025 | CoMotion: Concurrent Multi-person 3D Motion. Alejandro Newell, Peiyun Hu, Lahav Lipson, Stephan R. Richter, Vladlen Koltun |
| 2025 | CoRNStack: High-Quality Contrastive Data for Better Code Retrieval and Reranking. Tarun Suresh, Revanth Gangi Reddy, Yifei Xu, Zach Nussbaum, Andriy Mulyar, Brandon Duderstadt, Heng Ji |
| 2025 | CoTFormer: A Chain of Thought Driven Architecture with Budget-Adaptive Computation Cost at Inference. Amirkeivan Mohtashami, Matteo Pagliardini, Martin Jaggi |
| 2025 | Cocoon: Robust Multi-Modal Perception with Uncertainty-Aware Sensor Fusion. Minkyoung Cho, Yulong Cao, Jiachen Sun, Qingzhao Zhang, Marco Pavone, Jeong Joon Park, Heng Yang, Zhuoqing Mao |
| 2025 | CodeMMLU: A Multi-Task Benchmark for Assessing Code Understanding & Reasoning Capabilities of CodeLLMs. Dung Manh Nguyen, Thang Chau Phan, Nam Le Hai, Tien-Thong Doan, Nam V. Nguyen, Quang Pham, Nghi D. Q. Bui |
| 2025 | CodePlan: Unlocking Reasoning Potential in Large Language Models by Scaling Code-form Planning. Jiaxin Wen, Jian Guan, Hongning Wang, Wei Wu, Minlie Huang |
| 2025 | CofCA: A STEP-WISE Counterfactual Multi-hop QA benchmark. Jian Wu, Linyi Yang, Zhen Wang, Manabu Okumura, Yue Zhang |
| 2025 | CogCoM: A Visual Language Model with Chain-of-Manipulations Reasoning. Ji Qi, Ming Ding, Weihan Wang, Yushi Bai, Qingsong Lv, Wenyi Hong, Bin Xu, Lei Hou, Juanzi Li, Yuxiao Dong, Jie Tang |
| 2025 | CogVideoX: Text-to-Video Diffusion Models with An Expert Transformer. Zhuoyi Yang, Jiayan Teng, Wendi Zheng, Ming Ding, Shiyu Huang, Jiazheng Xu, Yuanming Yang, Wenyi Hong, Xiaohan Zhang, Guanyu Feng, Da Yin, Yuxuan Zhang, Weihan Wang, Yean Cheng, Bin Xu, Xiaotao Gu, Yuxiao Dong, Jie Tang |
| 2025 | ColPali: Efficient Document Retrieval with Vision Language Models. Manuel Faysse, Hugues Sibille, Tony Wu, Bilel Omrani, Gautier Viaud, Céline Hudelot, Pierre Colombo |
| 2025 | Collab: Controlled Decoding using Mixture of Agents for LLM Alignment. Souradip Chakraborty, Sujay Bhatt, Udari Madhushani Sehwag, Soumya Suvra Ghosal, Jiahao Qiu, Mengdi Wang, Dinesh Manocha, Furong Huang, Alec Koppel, Sumitra Ganesh |
| 2025 | CollabEdit: Towards Non-destructive Collaborative Knowledge Editing. Jiamu Zheng, Jinghuai Zhang, Tianyu Du, Xuhong Zhang, Jianwei Yin, Tao Lin |
| 2025 | Collaborative Discrete-Continuous Black-Box Prompt Learning for Language Models. Hualin Zhang, Haozhen Zhang, Zhekai Liu, Bin Gu, Yi Chang |
| 2025 | Collapsed Language Models Promote Fairness. Jingxuan Xu, Wuyang Chen, Linyi Li, Yao Zhao, Yunchao Wei |
| 2025 | ComLoRA: A Competitive Learning Approach for Enhancing LoRA. Qiushi Huang, Tom Ko, Lilian Tang, Yu Zhang |
| 2025 | ComPC: Completing a 3D Point Cloud with 2D Diffusion Priors. Tianxin Huang, Zhiwen Yan, Yuyang Zhao, Gim Hee Lee |
| 2025 | ComaDICE: Offline Cooperative Multi-Agent Reinforcement Learning with Stationary Distribution Shift Regularization. The Viet Bui, Thanh Hong Nguyen, Tien Anh Mai |
| 2025 | Combatting Dimensional Collapse in LLM Pre-Training Data via Submodular File Selection. Ziqing Fan, Siyuan Du, Shengchao Hu, Pingjie Wang, Li Shen, Ya Zhang, Dacheng Tao, Yanfeng Wang |
| 2025 | Combining Induction and Transduction for Abstract Reasoning. Wen-Ding Li, Keya Hu, Carter Larsen, Yuqing Wu, Simon Alford, Caleb Woo, Spencer M. Dunn, Hao Tang, Wei-Long Zheng, Yewen Pu, Kevin Ellis |
| 2025 | Commit0: Library Generation from Scratch. Wenting Zhao, Nan Jiang, Celine Lee, Justin T. Chiu, Claire Cardie, Matthias Gallé, Alexander M. Rush |
| 2025 | Comparing Targeting Strategies for Maximizing Social Welfare with Limited Resources. Vibhhu Sharma, Bryan Wilder |
| 2025 | Comparing noisy neural population dynamics using optimal transport distances. Amin Nejatbakhsh, Victor Geadah, Alex H. Williams, David Lipshutz |
| 2025 | Competing Large Language Models in Multi-Agent Gaming Environments. Jen-tse Huang, Eric John Li, Man Ho Lam, Tian Liang, Wenxuan Wang, Youliang Yuan, Wenxiang Jiao, Xing Wang, Zhaopeng Tu, Michael R. Lyu |
| 2025 | Competition Dynamics Shape Algorithmic Phases of In-Context Learning. Core Francisco Park, Ekdeep Singh Lubana, Hidenori Tanaka |
| 2025 | Competitive Fair Scheduling with Predictions. Tianming Zhao, Chunqiu Xia, Xiaomin Chang, Chunhao Li, Wei Li, Albert Y. Zomaya |
| 2025 | Complementary Label Learning with Positive Label Guessing and Negative Label Enhancement. Yuhang Li, Zhuying Li, Yuheng Jia |
| 2025 | Complexity Lower Bounds of Adaptive Gradient Algorithms for Non-convex Stochastic Optimization under Relaxed Smoothness. Michael Crawshaw, Mingrui Liu |
| 2025 | Composable Interventions for Language Models. Arinbjörn Kolbeinsson, Kyle O'Brien, Tianjin Huang, Shanghua Gao, Shiwei Liu, Jonathan Richard Schwarz, Anurag Jayant Vaidya, Faisal Mahmood, Marinka Zitnik, Tianlong Chen, Thomas Hartvigsen |
| 2025 | Composing Unbalanced Flows for Flexible Docking and Relaxation. Gabriele Corso, Vignesh Ram Somnath, Noah Getz, Regina Barzilay, Tommi S. Jaakkola, Andreas Krause |
| 2025 | Compositional 4D Dynamic Scenes Understanding with Physics Priors for Video Question Answering. Xingrui Wang, Wufei Ma, Angtian Wang, Shuo Chen, Adam Kortylewski, Alan L. Yuille |
| 2025 | Compositional Entailment Learning for Hyperbolic Vision-Language Models. Avik Pal, Max van Spengler, Guido Maria D'Amely di Melendugno, Alessandro Flaborea, Fabio Galasso, Pascal Mettes |
| 2025 | Compositional simulation-based inference for time series. Manuel Glöckler, Shoji Toyota, Kenji Fukumizu, Jakob H. Macke |
| 2025 | Computational Explorations of Total Variation Distance. Arnab Bhattacharyya, Sutanu Gayen, Kuldeep S. Meel, Dimitrios Myrisiotis, Aduri Pavan, N. V. Vinodchandran |
| 2025 | Computational Limits of Low-Rank Adaptation (LoRA) Fine-Tuning for Transformer Models. Jerry Yao-Chieh Hu, Maojiang Su, En-Jui Kuo, Zhao Song, Han Liu |
| 2025 | Computationally Efficient RL under Linear Bellman Completeness for Deterministic Dynamics. Runzhe Wu, Ayush Sekhari, Akshay Krishnamurthy, Wen Sun |
| 2025 | Compute-Constrained Data Selection. Junjie Oscar Yin, Alexander M. Rush |
| 2025 | Compute-Optimal LLMs Provably Generalize Better with Scale. Marc Anton Finzi, Sanyam Kapoor, Diego Granziol, Anming Gu, Christopher De Sa, J. Zico Kolter, Andrew Gordon Wilson |
| 2025 | Computing Circuits Optimization via Model-Based Circuit Genetic Evolution. Zhihai Wang, Jie Wang, Xilin Xia, Dongsheng Zuo, Lei Chen, Yuzhe Ma, Jianye Hao, Mingxuan Yuan, Feng Wu |
| 2025 | ConFIG: Towards Conflict-free Training of Physics Informed Neural Networks. Qiang Liu, Mengyu Chu, Nils Thuerey |
| 2025 | ConMix: Contrastive Mixup at Representation Level for Long-tailed Deep Clustering. Zhixin Li, Yuheng Jia |
| 2025 | Concept Bottleneck Language Models For Protein Design. Aya Abdelsalam Ismail, Tuomas P. Oikarinen, Amy Wang, Julius Adebayo, Samuel Don Stanton, Héctor Corrada Bravo, Kyunghyun Cho, Nathan C. Frey |
| 2025 | Concept Bottleneck Large Language Models. Chung-En Sun, Tuomas P. Oikarinen, Berk Ustun, Tsui-Wei Weng |
| 2025 | Concept Pinpoint Eraser for Text-to-image Diffusion Models via Residual Attention Gate. Byung Hyun Lee, Sungjin Lim, Seunggyu Lee, Dong Un Kang, Se Young Chun |
| 2025 | Concept-ROT: Poisoning Concepts in Large Language Models with Model Editing. Keltin Grimes, Marco Christiani, David Shriver, Marissa Catherine Connor |
| 2025 | ConceptPrune: Concept Editing in Diffusion Models via Skilled Neuron Pruning. Ruchika Chavhan, Da Li, Timothy M. Hospedales |
| 2025 | ConcreTizer: Model Inversion Attack via Occupancy Classification and Dispersion Control for 3D Point Cloud Restoration. Youngseok Kim, Sunwook Hwang, Hyung-Sin Kim, Saewoong Bahk |
| 2025 | Conditional Diffusion Models are Minimax-Optimal and Manifold-Adaptive for Conditional Distribution Estimation. Rong Tang, Lizhen Lin, Yun Yang |
| 2025 | Conditional Diffusion with Ordinal Regression: Longitudinal Data Generation for Neurodegenerative Disease Studies. Hyuna Cho, Ziquan Wei, Seungjoo Lee, Tingting Dan, Guorong Wu, Won Hwa Kim |
| 2025 | Conditional Testing based on Localized Conformal p-values. Xiaoyang Wu, Lin Lu, Zhaojun Wang, Changliang Zou |
| 2025 | Confidence Elicitation: A New Attack Vector for Large Language Models. Brian Formento, Chuan-Sheng Foo, See-Kiong Ng |
| 2025 | Conflict-Averse Gradient Aggregation for Constrained Multi-Objective Reinforcement Learning. Dohyeong Kim, Mineui Hong, Jeongho Park, Songhwai Oh |
| 2025 | Conformal Generative Modeling with Improved Sample Efficiency through Sequential Greedy Filtering. Klaus-Rudolf Kladny, Bernhard Schölkopf, Michael Muehlebach |
| 2025 | Conformal Language Model Reasoning with Coherent Factuality. Maxon Rubin-Toles, Maya Gambhir, Keshav Ramji, Aaron Roth, Surbhi Goel |
| 2025 | Conformal Prediction Sets Can Cause Disparate Impact. Jesse C. Cresswell, Bhargava Kumar, Yi Sui, Mouloud Belbahri |
| 2025 | Conformal Structured Prediction. Botong Zhang, Shuo Li, Osbert Bastani |
| 2025 | Conformalized Interactive Imitation Learning: Handling Expert Shift and Intermittent Feedback. Michelle D. Zhao, Henny Admoni, Reid G. Simmons, Aaditya Ramdas, Andrea Bajcsy |
| 2025 | Conformalized Survival Analysis for General Right-Censored Data. Hen Davidov, Shai Feldman, Gil Shamai, Ron Kimmel, Yaniv Romano |
| 2025 | Connecting Federated ADMM to Bayes. Siddharth Swaroop, Mohammad Emtiyaz Khan, Finale Doshi-Velez |
| 2025 | Connectome Mapping: Shape-Memory Network via Interpretation of Contextual Semantic Information. Kyungsu Lee, Haeyun Lee, Jae Youn Hwang |
| 2025 | Conservative Contextual Bandits: Beyond Linear Representations. Rohan Deb, Mohammad Ghavamzadeh, Arindam Banerjee |
| 2025 | Consistency Checks for Language Model Forecasters. Daniel Paleka, Abhimanyu Pallavi Sudhir, Alejandro Alvarez, Vineeth Bhat, Adam Shen, Evan Wang, Florian Tramèr |
| 2025 | Consistency Models Made Easy. Zhengyang Geng, Ashwini Pokle, Weijian Luo, Justin Lin, J. Zico Kolter |
| 2025 | Consistent Flow Distillation for Text-to-3D Generation. Runjie Yan, Yinbo Chen, Xiaolong Wang |
| 2025 | Constraint-Conditioned Actor-Critic for Offline Safe Reinforcement Learning. Zijian Guo, Weichao Zhou, Shengao Wang, Wenchao Li |
| 2025 | Constructing Confidence Intervals for Average Treatment Effects from Multiple Datasets. Yuxin Wang, Maresa Schröder, Dennis Frauen, Jonas Schweisthal, Konstantin Hess, Stefan Feuerriegel |
| 2025 | Content-Style Learning from Unaligned Domains: Identifiability under Unknown Latent Dimensions. Sagar Shrestha, Xiao Fu |
| 2025 | Context Clues: Evaluating Long Context Models for Clinical Prediction Tasks on EHR Data. Michael Wornow, Suhana Bedi, Miguel Angel Fuentes Hernandez, Ethan Steinberg, Jason Alan Fries, Christopher Ré, Sanmi Koyejo, Nigam Shah |
| 2025 | Context Steering: Controllable Personalization at Inference Time. Jerry Zhi-Yang He, Sashrika Pandey, Mariah L. Schrum, Anca D. Dragan |
| 2025 | Context-Alignment: Activating and Enhancing LLMs Capabilities in Time Series. Yuxiao Hu, Qian Li, Dongxiao Zhang, Jinyue Yan, Yuntian Chen |
| 2025 | Context-Parametric Inversion: Why Instruction Finetuning May Not Actually Improve Context Reliance. Sachin Goyal, Christina Baek, J. Zico Kolter, Aditi Raghunathan |
| 2025 | Context-aware Dynamic Pruning for Speech Foundation Models. Masao Someki, Yifan Peng, Siddhant Arora, Markus Müller, Athanasios Mouchtaris, Grant P. Strimel, Jing Liu, Shinji Watanabe |
| 2025 | ContextGNN: Beyond Two-Tower Recommendation Systems. Yiwen Yuan, Zecheng Zhang, Xinwei He, Akihiro Nitta, Weihua Hu, Manan Shah, Blaz Stojanovic, Shenyang Huang, Jan Eric Lenssen, Jure Leskovec, Matthias Fey |
| 2025 | Contextual Document Embeddings. John Xavier Morris, Alexander M. Rush |
| 2025 | Contextual Self-paced Learning for Weakly Supervised Spatio-Temporal Video Grounding. Akash Kumar, Zsolt Kira, Yogesh S. Rawat |
| 2025 | Contextualizing biological perturbation experiments through language. Menghua Wu, Russell Littman, Jacob Levine, Lin Qiu, Tommaso Biancalani, David Richmond, Jan-Christian Huetter |
| 2025 | Continual Slow-and-Fast Adaptation of Latent Neural Dynamics (CoSFan): Meta-Learning What-How & When to Adapt. Ryan Missel, Linwei Wang |
| 2025 | Continuity-Preserving Convolutional Autoencoders for Learning Continuous Latent Dynamical Models from Images. Aiqing Zhu, Yuting Pan, Qianxiao Li |
| 2025 | Continuous Autoregressive Modeling with Stochastic Monotonic Alignment for Speech Synthesis. Weiwei Lin, Chenhang He |
| 2025 | Continuous Diffusion for Mixed-Type Tabular Data. Markus Mueller, Kathrin Gruber, Dennis Fok |
| 2025 | Continuous Ensemble Weather Forecasting with Diffusion models. Martin Andrae, Tomas Landelius, Joel Oskarsson, Fredrik Lindsten |
| 2025 | Continuous Exposure Learning for Low-light Image Enhancement using Neural ODEs. Donggoo Jung, Daehyun Kim, Tae Hyun Kim |
| 2025 | ContraDiff: Planning Towards High Return States via Contrastive Learning. Yixiang Shan, Zhengbang Zhu, Ting Long, Qifan Liang, Yi Chang, Weinan Zhang, Liang Yin |
| 2025 | Contractive Dynamical Imitation Policies for Efficient Out-of-Sample Recovery. Amin Abyaneh, Mahrokh Ghoddousi Boroujeni, Hsiu-Chin Lin, Giancarlo Ferrari-Trecate |
| 2025 | Contrastive Learning from Synthetic Audio Doppelgängers. Manuel Cherep, Nikhil Singh |
| 2025 | Control-oriented Clustering of Visual Latent Representation. Han Qi, Haocheng Yin, Heng Yang |
| 2025 | ControlAR: Controllable Image Generation with Autoregressive Models. Zongming Li, Tianheng Cheng, Shoufa Chen, Peize Sun, Haocheng Shen, Longjin Ran, Xiaoxin Chen, Wenyu Liu, Xinggang Wang |
| 2025 | Controllable Blur Data Augmentation Using 3D-Aware Motion Estimation. Insoo Kim, Hana Lee, Hyong-Euk Lee, Jinwoo Shin |
| 2025 | Controllable Context Sensitivity and the Knob Behind It. Julian Minder, Kevin Du, Niklas Stoehr, Giovanni Monea, Chris Wendler, Robert West, Ryan Cotterell |
| 2025 | Controllable Generation via Locally Constrained Resampling. Kareem Ahmed, Kai-Wei Chang, Guy Van den Broeck |
| 2025 | Controllable Safety Alignment: Inference-Time Adaptation to Diverse Safety Requirements. Jingyu Zhang, Ahmed Elgohary, Ahmed Magooda, Daniel Khashabi, Benjamin Van Durme |
| 2025 | Controllable Satellite-to-Street-View Synthesis with Precise Pose Alignment and Zero-Shot Environmental Control. Xianghui Ze, Zhenbo Song, QiWei Wang, Jianfeng Lu, Yujiao Shi |
| 2025 | Controllable Unlearning for Image-to-Image Generative Models via ϵ-Constrained Optimization. Xiaohua Feng, Yuyuan Li, Chaochao Chen, Li Zhang, Longfei Li, Jun Zhou, Xiaolin Zheng |
| 2025 | Controlled LLM Decoding via Discrete Auto-regressive Biasing. Patrick Pynadath, Ruqi Zhang |
| 2025 | Controlling Language and Diffusion Models by Transporting Activations. Pau Rodríguez, Arno Blaas, Michal Klein, Luca Zappella, Nicholas Apostoloff, Marco Cuturi, Xavier Suau |
| 2025 | Controlling Space and Time with Diffusion Models. Daniel Watson, Saurabh Saxena, Lala Li, Andrea Tagliasacchi, David J. Fleet |
| 2025 | ConvCodeWorld: Benchmarking Conversational Code Generation in Reproducible Feedback Environments. Hojae Han, Seung-won Hwang, Rajhans Samdani, Yuxiong He |
| 2025 | Convergence and Implicit Bias of Gradient Descent on Continual Linear Classification. Hyunji Jung, Hanseul Cho, Chulhee Yun |
| 2025 | Convergence of Distributed Adaptive Optimization with Local Updates. Ziheng Cheng, Margalit Glasgow |
| 2025 | Convergence of Score-Based Discrete Diffusion Models: A Discrete-Time Analysis. Zikun Zhang, Zixiang Chen, Quanquan Gu |
| 2025 | Convergent Privacy Loss of Noisy-SGD without Convexity and Smoothness. Eli Chien, Pan Li |
| 2025 | Convex Formulations for Training Two-Layer ReLU Neural Networks. Karthik Prakhya, Tolga Birdal, Alp Yurtsever |
| 2025 | Copyright-Protected Language Generation via Adaptive Model Fusion. Javier Abad, Konstantin Donhauser, Francesco Pinto, Fanny Yang |
| 2025 | Coreset Selection via Reducible Loss in Continual Learning. Ruilin Tong, Yuhang Liu, Javen Qinfeng Shi, Dong Gong |
| 2025 | Coreset Spectral Clustering. Ben Jourdan, Gregory Schwartzman, Peter Macgregor, He Sun |
| 2025 | Correcting the Mythos of KL-Regularization: Direct Alignment without Overoptimization via Chi-Squared Preference Optimization. Audrey Huang, Wenhao Zhan, Tengyang Xie, Jason D. Lee, Wen Sun, Akshay Krishnamurthy, Dylan J. Foster |
| 2025 | Correlated Proxies: A New Definition and Improved Mitigation for Reward Hacking. Cassidy Laidlaw, Shivam Singhal, Anca D. Dragan |
| 2025 | Correlating instruction-tuning (in multimodal models) with vision-language processing (in the brain). Subba Reddy Oota, Akshett Rai Jindal, Ishani Mondal, Khushbu Pahwa, Satya Sai Srinath Namburi GNVV, Manish Shrivastava, Maneesh Kumar Singh, Bapi Raju Surampudi, Manish Gupta |
| 2025 | Correlation and Navigation in the Vocabulary Key Representation Space of Language Models. Letian Peng, Chenyang An, Jingbo Shang |
| 2025 | Counterfactual Concept Bottleneck Models. Gabriele Dominici, Pietro Barbiero, Francesco Giannini, Martin Gjoreski, Giuseppe Marra, Marc Langheinrich |
| 2025 | Counterfactual Generative Modeling with Variational Causal Inference. Yulun Wu, Louie McConnell, Claudia Iriondo |
| 2025 | Counterfactual Realizability. Arvind Raghavan, Elias Bareinboim |
| 2025 | CraftRTL: High-quality Synthetic Data Generation for Verilog Code Models with Correct-by-Construction Non-Textual Representations and Targeted Code Repair. Mingjie Liu, Yun-Da Tsai, Wenfei Zhou, Haoxing Ren |
| 2025 | Credal Wrapper of Model Averaging for Uncertainty Estimation in Classification. Kaizheng Wang, Fabio Cuzzolin, Keivan Shariatmadar, David Moens, Hans Hallez |
| 2025 | Credit-based self organizing maps: training deep topographic networks with minimal performance degradation. Amirozhan Dehghani, Xinyu Qian, Asa Farahani, Pouya Bashivan |
| 2025 | Cross the Gap: Exposing the Intra-modal Misalignment in CLIP via Modality Inversion. Marco Mistretta, Alberto Baldrati, Lorenzo Agnolucci, Marco Bertini, Andrew D. Bagdanov |
| 2025 | Cross-Attention Head Position Patterns Can Align with Human Visual Concepts in Text-to-Image Generative Models. Jungwon Park, Jungmin Ko, Dongnam Byun, Jangwon Suh, Wonjong Rhee |
| 2025 | Cross-Domain Off-Policy Evaluation and Learning for Contextual Bandits. Yuta Natsubori, Masataka Ushiku, Yuta Saito |
| 2025 | Cross-Domain Offline Policy Adaptation with Optimal Transport and Dataset Constraint. Jiafei Lyu, Mengbei Yan, Zhongjian Qiao, Runze Liu, Xiaoteng Ma, Deheng Ye, Jingwen Yang, Zongqing Lu, Xiu Li |
| 2025 | Cross-Embodiment Dexterous Grasping with Reinforcement Learning. Haoqi Yuan, Bohan Zhou, Yuhui Fu, Zongqing Lu |
| 2025 | Cross-Entropy Is All You Need To Invert the Data Generating Process. Patrik Reizinger, Alice Bizeul, Attila Juhos, Julia E. Vogt, Randall Balestriero, Wieland Brendel, David A. Klindt |
| 2025 | Cross-Modal Safety Mechanism Transfer in Large Vision-Language Models. Shicheng Xu, Liang Pang, Yunchang Zhu, Huawei Shen, Xueqi Cheng |
| 2025 | CrossMPT: Cross-attention Message-passing Transformer for Error Correcting Codes. Seong-Joon Park, Heeyoul Kwak, Sang-Hyo Kim, Yongjune Kim, Jong-Seon No |
| 2025 | CryoFM: A Flow-based Foundation Model for Cryo-EM Densities. Yi Zhou, Yilai Li, Jing Yuan, Quanquan Gu |
| 2025 | CryoGEN: Generative Energy-based Models for Cryogenic Electron Tomography Reconstruction. Yunfei Teng, Yuxuan Ren, Kai Chen, Xi Chen, Zhaoming Chen, Qiwei Ye |
| 2025 | CtD: Composition through Decomposition in Emergent Communication. Boaz Carmeli, Ron Meir, Yonatan Belinkov |
| 2025 | CtrLoRA: An Extensible and Efficient Framework for Controllable Image Generation. Yifeng Xu, Zhenliang He, Shiguang Shan, Xilin Chen |
| 2025 | Ctrl-Adapter: An Efficient and Versatile Framework for Adapting Diverse Controls to Any Diffusion Model. Han Lin, Jaemin Cho, Abhay Zala, Mohit Bansal |
| 2025 | Ctrl-U: Robust Conditional Image Generation via Uncertainty-aware Reward Modeling. Guiyu Zhang, Huan-ang Gao, Zijian Jiang, Hao Zhao, Zhedong Zheng |
| 2025 | CubeDiff: Repurposing Diffusion-Based Image Models for Panorama Generation. Nikolai Kalischek, Michael Oechsle, Fabian Manhardt, Philipp Henzler, Konrad Schindler, Federico Tombari |
| 2025 | Curriculum-aware Training for Discriminating Molecular Property Prediction Models. Hansi Yang, Quanming Yao, James Kwok |
| 2025 | Cut Your Losses in Large-Vocabulary Language Models. Erik Wijmans, Brody Huval, Alexander Hertzberg, Vladlen Koltun, Philipp Krähenbühl |
| 2025 | Cut the Crap: An Economical Communication Pipeline for LLM-based Multi-Agent Systems. Guibin Zhang, Yanwei Yue, Zhixun Li, Sukwon Yun, Guancheng Wan, Kun Wang, Dawei Cheng, Jeffrey Xu Yu, Tianlong Chen |
| 2025 | Cybench: A Framework for Evaluating Cybersecurity Capabilities and Risks of Language Models. Andy K. Zhang, Neil Perry, Riya Dulepet, Joey Ji, Celeste Menders, Justin W. Lin, Eliot Jones, Gashon Hussein, Samantha Liu, Donovan Julian Jasper, Pura Peetathawatchai, Ari Glenn, Vikram Sivashankar, Daniel Zamoshchin, Leo Glikbarg, Derek Askaryar, Haoxiang Yang, Aolin Zhang, Rishi Alluri, Nathan Tran, et al. |
| 2025 | CyberHost: A One-stage Diffusion Framework for Audio-driven Talking Body Generation. Gaojie Lin, Jianwen Jiang, Chao Liang, Tianyun Zhong, Jiaqi Yang, Zerong Zheng, Yanbo Zheng |
| 2025 | CycleResearcher: Improving Automated Research via Automated Review. Yixuan Weng, Minjun Zhu, Guangsheng Bao, Hongbo Zhang, Jindong Wang, Yue Zhang, Linyi Yang |
| 2025 | Cyclic Contrastive Knowledge Transfer for Open-Vocabulary Object Detection. Chuhan Zhang, Chaoyang Zhu, Pingcheng Dong, Long Chen, Dong Zhang |
| 2025 | D-FINE: Redefine Regression Task of DETRs as Fine-grained Distribution Refinement. Yansong Peng, Hebei Li, Peixi Wu, Yueyi Zhang, Xiaoyan Sun, Feng Wu |
| 2025 | D2O: Dynamic Discriminative Operations for Efficient Long-Context Inference of Large Language Models. Zhongwei Wan, Xinjian Wu, Yu Zhang, Yi Xin, Chaofan Tao, Zhihong Zhu, Xin Wang, Siqi Luo, Jing Xiong, Longyue Wang, Mi Zhang |
| 2025 | DAMO: Decoding by Accumulating Activations Momentum for Mitigating Hallucinations in Vision-Language Models. Kaishen Wang, Hengrui Gu, Meijun Gao, Kaixiong Zhou |
| 2025 | DARE the Extreme: Revisiting Delta-Parameter Pruning For Fine-Tuned Models. Wenlong Deng, Yize Zhao, Vala Vakilian, Minghui Chen, Xiaoxiao Li, Christos Thrampoulidis |
| 2025 | DAWN: Dynamic Frame Avatar with Non-autoregressive Diffusion Framework for Talking head Video Generation. Hanbo Cheng, Limin Lin, Chenyu Liu, Pengcheng Xia, Pengfei Hu, Jiefeng Ma, Jun Du, Jia Pan |
| 2025 | DCT-CryptoNets: Scaling Private Inference in the Frequency Domain. Arjun Roy, Kaushik Roy |
| 2025 | DECO: Unleashing the Potential of ConvNets for Query-based Detection and Segmentation. Xinghao Chen, Siwei Li, Yijing Yang, Yunhe Wang |
| 2025 | DEEM: Diffusion models serve as the eyes of large language models for image perception. Run Luo, Yunshui Li, Longze Chen, Wanwei He, Ting-En Lin, Ziqiang Liu, Lei Zhang, Zikai Song, Hamid Rokny, Xiaobo Xia, Tongliang Liu, Binyuan Hui, Min Yang |
| 2025 | DELIFT: Data Efficient Language model Instruction Fine-Tuning. Ishika Agarwal, Krishnateja Killamsetty, Lucian Popa, Marina Danilevsky |
| 2025 | DEPT: Decoupled Embeddings for Pre-training Language Models. Alex Iacob, Lorenzo Sani, Meghdad Kurmanji, William F. Shen, Xinchi Qiu, Dongqi Cai, Yan Gao, Nicholas Donald Lane |
| 2025 | DEPfold: RNA Secondary Structure Prediction as Dependency Parsing. Ke Wang, Shay B. Cohen |
| 2025 | DGQ: Distribution-Aware Group Quantization for Text-to-Image Diffusion Models. Hyogon Ryu, NaHyeon Park, Hyunjung Shim |
| 2025 | DICE: Data Influence Cascade in Decentralized Learning. Tongtian Zhu, Wenhao Li, Can Wang, Fengxiang He |
| 2025 | DICE: End-to-end Deformation Capture of Hand-Face Interactions from a Single Image. Qingxuan Wu, Zhiyang Dou, Sirui Xu, Soshi Shimada, Chen Wang, Zhengming Yu, Yuan Liu, Cheng Lin, Zeyu Cao, Taku Komura, Vladislav Golyanik, Christian Theobalt, Wenping Wang, Lingjie Liu |
| 2025 | DLEFT-MKC: Dynamic Late Fusion Multiple Kernel Clustering with Robust Tensor Learning via Min-Max Optimization. Yi Zhang, Siwei Wang, Jiyuan Liu, Shengju Yu, Zhibin Dong, Suyuan Liu, Xinwang Liu, En Zhu |
| 2025 | DOCS: Quantifying Weight Similarity for Deeper Insights into Large Language Models. Zeping Min, Xinshang Wang |
| 2025 | DOPL: Direct Online Preference Learning for Restless Bandits with Preference Feedback. Guojun Xiong, Ujwal Dinesha, Debajoy Mukherjee, Jian Li, Srinivas Shakkottai |
| 2025 | DOTS: Learning to Reason Dynamically in LLMs via Optimal Reasoning Trajectories Search. Murong Yue, Wenlin Yao, Haitao Mi, Dian Yu, Ziyu Yao, Dong Yu |
| 2025 | DPLM-2: A Multimodal Diffusion Protein Language Model. Xinyou Wang, Zaixiang Zheng, Fei Ye, Dongyu Xue, Shujian Huang, Quanquan Gu |
| 2025 | DPaI: Differentiable Pruning at Initialization with Node-Path Balance Principle. Lichuan Xiang, Quan Nguyen-Tri, Lan-Cuong Nguyen, Hoang Pham, Khoat Than, Long Tran-Thanh, Hongkai Wen |
| 2025 | DRESSing Up LLM: Efficient Stylized Question-Answering via Style Subspace Editing. Xinyu Ma, Yifeng Xu, Yang Lin, Tianlong Wang, Xu Chu, Xin Gao, Junfeng Zhao, Yasha Wang |
| 2025 | DRL: Decomposed Representation Learning for Tabular Anomaly Detection. Hangting Ye, He Zhao, Wei Fan, Mingyuan Zhou, Dandan Guo, Yi Chang |
| 2025 | DRoC: Elevating Large Language Models for Complex Vehicle Routing via Decomposed Retrieval of Constraints. Xia Jiang, Yaoxin Wu, Chenhao Zhang, Yingqian Zhang |
| 2025 | DRoP: Distributionally Robust Data Pruning. Artem M. Vysogorets, Kartik Ahuja, Julia Kempe |
| 2025 | DS-LLM: Leveraging Dynamical Systems to Enhance Both Training and Inference of Large Language Models. Ruibing Song, Chuan Liu, Chunshu Wu, Ang Li, Dongfang Liu, Ying Nian Wu, Tong Geng |
| 2025 | DSBench: How Far Are Data Science Agents from Becoming Data Science Experts? Liqiang Jing, Zhehui Huang, Xiaoyang Wang, Wenlin Yao, Wenhao Yu, Kaixin Ma, Hongming Zhang, Xinya Du, Dong Yu |
| 2025 | DSPO: Direct Score Preference Optimization for Diffusion Model Alignment. Huaisheng Zhu, Teng Xiao, Vasant G. Honavar |
| 2025 | DUALFormer: Dual Graph Transformer. Jiaming Zhuo, Yuwei Liu, Yintong Lu, Ziyi Ma, Kun Fu, Chuan Wang, Yuanfang Guo, Zhen Wang, Xiaochun Cao, Liang Yang |
| 2025 | DUET: Decentralized Bilevel Optimization without Lower-Level Strong Convexity. Zhen Qin, Zhuqing Liu, Songtao Lu, Yingbin Liang, Jia Liu |
| 2025 | DaWin: Training-free Dynamic Weight Interpolation for Robust Adaptation. Changdae Oh, Yixuan Li, Kyungwoo Song, Sangdoo Yun, Dongyoon Han |
| 2025 | DailyDilemmas: Revealing Value Preferences of LLMs with Quandaries of Daily Life. Yu Ying Chiu, Liwei Jiang, Yejin Choi |
| 2025 | DarkBench: Benchmarking Dark Patterns in Large Language Models. Esben Kran, Jord Nguyen, Akash Kundu, Sami Jawhar, Jinsuk Park, Mateusz Maria Jurewicz |
| 2025 | DartControl: A Diffusion-Based Autoregressive Motion Model for Real-Time Text-Driven Motion Control. Kaifeng Zhao, Gen Li, Siyu Tang |
| 2025 | Data Center Cooling System Optimization Using Offline Reinforcement Learning. Xianyuan Zhan, Xiangyu Zhu, Peng Cheng, Xiao Hu, Ziteng He, Hanfei Geng, Jichao Leng, Huiwen Zheng, Chenhui Liu, Tianshun Hong, Yan Liang, Yunxin Liu, Feng Zhao |
| 2025 | Data Distillation for extrapolative protein design through exact preference optimization. Mostafa Karimi, Sharmi Banerjee, Tommi S. Jaakkola, Bella Dubrov, Shang Shang, Ron Benson |
| 2025 | Data Mixing Laws: Optimizing Data Mixtures by Predicting Language Modeling Performance. Jiasheng Ye, Peiju Liu, Tianxiang Sun, Jun Zhan, Yunhua Zhou, Xipeng Qiu |
| 2025 | Data Pruning by Information Maximization. Haoru Tan, Sitong Wu, Wei Huang, Shizhen Zhao, Xiaojuan Qi |
| 2025 | Data Scaling Laws in Imitation Learning for Robotic Manipulation. Fanqi Lin, Yingdong Hu, Pingyue Sheng, Chuan Wen, Jiacheng You, Yang Gao |
| 2025 | Data Selection via Optimal Control for Language Models. Yuxian Gu, Li Dong, Hongning Wang, Yaru Hao, Qingxiu Dong, Furu Wei, Minlie Huang |
| 2025 | Data Shapley in One Training Run. Jiachen T. Wang, Prateek Mittal, Dawn Song, Ruoxi Jia |
| 2025 | Data Taggants: Dataset Ownership Verification Via Harmless Targeted Data Poisoning. Wassim Bouaziz, Nicolas Usunier, El-Mahdi El-Mhamdi |
| 2025 | Data Unlearning in Diffusion Models. Silas Alberti, Kenan Hasanaliyev, Manav Shah, Stefano Ermon |
| 2025 | Data-adaptive Differentially Private Prompt Synthesis for In-Context Learning. Fengyu Gao, Ruida Zhou, Tianhao Wang, Cong Shen, Jing Yang |
| 2025 | Data-centric Prediction Explanation via Kernelized Stein Discrepancy. Mahtab Sarvmaili, Hassan Sajjad, Ga Wu |
| 2025 | DataEnvGym: Data Generation Agents in Teacher Environments with Student Feedback. Zaid Khan, Elias Stengel-Eskin, Jaemin Cho, Mohit Bansal |
| 2025 | DataGen: Unified Synthetic Dataset Generation via Large Language Models. Yue Huang, Siyuan Wu, Chujie Gao, Dongping Chen, Qihui Zhang, Yao Wan, Tianyi Zhou, Chaowei Xiao, Jianfeng Gao, Lichao Sun, Xiangliang Zhang |
| 2025 | DataMan: Data Manager for Pre-training Large Language Models. Ru Peng, Kexin Yang, Yawen Zeng, Junyang Lin, Dayiheng Liu, Junbo Zhao |
| 2025 | Dataset Distillation via Knowledge Distillation: Towards Efficient Self-Supervised Pre-training of Deep Networks. Siddharth Joshi, Jiayi Ni, Baharan Mirzasoleiman |
| 2025 | Dataset Ownership Verification in Contrastive Pre-trained Models. Yuechen Xie, Jie Song, Mengqi Xue, Haofei Zhang, Xingen Wang, Bingde Hu, Genlang Chen, Mingli Song |
| 2025 | DeFT: Decoding with Flash Tree-attention for Efficient Tree-structured LLM Inference. Jinwei Yao, Kaiqi Chen, Kexun Zhang, Jiaxuan You, Binhang Yuan, Zeke Wang, Tao Lin |
| 2025 | DeLLMa: Decision Making Under Uncertainty with Large Language Models. Ollie Liu, Deqing Fu, Dani Yogatama, Willie Neiswanger |
| 2025 | DebGCD: Debiased Learning with Distribution Guidance for Generalized Category Discovery. Yuanpei Liu, Kai Han |
| 2025 | Debiasing Federated Learning with Correlated Client Participation. Zhenyu Sun, Ziyang Zhang, Zheng Xu, Gauri Joshi, Pranay Sharma, Ermin Wei |
| 2025 | Debiasing Mini-Batch Quadratics for Applications in Deep Learning. Lukas Tatzel, Bálint Mucsányi, Osane Hackel, Philipp Hennig |
| 2025 | Decentralized Optimization with Coupled Constraints. Demyan Yarmoshik, Alexander Rogozin, Nikita Kiselev, Daniil Dorin, Alexander V. Gasnikov, Dmitry Kovalev |
| 2025 | Decentralized Sporadic Federated Learning: A Unified Algorithmic Framework with Convergence Guarantees. Shahryar Zehtabi, Dong-Jun Han, Rohit Parasnis, Seyyedali Hosseinalipour, Christopher G. Brinton |
| 2025 | DeciMamba: Exploring the Length Extrapolation Potential of Mamba. Assaf Ben-Kish, Itamar Zimerman, Shady Abu-Hussein, Nadav Cohen, Amir Globerson, Lior Wolf, Raja Giryes |
| 2025 | Decision Information Meets Large Language Models: The Future of Explainable Operations Research. Yansen Zhang, Qingcan Kang, Wing Yin Yu, Hailei Gong, Xiaojin Fu, Xiongwei Han, Tao Zhong, Chen Ma |
| 2025 | Decision Tree Induction Through LLMs via Semantically-Aware Evolution. Tennison Liu, Nicolas Huynh, Mihaela van der Schaar |
| 2025 | Decoding Game: On Minimax Optimality of Heuristic Text Generation Strategies. Sijin Chen, Omar Hagrass, Jason Matthew Klusowski |
| 2025 | Decomposition Polyhedra of Piecewise Linear Functions. Marie-Charlotte Brandenburg, Moritz Leo Grillo, Christoph Hertrich |
| 2025 | Deconstructing Denoising Diffusion Models for Self-Supervised Learning. Xinlei Chen, Zhuang Liu, Saining Xie, Kaiming He |
| 2025 | Deconstructing What Makes a Good Optimizer for Autoregressive Language Models. Rosie Zhao, Depen Morwani, David Brandfonbrener, Nikhil Vyas, Sham M. Kakade |
| 2025 | Decoupled Finetuning for Domain Generalizable Semantic Segmentation. Jaehyun Pahk, Donghyeon Kwon, Seong Joon Oh, Suha Kwak |
| 2025 | Decoupled Graph Energy-based Model for Node Out-of-Distribution Detection on Heterophilic Graphs. Yuhan Chen, Yihong Luo, Yifan Song, Pengwen Dai, Jing Tang, Xiaochun Cao |
| 2025 | Decoupled Subgraph Federated Learning. Javad Aliakbari, Johan Östman, Alexandre Graell i Amat |
| 2025 | Decoupling Angles and Strength in Low-rank Adaptation. Massimo Bini, Leander Girrbach, Zeynep Akata |
| 2025 | Decoupling Layout from Glyph in Online Chinese Handwriting Generation. Minsi Ren, Yan-Ming Zhang, Yi Chen |
| 2025 | Deep Compression Autoencoder for Efficient High-Resolution Diffusion Models. Junyu Chen, Han Cai, Junsong Chen, Enze Xie, Shang Yang, Haotian Tang, Muyang Li, Song Han |
| 2025 | Deep Distributed Optimization for Large-Scale Quadratic Programming. Augustinos D. Saravanos, Hunter Kuperman, Alex Oshin, Arshiya Taj Abdul, Vincent Pacelli, Evangelos A. Theodorou |
| 2025 | Deep Incomplete Multi-view Learning via Cyclic Permutation of VAEs. Xin Gao, Jian Pu |
| 2025 | Deep Kernel Posterior Learning under Infinite Variance Prior Weights. Jorge Loría, Anindya Bhadra |
| 2025 | Deep Kernel Relative Test for Machine-generated Text Detection. Yiliao Song, Zhenqiao Yuan, Shuhai Zhang, Zhen Fang, Jun Yu, Feng Liu |
| 2025 | Deep Learning Alternatives Of The Kolmogorov Superposition Theorem. Leonardo Ferreira Guilhoto, Paris Perdikaris |
| 2025 | Deep Linear Probe Generators for Weight Space Learning. Jonathan Kahana, Eliahu Horwitz, Imri Shuval, Yedid Hoshen |
| 2025 | Deep MMD Gradient Flow without adversarial training. Alexandre Galashov, Valentin De Bortoli, Arthur Gretton |
| 2025 | Deep Networks Learn Features From Local Discontinuities in the Label Function. Prithaj Banerjee, Harish Guruprasad Ramaswamy, Mahesh Lorik Yadav, Chandra Shekar Lakshminarayanan |
| 2025 | Deep Random Features for Scalable Interpolation of Spatiotemporal Data. Weibin Chen, Azhir Mahmood, Michel Tsamados, So Takao |
| 2025 | Deep Signature: Characterization of Large-Scale Molecular Dynamics. Tiexin Qin, Mengxu Zhu, Chunyang Li, Terry Lyons, Hong Yan, Haoliang Li |
| 2025 | Deep Weight Factorization: Sparse Learning Through the Lens of Artificial Symmetries. Chris Kolb, Tobias Weber, Bernd Bischl, David Rügamer |
| 2025 | DeepGate4: Efficient and Effective Representation Learning for Circuit Design at Scale. Ziyang Zheng, Shan Huang, Jianyuan Zhong, Zhengyuan Shi, Guohao Dai, Ningyi Xu, Qiang Xu |
| 2025 | DeepLTL: Learning to Efficiently Satisfy Complex LTL Specifications for Multi-Task RL. Mathias Jackermeier, Alessandro Abate |
| 2025 | DeepRTL: Bridging Verilog Understanding and Generation with a Unified Representation Model. Yi Liu, Changran Xu, Yunhao Zhou, Zeju Li, Qiang Xu |
| 2025 | DeepSeek-Prover-V1.5: Harnessing Proof Assistant Feedback for Reinforcement Learning and Monte-Carlo Tree Search. Huajian Xin, Z. Z. Ren, Junxiao Song, Zhihong Shao, Wanjia Zhao, Haocheng Wang, Bo Liu, Liyue Zhang, Xuan Lu, Qiushi Du, Wenjun Gao, Haowei Zhang, Qihao Zhu, Dejian Yang, Zhibin Gou, Z. F. Wu, Fuli Luo, Chong Ruan |
| 2025 | DeepTAGE: Deep Temporal-Aligned Gradient Enhancement for Optimizing Spiking Neural Networks. Wei Liu, Li Yang, Mingxuan Zhao, Shuxun Wang, Jin Gao, Wenjuan Li, Bing Li, Weiming Hu |
| 2025 | DeeperForward: Enhanced Forward-Forward Training for Deeper and Better Performance. Liang Sun, Yang Zhang, Weizhao He, Jiajun Wen, Linlin Shen, Weicheng Xie |
| 2025 | DelTA: An Online Document-Level Translation Agent Based on Multi-Level Memory. Yutong Wang, Jiali Zeng, Xuebo Liu, Derek F. Wong, Fandong Meng, Jie Zhou, Min Zhang |
| 2025 | Delta: Dense Efficient Long-Range 3D tracking for any video. Tuan Duc Ngo, Peiye Zhuang, Evangelos Kalogerakis, Chuang Gan, Sergey Tulyakov, Hsin-Ying Lee, Chaoyang Wang |
| 2025 | Democratic Training Against Universal Adversarial Perturbations. Bing Sun, Jun Sun, Wei Zhao |
| 2025 | Demystifying Online Clustering of Bandits: Enhanced Exploration Under Stochastic and Smoothed Adversarial Contexts. Zhuohua Li, Maoli Liu, Xiangxiang Dai, John C. S. Lui |
| 2025 | Demystifying Topological Message-Passing with Relational Structures: A Case Study on Oversquashing in Simplicial Message-Passing. Diaaeldin Taha, James Chapman, Marzieh Eidi, Karel Devriendt, Guido Montúfar |
| 2025 | Demystifying the Token Dynamics of Deep Selective State Space Models. Thieu N. Vo, Duy-Tung Pham, Xin T. Tong, Tan Minh Nguyen |
| 2025 | DenoiseVAE: Learning Molecule-Adaptive Noise Distributions for Denoising-based 3D Molecular Pre-training. Yurou Liu, Jiahao Chen, Rui Jiao, Jiangmeng Li, Wenbing Huang, Bing Su |
| 2025 | Denoising Autoregressive Transformers for Scalable Text-to-Image Generation. Jiatao Gu, Yuyang Wang, Yizhe Zhang, Qihang Zhang, Dinghuai Zhang, Navdeep Jaitly, Joshua M. Susskind, Shuangfei Zhai |
| 2025 | Denoising Task Difficulty-based Curriculum for Training Diffusion Models. Jin-Young Kim, Hyojun Go, Soonwoo Kwon, Hyun-Gyoon Kim |
| 2025 | Denoising as Adaptation: Noise-Space Domain Adaptation for Image Restoration. Kang Liao, Zongsheng Yue, Zhouxia Wang, Chen Change Loy |
| 2025 | Denoising with a Joint-Embedding Predictive Architecture. Dengsheng Chen, Jie Hu, Xiaoming Wei, Enhua Wu |
| 2025 | Dense Video Object Captioning from Disjoint Supervision. Xingyi Zhou, Anurag Arnab, Chen Sun, Cordelia Schmid |
| 2025 | DenseGrounding: Improving Dense Language-Vision Semantics for Ego-centric 3D Visual Grounding. Henry Zheng, Hao Shi, Qihang Peng, Yong Xien Chng, Rui Huang, Yepeng Weng, Zhongchao Shi, Gao Huang |
| 2025 | DenseMatcher: Learning 3D Semantic Correspondence for Category-Level Manipulation from a Single Demo. Junzhe Zhu, Yuanchen Ju, Junyi Zhang, Muhan Wang, Zhecheng Yuan, Kaizhe Hu, Huazhe Xu |
| 2025 | Density estimation with LLMs: a geometric investigation of in-context learning trajectories. Toni J. B. Liu, Nicolas Boullé, Raphaël Sarfati, Christopher J. Earls |
| 2025 | Depth Any Video with Scalable Synthetic Data. Honghui Yang, Di Huang, Wei Yin, Chunhua Shen, Haifeng Liu, Xiaofei He, Binbin Lin, Wanli Ouyang, Tong He |
| 2025 | Depth Pro: Sharp Monocular Metric Depth in Less Than a Second. Alexey Bochkovskiy, Amaël Delaunoy, Hugo Germain, Marcel Santos, Yichao Zhou, Stephan R. Richter, Vladlen Koltun |
| 2025 | Deriving Causal Order from Single-Variable Interventions: Guarantees & Algorithm. Mathieu Chevalley, Patrick Schwab, Arash Mehrjou |
| 2025 | Descent with Misaligned Gradients and Applications to Hidden Convexity. Aditya Bhaskara, Ashok Cutkosky, Ravi Kumar, Manish Purohit |
| 2025 | Designing Concise ConvNets with Columnar Stages. Ashish Kumar, Jaesik Park |
| 2025 | Designing Mechanical Meta-Materials by Learning Equivariant Flows. Mehran Mirramezani, Anne S. Meeussen, Katia Bertoldi, Peter Orbanz, Ryan P. Adams |
| 2025 | Detecting Backdoor Samples in Contrastive Language Image Pretraining. Hanxun Huang, Sarah Monazam Erfani, Yige Li, Xingjun Ma, James Bailey |
| 2025 | Determine-Then-Ensemble: Necessity of Top-k Union for Large Language Model Ensembling. Yuxuan Yao, Han Wu, Mingyang Liu, Sichun Luo, Xiongwei Han, Jie Liu, Zhijiang Guo, Linqi Song |
| 2025 | DexTrack: Towards Generalizable Neural Tracking Control for Dexterous Manipulation from Human References. Xueyi Liu, Jianibieke Adalibieke, Qianwei Han, Yuzhe Qin, Li Yi |
| 2025 | DiSK: Differentially Private Optimizer with Simplified Kalman Filter for Noise Reduction. Xinwei Zhang, Zhiqi Bu, Borja Balle, Mingyi Hong, Meisam Razaviyayn, Vahab Mirrokni |
| 2025 | DiTTo-TTS: Diffusion Transformers for Scalable Text-to-Speech without Domain-Specific Factors. Keon Lee, Dong Won Kim, Jaehyeon Kim, Seungjun Chung, Jaewoong Cho |
| 2025 | Diff-2-in-1: Bridging Generation and Dense Perception with Diffusion Models. Shuhong Zheng, Zhipeng Bao, Ruoyu Zhao, Martial Hebert, Yu-Xiong Wang |
| 2025 | Diff-PIC: Revolutionizing Particle-In-Cell Nuclear Fusion Simulation with Diffusion Models. Chuan Liu, Chunshu Wu, Shihui Cao, Mingkai Chen, James Chenhao Liang, Ang Li, Michael Huang, Chuang Ren, Ying Nian Wu, Dongfang Liu, Tong Geng |
| 2025 | Diff-Prompt: Diffusion-Driven Prompt Generator with Mask Supervision. Weicai Yan, Wang Lin, Zirun Guo, Ye Wang, Fangming Feng, Xiaoda Yang, Zehan Wang, Tao Jin |
| 2025 | Diff3DS: Generating View-Consistent 3D Sketch via Differentiable Curve Rendering. Yibo Zhang, Lihong Wang, Changqing Zou, Tieru Wu, Rui Ma |
| 2025 | DiffGAD: A Diffusion-based Unsupervised Graph Anomaly Detector. Jinghan Li, Yuan Gao, Jinda Lu, Junfeng Fang, Congcong Wen, Hui Lin, Xiang Wang |
| 2025 | DiffPC: Diffusion-based High Perceptual Fidelity Image Compression with Semantic Refinement. Yichong Xia, Yimin Zhou, Jinpeng Wang, Baoyi An, Haoqian Wang, Yaowei Wang, Bin Chen |
| 2025 | DiffPuter: Empowering Diffusion Models for Missing Data Imputation. Hengrui Zhang, Liancheng Fang, Qitian Wu, Philip S. Yu |
| 2025 | DiffSplat: Repurposing Image Diffusion Models for Scalable Gaussian Splat Generation. Chenguo Lin, Panwang Pan, Bangbang Yang, Zeming Li, Yadong Mu |
| 2025 | Difference-of-submodular Bregman Divergence. Masanari Kimura, Takahiro Kawashima, Tasuku Soma, Hideitsu Hino |
| 2025 | Differentiable Causal Discovery for Latent Hierarchical Causal Models. Parjanya Prajakta Prashant, Ignavier Ng, Kun Zhang, Biwei Huang |
| 2025 | Differentiable Integer Linear Programming. Zijie Geng, Jie Wang, Xijun Li, Fangzhou Zhu, Jianye Hao, Bin Li, Feng Wu |
| 2025 | Differentiable Optimization of Similarity Scores Between Models and Brains. Nathan Cloos, Moufan Li, Markus Siegel, Scott L. Brincat, Earl K. Miller, Guangyu Robert Yang, Christopher J. Cueva |
| 2025 | Differentiable Rule Induction from Raw Sequence Inputs. Kun Gao, Katsumi Inoue, Yongzhi Cao, Hanpin Wang, Yang Feng |
| 2025 | Differentiable and Learnable Wireless Simulation with Geometric Transformers. Thomas Hehn, Markus Peschl, Tribhuvanesh Orekondy, Arash Behboodi, Johann Brehmer |
| 2025 | Differential Transformer. Tianzhu Ye, Li Dong, Yuqing Xia, Yutao Sun, Yi Zhu, Gao Huang, Furu Wei |
| 2025 | Differential learning kinetics govern the transition from memorization to generalization during in-context learning. Alex Nguyen, Gautam Reddy |
| 2025 | Differentially Private Federated Learning with Time-Adaptive Privacy Spending. Shahrzad Kiani, Nupur Kulkarni, Adam Dziedzic, Stark C. Draper, Franziska Boenisch |
| 2025 | Differentially Private Steering for Large Language Model Alignment. Anmol Goel, Yaxi Hu, Iryna Gurevych, Amartya Sanyal |
| 2025 | Differentially private learners for heterogeneous treatment effects. Maresa Schröder, Valentyn Melnychuk, Stefan Feuerriegel |
| 2025 | Differentially private optimization for non-decomposable objective functions. Weiwei Kong, Andrés Muñoz Medina, Mónica Ribero |
| 2025 | Differentiation and Specialization of Attention Heads via the Refined Local Learning Coefficient. George Wang, Jesse Hoogland, Stan van Wingerden, Zach Furman, Daniel Murfet |
| 2025 | Diffusing States and Matching Scores: A New Framework for Imitation Learning. Runzhe Wu, Yiding Chen, Gokul Swamy, Kianté Brantley, Wen Sun |
| 2025 | Diffusing to the Top: Boost Graph Neural Networks with Minimal Hyperparameter Tuning. Lequan Lin, Dai Shi, Andi Han, Zhiyong Wang, Junbin Gao |
| 2025 | Diffusion Actor-Critic: Formulating Constrained Policy Iteration as Diffusion Noise Regression for Offline Reinforcement Learning. Linjiajie Fang, Ruoxue Liu, Jing Zhang, Wenjia Wang, Bingyi Jing |
| 2025 | Diffusion Attribution Score: Evaluating Training Data Influence in Diffusion Models. Jinxu Lin, Linwei Tao, Minjing Dong, Chang Xu |
| 2025 | Diffusion Bridge AutoEncoders for Unsupervised Representation Learning. Yeongmin Kim, Kwanghyeon Lee, Minsang Park, Byeonghu Na, Il-Chul Moon |
| 2025 | Diffusion Bridge Implicit Models. Kaiwen Zheng, Guande He, Jianfei Chen, Fan Bao, Jun Zhu |
| 2025 | Diffusion Feedback Helps CLIP See Better. Wenxuan Wang, Quan Sun, Fan Zhang, Yepeng Tang, Jing Liu, Xinlong Wang |
| 2025 | Diffusion Generative Modeling for Spatially Resolved Gene Expression Inference from Histology Images. Sichen Zhu, Yuchen Zhu, Molei Tao, Peng Qiu |
| 2025 | Diffusion Models Are Real-Time Game Engines. Dani Valevski, Yaniv Leviathan, Moab Arar, Shlomi Fruchter |
| 2025 | Diffusion Models are Evolutionary Algorithms. Yanbo Zhang, Benedikt Hartl, Hananel Hazan, Michael Levin |
| 2025 | Diffusion Models as Cartoonists: The Curious Case of High Density Regions. Rafal Karczewski, Markus Heinonen, Vikas Garg |
| 2025 | Diffusion On Syntax Trees For Program Synthesis. Shreyas Kapur, Erik Jenner, Stuart Russell |
| 2025 | Diffusion Policy Policy Optimization. Allen Z. Ren, Justin Lidard, Lars Lien Ankile, Anthony Simeonov, Pulkit Agrawal, Anirudha Majumdar, Benjamin Burchfiel, Hongkai Dai, Max Simchowitz |
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| 2025 | Diffusion Transformer Captures Spatial-Temporal Dependencies: A Theory for Gaussian Process Data. Hengyu Fu, Zehao Dou, Jiawei Guo, Mengdi Wang, Minshuo Chen |
| 2025 | Diffusion Transformers for Tabular Data Time Series Generation. Fabrizio Garuti, Enver Sangineto, Simone Luetto, Lorenzo Forni, Rita Cucchiara |
| 2025 | Diffusion-Based Planning for Autonomous Driving with Flexible Guidance. Yinan Zheng, Ruiming Liang, Kexin Zheng, Jinliang Zheng, Liyuan Mao, Jianxiong Li, Weihao Gu, Rui Ai, Shengbo Eben Li, Xianyuan Zhan, Jingjing Liu |
| 2025 | Diffusion-NPO: Negative Preference Optimization for Better Preference Aligned Generation of Diffusion Models. Fu-Yun Wang, Yunhao Shui, Jingtan Piao, Keqiang Sun, Hongsheng Li |
| 2025 | Diffusion-based Decoupled Deterministic and Uncertain Framework for Probabilistic Multivariate Time Series Forecasting. Qi Li, Zhenyu Zhang, Lei Yao, Zhaoxia Li, Tianyi Zhong, Yong Zhang |
| 2025 | Diffusion-based Neural Network Weights Generation. Bedionita Soro, Bruno Andreis, Hayeon Lee, Wonyong Jeong, Song Chong, Frank Hutter, Sung Ju Hwang |
| 2025 | Diffusion2: Dynamic 3D Content Generation via Score Composition of Video and Multi-view Diffusion Models. Zeyu Yang, Zijie Pan, Chun Gu, Li Zhang |
| 2025 | DiffusionGuard: A Robust Defense Against Malicious Diffusion-based Image Editing. June Suk Choi, Kyungmin Lee, Jongheon Jeong, Saining Xie, Jinwoo Shin, Kimin Lee |
| 2025 | Digi-Q: Learning VLM Q-Value Functions for Training Device-Control Agents. Hao Bai, Yifei Zhou, Li Erran Li, Sergey Levine, Aviral Kumar |
| 2025 | Dimension Agnostic Neural Processes. Hyungi Lee, Chaeyun Jang, Dongbok Lee, Juho Lee |
| 2025 | Direct Distributional Optimization for Provable Alignment of Diffusion Models. Ryotaro Kawata, Kazusato Oko, Atsushi Nitanda, Taiji Suzuki |
| 2025 | Direct Post-Training Preference Alignment for Multi-Agent Motion Generation Model Using Implicit Feedback from Pre-training Demonstrations. Thomas Tian, Kratarth Goel |
| 2025 | Directional Gradient Projection for Robust Fine-Tuning of Foundation Models. Chengyue Huang, Junjiao Tian, Brisa Maneechotesuwan, Shivang Chopra, Zsolt Kira |
| 2025 | DisEnvisioner: Disentangled and Enriched Visual Prompt for Customized Image Generation. Jing He, Haodong Li, Yongzhe Hu, Guibao Shen, Yingjie Cai, Weichao Qiu, Ying-Cong Chen |
| 2025 | DisPose: Disentangling Pose Guidance for Controllable Human Image Animation. Hongxiang Li, Yaowei Li, Yuhang Yang, Junjie Cao, Zhihong Zhu, Xuxin Cheng, Long Chen |
| 2025 | Discovering Clone Negatives via Adaptive Contrastive Learning for Image-Text Matching. Renjie Pan, Jihao Dong, Hua Yang |
| 2025 | Discovering Group Structures via Unitary Representation Learning. Dongsung Huh |
| 2025 | Discovering Influential Neuron Path in Vision Transformers. Yifan Wang, Yifei Liu, Yingdong Shi, Changming Li, Anqi Pang, Sibei Yang, Jingyi Yu, Kan Ren |
| 2025 | Discovering Temporally Compositional Neural Manifolds with Switching Infinite GPFA. Changmin Yu, Maneesh Sahani, Máté Lengyel |
| 2025 | DiscoveryBench: Towards Data-Driven Discovery with Large Language Models. Bodhisattwa Prasad Majumder, Harshit Surana, Dhruv Agarwal, Bhavana Dalvi Mishra, Abhijeetsingh Meena, Aryan Prakhar, Tirth Vora, Tushar Khot, Ashish Sabharwal, Peter Clark |
| 2025 | Discrete Codebook World Models for Continuous Control. Aidan Scannell, Mohammadreza Nakhaeinezhadfard, Kalle Kujanpää, Yi Zhao, Kevin Sebastian Luck, Arno Solin, Joni Pajarinen |
| 2025 | Discrete Copula Diffusion. Anji Liu, Oliver Broadrick, Mathias Niepert, Guy Van den Broeck |
| 2025 | Discrete Diffusion Schrödinger Bridge Matching for Graph Transformation. Jun Hyeong Kim, Seonghwan Kim, Seokhyun Moon, Hyeongwoo Kim, Jeheon Woo, Woo Youn Kim |
| 2025 | Discrete Distribution Networks. Lei Yang |
| 2025 | Discrete GCBF Proximal Policy Optimization for Multi-agent Safe Optimal Control. Songyuan Zhang, Oswin So, Mitchell Black, Chuchu Fan |
| 2025 | Discrete Latent Plans via Semantic Skill Abstractions. Haobin Jiang, Jiangxing Wang, Zongqing Lu |
| 2025 | Discretization-invariance? On the Discretization Mismatch Errors in Neural Operators. Wenhan Gao, Ruichen Xu, Yuefan Deng, Yi Liu |
| 2025 | Discriminating image representations with principal distortions. Jenelle Feather, David Lipshutz, Sarah E. Harvey, Alex H. Williams, Eero P. Simoncelli |
| 2025 | Discriminator-Guided Embodied Planning for LLM Agent. Haofu Qian, Chenjia Bai, Jiatao Zhang, Fei Wu, Wei Song, Xuelong Li |
| 2025 | Disentangled Representation Learning with the Gromov-Monge Gap. Théo Uscidda, Luca Eyring, Karsten Roth, Fabian J. Theis, Zeynep Akata, Marco Cuturi |
| 2025 | Disentangling 3D Animal Pose Dynamics with Scrubbed Conditional Latent Variables. Joshua Huang Wu, Hari Koneru, James Russell Ravenel, Anshuman Sabath, James Michael Roach, Shaun Sze-Xian Lim, Michael R. Tadross, Alex H. Williams, Timothy W. Dunn |
| 2025 | Disentangling Representations through Multi-task Learning. Pantelis Vafidis, Aman Bhargava, Antonio Rangel |
| 2025 | Dissecting Adversarial Robustness of Multimodal LM Agents. Chen Henry Wu, Rishi Rajesh Shah, Jing Yu Koh, Russ Salakhutdinov, Daniel Fried, Aditi Raghunathan |
| 2025 | Dist Loss: Enhancing Regression in Few-Shot Region through Distribution Distance Constraint. Guangkun Nie, Gongzheng Tang, Shenda Hong |
| 2025 | DistRL: An Asynchronous Distributed Reinforcement Learning Framework for On-Device Control Agent. Taiyi Wang, Zhihao Wu, Jianheng Liu, Jianye Hao, Jun Wang, Kun Shao |
| 2025 | Distance-Based Tree-Sliced Wasserstein Distance. Hoang V. Tran, Minh-Khoi Nguyen-Nhat, Huyen Trang Pham, Thanh T. Chu, Tam Le, Tan Minh Nguyen |
| 2025 | DistillHGNN: A Knowledge Distillation Approach for High-Speed Hypergraph Neural Networks. Saman Forouzandeh, Parham Moradi, Mahdi Jalili |
| 2025 | Distilled Decoding 1: One-step Sampling of Image Auto-regressive Models with Flow Matching. Enshu Liu, Xuefei Ning, Yu Wang, Zinan Lin |
| 2025 | Distilling Dataset into Neural Field. DongHyeok Shin, HeeSun Bae, Gyuwon Sim, Wanmo Kang, Il-Chul Moon |
| 2025 | Distilling Reinforcement Learning Algorithms for In-Context Model-Based Planning. Jaehyeon Son, Soochan Lee, Gunhee Kim |
| 2025 | Distilling Structural Representations into Protein Sequence Models. Jeffrey Ouyang-Zhang, Chengyue Gong, Yue Zhao, Philipp Krähenbühl, Adam R. Klivans, Daniel Jesus Diaz |
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| 2025 | Distribution Backtracking Builds A Faster Convergence Trajectory for Diffusion Distillation. Shengyuan Zhang, Ling Yang, Zejian Li, An Zhao, Chenye Meng, Changyuan Yang, Guang Yang, Zhiyuan Yang, Lingyun Sun |
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| 2025 | Distribution-Specific Agnostic Conditional Classification With Halfspaces. Jizhou Huang, Brendan Juba |
| 2025 | Distributional Associations vs In-Context Reasoning: A Study of Feed-forward and Attention Layers. Lei Chen, Joan Bruna, Alberto Bietti |
| 2025 | Divergence of Neural Tangent Kernel in Classification Problems. Zixiong Yu, Songtao Tian, Guhan Chen |
| 2025 | Divergence-Regularized Discounted Aggregation: Equilibrium Finding in Multiplayer Partially Observable Stochastic Games. Runyu Lu, Yuanheng Zhu, Dongbin Zhao |
| 2025 | Divergence-enhanced Knowledge-guided Context Optimization for Visual-Language Prompt Tuning. Yilun Li, MiaoMiao Cheng, Xu Han, Wei Song |
| 2025 | Diverse Policies Recovering via Pointwise Mutual Information Weighted Imitation Learning. Hanlin Yang, Jian Yao, Weiming Liu, Qing Wang, Hanmin Qin, Hansheng Kong, Kirk Tang, Jiechao Xiong, Chao Yu, Kai Li, Junliang Xing, Hongwu Chen, Juchao Zhuo, Qiang Fu, Yang Wei, Haobo Fu |
| 2025 | Diverse Preference Learning for Capabilities and Alignment. Stewart Slocum, Asher Parker-Sartori, Dylan Hadfield-Menell |
| 2025 | Diversity Empowers Intelligence: Integrating Expertise of Software Engineering Agents. Kexun Zhang, Weiran Yao, Zuxin Liu, Yihao Feng, Zhiwei Liu, Rithesh R. N., Tian Lan, Lei Li, Renze Lou, Jiacheng Xu, Bo Pang, Yingbo Zhou, Shelby Heinecke, Silvio Savarese, Huan Wang, Caiming Xiong |
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| 2025 | Do Deep Neural Network Solutions Form a Star Domain? Ankit Sonthalia, Alexander Rubinstein, Ehsan Abbasnejad, Seong Joon Oh |
| 2025 | Do Egocentric Video-Language Models Truly Understand Hand-Object Interactions? Boshen Xu, Ziheng Wang, Yang Du, Zhinan Song, Sipeng Zheng, Qin Jin |
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| 2025 | Do LLMs have Consistent Values? Naama Rozen, Liat Bezalel, Gal Elidan, Amir Globerson, Ella Daniel |
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| 2025 | Do as I do (Safely): Mitigating Task-Specific Fine-tuning Risks in Large Language Models. Francisco Eiras, Aleksandar Petrov, Philip Torr, M. Pawan Kumar, Adel Bibi |
| 2025 | Do as We Do, Not as You Think: the Conformity of Large Language Models. Zhiyuan Weng, Guikun Chen, Wenguan Wang |
| 2025 | DoF: A Diffusion Factorization Framework for Offline Multi-Agent Reinforcement Learning. Chao Li, Ziwei Deng, Chenxing Lin, Wenqi Chen, Yongquan Fu, Weiquan Liu, Chenglu Wen, Cheng Wang, Siqi Shen |
| 2025 | Dobi-SVD: Differentiable SVD for LLM Compression and Some New Perspectives. Qinsi Wang, Jinghan Ke, Masayoshi Tomizuka, Kurt Keutzer, Chenfeng Xu |
| 2025 | DocMIA: Document-Level Membership Inference Attacks against DocVQA Models. Khanh Nguyen, Raouf Kerkouche, Mario Fritz, Dimosthenis Karatzas |
| 2025 | Does Refusal Training in LLMs Generalize to the Past Tense? Maksym Andriushchenko, Nicolas Flammarion |
| 2025 | Does SGD really happen in tiny subspaces? Minhak Song, Kwangjun Ahn, Chulhee Yun |
| 2025 | Does Safety Training of LLMs Generalize to Semantically Related Natural Prompts? Sravanti Addepalli, Yerram Varun, Arun Suggala, Karthikeyan Shanmugam, Prateek Jain |
| 2025 | Does Spatial Cognition Emerge in Frontier Models? Santhosh Kumar Ramakrishnan, Erik Wijmans, Philipp Krähenbühl, Vladlen Koltun |
| 2025 | Does Training with Synthetic Data Truly Protect Privacy? Yunpeng Zhao, Jie Zhang |
| 2025 | Domain Guidance: A Simple Transfer Approach for a Pre-trained Diffusion Model. Jincheng Zhong, Xiangcheng Zhang, Jianmin Wang, Mingsheng Long |
| 2025 | Don't Take Things Out of Context: Attention Intervention for Enhancing Chain-of-Thought Reasoning in Large Language Models. Shaotian Yan, Chen Shen, Wenxiao Wang, Liang Xie, Junjie Liu, Jieping Ye |
| 2025 | Don't flatten, tokenize! Unlocking the key to SoftMoE's efficacy in deep RL. Ghada Sokar, Johan S. Obando-Ceron, Aaron C. Courville, Hugo Larochelle, Pablo Samuel Castro |
| 2025 | Don't stop me Now: Embedding based Scheduling for LLMS. Rana Shahout, Eran Malach, Chunwei Liu, Weifan Jiang, Minlan Yu, Michael Mitzenmacher |
| 2025 | Doubly Optimal Policy Evaluation for Reinforcement Learning. Shuze Daniel Liu, Claire Chen, Shangtong Zhang |
| 2025 | Doubly robust identification of treatment effects from multiple environments. Piersilvio De Bartolomeis, Julia Kostin, Javier Abad, Yixin Wang, Fanny Yang |
| 2025 | Drama: Mamba-Enabled Model-Based Reinforcement Learning Is Sample and Parameter Efficient. Wenlong Wang, Ivana Dusparic, Yucheng Shi, Ke Zhang, Vinny Cahill |
| 2025 | Draw-and-Understand: Leveraging Visual Prompts to Enable MLLMs to Comprehend What You Want. Weifeng Lin, Xinyu Wei, Ruichuan An, Peng Gao, Bocheng Zou, Yulin Luo, Siyuan Huang, Shanghang Zhang, Hongsheng Li |
| 2025 | Dream to Manipulate: Compositional World Models Empowering Robot Imitation Learning with Imagination. Leonardo Barcellona, Andrii Zadaianchuk, Davide Allegro, Samuele Papa, Stefano Ghidoni, Efstratios Gavves |
| 2025 | DreamBench++: A Human-Aligned Benchmark for Personalized Image Generation. Yuang Peng, Yuxin Cui, Haomiao Tang, Zekun Qi, Runpei Dong, Jing Bai, Chunrui Han, Zheng Ge, Xiangyu Zhang, Shu-Tao Xia |
| 2025 | DreamCatalyst: Fast and High-Quality 3D Editing via Controlling Editability and Identity Preservation. Jiwook Kim, Seonho Lee, Jaeyo Shin, Jiho Choi, Hyunjung Shim |
| 2025 | DreamDistribution: Learning Prompt Distribution for Diverse In-distribution Generation. Brian Nlong Zhao, Yuhang Xiao, Jiashu Xu, Xinyang Jiang, Yifan Yang, Dongsheng Li, Laurent Itti, Vibhav Vineet, Yunhao Ge |
| 2025 | Dreamweaver: Learning Compositional World Models from Pixels. Junyeob Baek, Yi-Fu Wu, Gautam Singh, Sungjin Ahn |
| 2025 | DriveTransformer: Unified Transformer for Scalable End-to-End Autonomous Driving. Xiaosong Jia, Junqi You, Zhiyuan Zhang, Junchi Yan |
| 2025 | Drop-Upcycling: Training Sparse Mixture of Experts with Partial Re-initialization. Taishi Nakamura, Takuya Akiba, Kazuki Fujii, Yusuke Oda, Rio Yokota, Jun Suzuki |
| 2025 | Dual Process Learning: Controlling Use of In-Context vs. In-Weights Strategies with Weight Forgetting. Suraj Anand, Michael A. Lepori, Jack Merullo, Ellie Pavlick |
| 2025 | Dualformer: Controllable Fast and Slow Thinking by Learning with Randomized Reasoning Traces. DiJia Su, Sainbayar Sukhbaatar, Michael Rabbat, Yuandong Tian, Qinqing Zheng |
| 2025 | DuoAttention: Efficient Long-Context LLM Inference with Retrieval and Streaming Heads. Guangxuan Xiao, Jiaming Tang, Jingwei Zuo, Junxian Guo, Shang Yang, Haotian Tang, Yao Fu, Song Han |
| 2025 | Duoduo CLIP: Efficient 3D Understanding with Multi-View Images. Han-Hung Lee, Yiming Zhang, Angel X. Chang |
| 2025 | Durable Quantization Conditioned Misalignment Attack on Large Language Models. Peiran Dong, Haowei Li, Song Guo |
| 2025 | DyCAST: Learning Dynamic Causal Structure from Time Series. Yue Cheng, Bochen Lyu, Weiwei Xing, Zhanxing Zhu |
| 2025 | DynAlign: Unsupervised Dynamic Taxonomy Alignment for Cross-Domain Segmentation. Han Sun, Rui Gong, Ismail Nejjar, Olga Fink |
| 2025 | DynFrs: An Efficient Framework for Machine Unlearning in Random Forest. Shurong Wang, Zhuoyang Shen, Xinbao Qiao, Tongning Zhang, Meng Zhang |
| 2025 | DynaMath: A Dynamic Visual Benchmark for Evaluating Mathematical Reasoning Robustness of Vision Language Models. Chengke Zou, Xingang Guo, Rui Yang, Junyu Zhang, Bin Hu, Huan Zhang |
| 2025 | DynaPrompt: Dynamic Test-Time Prompt Tuning. Zehao Xiao, Shilin Yan, Jack Hong, Jiayin Cai, Xiaolong Jiang, Yao Hu, Jiayi Shen, Qi Wang, Cees G. M. Snoek |
| 2025 | Dynamic Assortment Selection and Pricing with Censored Preference Feedback. Jung-Hun Kim, Min-hwan Oh |
| 2025 | Dynamic Contrastive Skill Learning with State-Transition Based Skill Clustering and Dynamic Length Adjustment. Jinwoo Choi, Seung-Woo Seo |
| 2025 | Dynamic Diffusion Transformer. Wangbo Zhao, Yizeng Han, Jiasheng Tang, Kai Wang, Yibing Song, Gao Huang, Fan Wang, Yang You |
| 2025 | Dynamic Gaussians Mesh: Consistent Mesh Reconstruction from Dynamic Scenes. Isabella Liu, Hao Su, Xiaolong Wang |
| 2025 | Dynamic Loss-Based Sample Reweighting for Improved Large Language Model Pretraining. Daouda Sow, Herbert Woisetschläger, Saikiran Bulusu, Shiqiang Wang, Hans-Arno Jacobsen, Yingbin Liang |
| 2025 | Dynamic Low-Rank Sparse Adaptation for Large Language Models. Weizhong Huang, Yuxin Zhang, Xiawu Zheng, Yang Liu, Jing Lin, Yiwu Yao, Rongrong Ji |
| 2025 | Dynamic Mixture of Experts: An Auto-Tuning Approach for Efficient Transformer Models. Yongxin Guo, Zhenglin Cheng, Xiaoying Tang, Zhaopeng Tu, Tao Lin |
| 2025 | Dynamic Modeling of Patients, Modalities and Tasks via Multi-modal Multi-task Mixture of Experts. Chenwei Wu, Zitao Shuai, Zhengxu Tang, Luning Wang, Liyue Shen |
| 2025 | Dynamic Multimodal Evaluation with Flexible Complexity by Vision-Language Bootstrapping. Yue Yang, Shuibo Zhang, Kaipeng Zhang, Yi Bin, Yu Wang, Ping Luo, Wenqi Shao |
| 2025 | Dynamic Negative Guidance of Diffusion Models. Felix Koulischer, Johannes Deleu, Gabriel Raya, Thomas Demeester, Luca Ambrogioni |
| 2025 | Dynamic Neural Fortresses: An Adaptive Shield for Model Extraction Defense. Siyu Luan, Zhenyi Wang, Li Shen, Zonghua Gu, Chao Wu, Dacheng Tao |
| 2025 | Dynamic Sparse Training versus Dense Training: The Unexpected Winner in Image Corruption Robustness. Boqian Wu, Qiao Xiao, Shunxin Wang, Nicola Strisciuglio, Mykola Pechenizkiy, Maurice van Keulen, Decebal Constantin Mocanu, Elena Mocanu |
| 2025 | Dynamic-LLaVA: Efficient Multimodal Large Language Models via Dynamic Vision-language Context Sparsification. Wenxuan Huang, Zijie Zhai, Yunhang Shen, Shaosheng Cao, Fei Zhao, Xiangfeng Xu, Zheyu Ye, Shaohui Lin |
| 2025 | Dynamic-SUPERB Phase-2: A Collaboratively Expanding Benchmark for Measuring the Capabilities of Spoken Language Models with 180 Tasks. Chien-yu Huang, Wei-Chih Chen, Shu-Wen Yang, Andy T. Liu, Chen-An Li, Yu-Xiang Lin, Wei-Cheng Tseng, Anuj Diwan, Yi-Jen Shih, Jiatong Shi, William Chen, Chih-Kai Yang, Xuanjun Chen, Chi-Yuan Hsiao, Puyuan Peng, Shih-Heng Wang, Chun-Yi Kuan, Ke-Han Lu, Kai-Wei Chang, Fabian Alejandro Ritter Gutierrez, et al. |
| 2025 | DynamicCity: Large-Scale 4D Occupancy Generation from Dynamic Scenes. Hengwei Bian, Lingdong Kong, Haozhe Xie, Liang Pan, Yu Qiao, Ziwei Liu |
| 2025 | Dynamical Diffusion: Learning Temporal Dynamics with Diffusion Models. Xingzhuo Guo, Yu Zhang, Baixu Chen, Haoran Xu, Jianmin Wang, Mingsheng Long |
| 2025 | Dysca: A Dynamic and Scalable Benchmark for Evaluating Perception Ability of LVLMs. Jie Zhang, Zhongqi Wang, Mengqi Lei, Zheng Yuan, Bei Yan, Shiguang Shan, Xilin Chen |
| 2025 | E(3)-equivariant models cannot learn chirality: Field-based molecular generation. Alexandru Dumitrescu, Dani Korpela, Markus Heinonen, Yogesh Verma, Valerii Iakovlev, Vikas Garg, Harri Lähdesmäki |
| 2025 | E(n) Equivariant Topological Neural Networks. Claudio Battiloro, Ege Karaismailoglu, Mauricio Tec, George Dasoulas, Michelle Audirac, Francesca Dominici |
| 2025 | EC-DIT: Scaling Diffusion Transformers with Adaptive Expert-Choice Routing. Haotian Sun, Tao Lei, Bowen Zhang, Yanghao Li, Haoshuo Huang, Ruoming Pang, Bo Dai, Nan Du |
| 2025 | EC-Diffuser: Multi-Object Manipulation via Entity-Centric Behavior Generation. Carl Qi, Dan Haramati, Tal Daniel, Aviv Tamar, Amy Zhang |
| 2025 | ECD: A Machine Learning Benchmark for Predicting Enhanced-Precision Electronic Charge Density in Crystalline Inorganic Materials. Pin Chen, Zexin Xu, Qing Mo, Hongjin Zhong, Fengyang Xu, Yutong Lu |
| 2025 | ECHOPulse: ECG Controlled Echocardio-gram Video Generation. Yiwei Li, Sekeun Kim, Zihao Wu, Hanqi Jiang, Yi Pan, Pengfei Jin, Sifan Song, Yucheng Shi, Xiaowei Yu, Tianze Yang, Tianming Liu, Quanzheng Li, Xiang Li |
| 2025 | EDiT: A Local-SGD-Based Efficient Distributed Training Method for Large Language Models. Jialiang Cheng, Ning Gao, Yun Yue, Zhiling Ye, Jiadi Jiang, Jian Sha |
| 2025 | EG4D: Explicit Generation of 4D Object without Score Distillation. Qi Sun, Zhiyang Guo, Ziyu Wan, Jing Nathan Yan, Shengming Yin, Wengang Zhou, Jing Liao, Houqiang Li |
| 2025 | ELBOing Stein: Variational Bayes with Stein Mixture Inference. Ola Rønning, Eric T. Nalisnick, Christophe Ley, Padhraic Smyth, Thomas Hamelryck |
| 2025 | ELFS: Label-Free Coreset Selection with Proxy Training Dynamics. Haizhong Zheng, Elisa Tsai, Yifu Lu, Jiachen Sun, Brian R. Bartoldson, Bhavya Kailkhura, Atul Prakash |
| 2025 | ELICIT: LLM Augmentation Via External In-context Capability. Futing Wang, Jianhao Yan, Yue Zhang, Tao Lin |
| 2025 | EMMA: Empowering Multi-modal Mamba with Structural and Hierarchical Alignment. Yifei Xing, Xiangyuan Lan, Ruiping Wang, Dongmei Jiang, Wenjun Huang, Qingfang Zheng, Yaowei Wang |
| 2025 | EMOS: Embodiment-aware Heterogeneous Multi-robot Operating System with LLM Agents. Junting Chen, Checheng Yu, Xunzhe Zhou, Tianqi Xu, Yao Mu, Mengkang Hu, Wenqi Shao, Yikai Wang, Guohao Li, Lin Shao |
| 2025 | ESE: Espresso Sentence Embeddings. Xianming Li, Zongxi Li, Jing Li, Haoran Xie, Qing Li |
| 2025 | ETA: Evaluating Then Aligning Safety of Vision Language Models at Inference Time. Yi Ding, Bolian Li, Ruqi Zhang |
| 2025 | EVA: Geometric Inverse Design for Fast Protein Motif-Scaffolding with Coupled Flow. Yufei Huang, Yunshu Liu, Lirong Wu, Haitao Lin, Cheng Tan, Odin Zhang, Zhangyang Gao, Siyuan Li, Zicheng Liu, Yunfan Liu, Tailin Wu, Stan Z. Li |
| 2025 | Eagle: Exploring The Design Space for Multimodal LLMs with Mixture of Encoders. Min Shi, Fuxiao Liu, Shihao Wang, Shijia Liao, Subhashree Radhakrishnan, Yilin Zhao, De-An Huang, Hongxu Yin, Karan Sapra, Yaser Yacoob, Humphrey Shi, Bryan Catanzaro, Andrew Tao, Jan Kautz, Zhiding Yu, Guilin Liu |
| 2025 | Earlier Tokens Contribute More: Learning Direct Preference Optimization From Temporal Decay Perspective. Ruichen Shao, Bei Li, Gangao Liu, Yang Chen, ZhouXiang, Jingang Wang, Xunliang Cai, Peng Li |
| 2025 | Easing Training Process of Rectified Flow Models Via Lengthening Inter-Path Distance. Shifeng Xu, Yanzhu Liu, Adams Wai-Kin Kong |
| 2025 | EcoFace: Audio-Visual Emotional Co-Disentanglement Speech-Driven 3D Talking Face Generation. Jiajian Xie, Shengyu Zhang, Mengze Li, Chengfei Lv, Zhou Zhao, Fei Wu |
| 2025 | Edge Prompt Tuning for Graph Neural Networks. Xingbo Fu, Yinhan He, Jundong Li |
| 2025 | Edge-aware Image Smoothing with Relative Wavelet Domain Representation. Huiqing Qi, Xiaoliu Luo, Tingting Li, Fang Li |
| 2025 | EdgeRunner: Auto-regressive Auto-encoder for Artistic Mesh Generation. Jiaxiang Tang, Zhaoshuo Li, Zekun Hao, Xian Liu, Gang Zeng, Ming-Yu Liu, Qinsheng Zhang |
| 2025 | EditRoom: LLM-parameterized Graph Diffusion for Composable 3D Room Layout Editing. Kaizhi Zheng, Xiaotong Chen, Xuehai He, Jing Gu, Linjie Li, Zhengyuan Yang, Kevin Lin, Jianfeng Wang, Lijuan Wang, Xin Eric Wang |
| 2025 | Effective Interplay between Sparsity and Quantization: From Theory to Practice. Simla Burcu Harma, Ayan Chakraborty, Elizaveta Kostenok, Danila Mishin, Dongho Ha, Babak Falsafi, Martin Jaggi, Ming Liu, Yunho Oh, Suvinay Subramanian, Amir Yazdanbakhsh |
| 2025 | Effective and Efficient Time-Varying Counterfactual Prediction with State-Space Models. Haotian Wang, Haoxuan Li, Hao Zou, Haoang Chi, Long Lan, Wanrong Huang, Wenjing Yang |
| 2025 | Effective post-training embedding compression via temperature control in contrastive training. Georgiana Dinu, Corey D. Barrett, Yi Xiang, Miguel Romero Calvo, Anna Currey, Xing Niu |
| 2025 | Efficient Action-Constrained Reinforcement Learning via Acceptance-Rejection Method and Augmented MDPs. Wei Hung, Shao-Hua Sun, Ping-Chun Hsieh |
| 2025 | Efficient Active Imitation Learning with Random Network Distillation. Emilien Biré, Anthony Kobanda, Ludovic Denoyer, Rémy Portelas |
| 2025 | Efficient Alternating Minimization with Applications to Weighted Low Rank Approximation. Zhao Song, Mingquan Ye, Junze Yin, Lichen Zhang |
| 2025 | Efficient Automated Circuit Discovery in Transformers using Contextual Decomposition. Aliyah R. Hsu, Georgia Zhou, Yeshwanth Cherapanamjeri, Yaxuan Huang, Anobel Y. Odisho, Peter R. Carroll, Bin Yu |
| 2025 | Efficient Biological Data Acquisition through Inference Set Design. Ihor Neporozhnii, Julien Roy, Emmanuel Bengio, Jason S. Hartford |
| 2025 | Efficient Causal Decision Making with One-sided Feedback. Jianing Chu, Shu Yang, Wenbin Lu, Pulak Ghosh |
| 2025 | Efficient Cross-Episode Meta-RL. Gresa Shala, André Biedenkapp, Pierre Krack, Florian Walter, Josif Grabocka |
| 2025 | Efficient Dictionary Learning with Switch Sparse Autoencoders. Anish Mudide, Joshua Engels, Eric J. Michaud, Max Tegmark, Christian Schröder de Witt |
| 2025 | Efficient Diffusion Transformer Policies with Mixture of Expert Denoisers for Multitask Learning. Moritz Reuss, Jyothish Pari, Pulkit Agrawal, Rudolf Lioutikov |
| 2025 | Efficient Discovery of Pareto Front for Multi-Objective Reinforcement Learning. Ruohong Liu, Yuxin Pan, Linjie Xu, Lei Song, Pengcheng You, Yize Chen, Jiang Bian |
| 2025 | Efficient Distribution Matching of Representations via Noise-Injected Deep InfoMax. Ivan Butakov, Alexander Semenenko, Alexander Tolmachev, Andrey Gladkov, Marina Munkhoeva, Alexey A. Frolov |
| 2025 | Efficient Diversity-Preserving Diffusion Alignment via Gradient-Informed GFlowNets. Zhen Liu, Tim Z. Xiao, Weiyang Liu, Yoshua Bengio, Dinghuai Zhang |
| 2025 | Efficient Evolutionary Search Over Chemical Space with Large Language Models. Haorui Wang, Marta Skreta, Cher Tian Ser, Wenhao Gao, Lingkai Kong, Felix Strieth-Kalthoff, Chenru Duan, Yuchen Zhuang, Yue Yu, Yanqiao Zhu, Yuanqi Du, Alán Aspuru-Guzik, Kirill Neklyudov, Chao Zhang |
| 2025 | Efficient Exploration and Discriminative World Model Learning with an Object-Centric Abstraction. Anthony GX-Chen, Kenneth Marino, Rob Fergus |
| 2025 | Efficient Imitation under Misspecification. Nicolas A. Espinosa Dice, Sanjiban Choudhury, Wen Sun, Gokul Swamy |
| 2025 | Efficient Inference for Large Language Model-based Generative Recommendation. Xinyu Lin, Chaoqun Yang, Wenjie Wang, Yongqi Li, Cunxiao Du, Fuli Feng, See-Kiong Ng, Tat-Seng Chua |
| 2025 | Efficient Interpolation between Extragradient and Proximal Methods for Weak MVIs. Thomas Pethick, Ioannis Mavrothalassitis, Volkan Cevher |
| 2025 | Efficient Jailbreak Attack sequences on Large Language Models via Multi-Armed Bandit-based Context switching. Aditya Ramesh, Shivam Bhardwaj, Aditya Saibewar, Manohar Kaul |
| 2025 | Efficient Learning with Sine-Activated Low-Rank Matrices. Yiping Ji, Hemanth Saratchandran, Cameron Gordon, Zeyu Zhang, Simon Lucey |
| 2025 | Efficient Low-Bit Quantization with Adaptive Scales for Multi-Task Co-Training. Boyu Liu, Haoyu Huang, Linlin Yang, Yanjing Li, Guodong Guo, Xianbin Cao, Baochang Zhang |
| 2025 | Efficient Masked AutoEncoder for Video Object Counting and A Large-Scale Benchmark. Bing Cao, Quanhao Lu, Jiekang Feng, Qilong Wang, Pengfei Zhu, Qinghua Hu |
| 2025 | Efficient Model Editing with Task-Localized Sparse Fine-tuning. Leonardo Iurada, Marco Ciccone, Tatiana Tommasi |
| 2025 | Efficient Model-Based Reinforcement Learning Through Optimistic Thompson Sampling. Jasmine Bayrooti, Carl Henrik Ek, Amanda Prorok |
| 2025 | Efficient Multi-agent Offline Coordination via Diffusion-based Trajectory Stitching. Lei Yuan, Yuqi Bian, Lihe Li, Ziqian Zhang, Cong Guan, Yang Yu |
| 2025 | Efficient Neuron Segmentation in Electron Microscopy by Affinity-Guided Queries. Hang Chen, Chufeng Tang, Xiao Li, Xiaolin Hu |
| 2025 | Efficient Off-Policy Learning for High-Dimensional Action Spaces. Fabian Otto, Philipp Becker, Ngo Anh Vien, Gerhard Neumann |
| 2025 | Efficient Online Pruning and Abstraction for Imperfect Information Extensive-Form Games. Boning Li, Longbo Huang |
| 2025 | Efficient Online Reinforcement Learning Fine-Tuning Need Not Retain Offline Data. Zhiyuan Zhou, Andy Peng, Qiyang Li, Sergey Levine, Aviral Kumar |
| 2025 | Efficient Perplexity Bound and Ratio Matching in Discrete Diffusion Language Models. Etrit Haxholli, Yeti Ziya Gurbuz, Ogul Can, Eli Waxman |
| 2025 | Efficient Policy Evaluation with Safety Constraint for Reinforcement Learning. Claire Chen, Shuze Daniel Liu, Shangtong Zhang |
| 2025 | Efficient Reinforcement Learning with Large Language Model Priors. Xue Yan, Yan Song, Xidong Feng, Mengyue Yang, Haifeng Zhang, Haitham Bou-Ammar, Jun Wang |
| 2025 | Efficient Residual Learning with Mixture-of-Experts for Universal Dexterous Grasping. Ziye Huang, Haoqi Yuan, Yuhui Fu, Zongqing Lu |
| 2025 | Efficient Source-Free Time-Series Adaptation via Parameter Subspace Disentanglement. Gaurav Patel, Christopher Michael Sandino, Behrooz Mahasseni, Ellen L. Zippi, Erdrin Azemi, Ali Moin, Juri Minxha |
| 2025 | Efficient Sparse PCA via Block-Diagonalization. Alberto Del Pia, Dekun Zhou, Yinglun Zhu |
| 2025 | Efficient Top-m Data Values Identification for Data Selection. Xiaoqiang Lin, Xinyi Xu, See-Kiong Ng, Bryan Kian Hsiang Low |
| 2025 | Efficient Training of Neural Stochastic Differential Equations by Matching Finite Dimensional Distributions. Jianxin Zhang, Josh Viktorov, Doosan Jung, Emily Pitler |
| 2025 | Efficient and Accurate Explanation Estimation with Distribution Compression. Hubert Baniecki, Giuseppe Casalicchio, Bernd Bischl, Przemyslaw Biecek |
| 2025 | Efficient and Context-Aware Label Propagation for Zero-/Few-Shot Training-Free Adaptation of Vision-Language Model. Yushu Li, Yongyi Su, Adam Goodge, Kui Jia, Xun Xu |
| 2025 | Efficient and Robust Neural Combinatorial Optimization via Wasserstein-Based Coresets. Xu Wang, Fuyou Miao, Wenjie Liu, Yan Xiong |
| 2025 | Efficient and Trustworthy Causal Discovery with Latent Variables and Complex Relations. Xiu-Chuan Li, Tongliang Liu |
| 2025 | Efficient stagewise pretraining via progressive subnetworks. Abhishek Panigrahi, Nikunj Saunshi, Kaifeng Lyu, Sobhan Miryoosefi, Sashank J. Reddi, Satyen Kale, Sanjiv Kumar |
| 2025 | Efficiently Democratizing Medical LLMs for 50 Languages via a Mixture of Language Family Experts. Guorui Zheng, Xidong Wang, Juhao Liang, Nuo Chen, Yuping Zheng, Benyou Wang |
| 2025 | Efficiently Learning at Test-Time: Active Fine-Tuning of LLMs. Jonas Hübotter, Sascha Bongni, Ido Hakimi, Andreas Krause |
| 2025 | Efficiently Parameterized Neural Metriplectic Systems. Anthony Gruber, Kookjin Lee, Haksoo Lim, Noseong Park, Nathaniel Trask |
| 2025 | EffoVPR: Effective Foundation Model Utilization for Visual Place Recognition. Issar Tzachor, Boaz Lerner, Matan Levy, Michael Green, Tal Berkovitz Shalev, Gavriel Habib, Dvir Samuel, Noam Korngut Zailer, Or Shimshi, Nir Darshan, Rami Ben-Ari |
| 2025 | EgoExo-Gen: Ego-centric Video Prediction by Watching Exo-centric Videos. Jilan Xu, Yifei Huang, Baoqi Pei, Junlin Hou, Qingqiu Li, Guo Chen, Yuejie Zhang, Rui Feng, Weidi Xie |
| 2025 | EgoSim: Egocentric Exploration in Virtual Worlds with Multi-modal Conditioning. Wei Yu, Songheng Yin, Steve Easterbrook, Animesh Garg |
| 2025 | Eia: Environmental Injection Attack on Generalist Web Agents for Privacy Leakage. Zeyi Liao, Lingbo Mo, Chejian Xu, Mintong Kang, Jiawei Zhang, Chaowei Xiao, Yuan Tian, Bo Li, Huan Sun |
| 2025 | ElasticTok: Adaptive Tokenization for Image and Video. Wilson Yan, Volodymyr Mnih, Aleksandra Faust, Matei Zaharia, Pieter Abbeel, Hao Liu |
| 2025 | Eliciting Human Preferences with Language Models. Belinda Z. Li, Alex Tamkin, Noah D. Goodman, Jacob Andreas |
| 2025 | Eliminating Oversaturation and Artifacts of High Guidance Scales in Diffusion Models. Seyedmorteza Sadat, Otmar Hilliges, Romann M. Weber |
| 2025 | Eliminating Position Bias of Language Models: A Mechanistic Approach. Ziqi Wang, Hanlin Zhang, Xiner Li, Kuan-Hao Huang, Chi Han, Shuiwang Ji, Sham M. Kakade, Hao Peng, Heng Ji |
| 2025 | Elliptic Loss Regularization. Ali Hasan, Haoming Yang, Yuting Ng, Vahid Tarokh |
| 2025 | Elucidating the Preconditioning in Consistency Distillation. Kaiwen Zheng, Guande He, Jianfei Chen, Fan Bao, Jun Zhu |
| 2025 | EmbedLLM: Learning Compact Representations of Large Language Models. Richard Zhuang, Tianhao Wu, Zhaojin Wen, Andrew Li, Jiantao Jiao, Kannan Ramchandran |
| 2025 | EmbodiedSAM: Online Segment Any 3D Thing in Real Time. Xiuwei Xu, Huangxing Chen, Linqing Zhao, Ziwei Wang, Jie Zhou, Jiwen Lu |
| 2025 | Emergence of a High-Dimensional Abstraction Phase in Language Transformers. Emily Cheng, Diego Doimo, Corentin Kervadec, Iuri Macocco, Lei Yu, Alessandro Laio, Marco Baroni |
| 2025 | Emergence of meta-stable clustering in mean-field transformer models. Giuseppe Bruno, Federico Pasqualotto, Andrea Agazzi |
| 2025 | Emergent Orientation Maps - - Mechanisms, Coding Efficiency and Robustness. Haixin Zhong, Haoyu Wang, Wei P. Dai, Yuchao Huang, Mingyi Huang, Rubin Wang, Anna Wang Roe, Yuguo Yu |
| 2025 | Emerging Safety Attack and Defense in Federated Instruction Tuning of Large Language Models. Rui Ye, Jingyi Chai, Xiangrui Liu, Yaodong Yang, Yanfeng Wang, Siheng Chen |
| 2025 | Empowering LLM Agents with Zero-Shot Optimal Decision-Making through Q-learning. Jiajun Chai, Sicheng Li, Yuqian Fu, Dongbin Zhao, Yuanheng Zhu |
| 2025 | Empowering Users in Digital Privacy Management through Interactive LLM-Based Agents. Bolun Sun, Yifan Zhou, Haiyun Jiang |
| 2025 | Enabling Realtime Reinforcement Learning at Scale with Staggered Asynchronous Inference. Matthew Riemer, Gopeshh Subbaraj, Glen Berseth, Irina Rish |
| 2025 | Encryption-Friendly LLM Architecture. Donghwan Rho, Taeseong Kim, Minje Park, Jung Woo Kim, Hyunsik Chae, Ernest K. Ryu, Jung Hee Cheon |
| 2025 | End-to-end Learning of Gaussian Mixture Priors for Diffusion Sampler. Denis Blessing, Xiaogang Jia, Gerhard Neumann |
| 2025 | Endless Jailbreaks with Bijection Learning. Brian R. Y. Huang, Maximilian Li, Leonard Tang |
| 2025 | Endowing Visual Reprogramming with Adversarial Robustness. Shengjie Zhou, Xin Cheng, Haiyang Xu, Ming Yan, Tao Xiang, Feng Liu, Lei Feng |
| 2025 | Energy-Based Diffusion Language Models for Text Generation. Minkai Xu, Tomas Geffner, Karsten Kreis, Weili Nie, Yilun Xu, Jure Leskovec, Stefano Ermon, Arash Vahdat |
| 2025 | Energy-Weighted Flow Matching for Offline Reinforcement Learning. Shiyuan Zhang, Weitong Zhang, Quanquan Gu |
| 2025 | Energy-based Backdoor Defense Against Federated Graph Learning. Guancheng Wan, Zitong Shi, Wenke Huang, Guibin Zhang, Dacheng Tao, Mang Ye |
| 2025 | Enhance Multi-View Classification Through Multi-Scale Alignment and Expanded Boundary. Yuena Lin, Yiyuan Wang, Gengyu Lyu, Yongjian Deng, Haichun Cai, Huibin Lin, Haobo Wang, Zhen Yang |
| 2025 | Enhanced Diffusion Sampling via Extrapolation with Multiple ODE Solutions. Jinyoung Choi, Junoh Kang, Bohyung Han |
| 2025 | Enhancing Clustered Federated Learning: Integration of Strategies and Improved Methodologies. Yongxin Guo, Xiaoying Tang, Tao Lin |
| 2025 | Enhancing Cognition and Explainability of Multimodal Foundation Models with Self-Synthesized Data. Yucheng Shi, Quanzheng Li, Jin Sun, Xiang Li, Ninghao Liu |
| 2025 | Enhancing Compositional Text-to-Image Generation with Reliable Random Seeds. Shuangqi Li, Hieu Le, Jingyi Xu, Mathieu Salzmann |
| 2025 | Enhancing Document Understanding with Group Position Embedding: A Novel Approach to Incorporate Layout Information. Yuke Zhu, Yue Zhang, Dongdong Liu, Chi Xie, Zihua Xiong, Bo Zheng, Sheng Guo |
| 2025 | Enhancing End-to-End Autonomous Driving with Latent World Model. Yingyan Li, Lue Fan, Jiawei He, Yuqi Wang, Yuntao Chen, Zhaoxiang Zhang, Tieniu Tan |
| 2025 | Enhancing Federated Domain Adaptation with Multi-Domain Prototype-Based Federated Fine-Tuning. Jingyuan Zhang, Yiyang Duan, Shuaicheng Niu, Yang Cao, Wei Yang Bryan Lim |
| 2025 | Enhancing Graph Of Thought: Enhancing Prompts with LLM Rationales and Dynamic Temperature Control. Sunguk Shin, Youngjoon Kim |
| 2025 | Enhancing Language Model Agents using Diversity of Thoughts. Vijay Lingam, Behrooz Omidvar-Tehrani, Sujay Sanghavi, Gaurav Gupta, Sayan Ghosh, Linbo Liu, Jun Huan, Anoop Deoras |
| 2025 | Enhancing Learning with Label Differential Privacy by Vector Approximation. Puning Zhao, Jiafei Wu, Zhe Liu, Li Shen, Zhikun Zhang, Rongfei Fan, Le Sun, Qingming Li |
| 2025 | Enhancing Pre-trained Representation Classifiability can Boost its Interpretability. Shufan Shen, Zhaobo Qi, Junshu Sun, Qingming Huang, Qi Tian, Shuhui Wang |
| 2025 | Enhancing Prediction Performance through Influence Measure. Shuguang Yu, Wenqian Xu, Xinyi Zhou, Xuechun Wang, Hongtu Zhu, Fan Zhou |
| 2025 | Enhancing Robust Fairness via Confusional Spectral Regularization. Gaojie Jin, Sihao Wu, Jiaxu Liu, Tianjin Huang, Ronghui Mu |
| 2025 | Enhancing Uncertainty Estimation and Interpretability with Bayesian Non-negative Decision Layer. Xinyue Hu, Zhibin Duan, Bo Chen, Mingyuan Zhou |
| 2025 | Enhancing Zeroth-order Fine-tuning for Language Models with Low-rank Structures. Yiming Chen, Yuan Zhang, Liyuan Cao, Kun Yuan, Zaiwen Wen |
| 2025 | Enhancing the Scalability and Applicability of Kohn-Sham Hamiltonians for Molecular Systems. Yunyang Li, Zaishuo Xia, Lin Huang, Xinran Wei, Samuel Harshe, Han Yang, Erpai Luo, Zun Wang, Jia Zhang, Chang Liu, Bin Shao, Mark Gerstein |
| 2025 | Ensembles of Low-Rank Expert Adapters. Yinghao Li, Vianne R. Gao, Chao Zhang, MohamadAli Torkamani |
| 2025 | Ensembling Diffusion Models via Adaptive Feature Aggregation. Cong Wang, Kuan Tian, Yonghang Guan, Fei Shen, Zhiwei Jiang, Qing Gu, Jun Zhang |
| 2025 | Entropy-based Activation Function Optimization: A Method on Searching Better Activation Functions. Haoyuan Sun, Zihao Wu, Bo Xia, Pu Chang, Zibin Dong, Yifu Yuan, Yongzhe Chang, Xueqian Wang |
| 2025 | Episodic Memories Generation and Evaluation Benchmark for Large Language Models. Alexis Huet, Zied Ben-Houidi, Dario Rossi |
| 2025 | Episodic Novelty Through Temporal Distance. Yuhua Jiang, Qihan Liu, Yiqin Yang, Xiaoteng Ma, Dianyu Zhong, Hao Hu, Jun Yang, Bin Liang, Bo Xu, Chongjie Zhang, Qianchuan Zhao |
| 2025 | Epistemic Monte Carlo Tree Search. Yaniv Oren, Viliam Vadocz, Matthijs T. J. Spaan, Wendelin Boehmer |
| 2025 | EqNIO: Subequivariant Neural Inertial Odometry. Royina Karegoudra Jayanth, Yinshuang Xu, Ziyun Wang, Evangelos Chatzipantazis, Kostas Daniilidis, Daniel Gehrig |
| 2025 | Equivariant Denoisers Cannot Copy Graphs: Align Your Graph Diffusion Models. Najwa Laabid, Severi Rissanen, Markus Heinonen, Arno Solin, Vikas Garg |
| 2025 | Equivariant Masked Position Prediction for Efficient Molecular Representation. Junyi An, Chao Qu, Yunfei Shi, Xinhao Liu, Qianwei Tang, Fenglei Cao, Yuan Qi |
| 2025 | Equivariant Neural Functional Networks for Transformers. Hoang V. Tran, Thieu Vo, An Nguyen The, Tho Tran Huu, Minh-Khoi Nguyen-Nhat, Thanh Tran, Duy-Tung Pham, Tan Minh Nguyen |
| 2025 | Erasing Concept Combination from Text-to-Image Diffusion Model. Hongyi Nie, Quanming Yao, Yang Liu, Zhen Wang, Yatao Bian |
| 2025 | Error-quantified Conformal Inference for Time Series. Junxi Wu, Dongjian Hu, Yajie Bao, Shu-Tao Xia, Changliang Zou |
| 2025 | Estimating the Probabilities of Rare Outputs in Language Models. Gabriel Wu, Jacob Hilton |
| 2025 | Estimation of single-cell and tissue perturbation effect in spatial transcriptomics via Spatial Causal Disentanglement. Stathis Megas, Daniel G. Chen, Krzysztof Polanski, Moshe Eliasof, Carola-Bibiane Schönlieb, Sarah A. Teichmann |
| 2025 | Et-Seed: Efficient trajectory-Level SE(3) equivariant diffusion Policy. Chenrui Tie, Yue Chen, Ruihai Wu, Boxuan Dong, Zeyi Li, Chongkai Gao, Hao Dong |
| 2025 | EvA: Erasing Spurious Correlations with Activations. Qiyuan He, Kai Xu, Angela Yao |
| 2025 | Evaluating Large Language Models through Role-Guide and Self-Reflection: A Comparative Study. Lili Zhao, Yang Wang, Qi Liu, Mengyun Wang, Wei Chen, Zhichao Sheng, Shijin Wang |
| 2025 | Evaluating Semantic Variation in Text-to-Image Synthesis: A Causal Perspective. Xiangru Zhu, Penglei Sun, Yaoxian Song, Yanghua Xiao, Zhixu Li, Chengyu Wang, Jun Huang, Bei Yang, Xiaoxiao Xu |
| 2025 | Event-Driven Online Vertical Federated Learning. Ganyu Wang, Boyu Wang, Bin Gu, Charles Ling |
| 2025 | Everything is Editable: Extend Knowledge Editing to Unstructured Data in Large Language Models. Jingcheng Deng, Zihao Wei, Liang Pang, Hanxing Ding, Huawei Shen, Xueqi Cheng |
| 2025 | Everything, Everywhere, All at Once: Is Mechanistic Interpretability Identifiable? Maxime Méloux, Silviu Maniu, François Portet, Maxime Peyrard |
| 2025 | Evidential Learning-based Certainty Estimation for Robust Dense Feature Matching. Lile Cai, Chuan-Sheng Foo, Xun Xu, Zaiwang Gu, Jun Cheng, XuLei Yang |
| 2025 | ExACT: Teaching AI Agents to Explore with Reflective-MCTS and Exploratory Learning. Xiao Yu, Baolin Peng, Vineeth Vajipey, Hao Cheng, Michel Galley, Jianfeng Gao, Zhou Yu |
| 2025 | Exact Byte-Level Probabilities from Tokenized Language Models for FIM-Tasks and Model Ensembles. Buu Phan, Brandon Amos, Itai Gat, Marton Havasi, Matthew J. Muckley, Karen Ullrich |
| 2025 | Exact Certification of (Graph) Neural Networks Against Label Poisoning. Mahalakshmi Sabanayagam, Lukas Gosch, Stephan Günnemann, Debarghya Ghoshdastidar |
| 2025 | Exact Community Recovery under Side Information: Optimality of Spectral Algorithms. Julia Gaudio, Nirmit Joshi |
| 2025 | Exact Computation of Any-Order Shapley Interactions for Graph Neural Networks. Maximilian Muschalik, Fabian Fumagalli, Paolo Frazzetto, Janine Strotherm, Luca Hermes, Alessandro Sperduti, Eyke Hüllermeier, Barbara Hammer |
| 2025 | Examining Alignment of Large Language Models through Representative Heuristics: the case of political stereotypes. Sullam Jeoung, Yubin Ge, Haohan Wang, Jana Diesner |
| 2025 | Execution-guided within-prompt search for programming-by-example. Gust Verbruggen, Ashish Tiwari, Mukul Singh, Vu Le, Sumit Gulwani |
| 2025 | Expand and Compress: Exploring Tuning Principles for Continual Spatio-Temporal Graph Forecasting. Wei Chen, Yuxuan Liang |
| 2025 | Expected Return Symmetries. Darius Muglich, Johannes Forkel, Elise van der Pol, Jakob Nicolaus Foerster |
| 2025 | Expected Sliced Transport Plans. Xinran Liu, Rocio Diaz Martin, Yikun Bai, Ashkan Shahbazi, Matthew Thorpe, Akram Aldroubi, Soheil Kolouri |
| 2025 | Explain Yourself, Briefly! Self-Explaining Neural Networks with Concise Sufficient Reasons. Shahaf Bassan, Ron Eliav, Shlomit Gur |
| 2025 | Explaining Modern Gated-Linear RNNs via a Unified Implicit Attention Formulation. Itamar Zimerman, Ameen Ali, Lior Wolf |
| 2025 | Explanations of GNN on Evolving Graphs via Axiomatic Layer edges. Yazheng Liu, Sihong Xie |
| 2025 | Exploiting Distribution Constraints for Scalable and Efficient Image Retrieval. Mohammad Omama, Po-han Li, Sandeep P. Chinchali |
| 2025 | Exploiting Hidden Symmetry to Improve Objective Perturbation for DP Linear Learners with a Nonsmooth L1-Norm. Du Chen, Geoffrey A. Chua |
| 2025 | Exploiting Structure in Offline Multi-Agent RL: The Benefits of Low Interaction Rank. Wenhao Zhan, Scott Fujimoto, Zheqing Zhu, Jason D. Lee, Daniel Jiang, Yonathan Efroni |
| 2025 | Exploratory Preference Optimization: Harnessing Implicit Q*-Approximation for Sample-Efficient RLHF. Tengyang Xie, Dylan J. Foster, Akshay Krishnamurthy, Corby Rosset, Ahmed Hassan Awadallah, Alexander Rakhlin |
| 2025 | Explore Theory of Mind: program-guided adversarial data generation for theory of mind reasoning. Melanie Sclar, Jane Dwivedi-Yu, Maryam Fazel-Zarandi, Yulia Tsvetkov, Yonatan Bisk, Yejin Choi, Asli Celikyilmaz |
| 2025 | Exploring Learning Complexity for Efficient Downstream Dataset Pruning. Wenyu Jiang, Zhenlong Liu, Zejian Xie, Songxin Zhang, Bingyi Jing, Hongxin Wei |
| 2025 | Exploring Local Memorization in Diffusion Models via Bright Ending Attention. Chen Chen, Daochang Liu, Mubarak Shah, Chang Xu |
| 2025 | Exploring Prosocial Irrationality for LLM Agents: A Social Cognition View. Xuan Liu, Jie Zhang, Haoyang Shang, Song Guo, Chengxu Yang, Quanyan Zhu |
| 2025 | Exploring The Forgetting in Adversarial Training: A Novel Method for Enhancing Robustness. Xianglu Wang, Hu Ding |
| 2025 | Exploring The Loss Landscape Of Regularized Neural Networks Via Convex Duality. Sungyoon Kim, Aaron Mishkin, Mert Pilanci |
| 2025 | Exploring a Principled Framework for Deep Subspace Clustering. Xianghan Meng, Zhiyuan Huang, Wei He, Xianbiao Qi, Rong Xiao, Chun-Guang Li |
| 2025 | Exploring channel distinguishability in local neighborhoods of the model space in quantum neural networks. Sabrina Herbst, Sandeep Suresh Cranganore, Vincenzo De Maio, Ivona Brandic |
| 2025 | Exploring the Camera Bias of Person Re-identification. Myungseo Song, Jin-Woo Park, Jong-Seok Lee |
| 2025 | Exploring the Design Space of Visual Context Representation in Video MLLMs. Yifan Du, Yuqi Huo, Kun Zhou, Zijia Zhao, Haoyu Lu, Han Huang, Xin Zhao, Bingning Wang, Weipeng Chen, Ji-Rong Wen |
| 2025 | Exploring the Effectiveness of Object-Centric Representations in Visual Question Answering: Comparative Insights with Foundation Models. Amir Mohammad Karimi-Mamaghan, Samuele Papa, Karl Henrik Johansson, Stefan Bauer, Andrea Dittadi |
| 2025 | Exponential Topology-enabled Scalable Communication in Multi-agent Reinforcement Learning. Xinran Li, Xiaolu Wang, Chenjia Bai, Jun Zhang |
| 2025 | Exposure Bracketing Is All You Need For A High-Quality Image. Zhilu Zhang, Shuohao Zhang, Renlong Wu, Zifei Yan, Wangmeng Zuo |
| 2025 | Expressivity of Neural Networks with Random Weights and Learned Biases. Ezekiel Williams, Alexandre Payeur, Avery Hee-Woon Ryoo, Thomas Jiralerspong, Matthew G. Perich, Luca Mazzucato, Guillaume Lajoie |
| 2025 | Extendable and Iterative Structure Learning Strategy for Bayesian Networks. Hamid Kalantari, Russell Greiner, Pouria Ramazi |
| 2025 | Extending Mercer's expansion to indefinite and asymmetric kernels. Sungwoo Jeong, Alex Townsend |
| 2025 | F-Fidelity: A Robust Framework for Faithfulness Evaluation of Explainable AI. Xu Zheng, Farhad Shirani, Zhuomin Chen, Chaohao Lin, Wei Cheng, Wenbo Guo, Dongsheng Luo |
| 2025 | F3Set: Towards Analyzing Fast, Frequent, and Fine-grained Events from Videos. Zhaoyu Liu, Kan Jiang, Murong Ma, Zhe Hou, Yun Lin, Jin Song Dong |
| 2025 | FACTS: A Factored State-Space Framework for World Modelling. Nanbo Li, Firas Laakom, Yucheng Xu, Wenyi Wang, Jürgen Schmidhuber |
| 2025 | FIG: Flow with Interpolant Guidance for Linear Inverse Problems. Yici Yan, Yichi Zhang, Xiangming Meng, Zhizhen Zhao |
| 2025 | FIRING-Net: A filtered feature recycling network for speech enhancement. Xinmeng Xu, Yiqun Zhang, Jizhen Li, Yuhong Yang, Yong Luo, Weiping Tu |
| 2025 | FLIP: Flow-Centric Generative Planning as General-Purpose Manipulation World Model. Chongkai Gao, Haozhuo Zhang, Zhixuan Xu, Zhehao Cai, Lin Shao |
| 2025 | FLOPS: Forward Learning with OPtimal Sampling. Tao Ren, Zishi Zhang, Jinyang Jiang, Guanghao Li, Zeliang Zhang, Mingqian Feng, Yijie Peng |
| 2025 | FOSP: Fine-tuning Offline Safe Policy through World Models. Chenyang Cao, Yucheng Xin, Silang Wu, Longxiang He, Zichen Yan, Junbo Tan, Xueqian Wang |
| 2025 | FaceShot: Bring Any Character into Life. Junyao Gao, Yanan Sun, Fei Shen, Xin Jiang, Zhening Xing, Kai Chen, Cairong Zhao |
| 2025 | Facilitating Multi-turn Function Calling for LLMs via Compositional Instruction Tuning. Mingyang Chen, Haoze Sun, Tianpeng Li, Fan Yang, Hao Liang, Keer Lu, Bin Cui, Wentao Zhang, Zenan Zhou, Weipeng Chen |
| 2025 | Factor Graph-based Interpretable Neural Networks. Yicong Li, Kuanjiu Zhou, Shuo Yu, Qiang Zhang, Renqiang Luo, Xiaodong Li, Feng Xia |
| 2025 | Failures to Find Transferable Image Jailbreaks Between Vision-Language Models. Rylan Schaeffer, Dan Valentine, Luke Bailey, James Chua, Cristóbal Eyzaguirre, Zane Durante, Joe Benton, Brando Miranda, Henry Sleight, Tony Tong Wang, John Hughes, Rajashree Agrawal, Mrinank Sharma, Scott Emmons, Sanmi Koyejo, Ethan Perez |
| 2025 | Fair Clustering in the Sliding Window Model. Vincent Cohen-Addad, Shaofeng H.-C. Jiang, Qiaoyuan Yang, Yubo Zhang, Samson Zhou |
| 2025 | Fair Submodular Cover. Wenjing Chen, Shuo Xing, Samson Zhou, Victoria G. Crawford |
| 2025 | FairDen: Fair Density-Based Clustering. Lena Krieger, Anna Beer, Pernille Matthews, Anneka Myrup Thiesson, Ira Assent |
| 2025 | FairMT-Bench: Benchmarking Fairness for Multi-turn Dialogue in Conversational LLMs. Zhiting Fan, Ruizhe Chen, Tianxiang Hu, Zuozhu Liu |
| 2025 | FaithEval: Can Your Language Model Stay Faithful to Context, Even If "The Moon is Made of Marshmallows". Yifei Ming, Senthil Purushwalkam, Shrey Pandit, Zixuan Ke, Xuan-Phi Nguyen, Caiming Xiong, Shafiq Joty |
| 2025 | FakeShield: Explainable Image Forgery Detection and Localization via Multi-modal Large Language Models. Zhipei Xu, Xuanyu Zhang, Runyi Li, Zecheng Tang, Qing Huang, Jian Zhang |
| 2025 | Fantastic Copyrighted Beasts and How (Not) to Generate Them. Luxi He, Yangsibo Huang, Weijia Shi, Tinghao Xie, Haotian Liu, Yue Wang, Luke Zettlemoyer, Chiyuan Zhang, Danqi Chen, Peter Henderson |
| 2025 | Fantastic Targets for Concept Erasure in Diffusion Models and Where To Find Them. Anh Tuan Bui, Thuy-Trang Vu, Long Tung Vuong, Trung Le, Paul Montague, Tamas Abraham, Junae Kim, Dinh Phung |
| 2025 | Fast Direct: Query-Efficient Online Black-box Guidance for Diffusion-model Target Generation. Kim Yong Tan, Yueming Lyu, Ivor W. Tsang, Yew-Soon Ong |
| 2025 | Fast Feedforward 3D Gaussian Splatting Compression. Yihang Chen, Qianyi Wu, Mengyao Li, Weiyao Lin, Mehrtash Harandi, Jianfei Cai |
| 2025 | Fast Summation of Radial Kernels via QMC Slicing. Johannes Hertrich, Tim Jahn, Michael Quellmalz |
| 2025 | Fast Training of Sinusoidal Neural Fields via Scaling Initialization. Taesun Yeom, Sangyoon Lee, Jaeho Lee |
| 2025 | Fast Uncovering of Protein Sequence Diversity from Structure. Luca Alessandro Silva, Barthélémy Meynard-Piganeau, Carlo Lucibello, Christoph Feinauer |
| 2025 | Fast and Accurate Blind Flexible Docking. Zizhuo Zhang, Lijun Wu, Kaiyuan Gao, Jiangchao Yao, Tao Qin, Bo Han |
| 2025 | Fast and Slow Streams for Online Time Series Forecasting Without Information Leakage. Ying-yee Ava Lau, Zhiwen Shao, Dit-Yan Yeung |
| 2025 | Fast training and sampling of Restricted Boltzmann Machines. Nicolas Béreux, Aurélien Decelle, Cyril Furtlehner, Lorenzo Rosset, Beatriz Seoane |
| 2025 | Fast unsupervised ground metric learning with tree-Wasserstein distance. Kira Michaela Düsterwald, Samo Hromadka, Makoto Yamada |
| 2025 | Faster Algorithms for Structured Linear and Kernel Support Vector Machines. Yuzhou Gu, Zhao Song, Lichen Zhang |
| 2025 | Faster Cascades via Speculative Decoding. Harikrishna Narasimhan, Wittawat Jitkrittum, Ankit Singh Rawat, Seungyeon Kim, Neha Gupta, Aditya Krishna Menon, Sanjiv Kumar |
| 2025 | Faster Diffusion Sampling with Randomized Midpoints: Sequential and Parallel. Shivam Gupta, Linda Cai, Sitan Chen |
| 2025 | Faster Inference of Flow-Based Generative Models via Improved Data-Noise Coupling. Aram Davtyan, Leello Tadesse Dadi, Volkan Cevher, Paolo Favaro |
| 2025 | FasterCache: Training-Free Video Diffusion Model Acceleration with High Quality. Zhengyao Lv, Chenyang Si, Junhao Song, Zhenyu Yang, Yu Qiao, Ziwei Liu, Kwan-Yee K. Wong |
| 2025 | Fat-to-Thin Policy Optimization: Offline Reinforcement Learning with Sparse Policies. Lingwei Zhu, Han Wang, Yukie Nagai |
| 2025 | Feast Your Eyes: Mixture-of-Resolution Adaptation for Multimodal Large Language Models. Gen Luo, Yiyi Zhou, Yuxin Zhang, Xiawu Zheng, Xiaoshuai Sun, Rongrong Ji |
| 2025 | Feature Averaging: An Implicit Bias of Gradient Descent Leading to Non-Robustness in Neural Networks. Binghui Li, Zhixuan Pan, Kaifeng Lyu, Jian Li |
| 2025 | Feature Responsiveness Scores: Model-Agnostic Explanations for Recourse. Seung Hyun Cheon, Anneke Wernerfelt, Sorelle A. Friedler, Berk Ustun |
| 2025 | Feature-Based Online Bilateral Trade. Solenne Gaucher, Martino Bernasconi, Matteo Castiglioni, Andrea Celli, Vianney Perchet |
| 2025 | FedLWS: Federated Learning with Adaptive Layer-wise Weight Shrinking. Changlong Shi, Jinmeng Li, He Zhao, Dandan Guo, Yi Chang |
| 2025 | FedTMOS: Efficient One-Shot Federated Learning with Tsetlin Machine. Shannon How Shi Qi, Jagmohan Chauhan, Geoff V. Merrett, Jonathon S. Hare |
| 2025 | Federated Class-Incremental Learning: A Hybrid Approach Using Latent Exemplars and Data-Free Techniques to Address Local and Global Forgetting. Milad Khademi Nori, Il-Min Kim, Guanghui Wang |
| 2025 | Federated Continual Learning Goes Online: Uncertainty-Aware Memory Management for Vision Tasks and Beyond. Giuseppe Serra, Florian Buettner |
| 2025 | Federated Domain Generalization with Data-free On-server Matching Gradient. Trong-Binh Nguyen, Duong Minh Nguyen, Jinsun Park, Viet Quoc Pham, Won-Joo Hwang |
| 2025 | Federated Few-Shot Class-Incremental Learning. Muhammad Anwar Ma'sum, Mahardhika Pratama, Lin Liu, Habibullah, Ryszard Kowalczyk |
| 2025 | Federated Granger Causality Learning For Interdependent Clients With State Space Representation. Ayush Mohanty, Nazal Mohamed, Paritosh Ramanan, Nagi Gebraeel |
| 2025 | Federated Q-Learning with Reference-Advantage Decomposition: Almost Optimal Regret and Logarithmic Communication Cost. Zhong Zheng, Haochen Zhang, Lingzhou Xue |
| 2025 | Federated Residual Low-Rank Adaptation of Large Language Models. Yunlu Yan, Chun-Mei Feng, Wangmeng Zuo, Rick Siow Mong Goh, Yong Liu, Lei Zhu |
| 2025 | Feedback Favors the Generalization of Neural ODEs. Jindou Jia, Zihan Yang, Meng Wang, Kexin Guo, Jianfei Yang, Xiang Yu, Lei Guo |
| 2025 | Feedback Schrödinger Bridge Matching. Panagiotis Theodoropoulos, Nikolaos Komianos, Vincent Pacelli, Guan-Horng Liu, Evangelos A. Theodorou |
| 2025 | Fengbo: a Clifford Neural Operator pipeline for 3D PDEs in Computational Fluid Dynamics. Alberto Pepe, Mattia Montanari, Joan Lasenby |
| 2025 | Ferret-UI 2: Mastering Universal User Interface Understanding Across Platforms. Zhangheng Li, Keen You, Haotian Zhang, Di Feng, Harsh Agrawal, Xiujun Li, Mohana Prasad Sathya Moorthy, Jeffrey Nichols, Yinfei Yang, Zhe Gan |
| 2025 | Few for Many: Tchebycheff Set Scalarization for Many-Objective Optimization. Xi Lin, Yilu Liu, Xiaoyuan Zhang, Fei Liu, Zhenkun Wang, Qingfu Zhang |
| 2025 | Few-Class Arena: A Benchmark for Efficient Selection of Vision Models and Dataset Difficulty Measurement. Bryan Bo Cao, Lawrence O'Gorman, Michael Coss, Shubham Jain |
| 2025 | Fewer May Be Better: Enhancing Offline Reinforcement Learning with Reduced Dataset. Yiqin Yang, Quanwei Wang, Chenghao Li, Hao Hu, Chengjie Wu, Yuhua Jiang, Dianyu Zhong, Ziyou Zhang, Qianchuan Zhao, Chongjie Zhang, Bo Xu |
| 2025 | Fictitious Synthetic Data Can Improve LLM Factuality via Prerequisite Learning. Yujian Liu, Shiyu Chang, Tommi S. Jaakkola, Yang Zhang |
| 2025 | Fiddler: CPU-GPU Orchestration for Fast Inference of Mixture-of-Experts Models. Keisuke Kamahori, Tian Tang, Yile Gu, Kan Zhu, Baris Kasikci |
| 2025 | Field-DiT: Diffusion Transformer on Unified Video, 3D, and Game Field Generation. Kangfu Mei, Mo Zhou, Vishal M. Patel |
| 2025 | Filtered not Mixed: Filtering-Based Online Gating for Mixture of Large Language Models. Raeid Saqur, Anastasis Kratsios, Florian Krach, Yannick Limmer, Blanka Horvath, Frank Rudzicz |
| 2025 | Finally Rank-Breaking Conquers MNL Bandits: Optimal and Efficient Algorithms for MNL Assortment. Aadirupa Saha, Pierre Gaillard |
| 2025 | Find A Winning Sign: Sign Is All We Need to Win the Lottery. Junghun Oh, Sungyong Baik, Kyoung Mu Lee |
| 2025 | Finding Shared Decodable Concepts and their Negations in the Brain. Cory Daniel Efird, Alex Murphy, Joel Zylberberg, Alona Fyshe |
| 2025 | Fine-Grained Verifiers: Preference Modeling as Next-token Prediction in Vision-Language Alignment. Chenhang Cui, An Zhang, Yiyang Zhou, Zhaorun Chen, Gelei Deng, Huaxiu Yao, Tat-Seng Chua |
| 2025 | Fine-Tuning Attention Modules Only: Enhancing Weight Disentanglement in Task Arithmetic. Ruochen Jin, Bojian Hou, Jiancong Xiao, Weijie J. Su, Li Shen |
| 2025 | Fine-Tuning Discrete Diffusion Models via Reward Optimization with Applications to DNA and Protein Design. Chenyu Wang, Masatoshi Uehara, Yichun He, Amy Wang, Avantika Lal, Tommi S. Jaakkola, Sergey Levine, Aviv Regev, Hanchen Wang, Tommaso Biancalani |
| 2025 | Fine-tuning can Help Detect Pretraining Data from Large Language Models. Hengxiang Zhang, Songxin Zhang, Bingyi Jing, Hongxin Wei |
| 2025 | Fine-tuning with Reserved Majority for Noise Reduction. Shuyang Jiang, Yusheng Liao, Ya Zhang, Yanfeng Wang, Yu Wang |
| 2025 | First-Person Fairness in Chatbots. Tyna Eloundou, Alex Beutel, David G. Robinson, Keren Gu, Anna-Luisa Brakman, Pamela Mishkin, Meghan Shah, Johannes Heidecke, Lilian Weng, Adam Tauman Kalai |
| 2025 | Fitting Networks with a Cancellation Trick. Jiashun Jin, Jingming Wang |
| 2025 | Flash Inference: Near Linear Time Inference for Long Convolution Sequence Models and Beyond. Costin-Andrei Oncescu, Sanket Purandare, Stratos Idreos, Sham M. Kakade |
| 2025 | FlashMask: Efficient and Rich Mask Extension of FlashAttention. Guoxia Wang, Jinle Zeng, Xiyuan Xiao, Siming Wu, Jiabin Yang, Lujing Zheng, Zeyu Chen, Jiang Bian, Dianhai Yu, Haifeng Wang |
| 2025 | FlashRNN: I/O-Aware Optimization of Traditional RNNs on modern hardware. Korbinian Pöppel, Maximilian Beck, Sepp Hochreiter |
| 2025 | Flat Reward in Policy Parameter Space Implies Robust Reinforcement Learning. Hyun-Kyu Lee, Sung Whan Yoon |
| 2025 | Flavors of Margin: Implicit Bias of Steepest Descent in Homogeneous Neural Networks. Nikolaos Tsilivis, Gal Vardi, Julia Kempe |
| 2025 | FlexCAD: Unified and Versatile Controllable CAD Generation with Fine-tuned Large Language Models. Zhanwei Zhang, Shizhao Sun, Wenxiao Wang, Deng Cai, Jiang Bian |
| 2025 | FlexPrefill: A Context-Aware Sparse Attention Mechanism for Efficient Long-Sequence Inference. Xunhao Lai, Jianqiao Lu, Yao Luo, Yiyuan Ma, Xun Zhou |
| 2025 | FlickerFusion: Intra-trajectory Domain Generalizing Multi-agent Reinforcement Learning. Woosung Koh, Wonbeen Oh, Siyeol Kim, Suhin Shin, Hyeongjin Kim, Jaein Jang, Junghyun Lee, Se-Young Yun |
| 2025 | Flow Distillation Sampling: Regularizing 3D Gaussians with Pre-trained Matching Priors. Lin-Zhuo Chen, Kangjie Liu, Youtian Lin, Zhihao Li, Siyu Zhu, Xun Cao, Yao Yao |
| 2025 | Flow Matching with Gaussian Process Priors for Probabilistic Time Series Forecasting. Marcel Kollovieh, Marten Lienen, David Lüdke, Leo Schwinn, Stephan Günnemann |
| 2025 | Flow Matching with General Discrete Paths: A Kinetic-Optimal Perspective. Neta Shaul, Itai Gat, Marton Havasi, Daniel Severo, Anuroop Sriram, Peter Holderrieth, Brian Karrer, Yaron Lipman, Ricky T. Q. Chen |
| 2025 | Flow matching achieves almost minimax optimal convergence. Kenji Fukumizu, Taiji Suzuki, Noboru Isobe, Kazusato Oko, Masanori Koyama |
| 2025 | Flow-based Variational Mutual Information: Fast and Flexible Approximations. Caleb Dahlke, Jason Pacheco |
| 2025 | Flow: Modularized Agentic Workflow Automation. Boye Niu, Yiliao Song, Kai Lian, Yifan Shen, Yu Yao, Kun Zhang, Tongliang Liu |
| 2025 | FlowDec: A flow-based full-band general audio codec with high perceptual quality. Simon Welker, Matthew Le, Ricky T. Q. Chen, Wei-Ning Hsu, Timo Gerkmann, Alexander Richard, Yi-Chiao Wu |
| 2025 | Fluid: Scaling Autoregressive Text-to-image Generative Models with Continuous Tokens. Lijie Fan, Tianhong Li, Siyang Qin, Yuanzhen Li, Chen Sun, Michael Rubinstein, Deqing Sun, Kaiming He, Yonglong Tian |
| 2025 | Follow My Instruction and Spill the Beans: Scalable Data Extraction from Retrieval-Augmented Generation Systems. Zhenting Qi, Hanlin Zhang, Eric P. Xing, Sham M. Kakade, Himabindu Lakkaraju |
| 2025 | Following the Human Thread in Social Navigation. Luca Scofano, Alessio Sampieri, Tommaso Campari, Valentino Sacco, Indro Spinelli, Lamberto Ballan, Fabio Galasso |
| 2025 | For Better or For Worse? Learning Minimum Variance Features With Label Augmentation. Muthu Chidambaram, Rong Ge |
| 2025 | ForecastBench: A Dynamic Benchmark of AI Forecasting Capabilities. Ezra Karger, Houtan Bastani, Chen Yueh-Han, Zachary Jacobs, Danny Halawi, Fred Zhang, Philip Tetlock |
| 2025 | Forewarned is Forearmed: Harnessing LLMs for Data Synthesis via Failure-induced Exploration. Qintong Li, Jiahui Gao, Sheng Wang, Renjie Pi, Xueliang Zhao, Chuan Wu, Xin Jiang, Zhenguo Li, Lingpeng Kong |
| 2025 | Forget the Data and Fine-Tuning! Just Fold the Network to Compress. Dong Wang, Haris Sikic, Lothar Thiele, Olga Saukh |
| 2025 | Forgetting Transformer: Softmax Attention with a Forget Gate. Zhixuan Lin, Evgenii Nikishin, Xu Owen He, Aaron C. Courville |
| 2025 | Forking Paths in Neural Text Generation. Eric J. Bigelow, Ari Holtzman, Hidenori Tanaka, Tomer David Ullman |
| 2025 | FormalAlign: Automated Alignment Evaluation for Autoformalization. Jianqiao Lu, Yingjia Wan, Yinya Huang, Jing Xiong, Zhengying Liu, Zhijiang Guo |
| 2025 | Formation of Representations in Neural Networks. Liu Ziyin, Isaac L. Chuang, Tomer Galanti, Tomaso A. Poggio |
| 2025 | Forte : Finding Outliers with Representation Typicality Estimation. Debargha Ganguly, Warren Richard Morningstar, Andrew Seohwan Yu, Vipin Chaudhary |
| 2025 | Foundation Models Secretly Understand Neural Network Weights: Enhancing Hypernetwork Architectures with Foundation Models. Jeffrey Gu, Serena Yeung-Levy |
| 2025 | Fourier Head: Helping Large Language Models Learn Complex Probability Distributions. Nate Gillman, Daksh Aggarwal, Michael Freeman, Chen Sun |
| 2025 | Fourier Sliced-Wasserstein Embedding for Multisets and Measures. Tal Amir, Nadav Dym |
| 2025 | Fragment and Geometry Aware Tokenization of Molecules for Structure-Based Drug Design Using Language Models. Cong Fu, Xiner Li, Blake Olson, Heng Ji, Shuiwang Ji |
| 2025 | Frame-Voyager: Learning to Query Frames for Video Large Language Models. Sicheng Yu, Chengkai Jin, Huanyu Wang, Zhenghao Chen, Sheng Jin, Zhongrong Zuo, Xiaolei Xu, Zhenbang Sun, Bingni Zhang, Jiawei Wu, Hao Zhang, Qianru Sun |
| 2025 | Framer: Interactive Frame Interpolation. Wen Wang, Qiuyu Wang, Kecheng Zheng, Hao Ouyang, Zhekai Chen, Biao Gong, Hao Chen, Yujun Shen, Chunhua Shen |
| 2025 | FreCaS: Efficient Higher-Resolution Image Generation via Frequency-aware Cascaded Sampling. Zhengqiang Zhang, Ruihuang Li, Lei Zhang |
| 2025 | FreDF: Learning to Forecast in the Frequency Domain. Hao Wang, Lichen Pan, Yuan Shen, Zhichao Chen, Degui Yang, Yifei Yang, Sen Zhang, Xinggao Liu, Haoxuan Li, Dacheng Tao |
| 2025 | FreSh: Frequency Shifting for Accelerated Neural Representation Learning. Adam Kania, Marko Mihajlovic, Sergey Prokudin, Jacek Tabor, Przemyslaw Spurek |
| 2025 | Free Hunch: Denoiser Covariance Estimation for Diffusion Models Without Extra Costs. Severi Rissanen, Markus Heinonen, Arno Solin |
| 2025 | FreeCG: Free the Design Space of Clebsch-Gordan Transform for Machine Learning Force Fields. Shihao Shao, Haoran Geng, Zun Wang, Qinghua Cui |
| 2025 | FreeVS: Generative View Synthesis on Free Driving Trajectory. Qitai Wang, Lue Fan, Yuqi Wang, Yuntao Chen, Zhaoxiang Zhang |
| 2025 | FreqPrior: Improving Video Diffusion Models with Frequency Filtering Gaussian Noise. Yunlong Yuan, Yuanfan Guo, Chunwei Wang, Wei Zhang, Hang Xu, Li Zhang |
| 2025 | Frequency-Guided Masking for Enhanced Vision Self-Supervised Learning. Amin Karimi Monsefi, Mengxi Zhou, Nastaran Karimi Monsefi, Ser-Nam Lim, Wei-Lun Chao, Rajiv Ramnath |
| 2025 | From Artificial Needles to Real Haystacks: Improving Retrieval Capabilities in LLMs by Finetuning on Synthetic Data. Zheyang Xiong, Vasilis Papageorgiou, Kangwook Lee, Dimitris Papailiopoulos |
| 2025 | From Attention to Activation: Unraveling the Enigmas of Large Language Models. Prannay Kaul, Chengcheng Ma, Ismail Elezi, Jiankang Deng |
| 2025 | From Commands to Prompts: LLM-based Semantic File System for AIOS. Zeru Shi, Kai Mei, Mingyu Jin, Yongye Su, Chaoji Zuo, Wenyue Hua, Wujiang Xu, Yujie Ren, Zirui Liu, Mengnan Du, Dong Deng, Yongfeng Zhang |
| 2025 | From Decoupling to Adaptive Transformation: a Wider Optimization Space for PTQ. Zhaojing Wen, Qiulin Zhang, Yuan Zhang, Rudan Chen, Xichao Yang, Di Xie, Jiang Zhu |
| 2025 | From Exploration to Mastery: Enabling LLMs to Master Tools via Self-Driven Interactions. Changle Qu, Sunhao Dai, Xiaochi Wei, Hengyi Cai, Shuaiqiang Wang, Dawei Yin, Jun Xu, Ji-Rong Wen |
| 2025 | From Few to Many: Self-Improving Many-Shot Reasoners Through Iterative Optimization and Generation. Xingchen Wan, Han Zhou, Ruoxi Sun, Sercan Ö. Arik |
| 2025 | From GNNs to Trees: Multi-Granular Interpretability for Graph Neural Networks. Jie Yang, Yuwen Wang, Kaixuan Chen, Tongya Zheng, Yihe Zhou, Zhenbang Xiao, Ji Cao, Mingli Song, Shunyu Liu |
| 2025 | From Isolated Conversations to Hierarchical Schemas: Dynamic Tree Memory Representation for LLMs. Alireza Rezazadeh, Zichao Li, Wei Wei, Yujia Bao |
| 2025 | From Layers to States: A State Space Model Perspective to Deep Neural Network Layer Dynamics. Qinshuo Liu, Weiqin Zhao, Wei Huang, Yanwen Fang, Lequan Yu, Guodong Li |
| 2025 | From Lazy to Rich: Exact Learning Dynamics in Deep Linear Networks. Clémentine Carla Juliette Dominé, Nicolas Anguita, Alexandra Maria Proca, Lukas Braun, Daniel Kunin, Pedro A. M. Mediano, Andrew M. Saxe |
| 2025 | From Models to Microtheories: Distilling a Model's Topical Knowledge for Grounded Question-Answering. Nathaniel Weir, Bhavana Dalvi Mishra, Orion Weller, Oyvind Tafjord, Sam Hornstein, Alexander Sabol, Peter A. Jansen, Benjamin Van Durme, Peter Clark |
| 2025 | From Pixels to Tokens: Byte-Pair Encoding on Quantized Visual Modalities. Wanpeng Zhang, Zilong Xie, Yicheng Feng, Yijiang Li, Xingrun Xing, Sipeng Zheng, Zongqing Lu |
| 2025 | From Probability to Counterfactuals: the Increasing Complexity of Satisfiability in Pearl's Causal Hierarchy. Julian Dörfler, Benito van der Zander, Markus Bläser, Maciej Liskiewicz |
| 2025 | From Promise to Practice: Realizing High-performance Decentralized Training. Zesen Wang, Jiaojiao Zhang, Xuyang Wu, Mikael Johansson |
| 2025 | From Risk to Uncertainty: Generating Predictive Uncertainty Measures via Bayesian Estimation. Nikita Kotelevskii, Vladimir Kondratyev, Martin Takác, Eric Moulines, Maxim Panov |
| 2025 | From Search to Sampling: Generative Models for Robust Algorithmic Recourse. Prateek Garg, Lokesh Nagalapatti, Sunita Sarawagi |
| 2025 | From Sparse Dependence to Sparse Attention: Unveiling How Chain-of-Thought Enhances Transformer Sample Efficiency. Kaiyue Wen, Huaqing Zhang, Hongzhou Lin, Jingzhao Zhang |
| 2025 | From Tokens to Lattices: Emergent Lattice Structures in Language Models. Bo Xiong, Steffen Staab |
| 2025 | From Tokens to Words: On the Inner Lexicon of LLMs. Guy Kaplan, Matanel Oren, Yuval Reif, Roy Schwartz |
| 2025 | From an LLM Swarm to a PDDL-empowered Hive: Planning Self-executed Instructions in a Multi-modal Jungle. Kaustubh Vyas, Damien Graux, Yijun Yang, Sébastien Montella, Chenxin Diao, Wendi Zhou, Pavlos Vougiouklis, Ruofei Lai, Yang Ren, Keshuang Li, Jeff Z. Pan |
| 2025 | Fréchet Wavelet Distance: A Domain-Agnostic Metric for Image Generation. Lokesh Veeramacheneni, Moritz Wolter, Hilde Kuehne, Juergen Gall |
| 2025 | Fugatto 1: Foundational Generative Audio Transformer Opus 1. Rafael Valle, Rohan Badlani, Zhifeng Kong, Sang-gil Lee, Arushi Goel, Sungwon Kim, João Felipe Santos, Shuqi Dai, Siddharth Gururani, Aya Aljafari, Alexander H. Liu, Kevin J. Shih, Ryan Prenger, Wei Ping, Chao-Han Huck Yang, Bryan Catanzaro |
| 2025 | Fully-inductive Node Classification on Arbitrary Graphs. Jianan Zhao, Zhaocheng Zhu, Mikhail Galkin, Hesham Mostafa, Michael M. Bronstein, Jian Tang |
| 2025 | Functional Homotopy: Smoothing Discrete Optimization via Continuous Parameters for LLM Jailbreak Attacks. Zi Wang, Divyam Anshumaan, Ashish Hooda, Yudong Chen, Somesh Jha |
| 2025 | Fundamental Limitations on Subquadratic Alternatives to Transformers. Josh Alman, Hantao Yu |
| 2025 | Fundamental Limits of Prompt Tuning Transformers: Universality, Capacity and Efficiency. Jerry Yao-Chieh Hu, Wei-Po Wang, Ammar Gilani, Chenyang Li, Zhao Song, Han Liu |
| 2025 | G-LLaVA: Solving Geometric Problem with Multi-Modal Large Language Model. Jiahui Gao, Renjie Pi, Jipeng Zhang, Jiacheng Ye, Wanjun Zhong, Yufei Wang, Lanqing Hong, Jianhua Han, Hang Xu, Zhenguo Li, Lingpeng Kong |
| 2025 | GALA: Geometry-Aware Local Adaptive Grids for Detailed 3D Generation. Dingdong Yang, Yizhi Wang, Konrad Schindler, Ali Mahdavi Amiri, Hao Zhang |
| 2025 | GANDALF: Generative AttentioN based Data Augmentation and predictive modeLing Framework for personalized cancer treatment. Aishwarya Jayagopal, Yanrong Zhang, Robert John Walsh, Tuan Zea Tan, Anand D. Jeyasekharan, Vaibhav Rajan |
| 2025 | GDrag: Towards General-Purpose Interactive Editing with Anti-ambiguity Point Diffusion. Xiaojian Lin, Hanhui Li, Yuhao Cheng, Yiqiang Yan, Xiaodan Liang |
| 2025 | GETS: Ensemble Temperature Scaling for Calibration in Graph Neural Networks. Dingyi Zhuang, Chonghe Jiang, Yunhan Zheng, Shenhao Wang, Jinhua Zhao |
| 2025 | GEVRM: Goal-Expressive Video Generation Model For Robust Visual Manipulation. Hongyin Zhang, Pengxiang Ding, Shangke Lyu, Ying Peng, Donglin Wang |
| 2025 | GI-GS: Global Illumination Decomposition on Gaussian Splatting for Inverse Rendering. Hongze Chen, Zehong Lin, Jun Zhang |
| 2025 | GIFT: Unlocking Full Potential of Labels in Distilled Dataset at Near-zero Cost. Xinyi Shang, Peng Sun, Tao Lin |
| 2025 | GLOMA: Global Video Text Spotting with Morphological Association. Han Wang, Yanjie Wang, Yang Li, Can Huang |
| 2025 | GLoRa: A Benchmark to Evaluate the Ability to Learn Long-Range Dependencies in Graphs. Dongzhuoran Zhou, Evgeny Kharlamov, Egor V. Kostylev |
| 2025 | GMValuator: Similarity-based Data Valuation for Generative Models. Jiaxi Yang, Wenlong Deng, Benlin Liu, Yangsibo Huang, James Zou, Xiaoxiao Li |
| 2025 | GNNs Getting ComFy: Community and Feature Similarity Guided Rewiring. Celia Rubio-Madrigal, Adarsh Jamadandi, Rebekka Burkholz |
| 2025 | GOAL: A Generalist Combinatorial Optimization Agent Learner. Darko Drakulic, Sofia Michel, Jean-Marc Andreoli |
| 2025 | GOFA: A Generative One-For-All Model for Joint Graph Language Modeling. Lecheng Kong, Jiarui Feng, Hao Liu, Chengsong Huang, Jiaxin Huang, Yixin Chen, Muhan Zhang |
| 2025 | GOLD: Graph Out-of-Distribution Detection via Implicit Adversarial Latent Generation. Danny Wang, Ruihong Qiu, Guangdong Bai, Zi Huang |
| 2025 | GOttack: Universal Adversarial Attacks on Graph Neural Networks via Graph Orbits Learning. Md. Zulfikar Alom, Tran Gia Bao Ngo, Murat Kantarcioglu, Cuneyt Gurcan Akcora |
| 2025 | GPS: A Probabilistic Distributional Similarity with Gumbel Priors for Set-to-Set Matching. Ziming Zhang, Fangzhou Lin, Haotian Liu, Jose Morales, Haichong Zhang, Kazunori D. Yamada, Vijaya B. Kolachalama, Venkatesh Saligrama |
| 2025 | GPUDrive: Data-driven, multi-agent driving simulation at 1 million FPS. Saman Kazemkhani, Aarav Pandya, Daphne Cornelisse, Brennan Shacklett, Eugene Vinitsky |
| 2025 | GPromptShield: Elevating Resilience in Graph Prompt Tuning Against Adversarial Attacks. Shuhan Song, Ping Li, Ming Dun, Maolei Huang, Huawei Cao, Xiaochun Ye |
| 2025 | GRAIN: Exact Graph Reconstruction from Gradients. Maria Drencheva, Ivo Petrov, Maximilian Baader, Dimitar Iliev Dimitrov, Martin T. Vechev |
| 2025 | GROOT-2: Weakly Supervised Multimodal Instruction Following Agents. Shaofei Cai, Bowei Zhang, Zihao Wang, Haowei Lin, Xiaojian Ma, Anji Liu, Yitao Liang |
| 2025 | GReaTer: Gradients Over Reasoning Makes Smaller Language Models Strong Prompt Optimizers. Sarkar Snigdha Sarathi Das, Ryo Kamoi, Bo Pang, Yusen Zhang, Caiming Xiong, Rui Zhang |
| 2025 | GS-CPR: Efficient Camera Pose Refinement via 3D Gaussian Splatting. Changkun Liu, Shuai Chen, Yash Bhalgat, Siyan Hu, Ming Cheng, Zirui Wang, Victor Adrian Prisacariu, Tristan Braud |
| 2025 | GS-LiDAR: Generating Realistic LiDAR Point Clouds with Panoramic Gaussian Splatting. Junzhe Jiang, Chun Gu, Yurui Chen, Li Zhang |
| 2025 | GSBAK: top-K Geometric Score-based Black-box Attack. Md Farhamdur Reza, Richeng Jin, Tianfu Wu, Huaiyu Dai |
| 2025 | GSE: Group-wise Sparse and Explainable Adversarial Attacks. Shpresim Sadiku, Moritz Wagner, Sebastian Pokutta |
| 2025 | GSM-Symbolic: Understanding the Limitations of Mathematical Reasoning in Large Language Models. Iman Mirzadeh, Keivan Alizadeh, Hooman Shahrokhi, Oncel Tuzel, Samy Bengio, Mehrdad Farajtabar |
| 2025 | GTR: Improving Large 3D Reconstruction Models through Geometry and Texture Refinement. Peiye Zhuang, Songfang Han, Chaoyang Wang, Aliaksandr Siarohin, Jiaxu Zou, Michael Vasilkovsky, Vladislav Shakhrai, Sergei Korolev, Sergey Tulyakov, Hsin-Ying Lee |
| 2025 | GUI-World: A Video Benchmark and Dataset for Multimodal GUI-oriented Understanding. Dongping Chen, Yue Huang, Siyuan Wu, Jingyu Tang, Huichi Zhou, Qihui Zhang, Zhigang He, Yilin Bai, Chujie Gao, Liuyi Chen, Yiqiang Li, Chenlong Wang, Yue Yu, Tianshuo Zhou, Zhen Li, Yi Gui, Yao Wan, Pan Zhou, Jianfeng Gao, Lichao Sun |
| 2025 | GameArena: Evaluating LLM Reasoning through Live Computer Games. Lanxiang Hu, Qiyu Li, Anze Xie, Nan Jiang, Ion Stoica, Haojian Jin, Hao Zhang |
| 2025 | GameGen-X: Interactive Open-world Game Video Generation. Haoxuan Che, Xuanhua He, Quande Liu, Cheng Jin, Hao Chen |
| 2025 | Gap Preserving Distillation by Building Bidirectional Mappings with A Dynamic Teacher. Yong Guo, Shulian Zhang, Haolin Pan, Jing Liu, Yulun Zhang, Jian Chen |
| 2025 | Gap-Dependent Bounds for Q-Learning using Reference-Advantage Decomposition. Zhong Zheng, Haochen Zhang, Lingzhou Xue |
| 2025 | Gated Delta Networks: Improving Mamba2 with Delta Rule. Songlin Yang, Jan Kautz, Ali Hatamizadeh |
| 2025 | Gaussian Differentially Private Human Faces Under a Face Radial Curve Representation. Carlos J. Soto, Matthew Reimherr, Aleksandra B. Slavkovic, Mark Shriver |
| 2025 | Gaussian Ensemble Belief Propagation for Efficient Inference in High-Dimensional, Black-box Systems. Daniel MacKinlay, Russell Tsuchida, Daniel Edward Pagendam, Petra Kuhnert |
| 2025 | Gaussian Head & Shoulders: High Fidelity Neural Upper Body Avatars with Anchor Gaussian Guided Texture Warping. Tianhao (Walter) Wu, Jing Yang, Zhilin Guo, Jingyi Wan, Fangcheng Zhong, Cengiz Öztireli |
| 2025 | Gaussian Mixture Counterfactual Generator. Jong-Hoon Ahn, Akshay Vashist |
| 2025 | Gaussian Splatting Lucas-Kanade. Liuyue Xie, Joel Julin, Koichiro Niinuma, László Attila Jeni |
| 2025 | Gaussian-Based Instance-Adaptive Intensity Modeling for Point-Supervised Facial Expression Spotting. Yicheng Deng, Hideaki Hayashi, Hajime Nagahara |
| 2025 | Gaussian-Det: Learning Closed-Surface Gaussians for 3D Object Detection. Hongru Yan, Yu Zheng, Yueqi Duan |
| 2025 | GaussianAnything: Interactive Point Cloud Flow Matching for 3D Generation. Yushi Lan, Shangchen Zhou, Zhaoyang Lyu, Fangzhou Hong, Shuai Yang, Bo Dai, Xingang Pan, Chen Change Loy |
| 2025 | GaussianBlock: Building Part-Aware Compositional and Editable 3D Scene by Primitives and Gaussians. Shuyi Jiang, Qihao Zhao, Hossein Rahmani, De Wen Soh, Jun Liu, Na Zhao |
| 2025 | GeSubNet: Gene Interaction Inference for Disease Subtype Network Generation. Ziwei Yang, Zheng Chen, Xin Liu, Rikuto Kotoge, Peng Chen, Yasuko Matsubara, Yasushi Sakurai, Jimeng Sun |
| 2025 | GenARM: Reward Guided Generation with Autoregressive Reward Model for Test-Time Alignment. Yuancheng Xu, Udari Madhushani Sehwag, Alec Koppel, Sicheng Zhu, Bang An, Furong Huang, Sumitra Ganesh |
| 2025 | GenDataAgent: On-the-fly Dataset Augmentation with Synthetic Data. Zhiteng Li, Lele Chen, Jerone T. A. Andrews, Yunhao Ba, Yulun Zhang, Alice Xiang |
| 2025 | GenEx: Generating an Explorable World. Taiming Lu, Tianmin Shu, Alan L. Yuille, Daniel Khashabi, Jieneng Chen |
| 2025 | GenSE: Generative Speech Enhancement via Language Models using Hierarchical Modeling. Jixun Yao, Hexin Liu, Chen Chen, Yuchen Hu, Eng Siong Chng, Lei Xie |
| 2025 | GenVP: Generating Visual Puzzles with Contrastive Hierarchical VAEs. Kalliopi Basioti, Pritish Sahu, Tony Qingze Liu, Zihao Xu, Hao Wang, Vladimir Pavlovic |
| 2025 | GenXD: Generating Any 3D and 4D Scenes. Yuyang Zhao, Chung-Ching Lin, Kevin Lin, Zhiwen Yan, Linjie Li, Zhengyuan Yang, Jianfeng Wang, Gim Hee Lee, Lijuan Wang |
| 2025 | General Scene Adaptation for Vision-and-Language Navigation. Haodong Hong, Yanyuan Qiao, Sen Wang, Jiajun Liu, Qi Wu |
| 2025 | Generalizability of Neural Networks Minimizing Empirical Risk Based on Expressive Power. Lijia Yu, Yibo Miao, Yifan Zhu, Xiao-Shan Gao, Lijun Zhang |
| 2025 | Generalizable Human Gaussians from Single-View Image. Jinnan Chen, Chen Li, Jianfeng Zhang, Lingting Zhu, Buzhen Huang, Hanlin Chen, Gim Hee Lee |
| 2025 | Generalizable Motion Planning via Operator Learning. Sharath Matada, Luke Bhan, Yuanyuan Shi, Nikolay Atanasov |
| 2025 | Generalization Bounds and Model Complexity for Kolmogorov-Arnold Networks. Xianyang Zhang, Huijuan Zhou |
| 2025 | Generalization Bounds for Canonicalization: A Comparative Study with Group Averaging. Behrooz Tahmasebi, Stefanie Jegelka |
| 2025 | Generalization Guarantees for Representation Learning via Data-Dependent Gaussian Mixture Priors. Milad Sefidgaran, Abdellatif Zaidi, Piotr Krasnowski |
| 2025 | Generalization and Distributed Learning of GFlowNets. Tiago Silva, Amauri H. Souza, Omar Rivasplata, Vikas Garg, Samuel Kaski, Diego Mesquita |
| 2025 | Generalization in VAE and Diffusion Models: A Unified Information-Theoretic Analysis. Qi Chen, Jierui Zhu, Florian Shkurti |
| 2025 | Generalization through variance: how noise shapes inductive biases in diffusion models. John J. Vastola |
| 2025 | Generalization v.s. Memorization: Tracing Language Models' Capabilities Back to Pretraining Data. Xinyi Wang, Antonis Antoniades, Yanai Elazar, Alfonso Amayuelas, Alon Albalak, Kexun Zhang, William Yang Wang |
| 2025 | Generalization, Expressivity, and Universality of Graph Neural Networks on Attributed Graphs. Levi Rauchwerger, Stefanie Jegelka, Ron Levie |
| 2025 | Generalized Behavior Learning from Diverse Demonstrations. Varshith Sreeramdass, Rohan R. Paleja, Letian Chen, Sanne van Waveren, Matthew C. Gombolay |
| 2025 | Generalized Consistency Trajectory Models for Image Manipulation. Beomsu Kim, Jaemin Kim, Jeongsol Kim, Jong Chul Ye |
| 2025 | Generalized Principal-Agent Problem with a Learning Agent. Tao Lin, Yiling Chen |
| 2025 | Generalized Video Moment Retrieval. You Qin, Qilong Wu, Yicong Li, Wei Ji, Li Li, Pengcheng Cai, Lina Wei, Roger Zimmermann |
| 2025 | Generalizing Reasoning Problems to Longer Lengths. Changnan Xiao, Bing Liu |
| 2025 | Generalizing Weisfeiler-Lehman Kernels to Subgraphs. Dongkwan Kim, Alice Oh |
| 2025 | Generating CAD Code with Vision-Language Models for 3D Designs. Kamel Alrashedy, Pradyumna Tambwekar, Zulfiqar Haider Zaidi, Megan Langwasser, Wei Xu, Matthew C. Gombolay |
| 2025 | Generating Freeform Endoskeletal Robots. Muhan Li, Lingji Kong, Sam Kriegman |
| 2025 | Generating Graphs via Spectral Diffusion. Giorgia Minello, Alessandro Bicciato, Luca Rossi, Andrea Torsello, Luca Cosmo |
| 2025 | Generating Likely Counterfactuals Using Sum-Product Networks. Jiri Nemecek, Tomás Pevný, Jakub Marecek |
| 2025 | Generating Physical Dynamics under Priors. Zihan Zhou, Xiaoxue Wang, Tianshu Yu |
| 2025 | Generation and Comprehension Hand-in-Hand: Vision-guided Expression Diffusion for Boosting Referring Expression Generation and Comprehension. Jingcheng Ke, Jun-Cheng Chen, I-Hong Jhuo, Chia-Wen Lin, Yen-Yu Lin |
| 2025 | Generative Adapter: Contextualizing Language Models in Parameters with A Single Forward Pass. Tong Chen, Hao Fang, Patrick Xia, Xiaodong Liu, Benjamin Van Durme, Luke Zettlemoyer, Jianfeng Gao, Hao Cheng |
| 2025 | Generative Classifiers Avoid Shortcut Solutions. Alexander Cong Li, Ananya Kumar, Deepak Pathak |
| 2025 | Generative Flows on Synthetic Pathway for Drug Design. Seonghwan Seo, Minsu Kim, Tony Shen, Martin Ester, Jinkyoo Park, Sungsoo Ahn, Woo Youn Kim |
| 2025 | Generative Inbetweening: Adapting Image-to-Video Models for Keyframe Interpolation. Xiaojuan Wang, Boyang Zhou, Brian Curless, Ira Kemelmacher-Shlizerman, Aleksander Holynski, Steven M. Seitz |
| 2025 | Generative Monoculture in Large Language Models. Fan Wu, Emily Black, Varun Chandrasekaran |
| 2025 | Generative Representational Instruction Tuning. Niklas Muennighoff, Hongjin Su, Liang Wang, Nan Yang, Furu Wei, Tao Yu, Amanpreet Singh, Douwe Kiela |
| 2025 | Generative Verifiers: Reward Modeling as Next-Token Prediction. Lunjun Zhang, Arian Hosseini, Hritik Bansal, Mehran Kazemi, Aviral Kumar, Rishabh Agarwal |
| 2025 | Generator Matching: Generative modeling with arbitrary Markov processes. Peter Holderrieth, Marton Havasi, Jason Yim, Neta Shaul, Itai Gat, Tommi S. Jaakkola, Brian Karrer, Ricky T. Q. Chen, Yaron Lipman |
| 2025 | GeoILP: A Synthetic Dataset to Guide Large-Scale Rule Induction. Si Chen, Richong Zhang, Xu Zhang |
| 2025 | GeoLoRA: Geometric integration for parameter efficient fine-tuning. Steffen Schotthöfer, Emanuele Zangrando, Gianluca Ceruti, Francesco Tudisco, Jonas Kusch |
| 2025 | GeoX: Geometric Problem Solving Through Unified Formalized Vision-Language Pre-training. Renqiu Xia, Mingsheng Li, Hancheng Ye, Wenjie Wu, Hongbin Zhou, Jiakang Yuan, Tianshuo Peng, Xinyu Cai, Xiangchao Yan, Bin Wang, Conghui He, Botian Shi, Tao Chen, Junchi Yan, Bo Zhang |
| 2025 | Geometric Inductive Biases of Deep Networks: The Role of Data and Architecture. Sajad Movahedi, Antonio Orvieto, Seyed-Mohsen Moosavi-Dezfooli |
| 2025 | Geometry Image Diffusion: Fast and Data-Efficient Text-to-3D with Image-Based Surface Representation. Slava Elizarov, Ciara Rowles, Simon Donné |
| 2025 | Geometry of Lightning Self-Attention: Identifiability and Dimension. Nathan W. Henry, Giovanni Luca Marchetti, Kathlén Kohn |
| 2025 | Geometry of Long-Tailed Representation Learning: Rebalancing Features for Skewed Distributions. Lingjie Yi, Jiachen Yao, Weimin Lyu, Haibin Ling, Raphael Douady, Chao Chen |
| 2025 | Geometry of Neural Reinforcement Learning in Continuous State and Action Spaces. Saket Tiwari, Omer Gottesman, George Konidaris |
| 2025 | Geometry-Aware Approaches for Balancing Performance and Theoretical Guarantees in Linear Bandits. Yuwei Luo, Mohsen Bayati |
| 2025 | Geometry-aware RL for Manipulation of Varying Shapes and Deformable Objects. Tai Hoang, Huy Le, Philipp Becker, Ngo Anh Vien, Gerhard Neumann |
| 2025 | Glad: A Streaming Scene Generator for Autonomous Driving. Bin Xie, Yingfei Liu, Tiancai Wang, Jiale Cao, Xiangyu Zhang |
| 2025 | Glauber Generative Model: Discrete Diffusion Models via Binary Classification. Harshit Varma, Dheeraj Mysore Nagaraj, Karthikeyan Shanmugam |
| 2025 | Glimpse: Enabling White-Box Methods to Use Proprietary Models for Zero-Shot LLM-Generated Text Detection. Guangsheng Bao, Yanbin Zhao, Juncai He, Yue Zhang |
| 2025 | Global Convergence in Neural ODEs: Impact of Activation Functions. Tianxiang Gao, Siyuan Sun, Hailiang Liu, Hongyang Gao |
| 2025 | Global Convergence of Policy Gradient in Average Reward MDPs. Navdeep Kumar, Yashaswini Murthy, Itai Shufaro, Kfir Yehuda Levy, R. Srikant, Shie Mannor |
| 2025 | Global Identifiability of Overcomplete Dictionary Learning via L1 and Volume Minimization. Yuchen Sun, Kejun Huang |
| 2025 | Global Well-posedness and Convergence Analysis of Score-based Generative Models via Sharp Lipschitz Estimates. Connor Mooney, Zhongjian Wang, Jack Xin, Yifeng Yu |
| 2025 | GlycanML: A Multi-Task and Multi-Structure Benchmark for Glycan Machine Learning. Minghao Xu, Yunteng Geng, Yihang Zhang, Ling Yang, Jian Tang, Wentao Zhang |
| 2025 | Gnothi Seauton: Empowering Faithful Self-Interpretability in Black-Box Transformers. Shaobo Wang, Hongxuan Tang, Mingyang Wang, Hongrui Zhang, Xuyang Liu, Weiya Li, Xuming Hu, Linfeng Zhang |
| 2025 | Going Beyond Feature Similarity: Effective Dataset distillation based on Class-aware Conditional Mutual Information. Xinhao Zhong, Bin Chen, Hao Fang, Xulin Gu, Shu-Tao Xia, En-Hui Yang |
| 2025 | Going Beyond Static: Understanding Shifts with Time-Series Attribution. Jiashuo Liu, Nabeel Seedat, Peng Cui, Mihaela van der Schaar |
| 2025 | GoodDrag: Towards Good Practices for Drag Editing with Diffusion Models. Zewei Zhang, Huan Liu, Jun Chen, Xiangyu Xu |
| 2025 | GotenNet: Rethinking Efficient 3D Equivariant Graph Neural Networks. Sarp Aykent, Tian Xia |
| 2025 | GrabS: Generative Embodied Agent for 3D Object Segmentation without Scene Supervision. Zihui Zhang, Yafei Yang, Hongtao Wen, Bo Yang |
| 2025 | Gradient correlation is a key ingredient to accelerate SGD with momentum. Julien Hermant, Marien Renaud, Jean-François Aujol, Charles Dossal, Aude Rondepierre |
| 2025 | Gradient descent with generalized Newton's method. Zhiqi Bu, Shiyun Xu |
| 2025 | Gradient-Free Generation for Hard-Constrained Systems. Chaoran Cheng, Boran Han, Danielle C. Maddix, Abdul Fatir Ansari, Andrew Stuart, Michael W. Mahoney, Bernie Wang |
| 2025 | Gramian Multimodal Representation Learning and Alignment. Giordano Cicchetti, Eleonora Grassucci, Luigi Sigillo, Danilo Comminiello |
| 2025 | Grammar Reinforcement Learning: path and cycle counting in graphs with a Context-Free Grammar and Transformer approach. Jason Piquenot, Maxime Berar, Romain Raveaux, Pierre Héroux, Jean-Yves Ramel, Sébastien Adam |
| 2025 | Graph Assisted Offline-Online Deep Reinforcement Learning for Dynamic Workflow Scheduling. Yifan Yang, Gang Chen, Hui Ma, Cong Zhang, Zhiguang Cao, Mengjie Zhang |
| 2025 | Graph Neural Networks Are More Than Filters: Revisiting and Benchmarking from A Spectral Perspective. Yushun Dong, Patrick Soga, Yinhan He, Song Wang, Jundong Li |
| 2025 | Graph Neural Networks Can (Often) Count Substructures. Paolo Pellizzoni, Till Hendrik Schulz, Karsten M. Borgwardt |
| 2025 | Graph Neural Networks Gone Hogwild. Olga Solodova, Nick Richardson, Deniz Oktay, Ryan P. Adams |
| 2025 | Graph Neural Networks for Edge Signals: Orientation Equivariance and Invariance. Dominik Fuchsgruber, Tim Postuvan, Stephan Günnemann, Simon Geisler |
| 2025 | Graph Neural Preconditioners for Iterative Solutions of Sparse Linear Systems. Jie Chen |
| 2025 | Graph Neural Ricci Flow: Evolving Feature from a Curvature Perspective. Jialong Chen, Bowen Deng, Zhen Wang, Chuan Chen, Zibin Zheng |
| 2025 | Graph Sparsification via Mixture of Graphs. Guibin Zhang, Xiangguo Sun, Yanwei Yue, Chonghe Jiang, Kun Wang, Tianlong Chen, Shirui Pan |
| 2025 | Graph Transformers Dream of Electric Flow. Xiang Cheng, Lawrence Carin, Suvrit Sra |
| 2025 | Graph-Guided Scene Reconstruction from Images with 3D Gaussian Splatting. Chong Cheng, Gaochao Song, Yiyang Yao, Qinzheng Zhou, Gangjian Zhang, Hao Wang |
| 2025 | Graph-based Document Structure Analysis. Yufan Chen, Ruiping Liu, Junwei Zheng, Di Wen, Kunyu Peng, Jiaming Zhang, Rainer Stiefelhagen |
| 2025 | GraphArena: Evaluating and Exploring Large Language Models on Graph Computation. Jianheng Tang, Qifan Zhang, Yuhan Li, Nuo Chen, Jia Li |
| 2025 | GraphBridge: Towards Arbitrary Transfer Learning in GNNs. Li Ju, Xingyi Yang, Qi Li, Xinchao Wang |
| 2025 | GraphEval: A Lightweight Graph-Based LLM Framework for Idea Evaluation. Tao Feng, Yihang Sun, Jiaxuan You |
| 2025 | GraphRouter: A Graph-based Router for LLM Selections. Tao Feng, Yanzhen Shen, Jiaxuan You |
| 2025 | GravMAD: Grounded Spatial Value Maps Guided Action Diffusion for Generalized 3D Manipulation. Yangtao Chen, Zixuan Chen, Junhui Yin, Jing Huo, Pinzhuo Tian, Jieqi Shi, Yang Gao |
| 2025 | Greener GRASS: Enhancing GNNs with Encoding, Rewiring, and Attention. Tongzhou Liao, Barnabás Póczos |
| 2025 | GridMix: Exploring Spatial Modulation for Neural Fields in PDE Modeling. Honghui Wang, Shiji Song, Gao Huang |
| 2025 | Grokking at the Edge of Numerical Stability. Lucas Prieto, Melih Barsbey, Pedro A. M. Mediano, Tolga Birdal |
| 2025 | Grounding Continuous Representations in Geometry: Equivariant Neural Fields. David R. Wessels, David M. Knigge, Riccardo Valperga, Samuele Papa, Sharvaree P. Vadgama, Efstratios Gavves, Erik J. Bekkers |
| 2025 | Grounding Multimodal Large Language Model in GUI World. Weixian Lei, Difei Gao, Mike Zheng Shou |
| 2025 | Grounding Video Models to Actions through Goal Conditioned Exploration. Yunhao Luo, Yilun Du |
| 2025 | Grounding by Trying: LLMs with Reinforcement Learning-Enhanced Retrieval. Sheryl Hsu, Omar Khattab, Chelsea Finn, Archit Sharma |
| 2025 | Group Distributionally Robust Dataset Distillation with Risk Minimization. Saeed Vahidian, Mingyu Wang, Jianyang Gu, Vyacheslav Kungurtsev, Wei Jiang, Yiran Chen |
| 2025 | Group Downsampling with Equivariant Anti-aliasing. Md Ashiqur Rahman, Raymond A. Yeh |
| 2025 | Group Ligands Docking to Protein Pockets. Jiaqi Guan, Jiahan Li, Xiangxin Zhou, Xingang Peng, Sheng Wang, Yunan Luo, Jian Peng, Jianzhu Ma |
| 2025 | Group-robust Sample Reweighting for Subpopulation Shifts via Influence Functions. Rui Qiao, Zhaoxuan Wu, Jingtan Wang, Pang Wei Koh, Bryan Kian Hsiang Low |
| 2025 | Growth Inhibitors for Suppressing Inappropriate Image Concepts in Diffusion Models. Die Chen, Zhiwen Li, Mingyuan Fan, Cen Chen, Wenmeng Zhou, Yanhao Wang, Yaliang Li |
| 2025 | Guaranteed Generation from Large Language Models. Minbeom Kim, Thibaut Thonet, Jos Rozen, Hwaran Lee, Kyomin Jung, Marc Dymetman |
| 2025 | Guided Score identity Distillation for Data-Free One-Step Text-to-Image Generation. Mingyuan Zhou, Zhendong Wang, Huangjie Zheng, Hai Huang |
| 2025 | Gumbel Counterfactual Generation From Language Models. Shauli Ravfogel, Anej Svete, Vésteinn Snæbjarnarson, Ryan Cotterell |
| 2025 | Gyrogroup Batch Normalization. Ziheng Chen, Yue Song, Xiaojun Wu, Nicu Sebe |
| 2025 | HAINAN: Fast and Accurate Transducer for Hybrid-Autoregressive ASR. Hainan Xu, Travis M. Bartley, Vladimir Bataev, Boris Ginsburg |
| 2025 | HALL-E: Hierarchical Neural Codec Language Model for Minute-Long Zero-Shot Text-to-Speech Synthesis. Yuto Nishimura, Takumi Hirose, Masanari Ohi, Hideki Nakayama, Nakamasa Inoue |
| 2025 | HAMSTER: Hierarchical Action Models for Open-World Robot Manipulation. Yi Li, Yuquan Deng, Jesse Zhang, Joel Jang, Marius Memmel, Caelan Reed Garrett, Fabio Ramos, Dieter Fox, Anqi Li, Abhishek Gupta, Ankit Goyal |
| 2025 | HARDMath: A Benchmark Dataset for Challenging Problems in Applied Mathematics. Jingxuan Fan, Sarah Martinson, Erik Y. Wang, Kaylie Hausknecht, Jonah Brenner, Danxian Liu, Nianli Peng, Corey Wang, Michael P. Brenner |
| 2025 | HART: Efficient Visual Generation with Hybrid Autoregressive Transformer. Haotian Tang, Yecheng Wu, Shang Yang, Enze Xie, Junsong Chen, Junyu Chen, Zhuoyang Zhang, Han Cai, Yao Lu, Song Han |
| 2025 | HASARD: A Benchmark for Vision-Based Safe Reinforcement Learning in Embodied Agents. Tristan Tomilin, Meng Fang, Mykola Pechenizkiy |
| 2025 | HD-Painter: High-Resolution and Prompt-Faithful Text-Guided Image Inpainting with Diffusion Models. Hayk Manukyan, Andranik Sargsyan, Barsegh Atanyan, Zhangyang Wang, Shant Navasardyan, Humphrey Shi |
| 2025 | HELM: Hierarchical Encoding for mRNA Language Modeling. Mehdi Yazdani-Jahromi, Mangal Prakash, Tommaso Mansi, Artem Moskalev, Rui Liao |
| 2025 | HELMET: How to Evaluate Long-context Models Effectively and Thoroughly. Howard Yen, Tianyu Gao, Minmin Hou, Ke Ding, Daniel Fleischer, Peter Izsak, Moshe Wasserblat, Danqi Chen |
| 2025 | HERO: Human-Feedback Efficient Reinforcement Learning for Online Diffusion Model Finetuning. Ayano Hiranaka, Shang-Fu Chen, Chieh-Hsin Lai, Dongjun Kim, Naoki Murata, Takashi Shibuya, Wei-Hsiang Liao, Shao-Hua Sun, Yuki Mitsufuji |
| 2025 | HG-Adapter: Improving Pre-Trained Heterogeneous Graph Neural Networks with Dual Adapters. Yujie Mo, Runpeng Yu, Xiaofeng Zhu, Xinchao Wang |
| 2025 | HGM³: Hierarchical Generative Masked Motion Modeling with Hard Token Mining. Minjae Jeong, Yechan Hwang, Jaejin Lee, Sungyoon Jung, Won Hwa Kim |
| 2025 | HMoRA: Making LLMs More Effective with Hierarchical Mixture of LoRA Experts. Mengqi Liao, Wei Chen, Junfeng Shen, Shengnan Guo, Huaiyu Wan |
| 2025 | HOPE for a Robust Parameterization of Long-memory State Space Models. Annan Yu, Michael W. Mahoney, N. Benjamin Erichson |
| 2025 | HQ-Edit: A High-Quality Dataset for Instruction-based Image Editing. Mude Hui, Siwei Yang, Bingchen Zhao, Yichun Shi, Heng Wang, Peng Wang, Cihang Xie, Yuyin Zhou |
| 2025 | HQGS: High-Quality Novel View Synthesis with Gaussian Splatting in Degraded Scenes. Xin Lin, Shi Luo, Xiaojun Shan, Xiaoyu Zhou, Chao Ren, Lu Qi, Ming-Hsuan Yang, Nuno Vasconcelos |
| 2025 | HR-Extreme: A High-Resolution Dataset for Extreme Weather Forecasting. Nian Ran, Peng Xiao, Yue Wang, Wesley Shi, Jianxin Lin, Qi Meng, Richard Allmendinger |
| 2025 | HShare: Fast LLM Decoding by Hierarchical Key-Value Sharing. Huaijin Wu, Lianqiang Li, Hantao Huang, Tu Yi, Jihang Zhang, Minghui Yu, Junchi Yan |
| 2025 | HaDeMiF: Hallucination Detection and Mitigation in Large Language Models. Xiaoling Zhou, Mingjie Zhang, Zhemg Lee, Wei Ye, Shikun Zhang |
| 2025 | Hadamrnn: Binary and Sparse Ternary orthogonal RNNs. Armand Foucault, François Malgouyres, Franck Mamalet |
| 2025 | Hallo2: Long-Duration and High-Resolution Audio-Driven Portrait Image Animation. Jiahao Cui, Hui Li, Yao Yao, Hao Zhu, Hanlin Shang, Kaihui Cheng, Hang Zhou, Siyu Zhu, Jingdong Wang |
| 2025 | Halton Scheduler for Masked Generative Image Transformer. Victor Besnier, Mickaël Chen, David Hurych, Eduardo Valle, Matthieu Cord |
| 2025 | Handling Delay in Real-Time Reinforcement Learning. Ivan Anokhin, Rishav Rishav, Matthew Riemer, Stephen Chung, Irina Rish, Samira Ebrahimi Kahou |
| 2025 | HarmAug: Effective Data Augmentation for Knowledge Distillation of Safety Guard Models. Seanie Lee, Haebin Seong, Dong Bok Lee, Minki Kang, Xiaoyin Chen, Dominik Wagner, Yoshua Bengio, Juho Lee, Sung Ju Hwang |
| 2025 | Harnessing Diversity for Important Data Selection in Pretraining Large Language Models. Chi Zhang, Huaping Zhong, Kuan Zhang, Chengliang Chai, Rui Wang, Xinlin Zhuang, Tianyi Bai, Jiantao Qiu, Lei Cao, Ju Fan, Ye Yuan, Guoren Wang, Conghui He |
| 2025 | Harnessing Webpage UIs for Text-Rich Visual Understanding. Junpeng Liu, Tianyue Ou, Yifan Song, Yuxiao Qu, Wai Lam, Chenyan Xiong, Wenhu Chen, Graham Neubig, Xiang Yue |
| 2025 | Has the Deep Neural Network learned the Stochastic Process? An Evaluation Viewpoint. Harshit Kumar, Beomseok Kang, Biswadeep Chakraborty, Saibal Mukhopadhyay |
| 2025 | Have the VLMs Lost Confidence? A Study of Sycophancy in VLMs. Shuo Li, Tao Ji, Xiaoran Fan, Linsheng Lu, Leyi Yang, Yuming Yang, Zhiheng Xi, Rui Zheng, Yuran Wang, Xiaohui Zhao, Tao Gui, Qi Zhang, Xuanjing Huang |
| 2025 | HeadMap: Locating and Enhancing Knowledge Circuits in LLMs. Xuehao Wang, Liyuan Wang, Binghuai Lin, Yu Zhang |
| 2025 | Heavy-Tailed Diffusion Models. Kushagra Pandey, Jaideep Pathak, Yilun Xu, Stephan Mandt, Michael S. Pritchard, Arash Vahdat, Morteza Mardani |
| 2025 | Heavy-Tailed Diffusion with Denoising Levy Probabilistic Models. Dario Shariatian, Umut Simsekli, Alain Oliviero Durmus |
| 2025 | HelpSteer2-Preference: Complementing Ratings with Preferences. Zhilin Wang, Alexander Bukharin, Olivier Delalleau, Daniel Egert, Gerald Shen, Jiaqi Zeng, Oleksii Kuchaiev, Yi Dong |
| 2025 | Herald: A Natural Language Annotated Lean 4 Dataset. Guoxiong Gao, Yutong Wang, Jiedong Jiang, Qi Gao, Zihan Qin, Tianyi Xu, Bin Dong |
| 2025 | Hessian-Free Online Certified Unlearning. Xinbao Qiao, Meng Zhang, Ming Tang, Ermin Wei |
| 2025 | HexGen-2: Disaggregated Generative Inference of LLMs in Heterogeneous Environment. Youhe Jiang, Ran Yan, Binhang Yuan |
| 2025 | HiBug2: Efficient and Interpretable Error Slice Discovery for Comprehensive Model Debugging. Muxi Chen, Chenchen Zhao, Qiang Xu |
| 2025 | HiLo: A Learning Framework for Generalized Category Discovery Robust to Domain Shifts. Hongjun Wang, Sagar Vaze, Kai Han |
| 2025 | HiRA: Parameter-Efficient Hadamard High-Rank Adaptation for Large Language Models. Qiushi Huang, Tom Ko, Zhan Zhuang, Lilian Tang, Yu Zhang |
| 2025 | HiSplat: Hierarchical 3D Gaussian Splatting for Generalizable Sparse-View Reconstruction. Shengji Tang, Weicai Ye, Peng Ye, Weihao Lin, Yang Zhou, Tao Chen, Wanli Ouyang |
| 2025 | Hidden in the Noise: Two-Stage Robust Watermarking for Images. Kasra Arabi, Benjamin Feuer, R. Teal Witter, Chinmay Hegde, Niv Cohen |
| 2025 | Hierarchical Autoregressive Transformers: Combining Byte- and Word-Level Processing for Robust, Adaptable Language Models. Pit Neitemeier, Björn Deiseroth, Constantin Eichenberg, Lukas Balles |
| 2025 | Hierarchical Uncertainty Estimation for Learning-based Registration in Neuroimaging. Xiaoling Hu, Karthik Gopinath, Peirong Liu, Malte Hoffmann, Koen Van Leemput, Oula Puonti, Juan Eugenio Iglesias |
| 2025 | Hierarchical World Models as Visual Whole-Body Humanoid Controllers. Nicklas Hansen, Jyothir S. V, Vlad Sobal, Yann LeCun, Xiaolong Wang, Hao Su |
| 2025 | Hierarchically Encapsulated Representation for Protocol Design in Self-Driving Labs. Yu-Zhe Shi, Mingchen Liu, Fanxu Meng, Qiao Xu, Zhangqian Bi, Kun He, Lecheng Ruan, Qining Wang |
| 2025 | High-Dimensional Bayesian Optimisation with Gaussian Process Prior Variational Autoencoders. Siddharth Ramchandran, Manuel Haussmann, Harri Lähdesmäki |
| 2025 | High-Dynamic Radar Sequence Prediction for Weather Nowcasting Using Spatiotemporal Coherent Gaussian Representation. Ziye Wang, Yiran Qin, Lin Zeng, Ruimao Zhang |
| 2025 | High-Precision Dichotomous Image Segmentation via Probing Diffusion Capacity. Qian Yu, Peng-Tao Jiang, Hao Zhang, Jinwei Chen, Bo Li, Lihe Zhang, Huchuan Lu |
| 2025 | High-Quality Joint Image and Video Tokenization with Causal VAE. Dawit Mureja Argaw, Xian Liu, Qinsheng Zhang, Joon Son Chung, Ming-Yu Liu, Fitsum Reda |
| 2025 | High-dimension Prototype is a Better Incremental Object Detection Learner. Yanjie Wang, Liqun Chen, Tianming Zhao, Tao Zhang, Guodong Wang, Luxin Yan, Sheng Zhong, Jiahuan Zhou, Xu Zou |
| 2025 | High-dimensional Analysis of Knowledge Distillation: Weak-to-Strong Generalization and Scaling Laws. Muhammed Emrullah Ildiz, Halil Alperen Gozeten, Ege Onur Taga, Marco Mondelli, Samet Oymak |
| 2025 | High-quality Text-to-3D Character Generation with SparseCubes and Sparse Transformers. Jiachen Qian, Hongye Yang, Shuang Wu, Jingxi Xu, Feihu Zhang |
| 2025 | Higher-Order Graphon Neural Networks: Approximation and Cut Distance. Daniel Herbst, Stefanie Jegelka |
| 2025 | Highly Efficient Self-Adaptive Reward Shaping for Reinforcement Learning. Haozhe Ma, Zhengding Luo, Thanh Vinh Vo, Kuankuan Sima, Tze-Yun Leong |
| 2025 | Holistic Reasoning with Long-Context LMs: A Benchmark for Database Operations on Massive Textual Data. Seiji Maekawa, Hayate Iso, Nikita Bhutani |
| 2025 | Holistically Evaluating the Environmental Impact of Creating Language Models. Jacob Morrison, Clara Na, Jared Fernandez, Tim Dettmers, Emma Strubell, Jesse Dodge |
| 2025 | Holographic Node Representations: Pre-training Task-Agnostic Node Embeddings. Beatrice Bevilacqua, Joshua Robinson, Jure Leskovec, Bruno Ribeiro |
| 2025 | Homomorphism Counts as Structural Encodings for Graph Learning. Linus Bao, Emily Jin, Michael M. Bronstein, Ismail Ilkan Ceylan, Matthias Lanzinger |
| 2025 | Homomorphism Expressivity of Spectral Invariant Graph Neural Networks. Jingchu Gai, Yiheng Du, Bohang Zhang, Haggai Maron, Liwei Wang |
| 2025 | Horizon Generalization in Reinforcement Learning. Vivek Myers, Catherine Ji, Benjamin Eysenbach |
| 2025 | Hot-pluggable Federated Learning: Bridging General and Personalized FL via Dynamic Selection. Lei Shen, Zhenheng Tang, Lijun Wu, Yonggang Zhang, Xiaowen Chu, Tao Qin, Bo Han |
| 2025 | Hotspot-Driven Peptide Design via Multi-Fragment Autoregressive Extension. Jiahan Li, Tong Chen, Shitong Luo, Chaoran Cheng, Jiaqi Guan, Ruihan Guo, Sheng Wang, Ge Liu, Jian Peng, Jianzhu Ma |
| 2025 | How DNNs break the Curse of Dimensionality: Compositionality and Symmetry Learning. Arthur Jacot, Seok Hoan Choi, Yuxiao Wen |
| 2025 | How Discrete and Continuous Diffusion Meet: Comprehensive Analysis of Discrete Diffusion Models via a Stochastic Integral Framework. Yinuo Ren, Haoxuan Chen, Grant M. Rotskoff, Lexing Ying |
| 2025 | How Do Large Language Models Understand Graph Patterns? A Benchmark for Graph Pattern Comprehension. Xinnan Dai, Haohao Qu, Yifei Shen, Bohang Zhang, Qihao Wen, Wenqi Fan, Dongsheng Li, Jiliang Tang, Caihua Shan |
| 2025 | How Does Critical Batch Size Scale in Pre-training? Hanlin Zhang, Depen Morwani, Nikhil Vyas, Jingfeng Wu, Difan Zou, Udaya Ghai, Dean P. Foster, Sham M. Kakade |
| 2025 | How Does Vision-Language Adaptation Impact the Safety of Vision Language Models? Seongyun Lee, Geewook Kim, Jiyeon Kim, Hyunji Lee, Hoyeon Chang, Sue Hyun Park, Minjoon Seo |
| 2025 | How Far Are We from True Unlearnability? Kai Ye, Liangcai Su, Chenxiong Qian |
| 2025 | How Feature Learning Can Improve Neural Scaling Laws. Blake Bordelon, Alexander B. Atanasov, Cengiz Pehlevan |
| 2025 | How Gradient descent balances features: A dynamical analysis for two-layer neural networks. Zhenyu Zhu, Fanghui Liu, Volkan Cevher |
| 2025 | How Learnable Grids Recover Fine Detail in Low Dimensions: A Neural Tangent Kernel Analysis of Multigrid Parametric Encodings. Samuel Audia, Soheil Feizi, Matthias Zwicker, Dinesh Manocha |
| 2025 | How Low Can You Go? Searching for the Intrinsic Dimensionality of Complex Networks using Metric Node Embeddings. Nikolaos Nakis, Niels Raunkjær Holm, Andreas Lyhne Fiehn, Morten Mørup |
| 2025 | How Much is Unseen Depends Chiefly on Information About the Seen. Seongmin Lee, Marcel Boehme |
| 2025 | How Much is a Noisy Image Worth? Data Scaling Laws for Ambient Diffusion. Giannis Daras, Yeshwanth Cherapanamjeri, Constantinos Daskalakis |
| 2025 | How efficient is LLM-generated code? A rigorous & high-standard benchmark. Ruizhong Qiu, Weiliang Will Zeng, James Ezick, Christopher Lott, Hanghang Tong |
| 2025 | How many samples are needed to train a deep neural network? Pegah Golestaneh, Mahsa Taheri, Johannes Lederer |
| 2025 | How much of my dataset did you use? Quantitative Data Usage Inference in Machine Learning. Yao Tong, Jiayuan Ye, Sajjad Zarifzadeh, Reza Shokri |
| 2025 | How new data permeates LLM knowledge and how to dilute it. Chen Sun, Renat Aksitov, Andrey Zhmoginov, Nolan Andrew Miller, Max Vladymyrov, Ulrich Rueckert, Been Kim, Mark Sandler |
| 2025 | How to Evaluate Reward Models for RLHF. Evan Frick, Tianle Li, Connor Chen, Wei-Lin Chiang, Anastasios Nikolas Angelopoulos, Jiantao Jiao, Banghua Zhu, Joseph E. Gonzalez, Ion Stoica |
| 2025 | How to Find the Exact Pareto Front for Multi-Objective MDPs? Yining Li, Peizhong Ju, Ness B. Shroff |
| 2025 | How to Probe: Simple Yet Effective Techniques for Improving Post-hoc Explanations. Siddhartha Gairola, Moritz Böhle, Francesco Locatello, Bernt Schiele |
| 2025 | How to Verify Any (Reasonable) Distribution Property: Computationally Sound Argument Systems for Distributions. Tal Herman, Guy N. Rothblum |
| 2025 | Human Simulacra: Benchmarking the Personification of Large Language Models. Qiujie Xie, Qiming Feng, Tianqi Zhang, Qingqiu Li, Linyi Yang, Yuejie Zhang, Rui Feng, Liang He, Shang Gao, Yue Zhang |
| 2025 | Human-Aligned Chess With a Bit of Search. Yiming Zhang, Athul Paul Jacob, Vivian Lai, Daniel Fried, Daphne Ippolito |
| 2025 | Human-inspired Episodic Memory for Infinite Context LLMs. Zafeirios Fountas, Martin Benfeghoul, Adnan Oomerjee, Fenia Christopoulou, Gerasimos Lampouras, Haitham Bou-Ammar, Jun Wang |
| 2025 | Humanizing the Machine: Proxy Attacks to Mislead LLM Detectors. Tianchun Wang, Yuanzhou Chen, Zichuan Liu, Zhanwen Chen, Haifeng Chen, Xiang Zhang, Wei Cheng |
| 2025 | Hummingbird: High Fidelity Image Generation via Multimodal Context Alignment. Minh-Quan Le, Gaurav Mittal, Tianjian Meng, A S. M. Iftekhar, Vishwas Suryanarayanan, Barun Patra, Dimitris Samaras, Mei Chen |
| 2025 | HyPoGen: Optimization-Biased Hypernetworks for Generalizable Policy Generation. Hanxiang Ren, Li Sun, Xulong Wang, Pei Zhou, Zewen Wu, Siyan Dong, Difan Zou, Youyi Zheng, Yanchao Yang |
| 2025 | Hybrid Regularization Improves Diffusion-based Inverse Problem Solving. Hongkun Dou, Zeyu Li, Jinyang Du, Lijun Yang, Wen Yao, Yue Deng |
| 2025 | Hydra-SGG: Hybrid Relation Assignment for One-stage Scene Graph Generation. Minghan Chen, Guikun Chen, Wenguan Wang, Yi Yang |
| 2025 | Hymba: A Hybrid-head Architecture for Small Language Models. Xin Dong, Yonggan Fu, Shizhe Diao, Wonmin Byeon, Zijia Chen, Ameya Sunil Mahabaleshwarkar, Shih-Yang Liu, Matthijs Van Keirsbilck, Min-Hung Chen, Yoshi Suhara, Yingyan Celine Lin, Jan Kautz, Pavlo Molchanov |
| 2025 | Hyper-Connections. Defa Zhu, Hongzhi Huang, Zihao Huang, Yutao Zeng, Yunyao Mao, Banggu Wu, Qiyang Min, Xun Zhou |
| 2025 | HyperDAS: Towards Automating Mechanistic Interpretability with Hypernetworks. Jiuding Sun, Jing Huang, Sidharth Baskaran, Karel D'Oosterlinck, Christopher Potts, Michael Sklar, Atticus Geiger |
| 2025 | HyperFace: Generating Synthetic Face Recognition Datasets by Exploring Face Embedding Hypersphere. Hatef Otroshi-Shahreza, Sébastien Marcel |
| 2025 | HyperPLR: Hypergraph Generation through Projection, Learning, and Reconstruction. Weihuang Wen, Tianshu Yu |
| 2025 | Hyperbolic Genome Embeddings. Raiyan R. Khan, Philippe Chlenski, Itsik Pe'er |
| 2025 | Hypothetical Minds: Scaffolding Theory of Mind for Multi-Agent Tasks with Large Language Models. Logan Matthew Cross, Violet Xiang, Agam Bhatia, Daniel L. K. Yamins, Nick Haber |
| 2025 | I Can Hear You: Selective Robust Training for Deepfake Audio Detection. Zirui Zhang, Wei Hao, Aroon Sankoh, William Lin, Emanuel Mendiola-Ortiz, Junfeng Yang, Chengzhi Mao |
| 2025 | I-Con: A Unifying Framework for Representation Learning. Shaden Naif Alshammari, John R. Hershey, Axel Feldmann, William T. Freeman, Mark Hamilton |
| 2025 | I2AM: Interpreting Image-to-Image Latent Diffusion Models via Bi-Attribution Maps. Junseo Park, Hyeryung Jang |
| 2025 | I2VControl-Camera: Precise Video Camera Control with Adjustable Motion Strength. Wanquan Feng, Jiawei Liu, Pengqi Tu, Tianhao Qi, Mingzhen Sun, Tianxiang Ma, Songtao Zhao, SiYu Zhou, Qian He |
| 2025 | ICLR: In-Context Learning of Representations. Core Francisco Park, Andrew Lee, Ekdeep Singh Lubana, Yongyi Yang, Maya Okawa, Kento Nishi, Martin Wattenberg, Hidenori Tanaka |
| 2025 | IDA-VLM: Towards Movie Understanding via ID-Aware Large Vision-Language Model. Yatai Ji, Shilong Zhang, Jie Wu, Peize Sun, Weifeng Chen, Xuefeng Xiao, Sidi Yang, Yujiu Yang, Ping Luo |
| 2025 | IDArb: Intrinsic Decomposition for Arbitrary Number of Input Views and Illuminations. Zhibing Li, Tong Wu, Jing Tan, Mengchen Zhang, Jiaqi Wang, Dahua Lin |
| 2025 | IDInit: A Universal and Stable Initialization Method for Neural Network Training. Yu Pan, Chaozheng Wang, Zekai Wu, Qifan Wang, Min Zhang, Zenglin Xu |
| 2025 | IGL-Bench: Establishing the Comprehensive Benchmark for Imbalanced Graph Learning. Jiawen Qin, Haonan Yuan, Qingyun Sun, Lyujin Xu, Jiaqi Yuan, Pengfeng Huang, Zhaonan Wang, Xingcheng Fu, Hao Peng, Jianxin Li, Philip S. Yu |
| 2025 | ILLUSION: Unveiling Truth with a Comprehensive Multi-Modal, Multi-Lingual Deepfake Dataset. Kartik Thakral, Rishabh Ranjan, Akanksha Singh, Akshat Jain, Mayank Vatsa, Richa Singh |
| 2025 | IMDPrompter: Adapting SAM to Image Manipulation Detection by Cross-View Automated Prompt Learning. Quan Zhang, Yuxin Qi, Xi Tang, Jinwei Fang, Xi Lin, Ke Zhang, Chun Yuan |
| 2025 | INCLUDE: Evaluating Multilingual Language Understanding with Regional Knowledge. Angelika Romanou, Negar Foroutan, Anna Sotnikova, Zeming Chen, Sree Harsha Nelaturu, Shivalika Singh, Rishabh Maheshwary, Micol Altomare, Mohamed A. Haggag, Imanol Schlag, Marzieh Fadaee, Sara Hooker, Antoine Bosselut, Snegha A, Alfonso Amayuelas, Azril Hafizi Amirudin, Viraat Aryabumi, Danylo Boiko, Michael Chang, Jenny Chim, Gal Cohen, Aditya Kumar Dalmia, Abraham Diress, Sharad Duwal, Daniil Dzenhaliou, Daniel Fernando Erazo Florez, Fabian Farestam, Joseph Marvin Imperial, Shayekh Bin Islam, Perttu Isotalo, Maral Jabbarishiviari, Börje F. Karlsson, Eldar Khalilov, Christopher Klamm, Fajri Koto, Dominik Krzeminski, Gabriel Adriano de Melo, Syrielle Montariol, Yiyang Nan, Joel Niklaus, Jekaterina Novikova, Johan Samir Obando-Ceron, Debjit Paul, Esther Ploeger, Jebish Purbey, Swati Rajwal, Selvan Sunitha Ravi, Sara Rydell, Roshan Santhosh, Drishti Sharma, Marjana Prifti Skenduli, Arshia Soltani Moakhar, Bardia Soltani Moakhar, Ran Tamir, Ayush Kumar Tarun, Azmine Toushik Wasi, Thenuka Ovin Weerasinghe, Serhan Yilmaz, Mike Zhang |
| 2025 | INFER: A Neural-symbolic Model For Extrapolation Reasoning on Temporal Knowledge Graph. Ningyuan Li, Haihong E, Tianyu Yao, Tianyi Hu, Yuhan Li, Haoran Luo, Meina Song, Yifan Zhu |
| 2025 | INS: Interaction-aware Synthesis to Enhance Offline Multi-agent Reinforcement Learning. Yuqian Fu, Yuanheng Zhu, Jian Zhao, Jiajun Chai, Dongbin Zhao |
| 2025 | IPDreamer: Appearance-Controllable 3D Object Generation with Complex Image Prompts. Bohan Zeng, Shanglin Li, Yutang Feng, Ling Yang, Juan Zhang, Hong Li, Jiaming Liu, Conghui He, Wentao Zhang, Jianzhuang Liu, Baochang Zhang, Shuicheng Yan |
| 2025 | IRIS: LLM-Assisted Static Analysis for Detecting Security Vulnerabilities. Ziyang Li, Saikat Dutta, Mayur Naik |
| 2025 | IV-mixed Sampler: Leveraging Image Diffusion Models for Enhanced Video Synthesis. Shitong Shao, Zikai Zhou, Bai Lichen, Haoyi Xiong, Zeke Xie |
| 2025 | Identifiability for Gaussian Processes with Holomorphic Kernels. Ameer Qaqish, Didong Li |
| 2025 | Identifiable Exchangeable Mechanisms for Causal Structure and Representation Learning. Patrik Reizinger, Siyuan Guo, Ferenc Huszár, Bernhard Schölkopf, Wieland Brendel |
| 2025 | Identification of Intermittent Temporal Latent Process. Yuke Li, Yujia Zheng, Guangyi Chen, Kun Zhang, Heng Huang |
| 2025 | Identifying latent state transitions in non-linear dynamical systems. Çaglar Hizli, Çagatay Yildiz, Matthias Bethge, S. T. John, Pekka Marttinen |
| 2025 | Iformer: Integrating ConvNet and Transformer for Mobile Application. Chuanyang Zheng |
| 2025 | IgGM: A Generative Model for Functional Antibody and Nanobody Design. Rubo Wang, Fandi Wu, Xingyu Gao, Jiaxiang Wu, Peilin Zhao, Jianhua Yao |
| 2025 | ImDy: Human Inverse Dynamics from Imitated Observations. Xinpeng Liu, Junxuan Liang, Zili Lin, Haowen Hou, Yong-Lu Li, Cewu Lu |
| 2025 | ImProver: Agent-Based Automated Proof Optimization. Riyaz Ahuja, Jeremy Avigad, Prasad Tetali, Sean Welleck |
| 2025 | Image Watermarks are Removable using Controllable Regeneration from Clean Noise. Yepeng Liu, Yiren Song, Hai Ci, Yu Zhang, Haofan Wang, Mike Zheng Shou, Yuheng Bu |
| 2025 | Image and Video Tokenization with Binary Spherical Quantization. Yue Zhao, Yuanjun Xiong, Philipp Krähenbühl |
| 2025 | Image-level Memorization Detection via Inversion-based Inference Perturbation. Yue Jiang, Haokun Lin, Yang Bai, Bo Peng, Zhili Liu, Yueming Lyu, Yong Yang, Xing Zheng, Jing Dong |
| 2025 | ImageFolder: Autoregressive Image Generation with Folded Tokens. Xiang Li, Kai Qiu, Hao Chen, Jason Kuen, Jiuxiang Gu, Bhiksha Raj, Zhe Lin |
| 2025 | ImagineNav: Prompting Vision-Language Models as Embodied Navigator through Scene Imagination. Xinxin Zhao, Wenzhe Cai, Likun Tang, Teng Wang |
| 2025 | Immunogenicity Prediction with Dual Attention Enables Vaccine Target Selection. Song Li, Yang Tan, Song Ke, Liang Hong, Bingxin Zhou |
| 2025 | ImpScore: A Learnable Metric For Quantifying The Implicitness Level of Sentences. Yuxin Wang, Xiaomeng Zhu, Weimin Lyu, Saeed Hassanpour, Soroush Vosoughi |
| 2025 | Implicit Bias of Mirror Flow for Shallow Neural Networks in Univariate Regression. Shuang Liang, Guido Montúfar |
| 2025 | Implicit In-context Learning. Zhuowei Li, Zihao Xu, Ligong Han, Yunhe Gao, Song Wen, Di Liu, Hao Wang, Dimitris N. Metaxas |
| 2025 | Implicit Neural Surface Deformation with Explicit Velocity Fields. Lu Sang, Zehranaz Canfes, Dongliang Cao, Florian Bernard, Daniel Cremers |
| 2025 | Implicit Search via Discrete Diffusion: A Study on Chess. Jiacheng Ye, Zhenyu Wu, Jiahui Gao, Zhiyong Wu, Xin Jiang, Zhenguo Li, Lingpeng Kong |
| 2025 | Improved Algorithms for Kernel Matrix-Vector Multiplication Under Sparsity Assumptions. Piotr Indyk, Michael Kapralov, Kshiteej Sheth, Tal Wagner |
| 2025 | Improved Approximation Algorithms for k-Submodular Maximization via Multilinear Extension. Huanjian Zhou, Lingxiao Huang, Baoxiang Wang |
| 2025 | Improved Convergence Rate for Diffusion Probabilistic Models. Gen Li, Yuchen Jiao |
| 2025 | Improved Diffusion-based Generative Model with Better Adversarial Robustness. Zekun Wang, Mingyang Yi, Shuchen Xue, Zhenguo Li, Ming Liu, Bing Qin, Zhiming Ma |
| 2025 | Improved Finite-Particle Convergence Rates for Stein Variational Gradient Descent. Sayan Banerjee, Krishna Balasubramanian, Promit Ghosal |
| 2025 | Improved Sampling Algorithms for Lévy-Itô Diffusion Models. Vadim Popov, Assel Yermekova, Tasnima Sadekova, Artem Khrapov, Mikhail Sergeevich Kudinov |
| 2025 | Improved Sampling Of Diffusion Models In Fluid Dynamics With Tweedie's Formula. Youssef Shehata, Benjamin J. Holzschuh, Nils Thuerey |
| 2025 | Improved Techniques for Optimization-Based Jailbreaking on Large Language Models. Xiaojun Jia, Tianyu Pang, Chao Du, Yihao Huang, Jindong Gu, Yang Liu, Xiaochun Cao, Min Lin |
| 2025 | Improved Training Technique for Latent Consistency Models. Quan Dao, Khanh Doan, Di Liu, Trung Le, Dimitris N. Metaxas |
| 2025 | Improving Complex Reasoning with Dynamic Prompt Corruption: A Soft Prompt Optimization Approach. Sinan Fan, Liang Xie, Chen Shen, Ge Teng, Xiaosong Yuan, Xiaofeng Zhang, Chenxi Huang, Wenxiao Wang, Xiaofei He, Jieping Ye |
| 2025 | Improving Convergence Guarantees of Random Subspace Second-order Algorithm for Nonconvex Optimization. Rei Higuchi, Pierre-Louis Poirion, Akiko Takeda |
| 2025 | Improving Data Efficiency via Curating LLM-Driven Rating Systems. Jinlong Pang, Jiaheng Wei, Ankit Shah, Zhaowei Zhu, Yaxuan Wang, Chen Qian, Yang Liu, Yujia Bao, Wei Wei |
| 2025 | Improving Deep Regression with Tightness. Shihao Zhang, Yuguang Yan, Angela Yao |
| 2025 | Improving Equivariant Networks with Probabilistic Symmetry Breaking. Hannah Lawrence, Vasco Portilheiro, Yan Zhang, Sékou-Oumar Kaba |
| 2025 | Improving Generalization and Robustness in SNNs Through Signed Rate Encoding and Sparse Encoding Attacks. Bhaskar Mukhoty, Hilal AlQuabeh, Bin Gu |
| 2025 | Improving Graph Neural Networks by Learning Continuous Edge Directions. Seong Ho Pahng, Sahand Hormoz |
| 2025 | Improving Instruction-Following in Language Models through Activation Steering. Alessandro Stolfo, Vidhisha Balachandran, Safoora Yousefi, Eric Horvitz, Besmira Nushi |
| 2025 | Improving Language Model Distillation through Hidden State Matching. Sayantan Dasgupta, Trevor Cohn |
| 2025 | Improving Large Language Model Planning with Action Sequence Similarity. Xinran Zhao, Hanie Sedghi, Bernd Bohnet, Dale Schuurmans, Azade Nova |
| 2025 | Improving Long-Text Alignment for Text-to-Image Diffusion Models. Luping Liu, Chao Du, Tianyu Pang, Zehan Wang, Chongxuan Li, Dong Xu |
| 2025 | Improving Neural Network Accuracy by Concurrently Training with a Twin Network. Benjamin Vandersmissen, Lucas Deckers, José Oramas M. |
| 2025 | Improving Neural Optimal Transport via Displacement Interpolation. Jaemoo Choi, Yongxin Chen, Jaewoong Choi |
| 2025 | Improving Pretraining Data Using Perplexity Correlations. Tristan Thrush, Christopher Potts, Tatsunori Hashimoto |
| 2025 | Improving Probabilistic Diffusion Models With Optimal Diagonal Covariance Matching. Zijing Ou, Mingtian Zhang, Andi Zhang, Tim Z. Xiao, Yingzhen Li, David Barber |
| 2025 | Improving Reasoning Performance in Large Language Models via Representation Engineering. Bertram Højer, Oliver Simon Jarvis, Stefan Heinrich |
| 2025 | Improving Semantic Understanding in Speech Language Models via Brain-tuning. Omer Moussa, Dietrich Klakow, Mariya Toneva |
| 2025 | Improving Uncertainty Estimation through Semantically Diverse Language Generation. Lukas Aichberger, Kajetan Schweighofer, Mykyta Ielanskyi, Sepp Hochreiter |
| 2025 | Improving Unsupervised Constituency Parsing via Maximizing Semantic Information. Junjie Chen, Xiangheng He, Yusuke Miyao, Danushka Bollegala |
| 2025 | Improving the Sparse Structure Learning of Spiking Neural Networks from the View of Compression Efficiency. Jiangrong Shen, Qi Xu, Gang Pan, Badong Chen |
| 2025 | Imputation for prediction: beware of diminishing returns. Marine Le Morvan, Gaël Varoquaux |
| 2025 | In Search of Forgotten Domain Generalization. Prasanna Mayilvahanan, Roland S. Zimmermann, Thaddäus Wiedemer, Evgenia Rusak, Attila Juhos, Matthias Bethge, Wieland Brendel |
| 2025 | In vivo cell-type and brain region classification via multimodal contrastive learning. Han Yu, Hanrui Lyu, YiXun Xu, Charlie Windolf, Eric Kenji Lee, Fan Yang, Andrew M. Shelton, Olivier Winter, International Brain Laboratory, Eva L. Dyer, Chandramouli Chandrasekaran, Nicholas A. Steinmetz, Liam Paninski, Cole Lincoln Hurwitz |
| 2025 | In-Context Editing: Learning Knowledge from Self-Induced Distributions. Siyuan Qi, Bangcheng Yang, Kailin Jiang, Xiaobo Wang, Jiaqi Li, Yifan Zhong, Yaodong Yang, Zilong Zheng |
| 2025 | In-context Time Series Predictor. Jiecheng Lu, Yan Sun, Shihao Yang |
| 2025 | InCoDe: Interpretable Compressed Descriptions For Image Generation. Armand Comas Massague, Aditya Chattopadhyay, Feliu Formosa, Changyu Liu, Octavia I. Camps, René Vidal |
| 2025 | Incorporating Visual Correspondence into Diffusion Model for Virtual Try-On. Siqi Wan, Jingwen Chen, Yingwei Pan, Ting Yao, Tao Mei |
| 2025 | Incremental Causal Effect for Time to Treatment Initialization. Andrew Ying, Zhichen Zhao, Ronghui Xu |
| 2025 | Indirect Gradient Matching for Adversarial Robust Distillation. Hongsin Lee, Seungju Cho, Changick Kim |
| 2025 | Inference Optimal VLMs Need Fewer Visual Tokens and More Parameters. Kevin Y. Li, Sachin Goyal, João D. Semedo, J. Zico Kolter |
| 2025 | Inference Scaling Laws: An Empirical Analysis of Compute-Optimal Inference for LLM Problem-Solving. Yangzhen Wu, Zhiqing Sun, Shanda Li, Sean Welleck, Yiming Yang |
| 2025 | Inference Scaling for Long-Context Retrieval Augmented Generation. Zhenrui Yue, Honglei Zhuang, Aijun Bai, Kai Hui, Rolf Jagerman, Hansi Zeng, Zhen Qin, Dong Wang, Xuanhui Wang, Michael Bendersky |
| 2025 | Inference-Aware Fine-Tuning for Best-of-N Sampling in Large Language Models. Yinlam Chow, Guy Tennenholtz, Izzeddin Gur, Vincent Zhuang, Bo Dai, Aviral Kumar, Rishabh Agarwal, Sridhar Thiagarajan, Craig Boutilier, Aleksandra Faust |
| 2025 | Infilling Score: A Pretraining Data Detection Algorithm for Large Language Models. Negin Raoof, Litu Rout, Giannis Daras, Sujay Sanghavi, Constantine Caramanis, Sanjay Shakkottai, Alex Dimakis |
| 2025 | Infinite-Resolution Integral Noise Warping for Diffusion Models. Yitong Deng, Winnie Lin, Lingxiao Li, Dmitriy Smirnov, Ryan D. Burgert, Ning Yu, Vincent Dedun, Mohammad H. Taghavi |
| 2025 | Influence Functions for Scalable Data Attribution in Diffusion Models. Bruno Kacper Mlodozeniec, Runa Eschenhagen, Juhan Bae, Alexander Immer, David Krueger, Richard E. Turner |
| 2025 | Influence-Guided Diffusion for Dataset Distillation. Mingyang Chen, Jiawei Du, Bo Huang, Yi Wang, Xiaobo Zhang, Wei Wang |
| 2025 | InfoGS: Efficient Structure-Aware 3D Gaussians via Lightweight Information Shaping. Yunchao Zhang, Guandao Yang, Leonidas J. Guibas, Yanchao Yang |
| 2025 | Information Theoretic Text-to-Image Alignment. Chao Wang, Giulio Franzese, Alessandro Finamore, Massimo Gallo, Pietro Michiardi |
| 2025 | Injecting Universal Jailbreak Backdoors into LLMs in Minutes. Zhuowei Chen, Qiannan Zhang, Shichao Pei |
| 2025 | Injective flows for star-like manifolds. Marcello Massimo Negri, Jonathan Aellen, Volker Roth |
| 2025 | Inner Information Analysis Algorithm for Deep Neural Network based on Community. Guipeng Lan, Shuai Xiao, Meng Xi, Jiabao Wen, Jiachen Yang |
| 2025 | Innovative Thinking, Infinite Humor: Humor Research of Large Language Models through Structured Thought Leaps. Han Wang, Yilin Zhao, Dian Li, Xiaohan Wang, Sinbadliu, Xuguang Lan, Hui Wang |
| 2025 | Input Space Mode Connectivity in Deep Neural Networks. Jakub Vrábel, Ori Shem-Ur, Yaron Oz, David Krueger |
| 2025 | InsightBench: Evaluating Business Analytics Agents Through Multi-Step Insight Generation. Gaurav Sahu, Abhay Puri, Juan A. Rodríguez, Amirhossein Abaskohi, Mohammad Chegini, Alexandre Drouin, Perouz Taslakian, Valentina Zantedeschi, Alexandre Lacoste, David Vázquez, Nicolas Chapados, Christopher Pal, Sai Rajeswar, Issam H. Laradji |
| 2025 | Inspection and Control of Self-Generated-Text Recognition Ability in Llama3-8b-Instruct. Christopher Ackerman, Nina Panickssery |
| 2025 | InstaRevive: One-Step Image Enhancement via Dynamic Score Matching. Yixuan Zhu, Haolin Wang, Ao Li, Wenliang Zhao, Yansong Tang, Jingxuan Niu, Lei Chen, Jie Zhou, Jiwen Lu |
| 2025 | InstaSHAP: Interpretable Additive Models Explain Shapley Values Instantly. James Enouen, Yan Liu |
| 2025 | InstaTrain: Adaptive Training via Ultra-Fast Natural Annealing within Dynamical Systems. Chuan Liu, Ruibing Song, Chunshu Wu, Pouya Haghi, Tong Geng |
| 2025 | Instance-dependent Early Stopping. Suqin Yuan, Runqi Lin, Lei Feng, Bo Han, Tongliang Liu |
| 2025 | Instant Policy: In-Context Imitation Learning via Graph Diffusion. Vitalis Vosylius, Edward Johns |
| 2025 | InstantPortrait: One-Step Portrait Editing via Diffusion Multi-Objective Distillation. Zhixin Lai, Keqiang Sun, Fu-Yun Wang, Dhritiman Sagar, Erli Ding |
| 2025 | InstantSplamp: Fast and Generalizable Stenography Framework for Generative Gaussian Splatting. Chenxin Li, Hengyu Liu, Zhiwen Fan, Wuyang Li, Yifan Liu, Panwang Pan, Yixuan Yuan |
| 2025 | InstantSwap: Fast Customized Concept Swapping across Sharp Shape Differences. Chenyang Zhu, Kai Li, Yue Ma, Longxiang Tang, Chengyu Fang, Chubin Chen, Qifeng Chen, Xiu Li |
| 2025 | Instruct-SkillMix: A Powerful Pipeline for LLM Instruction Tuning. Simran Kaur, Simon Park, Anirudh Goyal, Sanjeev Arora |
| 2025 | InstructRAG: Instructing Retrieval-Augmented Generation via Self-Synthesized Rationales. Zhepei Wei, Wei-Lin Chen, Yu Meng |
| 2025 | Instructional Segment Embedding: Improving LLM Safety with Instruction Hierarchy. Tong Wu, Shujian Zhang, Kaiqiang Song, Silei Xu, Sanqiang Zhao, Ravi Agrawal, Sathish Reddy Indurthi, Chong Xiang, Prateek Mittal, Wenxuan Zhou |
| 2025 | Integral Performance Approximation for Continuous-Time Reinforcement Learning Control. Brent A. Wallace, Jennie Si |
| 2025 | Integrating Protein Dynamics into Structure-Based Drug Design via Full-Atom Stochastic Flows. Xiangxin Zhou, Yi Xiao, Haowei Lin, Xinheng He, Jiaqi Guan, Yang Wang, Qiang Liu, Feng Zhou, Liang Wang, Jianzhu Ma |
| 2025 | Integrative Decoding: Improving Factuality via Implicit Self-consistency. Yi Cheng, Xiao Liang, Yeyun Gong, Wen Xiao, Song Wang, Yuji Zhang, Wenjun Hou, Kaishuai Xu, Wenge Liu, Wenjie Li, Jian Jiao, Qi Chen, Peng Cheng, Wayne Xiong |
| 2025 | Intelligence at the Edge of Chaos. Shiyang Zhang, Aakash Patel, Syed Asad Rizvi, Nianchen Liu, Sizhuang He, Amin Karbasi, Emanuele Zappala, David van Dijk |
| 2025 | Intelligent Go-Explore: Standing on the Shoulders of Giant Foundation Models. Cong Lu, Shengran Hu, Jeff Clune |
| 2025 | Intent3D: 3D Object Detection in RGB-D Scans Based on Human Intention. Weitai Kang, Mengxue Qu, Jyoti Kini, Yunchao Wei, Mubarak Shah, Yan Yan |
| 2025 | InterLCM: Low-Quality Images as Intermediate States of Latent Consistency Models for Effective Blind Face Restoration. Senmao Li, Kai Wang, Joost van de Weijer, Fahad Shahbaz Khan, Chun-Le Guo, Shiqi Yang, Yaxing Wang, Jian Yang, Ming-Ming Cheng |
| 2025 | InterMask: 3D Human Interaction Generation via Collaborative Masked Modeling. Muhammad Gohar Javed, Chuan Guo, Li Cheng, Xingyu Li |
| 2025 | Interaction Asymmetry: A General Principle for Learning Composable Abstractions. Jack Brady, Julius von Kügelgen, Sébastien Lachapelle, Simon Buchholz, Thomas Kipf, Wieland Brendel |
| 2025 | Interactive Adjustment for Human Trajectory Prediction with Individual Feedback. Jianhua Sun, Yuxuan Li, Liang Chai, Cewu Lu |
| 2025 | Interactive Speculative Planning: Enhance Agent Efficiency through Co-design of System and User Interface. Wenyue Hua, Mengting Wan, Jagannath Shashank Subramanya Sai Vadrevu, Ryan Nadel, Yongfeng Zhang, Chi Wang |
| 2025 | Interference Among First-Price Pacing Equilibria: A Bias and Variance Analysis. Luofeng Liao, Christian Kroer, Sergei Leonenkov, Okke Schrijvers, Liang Shi, Nicolás Stier Moses, Congshan Zhang |
| 2025 | Interleaved Scene Graphs for Interleaved Text-and-Image Generation Assessment. Dongping Chen, Ruoxi Chen, Shu Pu, Zhaoyi Liu, Yanru Wu, Caixi Chen, Benlin Liu, Yue Huang, Yao Wan, Pan Zhou, Ranjay Krishna |
| 2025 | Intermediate Layer Classifiers for OOD generalization. Arnas Uselis, Seong Joon Oh |
| 2025 | Internet of Agents: Weaving a Web of Heterogeneous Agents for Collaborative Intelligence. Weize Chen, Ziming You, Ran Li, Yitong Guan, Chen Qian, Chenyang Zhao, Cheng Yang, Ruobing Xie, Zhiyuan Liu, Maosong Sun |
| 2025 | Interpretable Bilingual Multimodal Large Language Model for Diverse Biomedical Tasks. Lehan Wang, Haonan Wang, Honglong Yang, Jiaji Mao, Zehong Yang, Jun Shen, Xiaomeng Li |
| 2025 | Interpretable Causal Representation Learning for Biological Data in the Pathway Space. Jesus de la Fuente Cedeño, Robert Lehmann, Carlos Ruiz-Arenas, Jan Voges, Irene Marín-Goñi, Xabier Martinez de Morentin, David Gomez-Cabrero, Idoia Ochoa, Jesper Tegnér, Vincenzo Lagani, Mikel Hernaez |
| 2025 | Interpretable Unsupervised Joint Denoising and Enhancement for Real-World low-light Scenarios. Huaqiu Li, Xiaowan Hu, Haoqian Wang |
| 2025 | Interpretable Vision-Language Survival Analysis with Ordinal Inductive Bias for Computational Pathology. Pei Liu, Luping Ji, Jiaxiang Gou, Bo Fu, Mao Ye |
| 2025 | Interpreting Emergent Planning in Model-Free Reinforcement Learning. Thomas Bush, Stephen Chung, Usman Anwar, Adrià Garriga-Alonso, David Krueger |
| 2025 | Interpreting Language Reward Models via Contrastive Explanations. Junqi Jiang, Tom Bewley, Saumitra Mishra, Freddy Lécué, Manuela Veloso |
| 2025 | Interpreting and Editing Vision-Language Representations to Mitigate Hallucinations. Nick Jiang, Anish Kachinthaya, Suzanne Petryk, Yossi Gandelsman |
| 2025 | Interpreting the Second-Order Effects of Neurons in CLIP. Yossi Gandelsman, Alexei A. Efros, Jacob Steinhardt |
| 2025 | IntersectionZoo: Eco-driving for Benchmarking Multi-Agent Contextual Reinforcement Learning. Vindula Jayawardana, Baptiste Freydt, Ao Qu, Cameron Hickert, Zhongxia Yan, Cathy Wu |
| 2025 | Intervening Anchor Token: Decoding Strategy in Alleviating Hallucinations for MLLMs. Feilong Tang, Zile Huang, Chengzhi Liu, Qiang Sun, Harry Yang, Ser-Nam Lim |
| 2025 | Intrinsic Dimension Correlation: uncovering nonlinear connections in multimodal representations. Lorenzo Basile, Santiago Acevedo, Luca Bortolussi, Fabio Anselmi, Alex Rodriguez |
| 2025 | Intrinsic User-Centric Interpretability through Global Mixture of Experts. Vinitra Swamy, Syrielle Montariol, Julian Blackwell, Jibril Frej, Martin Jaggi, Tanja Käser |
| 2025 | Inverse Attention Agents for Multi-Agent Systems. Qian Long, Ruoyan Li, Minglu Zhao, Tao Gao, Demetri Terzopoulos |
| 2025 | Inverse Constitutional AI: Compressing Preferences into Principles. Arduin Findeis, Timo Kaufmann, Eyke Hüllermeier, Samuel Albanie, Robert Mullins |
| 2025 | Inverse Rendering using Multi-Bounce Path Tracing and Reservoir Sampling. Yuxin Dai, Qi Wang, Jingsen Zhu, Dianbing Xi, Yuchi Huo, Chen Qian, Ying He |
| 2025 | Inverse decision-making using neural amortized Bayesian actors. Dominik Straub, Tobias F. Niehues, Jan Peters, Constantin A. Rothkopf |
| 2025 | InverseBench: Benchmarking Plug-and-Play Diffusion Priors for Inverse Problems in Physical Sciences. Hongkai Zheng, Wenda Chu, Bingliang Zhang, Zihui Wu, Austin Wang, Berthy Feng, Caifeng Zou, Yu Sun, Nikola Borislavov Kovachki, Zachary E. Ross, Katherine L. Bouman, Yisong Yue |
| 2025 | InversionGNN: A Dual Path Network for Multi-Property Molecular Optimization. Yifan Niu, Ziqi Gao, Tingyang Xu, Yang Liu, Yatao Bian, Yu Rong, Junzhou Huang, Jia Li |
| 2025 | InvestESG: A multi-agent reinforcement learning benchmark for studying climate investment as a social dilemma. Xiaoxuan Hou, Jiayi Yuan, Joel Z. Leibo, Natasha Jaques |
| 2025 | Investigating Pattern Neurons in Urban Time Series Forecasting. Chengxin Wang, Yiran Zhao, Shaofeng Cai, Gary Tan |
| 2025 | Investigating the Pre-Training Dynamics of In-Context Learning: Task Recognition vs. Task Learning. Xiaolei Wang, Xinyu Tang, Junyi Li, Xin Zhao, Ji-Rong Wen |
| 2025 | Is Factuality Enhancement a Free Lunch For LLMs? Better Factuality Can Lead to Worse Context-Faithfulness. Baolong Bi, Shenghua Liu, Yiwei Wang, Lingrui Mei, Junfeng Fang, Hongcheng Gao, Shiyu Ni, Xueqi Cheng |
| 2025 | Is In-Context Learning Sufficient for Instruction Following in LLMs? Hao Zhao, Maksym Andriushchenko, Francesco Croce, Nicolas Flammarion |
| 2025 | Is Large-scale Pretraining the Secret to Good Domain Generalization? Piotr Teterwak, Kuniaki Saito, Theodoros Tsiligkaridis, Bryan A. Plummer, Kate Saenko |
| 2025 | Is Your Model Really A Good Math Reasoner? Evaluating Mathematical Reasoning with Checklist. Zihao Zhou, Shudong Liu, Maizhen Ning, Wei Liu, Jindong Wang, Derek F. Wong, Xiaowei Huang, Qiufeng Wang, Kaizhu Huang |
| 2025 | Is Your Multimodal Language Model Oversensitive to Safe Queries? Xirui Li, Hengguang Zhou, Ruochen Wang, Tianyi Zhou, Minhao Cheng, Cho-Jui Hsieh |
| 2025 | Is Your Video Language Model a Reliable Judge? Ming Liu, Wensheng Zhang |
| 2025 | Is uniform expressivity too restrictive? Towards efficient expressivity of GNNs. Sammy Khalife, Josué Tonelli-Cueto |
| 2025 | Isometric Regularization for Manifolds of Functional Data. Hyeongjun Heo, Seonghun Oh, Jae Yong Lee, Young Min Kim, Yonghyeon Lee |
| 2025 | It Helps to Take a Second Opinion: Teaching Smaller LLMs To Deliberate Mutually via Selective Rationale Optimisation. Sohan Patnaik, Milan Aggarwal, Sumit Bhatia, Balaji Krishnamurthy |
| 2025 | IterComp: Iterative Composition-Aware Feedback Learning from Model Gallery for Text-to-Image Generation. Xinchen Zhang, Ling Yang, Guohao Li, Yaqi Cai, Jiake Xie, Yong Tang, Yujiu Yang, Mengdi Wang, Bin Cui |
| 2025 | IterGen: Iterative Semantic-aware Structured LLM Generation with Backtracking. Shubham Ugare, Rohan Gumaste, Tarun Suresh, Gagandeep Singh, Sasa Misailovic |
| 2025 | Iterative Label Refinement Matters More than Preference Optimization under Weak Supervision. Yaowen Ye, Cassidy Laidlaw, Jacob Steinhardt |
| 2025 | Iterative Nash Policy Optimization: Aligning LLMs with General Preferences via No-Regret Learning. Yuheng Zhang, Dian Yu, Baolin Peng, Linfeng Song, Ye Tian, Mingyue Huo, Nan Jiang, Haitao Mi, Dong Yu |
| 2025 | Iterative Substructure Extraction for Molecular Relational Learning with Interactive Graph Information Bottleneck. Shuai Zhang, Junfeng Fang, Xuqiang Li, Hongxin Xiang, Alan Xia, Ye Wei, Wenjie Du, Yang Wang |
| 2025 | JPEG Inspired Deep Learning. Ahmed H. Salamah, Kaixiang Zheng, Yiwen Liu, En-Hui Yang |
| 2025 | Jailbreak Antidote: Runtime Safety-Utility Balance via Sparse Representation Adjustment in Large Language Models. Guobin Shen, Dongcheng Zhao, Yiting Dong, Xiang He, Yi Zeng |
| 2025 | Jailbreaking Leading Safety-Aligned LLMs with Simple Adaptive Attacks. Maksym Andriushchenko, Francesco Croce, Nicolas Flammarion |
| 2025 | Jailbreaking as a Reward Misspecification Problem. Zhihui Xie, Jiahui Gao, Lei Li, Zhenguo Li, Qi Liu, Lingpeng Kong |
| 2025 | Jamba: Hybrid Transformer-Mamba Language Models. Barak Lenz, Opher Lieber, Alan Arazi, Amir Bergman, Avshalom Manevich, Barak Peleg, Ben Aviram, Chen Almagor, Clara Fridman, Dan Padnos, Daniel Gissin, Daniel Jannai, Dor Muhlgay, Dor Zimberg, Edden M. Gerber, Elad Dolev, Eran Krakovsky, Erez Safahi, Erez Schwartz, Gal Cohen, et al. |
| 2025 | JetFormer: An autoregressive generative model of raw images and text. Michael Tschannen, André Susano Pinto, Alexander Kolesnikov |
| 2025 | Joint Fine-tuning and Conversion of Pretrained Speech and Language Models towards Linear Complexity. Mutian He, Philip N. Garner |
| 2025 | Joint Gradient Balancing for Data Ordering in Finite-Sum Multi-Objective Optimization. Hansi Yang, James T. Kwok |
| 2025 | Joint Graph Rewiring and Feature Denoising via Spectral Resonance. Jonas Linkerhägner, Cheng Shi, Ivan Dokmanic |
| 2025 | Joint Reward and Policy Learning with Demonstrations and Human Feedback Improves Alignment. Chenliang Li, Siliang Zeng, Zeyi Liao, Jiaxiang Li, Dongyeop Kang, Alfredo García, Mingyi Hong |
| 2025 | Judge Decoding: Faster Speculative Sampling Requires Going Beyond Model Alignment. Gregor Bachmann, Sotiris Anagnostidis, Albert Pumarola, Markos Georgopoulos, Artsiom Sanakoyeu, Yuming Du, Edgar Schönfeld, Ali K. Thabet, Jonas Kohler |
| 2025 | JudgeBench: A Benchmark for Evaluating LLM-Based Judges. Sijun Tan, Siyuan Zhuang, Kyle Montgomery, William Yuan Tang, Alejandro Cuadron, Chenguang Wang, Raluca A. Popa, Ion Stoica |
| 2025 | JudgeLM: Fine-tuned Large Language Models are Scalable Judges. Lianghui Zhu, Xinggang Wang, Xinlong Wang |
| 2025 | Jump Your Steps: Optimizing Sampling Schedule of Discrete Diffusion Models. Yong-Hyun Park, Chieh-Hsin Lai, Satoshi Hayakawa, Yuhta Takida, Yuki Mitsufuji |
| 2025 | Justice or Prejudice? Quantifying Biases in LLM-as-a-Judge. Jiayi Ye, Yanbo Wang, Yue Huang, Dongping Chen, Qihui Zhang, Nuno Moniz, Tian Gao, Werner Geyer, Chao Huang, Pin-Yu Chen, Nitesh V. Chawla, Xiangliang Zhang |
| 2025 | K-HALU: Multiple Answer Korean Hallucination Benchmark for Large Language Models. Jaehyung Seo, Heuiseok Lim |
| 2025 | KAA: Kolmogorov-Arnold Attention for Enhancing Attentive Graph Neural Networks. Taoran Fang, Tianhong Gao, Chunping Wang, Yihao Shang, Wei Chow, Lei Chen, Yang Yang |
| 2025 | KAN: Kolmogorov-Arnold Networks. Ziming Liu, Yixuan Wang, Sachin Vaidya, Fabian Ruehle, James Halverson, Marin Soljacic, Thomas Y. Hou, Max Tegmark |
| 2025 | KBLaM: Knowledge Base augmented Language Model. Xi Wang, Taketomo Isazawa, Liana Mikaelyan, James Hensman |
| 2025 | KGARevion: An AI Agent for Knowledge-Intensive Biomedical QA. Xiaorui Su, Yibo Wang, Shanghua Gao, Xiaolong Liu, Valentina Giunchiglia, Djork-Arné Clevert, Marinka Zitnik |
| 2025 | KLay: Accelerating Arithmetic Circuits for Neurosymbolic AI. Jaron Maene, Vincent Derkinderen, Pedro Zuidberg Dos Martires |
| 2025 | KOR-Bench: Benchmarking Language Models on Knowledge-Orthogonal Reasoning Tasks. Kaijing Ma, Xeron Du, Yunran Wang, Haoran Zhang, Zhoufutu Wen, Xingwei Qu, Jian Yang, Jiaheng Liu, Minghao Liu, Xiang Yue, Wenhao Huang, Ge Zhang |
| 2025 | KaSA: Knowledge-Aware Singular-Value Adaptation of Large Language Models. Fan Wang, Juyong Jiang, Chansung Park, Sunghun Kim, Jing Tang |
| 2025 | Kernel-based Optimally Weighted Conformal Time-Series Prediction. Jonghyeok Lee, Chen Xu, Yao Xie |
| 2025 | KiVA: Kid-inspired Visual Analogies for Testing Large Multimodal Models. Eunice Yiu, Maan Qraitem, Anisa Noor Majhi, Charlie Wong, Yutong Bai, Shiry Ginosar, Alison Gopnik, Kate Saenko |
| 2025 | KinFormer: Generalizable Dynamical Symbolic Regression for Catalytic Organic Reaction Kinetics. Jindou Chen, Jidong Tian, Liang Wu, ChenXinWei, Xiaokang Yang, Yaohui Jin, Yanyan Xu |
| 2025 | KinPFN: Bayesian Approximation of RNA Folding Kinetics using Prior-Data Fitted Networks. Dominik Scheuer, Frederic Runge, Jörg K. H. Franke, Michael T. Wolfinger, Christoph Flamm, Frank Hutter |
| 2025 | Kinetix: Investigating the Training of General Agents through Open-Ended Physics-Based Control Tasks. Michael T. Matthews, Michael Beukman, Chris Lu, Jakob Nicolaus Foerster |
| 2025 | Knowing Your Target: Target-Aware Transformer Makes Better Spatio-Temporal Video Grounding. Xin Gu, Yaojie Shen, Chenxi Luo, Tiejian Luo, Yan Huang, Yuewei Lin, Heng Fan, Libo Zhang |
| 2025 | Knowledge Distillation with Multi-granularity Mixture of Priors for Image Super-Resolution. Simiao Li, Yun Zhang, Wei Li, Hanting Chen, Wenjia Wang, Bingyi Jing, Shaohui Lin, Jie Hu |
| 2025 | Knowledge Entropy Decay during Language Model Pretraining Hinders New Knowledge Acquisition. Jiyeon Kim, Hyunji Lee, Hyowon Cho, Joel Jang, Hyeonbin Hwang, Seungpil Won, Youbin Ahn, Dohaeng Lee, Minjoon Seo |
| 2025 | Knowledge Graph Finetuning Enhances Knowledge Manipulation in Large Language Models. Hanzhu Chen, Xu Shen, Jie Wang, Zehao Wang, Qitan Lv, Junjie He, Rong Wu, Feng Wu, Jieping Ye |
| 2025 | Knowledge Localization: Mission Not Accomplished? Enter Query Localization! Yuheng Chen, Pengfei Cao, Yubo Chen, Kang Liu, Jun Zhao |
| 2025 | Kolmogorov-Arnold Transformer. Xingyi Yang, Xinchao Wang |
| 2025 | KooNPro: A Variance-Aware Koopman Probabilistic Model Enhanced by Neural Process for Time Series Forecasting. Ronghua Zheng, Hanru Bai, Weiyang Ding |
| 2025 | Kronecker Mask and Interpretive Prompts are Language-Action Video Learners. Jingyi Yang, Zitong Yu, Xiuming Ni, Jia He, Hui Li |
| 2025 | L-WISE: Boosting Human Visual Category Learning Through Model-Based Image Selection and Enhancement. Morgan Bruce Talbot, Gabriel Kreiman, James J. DiCarlo, Guy Gaziv |
| 2025 | L3Ms - Lagrange Large Language Models. Guneet S. Dhillon, Xingjian Shi, Yee Whye Teh, Alex Smola |
| 2025 | LANTERN: Accelerating Visual Autoregressive Models with Relaxed Speculative Decoding. Doohyuk Jang, Sihwan Park, June Yong Yang, Yeonsung Jung, Jihun Yun, Souvik Kundu, Sungyub Kim, Eunho Yang |
| 2025 | LARP: Tokenizing Videos with a Learned Autoregressive Generative Prior. Hanyu Wang, Saksham Suri, Yixuan Ren, Hao Chen, Abhinav Shrivastava |
| 2025 | LASER: A Neuro-Symbolic Framework for Learning Spatio-Temporal Scene Graphs with Weak Supervision. Jiani Huang, Ziyang Li, Mayur Naik, Ser-Nam Lim |
| 2025 | LASeR: Towards Diversified and Generalizable Robot Design with Large Language Models. Junru Song, Yang Yang, Huan Xiao, Wei Peng, Wen Yao, Feifei Wang |
| 2025 | LDAdam: Adaptive Optimization from Low-Dimensional Gradient Statistics. Thomas Robert, Mher Safaryan, Ionut-Vlad Modoranu, Dan Alistarh |
| 2025 | LICO: Large Language Models for In-Context Molecular Optimization. Tung Nguyen, Aditya Grover |
| 2025 | LICORICE: Label-Efficient Concept-Based Interpretable Reinforcement Learning. Zhuorui Ye, Stephanie Milani, Geoffrey J. Gordon, Fei Fang |
| 2025 | LIFe-GoM: Generalizable Human Rendering with Learned Iterative Feedback Over Multi-Resolution Gaussians-on-Mesh. Jing Wen, Alexander G. Schwing, Shenlong Wang |
| 2025 | LLM Unlearning via Loss Adjustment with Only Forget Data. Yaxuan Wang, Jiaheng Wei, Chris Yuhao Liu, Jinlong Pang, Quan Liu, Ankit Shah, Yujia Bao, Yang Liu, Wei Wei |
| 2025 | LLM-SR: Scientific Equation Discovery via Programming with Large Language Models. Parshin Shojaee, Kazem Meidani, Shashank Gupta, Amir Barati Farimani, Chandan K. Reddy |
| 2025 | LLM-based Typed Hyperresolution for Commonsense Reasoning with Knowledge Bases. Armin Toroghi, Ali Pesaranghader, Tanmana Sadhu, Scott Sanner |
| 2025 | LLM-wrapper: Black-Box Semantic-Aware Adaptation of Vision-Language Models for Referring Expression Comprehension. Amaia Cardiel, Eloi Zablocki, Elias Ramzi, Oriane Siméoni, Matthieu Cord |
| 2025 | LLMOPT: Learning to Define and Solve General Optimization Problems from Scratch. Caigao Jiang, Xiang Shu, Hong Qian, Xingyu Lu, Jun Zhou, Aimin Zhou, Yang Yu |
| 2025 | LLMs Can Plan Only If We Tell Them. Bilgehan Sel, Ruoxi Jia, Ming Jin |
| 2025 | LLMs Know More Than They Show: On the Intrinsic Representation of LLM Hallucinations. Hadas Orgad, Michael Toker, Zorik Gekhman, Roi Reichart, Idan Szpektor, Hadas Kotek, Yonatan Belinkov |
| 2025 | LLaMA-Omni: Seamless Speech Interaction with Large Language Models. Qingkai Fang, Shoutao Guo, Yan Zhou, Zhengrui Ma, Shaolei Zhang, Yang Feng |
| 2025 | LLaMaFlex: Many-in-one LLMs via Generalized Pruning and Weight Sharing. Ruisi Cai, Saurav Muralidharan, Hongxu Yin, Zhangyang Wang, Jan Kautz, Pavlo Molchanov |
| 2025 | LLaRA: Supercharging Robot Learning Data for Vision-Language Policy. Xiang Li, Cristina Mata, Jongwoo Park, Kumara Kahatapitiya, Yoo Sung Jang, Jinghuan Shang, Kanchana Ranasinghe, Ryan D. Burgert, Mu Cai, Yong Jae Lee, Michael S. Ryoo |
| 2025 | LLaVA-Interleave: Tackling Multi-image, Video, and 3D in Large Multimodal Models. Feng Li, Renrui Zhang, Hao Zhang, Yuanhan Zhang, Bo Li, Wei Li, Zejun Ma, Chunyuan Li |
| 2025 | LLaVA-Mini: Efficient Image and Video Large Multimodal Models with One Vision Token. Shaolei Zhang, Qingkai Fang, Zhe Yang, Yang Feng |
| 2025 | LLaVA-MoD: Making LLaVA Tiny via MoE-Knowledge Distillation. Fangxun Shu, Yue Liao, Lei Zhang, Le Zhuo, Chenning Xu, Guanghao Zhang, Haonan Shi, Long Chan, Tao Zhong, Zhelun Yu, Wanggui He, Siming Fu, Haoyuan Li, Si Liu, Hongsheng Li, Hao Jiang |
| 2025 | LOIRE: LifelOng learning on Incremental data via pre-trained language model gRowth Efficiently. Xue Han, Yitong Wang, Junlan Feng, Wenchun Gao, Qian Hu, Chao Deng |
| 2025 | LOKI: A Comprehensive Synthetic Data Detection Benchmark using Large Multimodal Models. Junyan Ye, Baichuan Zhou, Zilong Huang, Junan Zhang, Tianyi Bai, Hengrui Kang, Jun He, Honglin Lin, Zihao Wang, Tong Wu, Zhizheng Wu, Yiping Chen, Dahua Lin, Conghui He, Weijia Li |
| 2025 | LVSM: A Large View Synthesis Model with Minimal 3D Inductive Bias. Haian Jin, Hanwen Jiang, Hao Tan, Kai Zhang, Sai Bi, Tianyuan Zhang, Fujun Luan, Noah Snavely, Zexiang Xu |
| 2025 | LaGeM: A Large Geometry Model for 3D Representation Learning and Diffusion. Biao Zhang, Peter Wonka |
| 2025 | LaMP: Language-Motion Pretraining for Motion Generation, Retrieval, and Captioning. Zhe Li, Weihao Yuan, Yisheng He, Lingteng Qiu, Shenhao Zhu, Xiaodong Gu, Weichao Shen, Yuan Dong, Zilong Dong, Laurence Tianruo Yang |
| 2025 | LaMPlace: Learning to Optimize Cross-Stage Metrics in Macro Placement. Zijie Geng, Jie Wang, Ziyan Liu, Siyuan Xu, Zhentao Tang, Shixiong Kai, Mingxuan Yuan, Jianye Hao, Feng Wu |
| 2025 | Lambda-Skip Connections: the architectural component that prevents Rank Collapse. Federico Arangath Joseph, Jerome Sieber, Melanie Nicole Zeilinger, Carmen Amo Alonso |
| 2025 | LancBiO: Dynamic Lanczos-aided Bilevel Optimization via Krylov Subspace. Yan Yang, Bin Gao, Ya-Xiang Yuan |
| 2025 | Langevin Soft Actor-Critic: Efficient Exploration through Uncertainty-Driven Critic Learning. Haque Ishfaq, Guangyuan Wang, Sami Nur Islam, Doina Precup |
| 2025 | Language Agents Meet Causality - Bridging LLMs and Causal World Models. John Gkountouras, Matthias Lindemann, Phillip Lippe, Efstratios Gavves, Ivan Titov |
| 2025 | Language Guided Skill Discovery. Seungeun Rho, Laura Smith, Tianyu Li, Sergey Levine, Xue Bin Peng, Sehoon Ha |
| 2025 | Language Imbalance Driven Rewarding for Multilingual Self-improving. Wen Yang, Junhong Wu, Chen Wang, Chengqing Zong, Jiajun Zhang |
| 2025 | Language Model Alignment in Multilingual Trolley Problems. Zhijing Jin, Max Kleiman-Weiner, Giorgio Piatti, Sydney Levine, Jiarui Liu, Fernando Gonzalez Adauto, Francesco Ortu, András Strausz, Mrinmaya Sachan, Rada Mihalcea, Yejin Choi, Bernhard Schölkopf |
| 2025 | Language Models Are Implicitly Continuous. Samuele Marro, Davide Evangelista, X. Angelo Huang, Emanuele La Malfa, Michele Lombardi, Michael J. Wooldridge |
| 2025 | Language Models Learn to Mislead Humans via RLHF. Jiaxin Wen, Ruiqi Zhong, Akbir Khan, Ethan Perez, Jacob Steinhardt, Minlie Huang, Samuel R. Bowman, He He, Shi Feng |
| 2025 | Language Models Need Inductive Biases to Count Inductively. Yingshan Chang, Yonatan Bisk |
| 2025 | Language Models Trained to do Arithmetic Predict Human Risky and Intertemporal Choice. Jian-Qiao Zhu, Haijiang Yan, Thomas L. Griffiths |
| 2025 | Language Models are Advanced Anonymizers. Robin Staab, Mark Vero, Mislav Balunovic, Martin T. Vechev |
| 2025 | Language Representations Can be What Recommenders Need: Findings and Potentials. Leheng Sheng, An Zhang, Yi Zhang, Yuxin Chen, Xiang Wang, Tat-Seng Chua |
| 2025 | Language models scale reliably with over-training and on downstream tasks. Samir Yitzhak Gadre, Georgios Smyrnis, Vaishaal Shankar, Suchin Gururangan, Mitchell Wortsman, Rulin Shao, Jean Mercat, Alex Fang, Jeffrey Li, Sedrick Keh, Rui Xin, Marianna Nezhurina, Igor Vasiljevic, Luca Soldaini, Jenia Jitsev, Alex Dimakis, Gabriel Ilharco, Pang Wei Koh, Shuran Song, Thomas Kollar, et al. |
| 2025 | Language-Assisted Feature Transformation for Anomaly Detection. EungGu Yun, Heonjin Ha, Yeongwoo Nam, Bryan Dongik Lee |
| 2025 | Language-Image Models with 3D Understanding. Jang Hyun Cho, Boris Ivanovic, Yulong Cao, Edward Schmerling, Yue Wang, Xinshuo Weng, Boyi Li, Yurong You, Philipp Krähenbühl, Yan Wang, Marco Pavone |
| 2025 | Laplace Sample Information: Data Informativeness Through a Bayesian Lens. Johannes Kaiser, Kristian Schwethelm, Daniel Rueckert, Georgios Kaissis |
| 2025 | Large (Vision) Language Models are Unsupervised In-Context Learners. Artyom Gadetsky, Andrei Atanov, Yulun Jiang, Zhitong Gao, Ghazal Hosseini Mighan, Amir Zamir, Maria Brbic |
| 2025 | Large Convolutional Model Tuning via Filter Subspace. Wei Chen, Zichen Miao, Qiang Qiu |
| 2025 | Large Language Models Assume People are More Rational than We Really are. Ryan Liu, Jiayi Geng, Joshua C. Peterson, Ilia Sucholutsky, Thomas L. Griffiths |
| 2025 | Large Language Models Meet Symbolic Provers for Logical Reasoning Evaluation. Chengwen Qi, Ren Ma, Bowen Li, He Du, Binyuan Hui, Jinwang Wu, Yuanjun Laili, Conghui He |
| 2025 | Large Language Models Often Say One Thing and Do Another. Ruoxi Xu, Hongyu Lin, Xianpei Han, Jia Zheng, Weixiang Zhou, Le Sun, Yingfei Sun |
| 2025 | Large Language Models are Interpretable Learners. Ruochen Wang, Si Si, Felix X. Yu, Dorothea Wiesmann Rothuizen, Cho-Jui Hsieh, Inderjit S. Dhillon |
| 2025 | Large Language Models can Become Strong Self-Detoxifiers. Ching-Yun Ko, Pin-Yu Chen, Payel Das, Youssef Mroueh, Soham Dan, Georgios Kollias, Subhajit Chaudhury, Tejaswini Pedapati, Luca Daniel |
| 2025 | Large Scale Knowledge Washing. Yu Wang, Ruihan Wu, Zexue He, Xiusi Chen, Julian J. McAuley |
| 2025 | Large-scale and Fine-grained Vision-language Pre-training for Enhanced CT Image Understanding. Zhongyi Shui, Jianpeng Zhang, Weiwei Cao, Sinuo Wang, Ruizhe Guo, Le Lu, Lin Yang, Xianghua Ye, Tingbo Liang, Qi Zhang, Ling Zhang |
| 2025 | Lasso Bandit with Compatibility Condition on Optimal Arm. Harin Lee, Taehyun Hwang, Min-hwan Oh |
| 2025 | Last Iterate Convergence of Incremental Methods as a Model of Forgetting. Xufeng Cai, Jelena Diakonikolas |
| 2025 | Last-Iterate Convergence Properties of Regret-Matching Algorithms in Games. Yang Cai, Gabriele Farina, Julien Grand-Clément, Christian Kroer, Chung-wei Lee, Haipeng Luo, Weiqiang Zheng |
| 2025 | Latent Action Pretraining from Videos. Seonghyeon Ye, Joel Jang, Byeongguk Jeon, Se June Joo, Jianwei Yang, Baolin Peng, Ajay Mandlekar, Reuben Tan, Yu-Wei Chao, Bill Yuchen Lin, Lars Liden, Kimin Lee, Jianfeng Gao, Luke Zettlemoyer, Dieter Fox, Minjoon Seo |
| 2025 | Latent Bayesian Optimization via Autoregressive Normalizing Flows. Seunghun Lee, Jinyoung Park, Jaewon Chu, Minseo Yoon, Hyunwoo J. Kim |
| 2025 | Latent Radiance Fields with 3D-aware 2D Representations. Chaoyi Zhou, Xi Liu, Feng Luo, Siyu Huang |
| 2025 | Latent Safety-Constrained Policy Approach for Safe Offline Reinforcement Learning. Prajwal Koirala, Zhanhong Jiang, Soumik Sarkar, Cody H. Fleming |
| 2025 | Latent Space Chain-of-Embedding Enables Output-free LLM Self-Evaluation. Yiming Wang, Pei Zhang, Baosong Yang, Derek F. Wong, Rui Wang |
| 2025 | Latent-EnSF: A Latent Ensemble Score Filter for High-Dimensional Data Assimilation with Sparse Observation Data. Phillip Si, Peng Chen |
| 2025 | Law of the Weakest Link: Cross Capabilities of Large Language Models. Ming Zhong, Aston Zhang, Xuewei Wang, Rui Hou, Wenhan Xiong, Chenguang Zhu, Zhengxing Chen, Liang Tan, Chloe Bi, Mike Lewis, Sravya Popuri, Sharan Narang, Melanie Kambadur, Dhruv Mahajan, Sergey Edunov, Jiawei Han, Laurens van der Maaten |
| 2025 | Lawma: The Power of Specialization for Legal Annotation. Ricardo Dominguez-Olmedo, Vedant Nanda, Rediet Abebe, Stefan Bechtold, Christoph Engel, Jens Frankenreiter, Krishna P. Gummadi, Moritz Hardt, Michael Livermore |
| 2025 | Layer Swapping for Zero-Shot Cross-Lingual Transfer in Large Language Models. Lucas Bandarkar, Benjamin Muller, Pritish Yuvraj, Rui Hou, Nayan Singhal, Hongjiang Lv, Bing Liu |
| 2025 | LayerDAG: A Layerwise Autoregressive Diffusion Model for Directed Acyclic Graph Generation. Mufei Li, Viraj Shitole, Eli Chien, Changhai Man, Zhaodong Wang, Srinivas, Ying Zhang, Tushar Krishna, Pan Li |
| 2025 | Layerwise Recurrent Router for Mixture-of-Experts. Zihan Qiu, Zeyu Huang, Shuang Cheng, Yizhi Zhou, Zili Wang, Ivan Titov, Jie Fu |
| 2025 | Layout-your-3D: Controllable and Precise 3D Generation with 2D Blueprint. Junwei Zhou, Xueting Li, Lu Qi, Ming-Hsuan Yang |
| 2025 | LeFusion: Controllable Pathology Synthesis via Lesion-Focused Diffusion Models. Hantao Zhang, Yuhe Liu, Jiancheng Yang, Shouhong Wan, Xinyuan Wang, Wei Peng, Pascal Fua |
| 2025 | Lean-STaR: Learning to Interleave Thinking and Proving. Haohan Lin, Zhiqing Sun, Sean Welleck, Yiming Yang |
| 2025 | LeanAgent: Lifelong Learning for Formal Theorem Proving. Adarsh Kumarappan, Mo Tiwari, Peiyang Song, Robert Joseph George, Chaowei Xiao, Anima Anandkumar |
| 2025 | LeanQuant: Accurate and Scalable Large Language Model Quantization with Loss-error-aware Grid. Tianyi Zhang, Anshumali Shrivastava |
| 2025 | Learn Your Reference Model for Real Good Alignment. Alexey Gorbatovski, Boris Shaposhnikov, Alexey Malakhov, Nikita Surnachev, Yaroslav Aksenov, Ian Maksimov, Nikita Balagansky, Daniil Gavrilov |
| 2025 | Learn hybrid prototypes for multivariate time series anomaly detection. Ke-Yuan Shen |
| 2025 | Learn-by-interact: A Data-Centric Framework For Self-Adaptive Agents in Realistic Environments. Hongjin Su, Ruoxi Sun, Jinsung Yoon, Pengcheng Yin, Tao Yu, Sercan Ö. Arik |
| 2025 | Learnable Expansion of Graph Operators for Multi-Modal Feature Fusion. Dexuan Ding, Lei Wang, Liyun Zhu, Tom Gedeon, Piotr Koniusz |
| 2025 | Learned Reference-based Diffusion Sampler for multi-modal distributions. Maxence Noble, Louis Grenioux, Marylou Gabrié, Alain Oliviero Durmus |
| 2025 | Learning 3D Perception from Others' Predictions. Jinsu Yoo, Zhenyang Feng, Tai-Yu Pan, Yihong Sun, Cheng Perng Phoo, Xiangyu Chen, Mark E. Campbell, Kilian Q. Weinberger, Bharath Hariharan, Wei-Lun Chao |
| 2025 | Learning Causal Alignment for Reliable Disease Diagnosis. Mingzhou Liu, Ching-Wen Lee, Xinwei Sun, Xueqing Yu, Yu Qiao, Yizhou Wang |
| 2025 | Learning Chaos In A Linear Way. Xiaoyuan Cheng, Yi He, Yiming Yang, Xiao Xue, Sibo Cheng, Daniel Giles, Xiaohang Tang, Yukun Hu |
| 2025 | Learning Clustering-based Prototypes for Compositional Zero-Shot Learning. Hongyu Qu, Jianan Wei, Xiangbo Shu, Wenguan Wang |
| 2025 | Learning Color Equivariant Representations. Yulong Yang, Felix O'Mahony, Christine Allen-Blanchette |
| 2025 | Learning Continually by Spectral Regularization. Alex Lewandowski, Michal Bortkiewicz, Saurabh Kumar, András György, Dale Schuurmans, Mateusz Ostaszewski, Marlos C. Machado |
| 2025 | Learning Diagrams: A Graphical Language for Compositional Training Regimes. Mason Lary, Richard Samuelson, Alexander Wilentz, Alina Zare, Matthew Klawonn, James P. Fairbanks |
| 2025 | Learning Distributions of Complex Fluid Simulations with Diffusion Graph Networks. Mario Lino Valencia, Tobias Pfaff, Nils Thuerey |
| 2025 | Learning Diverse Attacks on Large Language Models for Robust Red-Teaming and Safety Tuning. Seanie Lee, Minsu Kim, Lynn Cherif, David Dobre, Juho Lee, Sung Ju Hwang, Kenji Kawaguchi, Gauthier Gidel, Yoshua Bengio, Nikolay Malkin, Moksh Jain |
| 2025 | Learning Dynamics of Deep Matrix Factorization Beyond the Edge of Stability. Avrajit Ghosh, Soo Min Kwon, Rongrong Wang, Saiprasad Ravishankar, Qing Qu |
| 2025 | Learning Dynamics of LLM Finetuning. Yi Ren, Danica J. Sutherland |
| 2025 | Learning Efficient Positional Encodings with Graph Neural Networks. Charilaos I. Kanatsoulis, Evelyn Choi, Stefanie Jegelka, Jure Leskovec, Alejandro Ribeiro |
| 2025 | Learning Equivariant Non-Local Electron Density Functionals. Nicholas Gao, Eike Eberhard, Stephan Günnemann |
| 2025 | Learning Evolving Tools for Large Language Models. Guoxin Chen, Zhong Zhang, Xin Cong, Fangda Guo, Yesai Wu, Yankai Lin, Wenzheng Feng, Yasheng Wang |
| 2025 | Learning Fine-Grained Representations through Textual Token Disentanglement in Composed Video Retrieval. Yue Wu, Zhaobo Qi, Yiling Wu, Junshu Sun, Yaowei Wang, Shuhui Wang |
| 2025 | Learning Gain Map for Inverse Tone Mapping. Yinuo Liao, Yuanshen Guan, Ruikang Xu, Jiacheng Li, Shida Sun, Zhiwei Xiong |
| 2025 | Learning General-purpose Biomedical Volume Representations using Randomized Synthesis. Neel Dey, Benjamin Billot, Hallee E. Wong, Clinton J. Wang, Mengwei Ren, Ellen Grant, Adrian V. Dalca, Polina Golland |
| 2025 | Learning Generalizable Skills from Offline Multi-Task Data for Multi-Agent Cooperation. Sicong Liu, Yang Shu, Chenjuan Guo, Bin Yang |
| 2025 | Learning Geometric Reasoning Networks For Robot Task And Motion Planning. Smail Ait Bouhsain, Rachid Alami, Thierry Siméon |
| 2025 | Learning Graph Invariance by Harnessing Spuriosity. Tianjun Yao, Yongqiang Chen, Kai Hu, Tongliang Liu, Kun Zhang, Zhiqiang Shen |
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| 2025 | Learning Hierarchical Polynomials of Multiple Nonlinear Features. Hengyu Fu, Zihao Wang, Eshaan Nichani, Jason D. Lee |
| 2025 | Learning High-Degree Parities: The Crucial Role of the Initialization. Emmanuel Abbe, Elisabetta Cornacchia, Jan Hazla, Donald Kougang-Yombi |
| 2025 | Learning How Hard to Think: Input-Adaptive Allocation of LM Computation. Mehul Damani, Idan Shenfeld, Andi Peng, Andreea Bobu, Jacob Andreas |
| 2025 | Learning Interleaved Image-Text Comprehension in Vision-Language Large Models. Chenyu Zhou, Mengdan Zhang, Peixian Chen, Chaoyou Fu, Yunhang Shen, Xiawu Zheng, Xing Sun, Rongrong Ji |
| 2025 | Learning Interpretable Hierarchical Dynamical Systems Models from Time Series Data. Manuel Brenner, Elias Weber, Georgia Koppe, Daniel Durstewitz |
| 2025 | Learning LLM-as-a-Judge for Preference Alignment. Ziyi Ye, Xiangsheng Li, Qiuchi Li, Qingyao Ai, Yujia Zhou, Wei Shen, Dong Yan, Yiqun Liu |
| 2025 | Learning Long Range Dependencies on Graphs via Random Walks. Dexiong Chen, Till Hendrik Schulz, Karsten M. Borgwardt |
| 2025 | Learning Mask Invariant Mutual Information for Masked Image Modeling. Tao Huang, Yanxiang Ma, Shan You, Chang Xu |
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| 2025 | Learning Multi-Index Models with Neural Networks via Mean-Field Langevin Dynamics. Alireza Mousavi Hosseini, Denny Wu, Murat A. Erdogdu |
| 2025 | Learning Neural Networks with Distribution Shift: Efficiently Certifiable Guarantees. Gautam Chandrasekaran, Adam R. Klivans, Lin Lin Lee, Konstantinos Stavropoulos |
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| 2025 | Learning Shape-Independent Transformation via Spherical Representations for Category-Level Object Pose Estimation. Huan Ren, Wenfei Yang, Xiang Liu, Shifeng Zhang, Tianzhu Zhang |
| 2025 | Learning Spatial-Semantic Features for Robust Video Object Segmentation. Xin Li, Deshui Miao, Zhenyu He, Yaowei Wang, Huchuan Lu, Ming-Hsuan Yang |
| 2025 | Learning Spatiotemporal Dynamical Systems from Point Process Observations. Valerii Iakovlev, Harri Lähdesmäki |
| 2025 | Learning Splitting Heuristics in Divide-and-Conquer SAT Solvers with Reinforcement Learning. Shumao Zhai, Ning Ge |
| 2025 | Learning Structured Representations by Embedding Class Hierarchy with Fast Optimal Transport. Siqi Zeng, Sixian Du, Makoto Yamada, Han Zhao |
| 2025 | Learning Structured Universe Graph with Outlier OOD Detection for Partial Matching. Zetian Jiang, Jiaxin Lu, Haizhao Fan, Tianzhe Wang, Junchi Yan |
| 2025 | Learning Successor Features with Distributed Hebbian Temporal Memory. Evgenii Aleksandrovich Dzhivelikian, Petr Kuderov, Aleksandr Panov |
| 2025 | Learning Task Belief Similarity with Latent Dynamics for Meta-Reinforcement Learning. Menglong Zhang, Fuyuan Qian, Quanying Liu |
| 2025 | Learning Transformer-based World Models with Contrastive Predictive Coding. Maxime Burchi, Radu Timofte |
| 2025 | Learning Video-Conditioned Policy on Unlabelled Data with Joint Embedding Predictive Transformer. Hao Luo, Zongqing Lu |
| 2025 | Learning View-invariant World Models for Visual Robotic Manipulation. Jing-Cheng Pang, Nan Tang, Kaiyuan Li, Yuting Tang, Xin-Qiang Cai, Zhen-Yu Zhang, Gang Niu, Masashi Sugiyama, Yang Yu |
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| 2025 | Learning a Neural Solver for Parametric PDEs to Enhance Physics-Informed Methods. Lise Le Boudec, Emmanuel de Bézenac, Louis Serrano, Ramon Daniel Regueiro-Espino, Yuan Yin, Patrick Gallinari |
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| 2025 | Learning from End User Data with Shuffled Differential Privacy over Kernel Densities. Tal Wagner |
| 2025 | Learning from Imperfect Human Feedback: A Tale from Corruption-Robust Dueling. Yuwei Cheng, Fan Yao, Xuefeng Liu, Haifeng Xu |
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| 2025 | Learning stochastic dynamics from snapshots through regularized unbalanced optimal transport. Zhenyi Zhang, Tiejun Li, Peijie Zhou |
| 2025 | Learning system dynamics without forgetting. Xikun Zhang, Dongjin Song, Yushan Jiang, Yixin Chen, Dacheng Tao |
| 2025 | Learning the Complexity of Weakly Noisy Quantum States. Yusen Wu, Bujiao Wu, Yanqi Song, Xiao Yuan, Jingbo Wang |
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| 2025 | Learning to Clarify: Multi-turn Conversations with Action-Based Contrastive Self-Training. Maximillian Chen, Ruoxi Sun, Tomas Pfister, Sercan Ö. Arik |
| 2025 | Learning to Communicate Through Implicit Communication Channels. Han Wang, Binbin Chen, Tieying Zhang, Baoxiang Wang |
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| 2025 | Learning to Discover Regulatory Elements for Gene Expression Prediction. Xingyu Su, Haiyang Yu, Degui Zhi, Shuiwang Ji |
| 2025 | Learning to Discretize Denoising Diffusion ODEs. Vinh Tong, Dung-Trung Hoang, Anji Liu, Guy Van den Broeck, Mathias Niepert |
| 2025 | Learning to Explore and Exploit with GNNs for Unsupervised Combinatorial Optimization. Utku Umur Acikalin, Aaron M. Ferber, Carla P. Gomes |
| 2025 | Learning to Generate Diverse Pedestrian Movements from Web Videos with Noisy Labels. Zhizheng Liu, Joe Lin, Wayne Wu, Bolei Zhou |
| 2025 | Learning to Help in Multi-Class Settings. Yu Wu, Yansong Li, Zeyu Dong, Nitya Sathyavageeswaran, Anand D. Sarwate |
| 2025 | Learning to Plan Before Answering: Self-Teaching LLMs to Learn Abstract Plans for Problem Solving. Jin Zhang, Flood Sung, Zhilin Yang, Yang Gao, Chongjie Zhang |
| 2025 | Learning to Search from Demonstration Sequences. Dixant Mittal, Liwei Kang, Wee Sun Lee |
| 2025 | Learning to Select Nodes in Branch and Bound with Sufficient Tree Representation. Sijia Zhang, Shuli Zeng, Shaoang Li, Feng Wu, Xiangyang Li |
| 2025 | Learning to Solve Differential Equation Constrained Optimization Problems. Vincenzo Di Vito Francesco, Mostafa Mohammadian, Kyri Baker, Ferdinando Fioretto |
| 2025 | Learning to Steer Markovian Agents under Model Uncertainty. Jiawei Huang, Vinzenz Thoma, Zebang Shen, Heinrich H. Nax, Niao He |
| 2025 | Learning to engineer protein flexibility. Petr Kouba, Joan Planas-Iglesias, Jirí Damborský, Jirí Sedlár, Stanislav Mazurenko, Josef Sivic |
| 2025 | Learning under Temporal Label Noise. Sujay Nagaraj, Walter Gerych, Sana Tonekaboni, Anna Goldenberg, Berk Ustun, Thomas Hartvigsen |
| 2025 | Learning vector fields of differential equations on manifolds with geometrically constrained operator-valued kernels. Daning Huang, Hanyang He, John Harlim, Yan Li |
| 2025 | Learning-Augmented Frequent Directions. Anders Aamand, Justin Y. Chen, Siddharth Gollapudi, Sandeep Silwal, Hao Wu |
| 2025 | Learning-Augmented Search Data Structures. Chunkai Fu, Brandon G. Nguyen, Jung Hoon Seo, Ryan S. Zesch, Samson Zhou |
| 2025 | Learning-Guided Rolling Horizon Optimization for Long-Horizon Flexible Job-Shop Scheduling. Sirui Li, Wenbin Ouyang, Yining Ma, Cathy Wu |
| 2025 | Leave-One-Out Stable Conformal Prediction. Kiljae Lee, Yuan Zhang |
| 2025 | Less is More: Masking Elements in Image Condition Features Avoids Content Leakages in Style Transfer Diffusion Models. Lin Zhu, Xinbing Wang, Chenghu Zhou, Qinying Gu, Nanyang Ye |
| 2025 | Let Me Grok for You: Accelerating Grokking via Embedding Transfer from a Weaker Model. Zhiwei Xu, Zhiyu Ni, Yixin Wang, Wei Hu |
| 2025 | Let SSMs be ConvNets: State-space Modeling with Optimal Tensor Contractions. Yan Ru Pei |
| 2025 | Let Your Features Tell The Differences: Understanding Graph Convolution By Feature Splitting. Yilun Zheng, Xiang Li, Sitao Luan, Xiaojiang Peng, Lihui Chen |
| 2025 | Let the Code LLM Edit Itself When You Edit the Code. Zhenyu He, Jun Zhang, Shengjie Luo, Jingjing Xu, Zhi Zhang, Di He |
| 2025 | LevAttention: Time, Space and Streaming Efficient Algorithm for Heavy Attentions. Ravindran Kannan, Chiranjib Bhattacharyya, Praneeth Kacham, David P. Woodruff |
| 2025 | Leveraging Driver Field-of-View for Multimodal Ego-Trajectory Prediction. M. Eren Akbiyik, Nedko Savov, Danda Pani Paudel, Nikola Popovic, Christian Vater, Otmar Hilliges, Luc Van Gool, Xi Wang |
| 2025 | Leveraging Flatness to Improve Information-Theoretic Generalization Bounds for SGD. Ze Peng, Jian Zhang, Yisen Wang, Lei Qi, Yinghuan Shi, Yang Gao |
| 2025 | Leveraging Sub-Optimal Data for Human-in-the-Loop Reinforcement Learning. Calarina Muslimani, Matthew E. Taylor |
| 2025 | Leveraging Submodule Linearity Enhances Task Arithmetic Performance in LLMs. Rui Dai, Sile Hu, Xu Shen, Yonggang Zhang, Xinmei Tian, Jieping Ye |
| 2025 | Leveraging Variable Sparsity to Refine Pareto Stationarity in Multi-Objective Optimization. Zeou Hu, Yaoliang Yu |
| 2025 | LiFT: Learning to Fine-Tune via Bayesian Parameter Efficient Meta Fine-Tuning. Minyoung Kim, Timothy M. Hospedales |
| 2025 | LiNeS: Post-training Layer Scaling Prevents Forgetting and Enhances Model Merging. Ke Wang, Nikolaos Dimitriadis, Alessandro Favero, Guillermo Ortiz-Jiménez, François Fleuret, Pascal Frossard |
| 2025 | Lie Algebra Canonicalization: Equivariant Neural Operators under arbitrary Lie Groups. Zakhar Shumaylov, Peter Zaika, James Rowbottom, Ferdia Sherry, Melanie Weber, Carola-Bibiane Schönlieb |
| 2025 | Lift Your Molecules: Molecular Graph Generation in Latent Euclidean Space. Mohamed Amine Ketata, Nicholas Gao, Johanna Sommer, Tom Wollschläger, Stephan Günnemann |
| 2025 | Lightning-Fast Image Inversion and Editing for Text-to-Image Diffusion Models. Dvir Samuel, Barak Meiri, Haggai Maron, Yoad Tewel, Nir Darshan, Shai Avidan, Gal Chechik, Rami Ben-Ari |
| 2025 | Lightweight Neural App Control. Filippos Christianos, Georgios Papoudakis, Thomas Coste, Jianye Hao, Jun Wang, Kun Shao |
| 2025 | Lightweight Predictive 3D Gaussian Splats. Junli Cao, Vidit Goel, Chaoyang Wang, Anil Kag, Ju Hu, Sergei Korolev, Chenfanfu Jiang, Sergey Tulyakov, Jian Ren |
| 2025 | Limits of Deep Learning: Sequence Modeling through the Lens of Complexity Theory. Nikola Zubic, Federico Soldà, Aurelio L. Sulser, Davide Scaramuzza |
| 2025 | Limits to scalable evaluation at the frontier: LLM as judge won't beat twice the data. Florian E. Dorner, Vivian Yvonne Nastl, Moritz Hardt |
| 2025 | Linear Combination of Saved Checkpoints Makes Consistency and Diffusion Models Better. Enshu Liu, Junyi Zhu, Zinan Lin, Xuefei Ning, Shuaiqi Wang, Matthew B. Blaschko, Sergey Yekhanin, Shengen Yan, Guohao Dai, Huazhong Yang, Yu Wang |
| 2025 | Linear Mode Connectivity in Differentiable Tree Ensembles. Ryuichi Kanoh, Mahito Sugiyama |
| 2025 | Linear Multistep Solver Distillation for Fast Sampling of Diffusion Models. Yuchen Liang, Xiangzhong Fang, Hanting Chen, Yunhe Wang |
| 2025 | Linear Partial Gromov-Wasserstein Embedding. Yikun Bai, Abihith Kothapalli, Hengrong Du, Rocio Diaz Martin, Soheil Kolouri |
| 2025 | Linear Representations of Political Perspective Emerge in Large Language Models. Junsol Kim, James Evans, Aaron Schein |
| 2025 | Linear SCM Identification in the Presence of Confounders and Gaussian Noise. Vahideh Sanjaroonpouri, Pouria Ramazi |
| 2025 | Linear Spherical Sliced Optimal Transport: A Fast Metric for Comparing Spherical Data. Xinran Liu, Yikun Bai, Rocio Diaz Martin, Kaiwen Shi, Ashkan Shahbazi, Bennett Allan Landman, Catie Chang, Soheil Kolouri |
| 2025 | Linear Transformer Topological Masking with Graph Random Features. Isaac Reid, Kumar Avinava Dubey, Deepali Jain, William F. Whitney, Amr Ahmed, Joshua Ainslie, Alex Bewley, Mithun George Jacob, Aranyak Mehta, David Rendleman, Connor Schenck, Richard E. Turner, René Wagner, Adrian Weller, Krzysztof Marcin Choromanski |
| 2025 | Linear combinations of latents in generative models: subspaces and beyond. Erik Bodin, Alexandru I. Stere, Dragos D. Margineantu, Carl Henrik Ek, Henry Moss |
| 2025 | Lines of Thought in Large Language Models. Raphaël Sarfati, Toni J. B. Liu, Nicolas Boullé, Christopher J. Earls |
| 2025 | Lipschitz Bandits in Optimal Space. Xiaoyi Zhu, Zengfeng Huang |
| 2025 | LiveBench: A Challenging, Contamination-Limited LLM Benchmark. Colin White, Samuel Dooley, Manley Roberts, Arka Pal, Benjamin Feuer, Siddhartha Jain, Ravid Shwartz-Ziv, Neel Jain, Khalid Saifullah, Sreemanti Dey, Shubh-Agrawal, Sandeep Singh Sandha, Siddartha V. Naidu, Chinmay Hegde, Yann LeCun, Tom Goldstein, Willie Neiswanger, Micah Goldblum |
| 2025 | LiveCodeBench: Holistic and Contamination Free Evaluation of Large Language Models for Code. Naman Jain, King Han, Alex Gu, Wen-Ding Li, Fanjia Yan, Tianjun Zhang, Sida Wang, Armando Solar-Lezama, Koushik Sen, Ion Stoica |
| 2025 | LiveXiv - A Multi-Modal live benchmark based on Arxiv papers content. Nimrod Shabtay, Felipe Maia Polo, Sivan Doveh, Wei Lin, Muhammad Jehanzeb Mirza, Leshem Choshen, Mikhail Yurochkin, Yuekai Sun, Assaf Arbelle, Leonid Karlinsky, Raja Giryes |
| 2025 | LoCA: Location-Aware Cosine Adaptation for Parameter-Efficient Fine-Tuning. Zhekai Du, Yinjie Min, Jingjing Li, Ke Lu, Changliang Zou, Liuhua Peng, Tingjin Chu, Mingming Gong |
| 2025 | LoCoDL: Communication-Efficient Distributed Learning with Local Training and Compression. Laurent Condat, Arto Maranjyan, Peter Richtárik |
| 2025 | LoLCATs: On Low-Rank Linearizing of Large Language Models. Michael Zhang, Simran Arora, Rahul Chalamala, Benjamin Frederick Spector, Alan Wu, Krithik Ramesh, Aaryan Singhal, Christopher Ré |
| 2025 | LoR-VP: Low-Rank Visual Prompting for Efficient Vision Model Adaptation. Can Jin, Ying Li, Mingyu Zhao, Shiyu Zhao, Zhenting Wang, Xiaoxiao He, Ligong Han, Tong Che, Dimitris N. Metaxas |
| 2025 | LoRA Done RITE: Robust Invariant Transformation Equilibration for LoRA Optimization. Jui-Nan Yen, Si Si, Zhao Meng, Felix X. Yu, Sai Surya Duvvuri, Inderjit S. Dhillon, Cho-Jui Hsieh, Sanjiv Kumar |
| 2025 | LoRA-Pro: Are Low-Rank Adapters Properly Optimized? Zhengbo Wang, Jian Liang, Ran He, Zilei Wang, Tieniu Tan |
| 2025 | LoRA-X: Bridging Foundation Models with Training-Free Cross-Model Adaptation. Farzad Farhadzadeh, Debasmit Das, Shubhankar Borse, Fatih Porikli |
| 2025 | LoRA3D: Low-Rank Self-Calibration of 3D Geometric Foundation models. Ziqi Lu, Heng Yang, Danfei Xu, Boyi Li, Boris Ivanovic, Marco Pavone, Yue Wang |
| 2025 | LoRanPAC: Low-rank Random Features and Pre-trained Models for Bridging Theory and Practice in Continual Learning. Liangzu Peng, Juan Elenter, Joshua Agterberg, Alejandro Ribeiro, René Vidal |
| 2025 | Local Loss Optimization in the Infinite Width: Stable Parameterization of Predictive Coding Networks and Target Propagation. Satoki Ishikawa, Rio Yokota, Ryo Karakida |
| 2025 | Local Patterns Generalize Better for Novel Anomalies. Yalong Jiang |
| 2025 | Local Steps Speed Up Local GD for Heterogeneous Distributed Logistic Regression. Michael Crawshaw, Blake Woodworth, Mingrui Liu |
| 2025 | Local convergence of simultaneous min-max algorithms to differential equilibrium on Riemannian manifold. Sixin Zhang |
| 2025 | Local-Prompt: Extensible Local Prompts for Few-Shot Out-of-Distribution Detection. Fanhu Zeng, Zhen Cheng, Fei Zhu, Hongxin Wei, Xu-Yao Zhang |
| 2025 | Locality Alignment Improves Vision-Language Models. Ian Connick Covert, Tony Sun, James Zou, Tatsunori Hashimoto |
| 2025 | Locality Sensitive Avatars From Video. Chunjin Song, Zhijie Wu, Shih-Yang Su, Bastian Wandt, Leonid Sigal, Helge Rhodin |
| 2025 | Locality-aware Gaussian Compression for Fast and High-quality Rendering. Seungjoo Shin, Jaesik Park, Sunghyun Cho |
| 2025 | Locally Connected Echo State Networks for Time Series Forecasting. Filip Matzner, Frantisek Mráz |
| 2025 | LocoVR: Multiuser Indoor Locomotion Dataset in Virtual Reality. Kojiro Takeyama, Yimeng Liu, Misha Sra |
| 2025 | Logic-Logit: A Logic-Based Approach to Choice Modeling. Shuhan Zhang, Wendi Ren, Shuang Li |
| 2025 | Logical Consistency of Large Language Models in Fact-Checking. Bishwamittra Ghosh, Sarah Hasan, Naheed Anjum Arafat, Arijit Khan |
| 2025 | Logically Consistent Language Models via Neuro-Symbolic Integration. Diego Calanzone, Stefano Teso, Antonio Vergari |
| 2025 | Logicbreaks: A Framework for Understanding Subversion of Rule-based Inference. Anton Xue, Avishree Khare, Rajeev Alur, Surbhi Goel, Eric Wong |
| 2025 | Long Context Compression with Activation Beacon. Peitian Zhang, Zheng Liu, Shitao Xiao, Ninglu Shao, Qiwei Ye, Zhicheng Dou |
| 2025 | Long-Context LLMs Meet RAG: Overcoming Challenges for Long Inputs in RAG. Bowen Jin, Jinsung Yoon, Jiawei Han, Sercan Ö. Arik |
| 2025 | Long-Context Linear System Identification. Oguz Kaan Yüksel, Mathieu Even, Nicolas Flammarion |
| 2025 | Long-Sequence Recommendation Models Need Decoupled Embeddings. Ningya Feng, Junwei Pan, Jialong Wu, Baixu Chen, Ximei Wang, Qian Li, Xian Hu, Jie Jiang, Mingsheng Long |
| 2025 | Long-Short Decision Transformer: Bridging Global and Local Dependencies for Generalized Decision-Making. Jincheng Wang, Penny Karanasou, Pengyuan Wei, Elia Gatti, Diego Martínez Plasencia, Dimitrios Kanoulas |
| 2025 | Long-horizon Visual Instruction Generation with Logic and Attribute Self-reflection. Yucheng Suo, Fan Ma, Kaixin Shen, Linchao Zhu, Yi Yang |
| 2025 | Long-tailed Adversarial Training with Self-Distillation. Seungju Cho, Hongsin Lee, Changick Kim |
| 2025 | Long-time asymptotics of noisy SVGD outside the population limit. Victor Priser, Pascal Bianchi, Adil Salim |
| 2025 | LongGenBench: Benchmarking Long-Form Generation in Long Context LLMs. Yuhao Wu, Ming Shan Hee, Zhiqiang Hu, Roy Ka-Wei Lee |
| 2025 | LongMamba: Enhancing Mamba's Long-Context Capabilities via Training-Free Receptive Field Enlargement. Zhifan Ye, Kejing Xia, Yonggan Fu, Xin Dong, Jihoon Hong, Xiangchi Yuan, Shizhe Diao, Jan Kautz, Pavlo Molchanov, Yingyan Celine Lin |
| 2025 | LongMemEval: Benchmarking Chat Assistants on Long-Term Interactive Memory. Di Wu, Hongwei Wang, Wenhao Yu, Yuwei Zhang, Kai-Wei Chang, Dong Yu |
| 2025 | LongPO: Long Context Self-Evolution of Large Language Models through Short-to-Long Preference Optimization. Guanzheng Chen, Xin Li, Michael Shieh, Lidong Bing |
| 2025 | LongVILA: Scaling Long-Context Visual Language Models for Long Videos. Yukang Chen, Fuzhao Xue, Dacheng Li, Qinghao Hu, Ligeng Zhu, Xiuyu Li, Yunhao Fang, Haotian Tang, Shang Yang, Zhijian Liu, Yihui He, Hongxu Yin, Pavlo Molchanov, Jan Kautz, Linxi Fan, Yuke Zhu, Yao Lu, Song Han |
| 2025 | LongWriter: Unleashing 10, 000+ Word Generation from Long Context LLMs. Yushi Bai, Jiajie Zhang, Xin Lv, Linzhi Zheng, Siqi Zhu, Lei Hou, Yuxiao Dong, Jie Tang, Juanzi Li |
| 2025 | Longhorn: State Space Models are Amortized Online Learners. Bo Liu, Rui Wang, Lemeng Wu, Yihao Feng, Peter Stone, Qiang Liu |
| 2025 | Look Before You Leap: Universal Emergent Mechanism for Retrieval in Language Models. Alexandre Variengien, Eric Winsor |
| 2025 | Looking Backward: Retrospective Backward Synthesis for Goal-Conditioned GFlowNets. Haoran He, Can Chang, Huazhe Xu, Ling Pan |
| 2025 | Looking Backward: Streaming Video-to-Video Translation with Feature Banks. Feng Liang, Akio Kodaira, Chenfeng Xu, Masayoshi Tomizuka, Kurt Keutzer, Diana Marculescu |
| 2025 | Looking Inward: Language Models Can Learn About Themselves by Introspection. Felix Jedidja Binder, James Chua, Tomek Korbak, Henry Sleight, John Hughes, Robert Long, Ethan Perez, Miles Turpin, Owain Evans |
| 2025 | Looking into User's Long-term Interests through the Lens of Conservative Evidential Learning. Dingrong Wang, Krishna Prasad Neupane, Ervine Zheng, Qi Yu |
| 2025 | Looped Transformers for Length Generalization. Ying Fan, Yilun Du, Kannan Ramchandran, Kangwook Lee |
| 2025 | Loopy: Taming Audio-Driven Portrait Avatar with Long-Term Motion Dependency. Jianwen Jiang, Chao Liang, Jiaqi Yang, Gaojie Lin, Tianyun Zhong, Yanbo Zheng |
| 2025 | Loss Landscape of Shallow ReLU-like Neural Networks: Stationary Points, Saddle Escape, and Network Embedding. Zhengqing Wu, Berfin Simsek, François Gaston Ged |
| 2025 | Lossy Compression with Pretrained Diffusion Models. Jeremy Vonderfecht, Feng Liu |
| 2025 | Lotus: Diffusion-based Visual Foundation Model for High-quality Dense Prediction. Jing He, Haodong Li, Wei Yin, Yixun Liang, Leheng Li, Kaiqiang Zhou, Hongbo Zhang, Bingbing Liu, Ying-Cong Chen |
| 2025 | Lr0.Fm: low-Resolution Zero-Shot Classification Benchmark for Foundation Models. Priyank Pathak, Shyam Marjit, Shruti Vyas, Yogesh S. Rawat |
| 2025 | LucidPPN: Unambiguous Prototypical Parts Network for User-centric Interpretable Computer Vision. Mateusz Pach, Koryna Lewandowska, Jacek Tabor, Bartosz Michal Zielinski, Dawid Damian Rymarczyk |
| 2025 | Lumina-T2X: Scalable Flow-based Large Diffusion Transformer for Flexible Resolution Generation. Peng Gao, Le Zhuo, Dongyang Liu, Ruoyi Du, Xu Luo, Longtian Qiu, Yuhang Zhang, Rongjie Huang, Shijie Geng, Renrui Zhang, Junlin Xie, Wenqi Shao, Zhengkai Jiang, Tianshuo Yang, Weicai Ye, Tong He, Jingwen He, Junjun He, Yu Qiao, Hongsheng Li |
| 2025 | MA-RLHF: Reinforcement Learning from Human Feedback with Macro Actions. Yekun Chai, Haoran Sun, Huang Fang, Shuohuan Wang, Yu Sun, Hua Wu |
| 2025 | MA2E: Addressing Partial Observability in Multi-Agent Reinforcement Learning with Masked Auto-Encoder. Sehyeok Kang, Yongsik Lee, Gahee Kim, Song Chong, Se-Young Yun |
| 2025 | MACPO: Weak-to-Strong Alignment via Multi-Agent Contrastive Preference Optimization. Yougang Lyu, Lingyong Yan, Zihan Wang, Dawei Yin, Pengjie Ren, Maarten de Rijke, Zhaochun Ren |
| 2025 | MAD-TD: Model-Augmented Data stabilizes High Update Ratio RL. Claas Voelcker, Marcel Hussing, Eric Eaton, Amir-massoud Farahmand, Igor Gilitschenski |
| 2025 | MADGEN: Mass-Spec attends to De Novo Molecular generation. Yinkai Wang, Xiaohui Chen, Liping Liu, Soha Hassoun |
| 2025 | MAESTRO: Masked Encoding Set Transformer with Self-Distillation. Matthew Eric Lee, Jaesik Kim, Matei Ionita, Jonghyun Lee, Michelle L. McKeague, Yonghyun Nam, Irene Khavin, Yidi Huang, Victoria Fang, Sokratis Apostolidis, Divij Mathew, Shwetank, Ajinkya Pattekar, Zahabia Rangwala, Amit Bar-Or, Benjamin A. Fensterheim, Benjamin A. Abramoff, Rennie L. Rhee, Damian Maseda, Allison R. Greenplate, et al. |
| 2025 | MAGE: Model-Level Graph Neural Networks Explanations via Motif-based Graph Generation. Zhaoning Yu, Hongyang Gao |
| 2025 | MAGNet: Motif-Agnostic Generation of Molecules from Scaffolds. Leon Hetzel, Johanna Sommer, Bastian Rieck, Fabian J. Theis, Stephan Günnemann |
| 2025 | MAI: A Multi-turn Aggregation-Iteration Model for Composed Image Retrieval. Yanzhe Chen, Zhiwen Yang, Jinglin Xu, Yuxin Peng |
| 2025 | MANTRA: The Manifold Triangulations Assemblage. Rubén Ballester, Ernst Röell, Daniel Bin Schmid, Mathieu Alain, Sergio Escalera, Carles Casacuberta, Bastian Rieck |
| 2025 | MAP: Low-compute Model Merging with Amortized Pareto Fronts via Quadratic Approximation. Lu Li, Tianyu Zhang, Zhiqi Bu, Suyuchen Wang, Huan He, Jie Fu, Yonghui Wu, Jiang Bian, Yong Chen, Yoshua Bengio |
| 2025 | MAP: Multi-Human-Value Alignment Palette. Xinran Wang, Qi Le, Ammar Ahmed, Enmao Diao, Yi Zhou, Nathalie Baracaldo, Jie Ding, Ali Anwar |
| 2025 | MAPS: Advancing Multi-Modal Reasoning in Expert-Level Physical Science. Erle Zhu, Yadi Liu, Zhe Zhang, Xujun Li, Jin Zhou, Xinjie Yu, Minlie Huang, Hongning Wang |
| 2025 | MAST: model-agnostic sparsified training. Yury Demidovich, Grigory Malinovsky, Egor Shulgin, Peter Richtárik |
| 2025 | MAVIS: Mathematical Visual Instruction Tuning with an Automatic Data Engine. Renrui Zhang, Xinyu Wei, Dongzhi Jiang, Ziyu Guo, Yichi Zhang, Chengzhuo Tong, Jiaming Liu, Aojun Zhou, Shanghang Zhang, Peng Gao, Hongsheng Li |
| 2025 | MCNC: Manifold-Constrained Reparameterization for Neural Compression. Chayne Thrash, Reed Andreas, Ali Abbasi, Parsa Nooralinejad, Soroush Abbasi Koohpayegani, Hamed Pirsiavash, Soheil Kolouri |
| 2025 | MDSGen: Fast and Efficient Masked Diffusion Temporal-Aware Transformers for Open-Domain Sound Generation. Trung X. Pham, Tri Ton, Chang D. Yoo |
| 2025 | MEGA-Bench: Scaling Multimodal Evaluation to over 500 Real-World Tasks. Jiacheng Chen, Tianhao Liang, Sherman Siu, Zhengqing Wang, Kai Wang, Yubo Wang, Yuansheng Ni, Ziyan Jiang, Wang Zhu, Bohan Lyu, Dongfu Jiang, Xuan He, Yuan Liu, Hexiang Hu, Xiang Yue, Wenhu Chen |
| 2025 | MELODI: Exploring Memory Compression for Long Contexts. Yinpeng Chen, DeLesley Hutchins, Aren Jansen, Andrey Zhmoginov, David Racz, Jesper Sparre Andersen |
| 2025 | MGCFNN: A Neural MultiGrid Solver with Novel Fourier Neural Network for High Wave Number Helmholtz Equations. Yan Xie, Minrui Lv, Chensong Zhang |
| 2025 | MGDA Converges under Generalized Smoothness, Provably. Qi Zhang, Peiyao Xiao, Shaofeng Zou, Kaiyi Ji |
| 2025 | MGMapNet: Multi-Granularity Representation Learning for End-to-End Vectorized HD Map Construction. Jing Yang, Minyue Jiang, Sen Yang, Xiao Tan, Yingying Li, Errui Ding, Jingdong Wang, Hanli Wang |
| 2025 | MIA-Bench: Towards Better Instruction Following Evaluation of Multimodal LLMs. Yusu Qian, Hanrong Ye, Jean-Philippe Fauconnier, Peter Grasch, Yinfei Yang, Zhe Gan |
| 2025 | MIA-DPO: Multi-Image Augmented Direct Preference Optimization For Large Vision-Language Models. Ziyu Liu, Yuhang Zang, Xiaoyi Dong, Pan Zhang, Yuhang Cao, Haodong Duan, Conghui He, Yuanjun Xiong, Dahua Lin, Jiaqi Wang |
| 2025 | MIM-Refiner: A Contrastive Learning Boost from Intermediate Pre-Trained Masked Image Modeling Representations. Benedikt Alkin, Lukas Miklautz, Sepp Hochreiter, Johannes Brandstetter |
| 2025 | MIND over Body: Adaptive Thinking using Dynamic Computation. Mrinal Mathur, Barak A. Pearlmutter, Sergey M. Plis |
| 2025 | MIND: Math Informed syNthetic Dialogues for Pretraining LLMs. Syeda Nahida Akter, Shrimai Prabhumoye, John Kamalu, Sanjeev Satheesh, Eric Nyberg, Mostofa Patwary, Mohammad Shoeybi, Bryan Catanzaro |
| 2025 | MIRACLE 3D: Memory-efficient Integrated Robust Approach for Continual Learning on 3D Point Clouds via Shape Model Construction. Hossein Resani, Behrooz Nasihatkon |
| 2025 | MIRAGE: Evaluating and Explaining Inductive Reasoning Process in Language Models. Jiachun Li, Pengfei Cao, Zhuoran Jin, Yubo Chen, Kang Liu, Jun Zhao |
| 2025 | MLE-bench: Evaluating Machine Learning Agents on Machine Learning Engineering. Jun Shern Chan, Neil Chowdhury, Oliver Jaffe, James Aung, Dane Sherburn, Evan Mays, Giulio Starace, Kevin Liu, Leon Maksin, Tejal Patwardhan, Aleksander Madry, Lilian Weng |
| 2025 | MLLM as Retriever: Interactively Learning Multimodal Retrieval for Embodied Agents. Junpeng Yue, Xinrun Xu, Börje F. Karlsson, Zongqing Lu |
| 2025 | MLLM can see? Dynamic Correction Decoding for Hallucination Mitigation. Chenxi Wang, Xiang Chen, Ningyu Zhang, Bozhong Tian, Haoming Xu, Shumin Deng, Huajun Chen |
| 2025 | MLLMs Know Where to Look: Training-free Perception of Small Visual Details with Multimodal LLMs. Jiarui Zhang, Mahyar Khayatkhoei, Prateek Chhikara, Filip Ilievski |
| 2025 | MLPs Learn In-Context on Regression and Classification Tasks. William Lingxiao Tong, Cengiz Pehlevan |
| 2025 | MM1.5: Methods, Analysis & Insights from Multimodal LLM Fine-tuning. Haotian Zhang, Mingfei Gao, Zhe Gan, Philipp Dufter, Nina Wenzel, Forrest Huang, Dhruti Shah, Xianzhi Du, Bowen Zhang, Yanghao Li, Sam Dodge, Keen You, Zhen Yang, Aleksei Timofeev, Mingze Xu, Hong-You Chen, Jean-Philippe Fauconnier, Zhengfeng Lai, Haoxuan You, Zirui Wang, et al. |
| 2025 | MMAD: A Comprehensive Benchmark for Multimodal Large Language Models in Industrial Anomaly Detection. Xi Jiang, Jian Li, Hanqiu Deng, Yong Liu, Bin-Bin Gao, Yifeng Zhou, Jialin Li, Chengjie Wang, Feng Zheng |
| 2025 | MMAU: A Massive Multi-Task Audio Understanding and Reasoning Benchmark. S. Sakshi, Utkarsh Tyagi, Sonal Kumar, Ashish Seth, Ramaneswaran Selvakumar, Oriol Nieto, Ramani Duraiswami, Sreyan Ghosh, Dinesh Manocha |
| 2025 | MMDT: Decoding the Trustworthiness and Safety of Multimodal Foundation Models. Chejian Xu, Jiawei Zhang, Zhaorun Chen, Chulin Xie, Mintong Kang, Yujin Potter, Zhun Wang, Zhuowen Yuan, Alexander Xiong, Zidi Xiong, Chenhui Zhang, Lingzhi Yuan, Yi Zeng, Peiyang Xu, Chengquan Guo, Andy Zhou, Jeffrey Ziwei Tan, Xuandong Zhao, Francesco Pinto, Zhen Xiang, et al. |
| 2025 | MMDisCo: Multi-Modal Discriminator-Guided Cooperative Diffusion for Joint Audio and Video Generation. Akio Hayakawa, Masato Ishii, Takashi Shibuya, Yuki Mitsufuji |
| 2025 | MME-RealWorld: Could Your Multimodal LLM Challenge High-Resolution Real-World Scenarios that are Difficult for Humans? Yifan Zhang, Huanyu Zhang, Haochen Tian, Chaoyou Fu, Shuangqing Zhang, Junfei Wu, Feng Li, Kun Wang, Qingsong Wen, Zhang Zhang, Liang Wang, Rong Jin |
| 2025 | MMEgo: Towards Building Egocentric Multimodal LLMs for Video QA. Hanrong Ye, Haotian Zhang, Erik A. Daxberger, Lin Chen, Zongyu Lin, Yanghao Li, Bowen Zhang, Haoxuan You, Dan Xu, Zhe Gan, Jiasen Lu, Yinfei Yang |
| 2025 | MMFakeBench: A Mixed-Source Multimodal Misinformation Detection Benchmark for LVLMs. Xuannan Liu, Zekun Li, Pei-Pei Li, Huaibo Huang, Shuhan Xia, Xing Cui, Linzhi Huang, Weihong Deng, Zhaofeng He |
| 2025 | MMIE: Massive Multimodal Interleaved Comprehension Benchmark for Large Vision-Language Models. Peng Xia, Siwei Han, Shi Qiu, Yiyang Zhou, Zhaoyang Wang, Wenhao Zheng, Zhaorun Chen, Chenhang Cui, Mingyu Ding, Linjie Li, Lijuan Wang, Huaxiu Yao |
| 2025 | MMIU: Multimodal Multi-image Understanding for Evaluating Large Vision-Language Models. Fanqing Meng, Jin Wang, Chuanhao Li, Quanfeng Lu, Hao Tian, Tianshuo Yang, Jiaqi Liao, Xizhou Zhu, Jifeng Dai, Yu Qiao, Ping Luo, Kaipeng Zhang, Wenqi Shao |
| 2025 | MMKE-Bench: A Multimodal Editing Benchmark for Diverse Visual Knowledge. Yuntao Du, Kailin Jiang, Zhi Gao, Chenrui Shi, Zilong Zheng, Siyuan Qi, Qing Li |
| 2025 | MMQA: Evaluating LLMs with Multi-Table Multi-Hop Complex Questions. Jian Wu, Linyi Yang, Dongyuan Li, Yuliang Ji, Manabu Okumura, Yue Zhang |
| 2025 | MMR: A Large-scale Benchmark Dataset for Multi-target and Multi-granularity Reasoning Segmentation. Donggon Jang, Yucheol Cho, Suin Lee, Taehyeon Kim, Daeshik Kim |
| 2025 | MMRole: A Comprehensive Framework for Developing and Evaluating Multimodal Role-Playing Agents. Yanqi Dai, Huanran Hu, Lei Wang, Shengjie Jin, Xu Chen, Zhiwu Lu |
| 2025 | MMSearch: Unveiling the Potential of Large Models as Multi-modal Search Engines. Dongzhi Jiang, Renrui Zhang, Ziyu Guo, Yanmin Wu, Jiayi Lei, Pengshuo Qiu, Pan Lu, Zehui Chen, Guanglu Song, Peng Gao, Yu Liu, Chunyuan Li, Hongsheng Li |
| 2025 | MMTEB: Massive Multilingual Text Embedding Benchmark. Kenneth C. Enevoldsen, Isaac Chung, Imene Kerboua, Márton Kardos, Ashwin Mathur, David Stap, Jay Gala, Wissam Siblini, Dominik Krzeminski, Genta Indra Winata, Saba Sturua, Saiteja Utpala, Mathieu Ciancone, Marion Schaeffer, Diganta Misra, Shreeya Dhakal, Jonathan Rystrøm, Roman Solomatin, Ömer Veysel Çagatan, Akash Kundu, et al. |
| 2025 | MMWorld: Towards Multi-discipline Multi-faceted World Model Evaluation in Videos. Xuehai He, Weixi Feng, Kaizhi Zheng, Yujie Lu, Wanrong Zhu, Jiachen Li, Yue Fan, Jianfeng Wang, Linjie Li, Zhengyuan Yang, Kevin Lin, William Yang Wang, Lijuan Wang, Xin Eric Wang |
| 2025 | MMed-RAG: Versatile Multimodal RAG System for Medical Vision Language Models. Peng Xia, Kangyu Zhu, Haoran Li, Tianze Wang, Weijia Shi, Sheng Wang, Linjun Zhang, James Zou, Huaxiu Yao |
| 2025 | MOFFlow: Flow Matching for Structure Prediction of Metal-Organic Frameworks. Nayoung Kim, Seongsu Kim, Minsu Kim, Jinkyoo Park, Sungsoo Ahn |
| 2025 | MOOSE-Chem: Large Language Models for Rediscovering Unseen Chemistry Scientific Hypotheses. Zonglin Yang, Wanhao Liu, Ben Gao, Tong Xie, Yuqiang Li, Wanli Ouyang, Soujanya Poria, Erik Cambria, Dongzhan Zhou |
| 2025 | MOS: Model Synergy for Test-Time Adaptation on LiDAR-Based 3D Object Detection. Zhuoxiao Chen, Junjie Meng, Mahsa Baktashmotlagh, Yonggang Zhang, Zi Huang, Yadan Luo |
| 2025 | MP-Mat: A 3D-and-Instance-Aware Human Matting and Editing Framework with Multiplane Representation. Siyi Jiao, Wenzheng Zeng, Yerong Li, Huayu Zhang, Changxin Gao, Nong Sang, Mike Zheng Shou |
| 2025 | MQuAKE-Remastered: Multi-Hop Knowledge Editing Can Only Be Advanced with Reliable Evaluations. Shaochen (Henry) Zhong, Yifan Lu, Lize Shao, Bhargav Bhushanam, Xiaocong Du, Yixin Wan, Yucheng Shi, Daochen Zha, Yiwei Wang, Ninghao Liu, Kaixiong Zhou, Shuai Xu, Kai-Wei Chang, Louis Feng, Vipin Chaudhary, Xia Hu |
| 2025 | MR-GSM8K: A Meta-Reasoning Benchmark for Large Language Model Evaluation. Zhongshen Zeng, Pengguang Chen, Shu Liu, Haiyun Jiang, Jiaya Jia |
| 2025 | MRAG-Bench: Vision-Centric Evaluation for Retrieval-Augmented Multimodal Models. Wenbo Hu, Jia-Chen Gu, Zi-Yi Dou, Mohsen Fayyaz, Pan Lu, Kai-Wei Chang, Nanyun Peng |
| 2025 | MS-Diffusion: Multi-subject Zero-shot Image Personalization with Layout Guidance. Xierui Wang, Siming Fu, Qihan Huang, Wanggui He, Hao Jiang |
| 2025 | MTSAM: Multi-Task Fine-Tuning for Segment Anything Model. Xuehao Wang, Zhan Zhuang, Feiyang Ye, Yu Zhang |
| 2025 | MTU-Bench: A Multi-granularity Tool-Use Benchmark for Large Language Models. Pei Wang, Yanan Wu, Noah Wang, Jiaheng Liu, Xiaoshuai Song, Z. Y. Peng, Ken Deng, Chenchen Zhang, Jiakai Wang, Junran Peng, Ge Zhang, Hangyu Guo, Zhaoxiang Zhang, Wenbo Su, Bo Zheng |
| 2025 | MUSE: Machine Unlearning Six-Way Evaluation for Language Models. Weijia Shi, Jaechan Lee, Yangsibo Huang, Sadhika Malladi, Jieyu Zhao, Ari Holtzman, Daogao Liu, Luke Zettlemoyer, Noah A. Smith, Chiyuan Zhang |
| 2025 | MVTokenFlow: High-quality 4D Content Generation using Multiview Token Flow. Hanzhuo Huang, Yuan Liu, Ge Zheng, Jiepeng Wang, Zhiyang Dou, Sibei Yang |
| 2025 | M^3PC: Test-time Model Predictive Control using Pretrained Masked Trajectory Model. Kehan Wen, Yutong Hu, Yao Mu, Lei Ke |
| 2025 | MaRS: A Fast Sampler for Mean Reverting Diffusion based on ODE and SDE Solvers. Ao Li, Wei Fang, Hongbo Zhao, Le Lu, Ge Yang, Minfeng Xu |
| 2025 | Machine Unlearning Fails to Remove Data Poisoning Attacks. Martin Pawelczyk, Jimmy Z. Di, Yiwei Lu, Gautam Kamath, Ayush Sekhari, Seth Neel |
| 2025 | Machine Unlearning via Simulated Oracle Matching. Kristian Georgiev, Roy Rinberg, Sung Min Park, Shivam Garg, Andrew Ilyas, Aleksander Madry, Seth Neel |
| 2025 | MaestroMotif: Skill Design from Artificial Intelligence Feedback. Martin Klissarov, Mikael Henaff, Roberta Raileanu, Shagun Sodhani, Pascal Vincent, Amy Zhang, Pierre-Luc Bacon, Doina Precup, Marlos C. Machado, Pierluca D'Oro |
| 2025 | MagicDec: Breaking the Latency-Throughput Tradeoff for Long Context Generation with Speculative Decoding. Ranajoy Sadhukhan, Jian Chen, Zhuoming Chen, Vashisth Tiwari, Ruihang Lai, Jinyuan Shi, Ian En-Hsu Yen, Avner May, Tianqi Chen, Beidi Chen |
| 2025 | MagicPIG: LSH Sampling for Efficient LLM Generation. Zhuoming Chen, Ranajoy Sadhukhan, Zihao Ye, Yang Zhou, Jianyu Zhang, Niklas Nolte, Yuandong Tian, Matthijs Douze, Léon Bottou, Zhihao Jia, Beidi Chen |
| 2025 | Magnetic Preference Optimization: Achieving Last-iterate Convergence for Language Model Alignment. Mingzhi Wang, Chengdong Ma, Qizhi Chen, Linjian Meng, Yang Han, Jiancong Xiao, Zhaowei Zhang, Jing Huo, Weijie J. Su, Yaodong Yang |
| 2025 | Magpie: Alignment Data Synthesis from Scratch by Prompting Aligned LLMs with Nothing. Zhangchen Xu, Fengqing Jiang, Luyao Niu, Yuntian Deng, Radha Poovendran, Yejin Choi, Bill Yuchen Lin |
| 2025 | Maintaining Structural Integrity in Parameter Spaces for Parameter Efficient Fine-tuning. Chongjie Si, Xuehui Wang, Xue Yang, Zhengqin Xu, Qingyun Li, Jifeng Dai, Yu Qiao, Xiaokang Yang, Wei Shen |
| 2025 | Make Haste Slowly: A Theory of Emergent Structured Mixed Selectivity in Feature Learning ReLU Networks. Devon Jarvis, Richard Klein, Benjamin Rosman, Andrew M. Saxe |
| 2025 | Making Text Embedders Few-Shot Learners. Chaofan Li, Minghao Qin, Shitao Xiao, Jianlyu Chen, Kun Luo, Defu Lian, Yingxia Shao, Zheng Liu |
| 2025 | Making Transformer Decoders Better Differentiable Indexers. Wuchao Li, Kai Zheng, Defu Lian, Qi Liu, Wentian Bao, Yunen Yu, Yang Song, Han Li, Kun Gai |
| 2025 | MallowsPO: Fine-Tune Your LLM with Preference Dispersions. Haoxian Chen, Hanyang Zhao, Henry Lam, David D. Yao, Wenpin Tang |
| 2025 | MamBEV: Enabling State Space Models to Learn Birds-Eye-View Representations. Hongyu Ke, Jack Morris, Kentaro Oguchi, Xiaofei Cao, Yongkang Liu, Haoxin Wang, Yi Ding |
| 2025 | MamKO: Mamba-based Koopman operator for modeling and predictive control. Zhaoyang Li, Minghao Han, Xunyuan Yin |
| 2025 | MambaExtend: A Training-Free Approach to Improve Long Context Extension of Mamba. Seyedarmin Azizi, Souvik Kundu, Mohammad Erfan Sadeghi, Massoud Pedram |
| 2025 | MambaPEFT: Exploring Parameter-Efficient Fine-Tuning for Mamba. Masakazu Yoshimura, Teruaki Hayashi, Yota Maeda |
| 2025 | MambaQuant: Quantizing the Mamba Family with Variance Aligned Rotation Methods. Zukang Xu, Yuxuan Yue, Xing Hu, Dawei Yang, Zhihang Yuan, Zixu Jiang, Zhixuan Chen, Jiangyong Yu, Chen Xu, Sifan Zhou |
| 2025 | ManiSkill-HAB: A Benchmark for Low-Level Manipulation in Home Rearrangement Tasks. Arth Shukla, Stone Tao, Hao Su |
| 2025 | Manifold Constraint Reduces Exposure Bias in Accelerated Diffusion Sampling. Yuzhe Yao, Jun Chen, Zeyi Huang, Haonan Lin, Mengmeng Wang, Guang Dai, Jingdong Wang |
| 2025 | Manifold Induced Biases for Zero-shot and Few-shot Detection of Generated Images. Jonathan Brokman, Amit Giloni, Omer Hofman, Roman Vainshtein, Hisashi Kojima, Guy Gilboa |
| 2025 | Manifolds, Random Matrices and Spectral Gaps: The geometric phases of generative diffusion. Enrico Ventura, Beatrice Achilli, Gianluigi Silvestri, Carlo Lucibello, Luca Ambrogioni |
| 2025 | Many-Objective Multi-Solution Transport. Ziyue Li, Tian Li, Virginia Smith, Jeff A. Bilmes, Tianyi Zhou |
| 2025 | MarS: a Financial Market Simulation Engine Powered by Generative Foundation Model. Junjie Li, Yang Liu, Weiqing Liu, Shikai Fang, Lewen Wang, Chang Xu, Jiang Bian |
| 2025 | Mask in the Mirror: Implicit Sparsification. Tom Jacobs, Rebekka Burkholz |
| 2025 | Mask-DPO: Generalizable Fine-grained Factuality Alignment of LLMs. Yuzhe Gu, Wenwei Zhang, Chengqi Lyu, Dahua Lin, Kai Chen |
| 2025 | MaskGCT: Zero-Shot Text-to-Speech with Masked Generative Codec Transformer. Yuancheng Wang, Haoyue Zhan, Liwei Liu, Ruihong Zeng, Haotian Guo, Jiachen Zheng, Qiang Zhang, Xueyao Zhang, Shunsi Zhang, Zhizheng Wu |
| 2025 | Masked Diffusion Models are Secretly Time-Agnostic Masked Models and Exploit Inaccurate Categorical Sampling. Kaiwen Zheng, Yongxin Chen, Hanzi Mao, Ming-Yu Liu, Jun Zhu, Qinsheng Zhang |
| 2025 | Masked Temporal Interpolation Diffusion for Procedure Planning in Instructional Videos. Yufan Zhou, Zhaobo Qi, Lingshuai Lin, Junqi Jing, Tingting Chai, Beichen Zhang, Shuhui Wang, Weigang Zhang |
| 2025 | Mastering Task Arithmetic: τJp as a Key Indicator for Weight Disentanglement. Kotaro Yoshida, Yuji Naraki, Takafumi Horie, Ryosuke Yamaki, Ryotaro Shimizu, Yuki Saito, Julian J. McAuley, Hiroki Naganuma |
| 2025 | MatExpert: Decomposing Materials Discovery By Mimicking Human Experts. Qianggang Ding, Santiago Miret, Bang Liu |
| 2025 | Matcha: Mitigating Graph Structure Shifts with Test-Time Adaptation. Wenxuan Bao, Zhichen Zeng, Zhining Liu, Hanghang Tong, Jingrui He |
| 2025 | MathCoder2: Better Math Reasoning from Continued Pretraining on Model-translated Mathematical Code. Zimu Lu, Aojun Zhou, Ke Wang, Houxing Ren, Weikang Shi, Junting Pan, Mingjie Zhan, Hongsheng Li |
| 2025 | MathGAP: Out-of-Distribution Evaluation on Problems with Arbitrarily Complex Proofs. Andreas Opedal, Haruki Shirakami, Bernhard Schölkopf, Abulhair Saparov, Mrinmaya Sachan |
| 2025 | Matrix Product Sketching via Coordinated Sampling. Majid Daliri, Juliana Freire, Danrong Li, Christopher Musco |
| 2025 | Matryoshka Multimodal Models. Mu Cai, Jianwei Yang, Jianfeng Gao, Yong Jae Lee |
| 2025 | MatryoshkaKV: Adaptive KV Compression via Trainable Orthogonal Projection. Bokai Lin, Zihao Zeng, Zipeng Xiao, Siqi Kou, Tianqi Hou, Xiaofeng Gao, Hao Zhang, Zhijie Deng |
| 2025 | Matérn Kernels for Tunable Implicit Surface Reconstruction. Maximilian Weiherer, Bernhard Egger |
| 2025 | MaxCutPool: differentiable feature-aware Maxcut for pooling in graph neural networks. Carlo Abate, Filippo Maria Bianchi |
| 2025 | MaxInfoRL: Boosting exploration in reinforcement learning through information gain maximization. Bhavya Sukhija, Stelian Coros, Andreas Krause, Pieter Abbeel, Carmelo Sferrazza |
| 2025 | Maximizing the Potential of Synthetic Data: Insights from Random Matrix Theory. Aymane El Firdoussi, Mohamed El Amine Seddik, Soufiane Hayou, Réda Alami, Ahmed Alzubaidi, Hakim Hacid |
| 2025 | McEval: Massively Multilingual Code Evaluation. Linzheng Chai, Shukai Liu, Jian Yang, Yuwei Yin, Ke Jin, Jiaheng Liu, Tao Sun, Ge Zhang, Changyu Ren, Hongcheng Guo, Noah Wang, Boyang Wang, Xianjie Wu, Bing Wang, Tongliang Li, Liqun Yang, Sufeng Duan, Zhaoxiang Zhang, Zhoujun Li |
| 2025 | MeToken: Uniform Micro-environment Token Boosts Post-Translational Modification Prediction. Cheng Tan, Zhenxiao Cao, Zhangyang Gao, Lirong Wu, Siyuan Li, Yufei Huang, Jun Xia, Bozhen Hu, Stan Z. Li |
| 2025 | Measuring And Improving Engagement of Text-to-Image Generation Models. Varun Khurana, Yaman Kumar Singla, Jayakumar Subramanian, Changyou Chen, Rajiv Ratn Shah, Zhiqiang Xu, Balaji Krishnamurthy |
| 2025 | Measuring And Improving Persuasiveness Of Large Language Models. Somesh Kumar Singh, Yaman Kumar Singla, Harini S. I, Balaji Krishnamurthy |
| 2025 | Measuring Non-Adversarial Reproduction of Training Data in Large Language Models. Michael Aerni, Javier Rando, Edoardo Debenedetti, Nicholas Carlini, Daphne Ippolito, Florian Tramèr |
| 2025 | Measuring and Enhancing Trustworthiness of LLMs in RAG through Grounded Attributions and Learning to Refuse. Maojia Song, Shang Hong Sim, Rishabh Bhardwaj, Hai Leong Chieu, Navonil Majumder, Soujanya Poria |
| 2025 | Measuring memorization in RLHF for code completion. Jamie Hayes, Ilia Shumailov, William P. Porter, Aneesh Pappu |
| 2025 | Mechanism and Emergence of Stacked Attention Heads in Multi-Layer Transformers. Tiberiu Musat |
| 2025 | Mechanistic Permutability: Match Features Across Layers. Nikita Balagansky, Ian Maksimov, Daniil Gavrilov |
| 2025 | MedTrinity-25M: A Large-scale Multimodal Dataset with Multigranular Annotations for Medicine. Yunfei Xie, Ce Zhou, Lang Gao, Juncheng Wu, Xianhang Li, Hong-Yu Zhou, Sheng Liu, Lei Xing, James Zou, Cihang Xie, Yuyin Zhou |
| 2025 | MediConfusion: Can you trust your AI radiologist? Probing the reliability of multimodal medical foundation models. Mohammad Shahab Sepehri, Zalan Fabian, Maryam Soltanolkotabi, Mahdi Soltanolkotabi |
| 2025 | Medium-Difficulty Samples Constitute Smoothed Decision Boundary for Knowledge Distillation on Pruned Datasets. Yudong Chen, Xuwei Xu, Frank de Hoog, Jiajun Liu, Sen Wang |
| 2025 | Meissonic: Revitalizing Masked Generative Transformers for Efficient High-Resolution Text-to-Image Synthesis. Jinbin Bai, Tian Ye, Wei Chow, Enxin Song, Qing-Guo Chen, Xiangtai Li, Zhen Dong, Lei Zhu, Shuicheng Yan |
| 2025 | Memory Efficient Transformer Adapter for Dense Predictions. Dong Zhang, Rui Yan, Pingcheng Dong, Kwang-Ting Cheng |
| 2025 | Memory Mosaics. Jianyu Zhang, Niklas Nolte, Ranajoy Sadhukhan, Beidi Chen, Léon Bottou |
| 2025 | Merging LoRAs like Playing LEGO: Pushing the Modularity of LoRA to Extremes Through Rank-Wise Clustering. Ziyu Zhao, Tao Shen, Didi Zhu, Zexi Li, Jing Su, Xuwu Wang, Fei Wu |
| 2025 | MeshAnything: Artist-Created Mesh Generation with Autoregressive Transformers. Yiwen Chen, Tong He, Di Huang, Weicai Ye, Sijin Chen, Jiaxiang Tang, Zhongang Cai, Lei Yang, Gang Yu, Guosheng Lin, Chi Zhang |
| 2025 | MeshMask: Physics-Based Simulations with Masked Graph Neural Networks. Paul Garnier, Vincent Lannelongue, Jonathan Viquerat, Elie Hachem |
| 2025 | Meta Flow Matching: Integrating Vector Fields on the Wasserstein Manifold. Lazar Atanackovic, Xi Zhang, Brandon Amos, Mathieu Blanchette, Leo J. Lee, Yoshua Bengio, Alexander Tong, Kirill Neklyudov |
| 2025 | Meta-Continual Learning of Neural Fields. Seungyoon Woo, Junhyeog Yun, Gunhee Kim |
| 2025 | Meta-Dynamical State Space Models for Integrative Neural Data Analysis. Ayesha Vermani, Josue Nassar, Hyungju Jeon, Matthew Dowling, Il Memming Park |
| 2025 | MetaDesigner: Advancing Artistic Typography through AI-Driven, User-Centric, and Multilingual WordArt Synthesis. Jun-Yan He, Zhi-Qi Cheng, Chenyang Li, Jingdong Sun, Qi He, Wangmeng Xiang, Hanyuan Chen, Jin-Peng Lan, Xianhui Lin, Kang Zhu, Bin Luo, Yifeng Geng, Xuansong Xie, Alexander G. Hauptmann |
| 2025 | MetaMetrics: Calibrating Metrics for Generation Tasks Using Human Preferences. Genta Indra Winata, David Anugraha, Lucky Susanto, Garry Kuwanto, Derry Tanti Wijaya |
| 2025 | MetaOOD: Automatic Selection of OOD Detection Models. Yuehan Qin, Yichi Zhang, Yi Nian, Xueying Ding, Yue Zhao |
| 2025 | MetaUrban: An Embodied AI Simulation Platform for Urban Micromobility. Wayne Wu, Honglin He, Jack He, Yiran Wang, Chenda Duan, Zhizheng Liu, Quanyi Li, Bolei Zhou |
| 2025 | Metalic: Meta-Learning In-Context with Protein Language Models. Jacob Beck, Shikha Surana, Manus McAuliffe, Oliver Bent, Thomas D. Barrett, Juan Jose Garau-Luis, Paul Duckworth |
| 2025 | Metamizer: A Versatile Neural Optimizer for Fast and Accurate Physics Simulations. Nils Wandel, Stefan Schulz, Reinhard Klein |
| 2025 | MeteoRA: Multiple-tasks Embedded LoRA for Large Language Models. Jingwei Xu, Junyu Lai, Yunpeng Huang |
| 2025 | Methods for Convex (L0, L1)-Smooth Optimization: Clipping, Acceleration, and Adaptivity. Eduard Gorbunov, Nazarii Tupitsa, Sayantan Choudhury, Alen Aliev, Peter Richtárik, Samuel Horváth, Martin Takác |
| 2025 | Methods with Local Steps and Random Reshuffling for Generally Smooth Non-Convex Federated Optimization. Yury Demidovich, Petr Ostroukhov, Grigory Malinovsky, Samuel Horváth, Martin Takác, Peter Richtárik, Eduard Gorbunov |
| 2025 | Metric-Driven Attributions for Vision Transformers. Chase Walker, Sumit Kumar Jha, Rickard Ewetz |
| 2025 | Microcanonical Langevin Ensembles: Advancing the Sampling of Bayesian Neural Networks. Emanuel Sommer, Jakob Robnik, Giorgi Nozadze, Uros Seljak, David Rügamer |
| 2025 | Min-K%++: Improved Baseline for Pre-Training Data Detection from Large Language Models. Jingyang Zhang, Jingwei Sun, Eric C. Yeats, Yang Ouyang, Martin Kuo, Jianyi Zhang, Hao (Frank) Yang, Hai Li |
| 2025 | Mind Control through Causal Inference: Predicting Clean Images from Poisoned Data. Mengxuan Hu, Zihan Guan, Yi Zeng, Junfeng Guo, Zhongliang Zhou, Jielu Zhang, Ruoxi Jia, Anil Kumar S. Vullikanti, Sheng Li |
| 2025 | Mind the GAP: Glimpse-based Active Perception improves generalization and sample efficiency of visual reasoning. Oleh Kolner, Thomas Ortner, Stanislaw Wozniak, Angeliki Pantazi |
| 2025 | Mind the Gap: Examining the Self-Improvement Capabilities of Large Language Models. Yuda Song, Hanlin Zhang, Carson Eisenach, Sham M. Kakade, Dean P. Foster, Udaya Ghai |
| 2025 | MindSearch: Mimicking Human Minds Elicits Deep AI Searcher. Zehui Chen, Kuikun Liu, Qiuchen Wang, Jiangning Liu, Wenwei Zhang, Kai Chen, Feng Zhao |
| 2025 | MindSimulator: Exploring Brain Concept Localization via Synthetic fMRI. Guangyin Bao, Qi Zhang, Zixuan Gong, Zhuojia Wu, Duoqian Miao |
| 2025 | Mini-Monkey: Alleviating the Semantic Sawtooth Effect for Lightweight MLLMs via Complementary Image Pyramid. Mingxin Huang, Yuliang Liu, Dingkang Liang, Lianwen Jin, Xiang Bai |
| 2025 | Mini-batch Coresets for Memory-efficient Language Model Training on Data Mixtures. Dang Nguyen, Wenhan Yang, Rathul Anand, Yu Yang, Baharan Mirzasoleiman |
| 2025 | MiniPLM: Knowledge Distillation for Pre-training Language Models. Yuxian Gu, Hao Zhou, Fandong Meng, Jie Zhou, Minlie Huang |
| 2025 | Minimal Impact ControlNet: Advancing Multi-ControlNet Integration. Shikun Sun, Min Zhou, Zixuan Wang, Xubin Li, Tiezheng Ge, Zijie Ye, Xiaoyu Qin, Junliang Xing, Bo Zheng, Jia Jia |
| 2025 | Minimal Variance Model Aggregation: A principled, non-intrusive, and versatile integration of black box models. Théo Bourdais, Houman Owhadi |
| 2025 | Minimalistic Predictions for Online Class Constraint Scheduling. Dorian Guyot, Alexandra Anna Lassota |
| 2025 | Minimax Optimal Reinforcement Learning with Quasi-Optimism. Harin Lee, Min-hwan Oh |
| 2025 | Minimax Optimal Two-Stage Algorithm For Moment Estimation Under Covariate Shift. Zhen Zhang, Xin Liu, Shaoli Wang, Jiaye Teng |
| 2025 | Mining your own secrets: Diffusion Classifier Scores for Continual Personalization of Text-to-Image Diffusion Models. Saurav Jha, Shiqi Yang, Masato Ishii, Mengjie Zhao, Christian Simon, Muhammad Jehanzeb Mirza, Dong Gong, Lina Yao, Shusuke Takahashi, Yuki Mitsufuji |
| 2025 | Misspecified Q-Learning with Sparse Linear Function Approximation: Tight Bounds on Approximation Error. Ally Yalei Du, Lin Yang, Ruosong Wang |
| 2025 | Mitigate the Gap: Improving Cross-Modal Alignment in CLIP. Sedigheh Eslami, Gerard de Melo |
| 2025 | Mitigating Information Loss in Tree-Based Reinforcement Learning via Direct Optimization. Sascha Marton, Tim Grams, Florian Vogt, Stefan Lüdtke, Christian Bartelt, Heiner Stuckenschmidt |
| 2025 | Mitigating Memorization in Language Models. Mansi Sakarvadia, Aswathy Ajith, Arham Mushtaq Khan, Nathaniel C. Hudson, Caleb Geniesse, Kyle Chard, Yaoqing Yang, Ian T. Foster, Michael W. Mahoney |
| 2025 | Mitigating Modality Prior-Induced Hallucinations in Multimodal Large Language Models via Deciphering Attention Causality. Guanyu Zhou, Yibo Yan, Xin Zou, Kun Wang, Aiwei Liu, Xuming Hu |
| 2025 | Mitigating Object Hallucination in MLLMs via Data-augmented Phrase-level Alignment. Pritam Sarkar, Sayna Ebrahimi, Ali Etemad, Ahmad Beirami, Sercan Ö. Arik, Tomas Pfister |
| 2025 | Mitigating Parameter Interference in Model Merging via Sharpness-Aware Fine-Tuning. Yeoreum Lee, Jinwook Jung, Sungyong Baik |
| 2025 | Mitigating Reward Over-Optimization in RLHF via Behavior-Supported Regularization. Juntao Dai, Taiye Chen, Yaodong Yang, Qian Zheng, Gang Pan |
| 2025 | Mitigating Spurious Correlations in Zero-Shot Multimodal Models. Shenyu Lu, Junyi Chai, Xiaoqian Wang |
| 2025 | Mitigating the Backdoor Effect for Multi-Task Model Merging via Safety-Aware Subspace. Jinluan Yang, Anke Tang, Didi Zhu, Zhengyu Chen, Li Shen, Fei Wu |
| 2025 | Mix-CPT: A Domain Adaptation Framework via Decoupling Knowledge Learning and Format Alignment. Jinhao Jiang, Junyi Li, Xin Zhao, Yang Song, Tao Zhang, Ji-Rong Wen |
| 2025 | Mix-LN: Unleashing the Power of Deeper Layers by Combining Pre-LN and Post-LN. Pengxiang Li, Lu Yin, Shiwei Liu |
| 2025 | MixEval-X: Any-to-any Evaluations from Real-world Data Mixture. Jinjie Ni, Yifan Song, Deepanway Ghosal, Bo Li, David Junhao Zhang, Xiang Yue, Fuzhao Xue, Yuntian Deng, Zian Zheng, Kaichen Zhang, Mahir Shah, Kabir Jain, Yang You, Michael Shieh |
| 2025 | MixMax: Distributional Robustness in Function Space via Optimal Data Mixtures. Anvith Thudi, Chris J. Maddison |
| 2025 | Mixture Compressor for Mixture-of-Experts LLMs Gains More. Wei Huang, Yue Liao, JianHui Liu, Ruifei He, Haoru Tan, Shiming Zhang, Hongsheng Li, Si Liu, Xiaojuan Qi |
| 2025 | Mixture of Attentions For Speculative Decoding. Matthieu Zimmer, Milan Gritta, Gerasimos Lampouras, Haitham Bou-Ammar, Jun Wang |
| 2025 | Mixture of Experts Made Personalized: Federated Prompt Learning for Vision-Language Models. Jun Luo, Chen Chen, Shandong Wu |
| 2025 | Mixture of In-Context Prompters for Tabular PFNs. Derek Qiang Xu, F. Olcay Cirit, Reza Asadi, Yizhou Sun, Wei Wang |
| 2025 | Mixture of Parrots: Experts improve memorization more than reasoning. Samy Jelassi, Clara Mohri, David Brandfonbrener, Alex Gu, Nikhil Vyas, Nikhil Anand, David Alvarez-Melis, Yuanzhi Li, Sham M. Kakade, Eran Malach |
| 2025 | Mixture-of-Agents Enhances Large Language Model Capabilities. Junlin Wang, Jue Wang, Ben Athiwaratkun, Ce Zhang, James Zou |
| 2025 | Mm-Embed: Universal Multimodal Retrieval with Multimodal LLMS. Sheng-Chieh Lin, Chankyu Lee, Mohammad Shoeybi, Jimmy Lin, Bryan Catanzaro, Wei Ping |
| 2025 | MoDGS: Dynamic Gaussian Splatting from Casually-captured Monocular Videos with Depth Priors. Qingming Liu, Yuan Liu, Jiepeng Wang, Xianqiang Lyu, Peng Wang, Wenping Wang, Junhui Hou |
| 2025 | MoDeGPT: Modular Decomposition for Large Language Model Compression. Chi-Heng Lin, Shangqian Gao, James Seale Smith, Abhishek Patel, Shikhar Tuli, Yilin Shen, Hongxia Jin, Yen-Chang Hsu |
| 2025 | MoE++: Accelerating Mixture-of-Experts Methods with Zero-Computation Experts. Peng Jin, Bo Zhu, Li Yuan, Shuicheng Yan |
| 2025 | MoLEx: Mixture of Layer Experts for Fine-tuning with Sparse Upcycling. Rachel S. Y. Teo, Tan Minh Nguyen |
| 2025 | MoS: Unleashing Parameter Efficiency of Low-Rank Adaptation with Mixture of Shards. Sheng Wang, Liheng Chen, Pengan Chen, Jingwei Dong, Boyang Xue, Jiyue Jiang, Lingpeng Kong, Chuan Wu |
| 2025 | Modality-Specialized Synergizers for Interleaved Vision-Language Generalists. Zhiyang Xu, Minqian Liu, Ying Shen, Joy Rimchala, Jiaxin Zhang, Qifan Wang, Yu Cheng, Lifu Huang |
| 2025 | Model Editing as a Robust and Denoised variant of DPO: A Case Study on Toxicity. Rheeya Uppaal, Apratim Dey, Yiting He, Yiqiao Zhong, Junjie Hu |
| 2025 | Model Equality Testing: Which Model is this API Serving? Irena Gao, Percy Liang, Carlos Guestrin |
| 2025 | Model Risk-sensitive Offline Reinforcement Learning. Gwangpyo Yoo, Honguk Woo |
| 2025 | Model merging with SVD to tie the Knots. George Stoica, Pratik Ramesh, Boglarka Ecsedi, Leshem Choshen, Judy Hoffman |
| 2025 | Model-Agnostic Knowledge Guided Correction for Improved Neural Surrogate Rollout. Bharat Srikishan, Daniel O'Malley, Mohamed Mehana, Nicholas Lubbers, Nikhil Muralidhar |
| 2025 | Model-Free Offline Reinforcement Learning with Enhanced Robustness. Chi Zhang, Zain Ulabedeen Farhat, George K. Atia, Yue Wang |
| 2025 | Model-agnostic meta-learners for estimating heterogeneous treatment effects over time. Dennis Frauen, Konstantin Hess, Stefan Feuerriegel |
| 2025 | Model-based Offline Reinforcement Learning with Lower Expectile Q-Learning. Kwanyoung Park, Youngwoon Lee |
| 2025 | Model-based RL as a Minimalist Approach to Horizon-Free and Second-Order Bounds. Zhiyong Wang, Dongruo Zhou, John C. S. Lui, Wen Sun |
| 2025 | Modeling Complex System Dynamics with Flow Matching Across Time and Conditions. Martin Rohbeck, Edward De Brouwer, Charlotte Bunne, Jan-Christian Huetter, Anne Biton, Kelvin Y. Chen, Aviv Regev, Romain Lopez |
| 2025 | Modeling Fine-Grained Hand-Object Dynamics for Egocentric Video Representation Learning. Baoqi Pei, Yifei Huang, Jilan Xu, Guo Chen, Yuping He, Lijin Yang, Yali Wang, Weidi Xie, Yu Qiao, Fei Wu, Limin Wang |
| 2025 | Modeling Future Conversation Turns to Teach LLMs to Ask Clarifying Questions. Michael J. Q. Zhang, W. Bradley Knox, Eunsol Choi |
| 2025 | Modeling Unseen Environments with Language-guided Composable Causal Components in Reinforcement Learning. Xinyue Wang, Biwei Huang |
| 2025 | Modeling dynamic social vision highlights gaps between deep learning and humans. Kathy Garcia, Emalie McMahon, Colin Conwell, Michael F. Bonner, Leyla Isik |
| 2025 | MolSpectra: Pre-training 3D Molecular Representation with Multi-modal Energy Spectra. Liang Wang, Shaozhen Liu, Yu Rong, Deli Zhao, Qiang Liu, Shu Wu, Liang Wang |
| 2025 | MonST3R: A Simple Approach for Estimating Geometry in the Presence of Motion. Junyi Zhang, Charles Herrmann, Junhwa Hur, Varun Jampani, Trevor Darrell, Forrester Cole, Deqing Sun, Ming-Hsuan Yang |
| 2025 | Moner: Motion Correction in Undersampled Radial MRI with Unsupervised Neural Representation. Qing Wu, Chenhe Du, Xuanyu Tian, Jingyi Yu, Yuyao Zhang, Hongjiang Wei |
| 2025 | Monet: Mixture of Monosemantic Experts for Transformers. Jungwoo Park, Ahn Young Jin, Kee-Eung Kim, Jaewoo Kang |
| 2025 | Monitoring Latent World States in Language Models with Propositional Probes. Jiahai Feng, Stuart Russell, Jacob Steinhardt |
| 2025 | Monte Carlo Planning with Large Language Model for Text-Based Game Agents. Zijing Shi, Meng Fang, Ling Chen |
| 2025 | Montessori-Instruct: Generate Influential Training Data Tailored for Student Learning. Xiaochuan Li, Zichun Yu, Chenyan Xiong |
| 2025 | Moral Alignment for LLM Agents. Elizaveta Tennant, Stephen Hailes, Mirco Musolesi |
| 2025 | More Experts Than Galaxies: Conditionally-Overlapping Experts with Biologically-Inspired Fixed Routing. Sagi Shaier, Francisco Pereira, Katharina von der Wense, Lawrence Hunter, Matt Jones |
| 2025 | More RLHF, More Trust? On The Impact of Preference Alignment On Trustworthiness. Aaron Jiaxun Li, Satyapriya Krishna, Himabindu Lakkaraju |
| 2025 | Morphing Tokens Draw Strong Masked Image Models. Taekyung Kim, Byeongho Heo, Dongyoon Han |
| 2025 | MorphoDiff: Cellular Morphology Painting with Diffusion Models. Zeinab Navidi, Jun Ma, Esteban Miglietta, Le Liu, Anne E. Carpenter, Beth A. Cimini, Benjamin Haibe-Kains, Bo Wang |
| 2025 | MotherNet: Fast Training and Inference via Hyper-Network Transformers. Andreas C. Mueller, Carlo Curino, Raghu Ramakrishnan |
| 2025 | Motion Control of High-Dimensional Musculoskeletal Systems with Hierarchical Model-Based Planning. Yunyue Wei, Shanning Zhuang, Vincent Zhuang, Yanan Sui |
| 2025 | Motion-Agent: A Conversational Framework for Human Motion Generation with LLMs. Qi Wu, Yubo Zhao, Yifan Wang, Xinhang Liu, Yu-Wing Tai, Chi-Keung Tang |
| 2025 | MotionAura: Generating High-Quality and Motion Consistent Videos using Discrete Diffusion. Onkar Kishor Susladkar, Jishu Sen Gupta, Chirag Sehgal, Sparsh Mittal, Rekha Singhal |
| 2025 | MotionClone: Training-Free Motion Cloning for Controllable Video Generation. Pengyang Ling, Jiazi Bu, Pan Zhang, Xiaoyi Dong, Yuhang Zang, Tong Wu, Huaian Chen, Jiaqi Wang, Yi Jin |
| 2025 | MotionDreamer: One-to-Many Motion Synthesis with Localized Generative Masked Transformer. Yilin Wang, Chuan Guo, Yuxuan Mu, Muhammad Gohar Javed, Xinxin Zuo, Juwei Lu, Hai Jiang, Li Cheng |
| 2025 | MovieDreamer: Hierarchical Generation for Coherent Long Visual Sequences. Canyu Zhao, Mingyu Liu, Wen Wang, Weihua Chen, Fan Wang, Hao Chen, Bo Zhang, Chunhua Shen |
| 2025 | MrSteve: Instruction-Following Agents in Minecraft with What-Where-When Memory. Junyeong Park, Junmo Cho, Sungjin Ahn |
| 2025 | MrT5: Dynamic Token Merging for Efficient Byte-level Language Models. Julie Kallini, Shikhar Murty, Christopher D. Manning, Christopher Potts, Róbert Csordás |
| 2025 | MuHBoost: Multi-Label Boosting For Practical Longitudinal Human Behavior Modeling. Nguyen T. Thach, Patrick Habecker, Anika R. Eisenbraun, Alex Mason, Kimberly Tyler, Bilal Khan, Hau Chan |
| 2025 | MuPT: A Generative Symbolic Music Pretrained Transformer. Xingwei Qu, Yuelin Bai, Yinghao Ma, Ziya Zhou, Ka Man Lo, Jiaheng Liu, Ruibin Yuan, Lejun Min, Xueling Liu, Tianyu Zhang, Xeron Du, Shuyue Guo, Yiming Liang, Yizhi Li, Shangda Wu, Junting Zhou, Tianyu Zheng, Ziyang Ma, Fengze Han, Wei Xue, Gus Xia, Emmanouil Benetos, Xiang Yue, Chenghua Lin, Xu Tan, Wenhao Huang, Jie Fu, Ge Zhang |
| 2025 | Mufu: Multilingual Fused Learning for Low-Resource Translation with LLM. Zheng Wei Lim, Nitish Gupta, Honglin Yu, Trevor Cohn |
| 2025 | MuirBench: A Comprehensive Benchmark for Robust Multi-image Understanding. Fei Wang, Xingyu Fu, James Y. Huang, Zekun Li, Qin Liu, Xiaogeng Liu, Mingyu Derek Ma, Nan Xu, Wenxuan Zhou, Kai Zhang, Tianyi Lorena Yan, Wenjie Jacky Mo, Hsiang-Hui Liu, Pan Lu, Chunyuan Li, Chaowei Xiao, Kai-Wei Chang, Dan Roth, Sheng Zhang, Hoifung Poon, Muhao Chen |
| 2025 | Multi-Dimensional Conformal Prediction. Yam Tawachi, Bracha Laufer-Goldshtein |
| 2025 | Multi-Draft Speculative Sampling: Canonical Decomposition and Theoretical Limits. Ashish J. Khisti, MohammadReza Ebrahimi, Hassan Dbouk, Arash Behboodi, Roland Memisevic, Christos Louizos |
| 2025 | Multi-Field Adaptive Retrieval. Millicent Li, Tongfei Chen, Benjamin Van Durme, Patrick Xia |
| 2025 | Multi-Label Node Classification with Label Influence Propagation. Yifei Sun, Zemin Liu, Bryan Hooi, Yang Yang, Rizal Fathony, Jia Chen, Bingsheng He |
| 2025 | Multi-Label Test-Time Adaptation with Bound Entropy Minimization. Xiangyu Wu, Feng Yu, Yang Yang, Qing-Guo Chen, Jianfeng Lu |
| 2025 | Multi-Modal and Multi-Attribute Generation of Single Cells with CFGen. Alessandro Palma, Till Richter, Hanyi Zhang, Manuel Lubetzki, Alexander Tong, Andrea Dittadi, Fabian J. Theis |
| 2025 | Multi-Perspective Data Augmentation for Few-shot Object Detection. Anh-Khoa Nguyen Vu, Quoc-Truong Truong, Vinh-Tiep Nguyen, Thanh Duc Ngo, Thanh-Toan Do, Tam V. Nguyen |
| 2025 | Multi-Resolution Decomposable Diffusion Model for Non-Stationary Time Series Anomaly Detection. Guojin Zhong, Pan Wang, Jin Yuan, Zhiyong Li, Long Chen |
| 2025 | Multi-Reward as Condition for Instruction-based Image Editing. Xin Gu, Ming Li, Libo Zhang, Fan Chen, Longyin Wen, Tiejian Luo, Sijie Zhu |
| 2025 | Multi-Robot Motion Planning with Diffusion Models. Yorai Shaoul, Itamar Mishani, Shivam Vats, Jiaoyang Li, Maxim Likhachev |
| 2025 | Multi-Scale Fusion for Object Representation. Rongzhen Zhao, Vivienne Huiling Wang, Juho Kannala, Joni Pajarinen |
| 2025 | Multi-Task Corrupted Prediction for Learning Robust Audio-Visual Speech Representation. Sungnyun Kim, Sungwoo Cho, Sangmin Bae, Kangwook Jang, Se-Young Yun |
| 2025 | Multi-Task Dense Predictions via Unleashing the Power of Diffusion. Yuqi Yang, Peng-Tao Jiang, Qibin Hou, Hao Zhang, Jinwei Chen, Bo Li |
| 2025 | Multi-agent cooperation through learning-aware policy gradients. Alexander Meulemans, Seijin Kobayashi, Johannes von Oswald, Nino Scherrer, Eric Elmoznino, Blake Aaron Richards, Guillaume Lajoie, Blaise Agüera y Arcas, João Sacramento |
| 2025 | Multi-domain Distribution Learning for De Novo Drug Design. Arne Schneuing, Ilia Igashov, Adrian W. Dobbelstein, Thomas Castiglione, Michael M. Bronstein, Bruno Correia |
| 2025 | Multi-level Certified Defense Against Poisoning Attacks in Offline Reinforcement Learning. Shijie Liu, Andrew Craig Cullen, Paul Montague, Sarah Monazam Erfani, Benjamin I. P. Rubinstein |
| 2025 | Multi-modal Agent Tuning: Building a VLM-Driven Agent for Efficient Tool Usage. Zhi Gao, Bofei Zhang, Pengxiang Li, Xiaojian Ma, Tao Yuan, Yue Fan, Yuwei Wu, Yunde Jia, Song-Chun Zhu, Qing Li |
| 2025 | Multi-modal brain encoding models for multi-modal stimuli. Subba Reddy Oota, Khushbu Pahwa, Mounika Marreddy, Maneesh Kumar Singh, Manish Gupta, Bapi Raju Surampudi |
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| 2025 | Multi-objective antibody design with constrained preference optimization. Milong Ren, ZaiKai He, Haicang Zhang |
| 2025 | Multi-session, multi-task neural decoding from distinct cell-types and brain regions. Mehdi Azabou, Krystal Xuejing Pan, Vinam Arora, Ian Jarratt Knight, Eva L. Dyer, Blake Aaron Richards |
| 2025 | Multiagent Finetuning: Self Improvement with Diverse Reasoning Chains. Vighnesh Subramaniam, Yilun Du, Joshua B. Tenenbaum, Antonio Torralba, Shuang Li, Igor Mordatch |
| 2025 | Multilevel Generative Samplers for Investigating Critical Phenomena. Ankur Singha, Elia Cellini, Kim Andrea Nicoli, Karl Jansen, Stefan Kühn, Shinichi Nakajima |
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| 2025 | Multimodal Lego: Model Merging and Fine-Tuning Across Topologies and Modalities in Biomedicine. Konstantin Hemker, Nikola Simidjievski, Mateja Jamnik |
| 2025 | Multimodal Quantitative Language for Generative Recommendation. Jianyang Zhai, Zi-Feng Mai, Chang-Dong Wang, Feidiao Yang, Xiawu Zheng, Hui Li, Yonghong Tian |
| 2025 | Multimodal Situational Safety. Kaiwen Zhou, Chengzhi Liu, Xuandong Zhao, Anderson Compalas, Dawn Song, Xin Eric Wang |
| 2025 | Multimodal Unsupervised Domain Generalization by Retrieving Across the Modality Gap. Christopher Liao, Christian So, Theodoros Tsiligkaridis, Brian Kulis |
| 2025 | Multimodality Helps Few-shot 3D Point Cloud Semantic Segmentation. Zhaochong An, Guolei Sun, Yun Liu, Runjia Li, Min Wu, Ming-Ming Cheng, Ender Konukoglu, Serge J. Belongie |
| 2025 | Multiple Heads are Better than One: Mixture of Modality Knowledge Experts for Entity Representation Learning. Yichi Zhang, Zhuo Chen, Lingbing Guo, Yajing Xu, Binbin Hu, Ziqi Liu, Wen Zhang, Huajun Chen |
| 2025 | Multiplicative Logit Adjustment Approximates Neural-Collapse-Aware Decision Boundary Adjustment. Naoya Hasegawa, Issei Sato |
| 2025 | Multiview Equivariance Improves 3D Correspondence Understanding with Minimal Feature Finetuning. Yang You, Yixin Li, Congyue Deng, Yue Wang, Leonidas J. Guibas |
| 2025 | MuseGNN: Forming Scalable, Convergent GNN Layers that Minimize a Sampling-Based Energy. Haitian Jiang, Renjie Liu, Zengfeng Huang, Yichuan Wang, Xiao Yan, Zhenkun Cai, Minjie Wang, David Wipf |
| 2025 | Mutual Effort for Efficiency: A Similarity-based Token Pruning for Vision Transformers in Self-Supervised Learning. Sheng Li, Qitao Tan, Yue Dai, Zhenglun Kong, Tianyu Wang, Jun Liu, Ao Li, Ninghao Liu, Yufei Ding, Xulong Tang, Geng Yuan |
| 2025 | Mutual Reasoning Makes Smaller LLMs Stronger Problem-Solver. Zhenting Qi, Mingyuan Ma, Jiahang Xu, Li Lyna Zhang, Fan Yang, Mao Yang |
| 2025 | N-ForGOT: Towards Not-forgetting and Generalization of Open Temporal Graph Learning. Liping Wang, Xujia Li, Jingshu Peng, Yue Wang, Chen Zhang, Yan Zhou, Lei Chen |
| 2025 | ND-SDF: Learning Normal Deflection Fields for High-Fidelity Indoor Reconstruction. Ziyu Tang, Weicai Ye, Yifan Wang, Di Huang, Hujun Bao, Tong He, Guofeng Zhang |
| 2025 | NEAR: A Training-Free Pre-Estimator of Machine Learning Model Performance. Raphael T. Husistein, Markus Reiher, Marco Eckhoff |
| 2025 | NExT-Mol: 3D Diffusion Meets 1D Language Modeling for 3D Molecule Generation. Zhiyuan Liu, Yanchen Luo, Han Huang, Enzhi Zhang, Sihang Li, Junfeng Fang, Yaorui Shi, Xiang Wang, Kenji Kawaguchi, Tat-Seng Chua |
| 2025 | NExUME: Adaptive Training and Inference for DNNs under Intermittent Power Environments. Cyan Subhra Mishra, Deeksha Chaudhary, Jack Sampson, Mahmut T. Kandemir, Chita R. Das |
| 2025 | NL-Eye: Abductive NLI For Images. Mor Ventura, Michael Toker, Nitay Calderon, Zorik Gekhman, Yonatan Bitton, Roi Reichart |
| 2025 | NNsight and NDIF: Democratizing Access to Open-Weight Foundation Model Internals. Jaden Fried Fiotto-Kaufman, Alexander Russell Loftus, Eric Todd, Jannik Brinkmann, Koyena Pal, Dmitrii Troitskii, Michael Ripa, Adam Belfki, Can Rager, Caden Juang, Aaron Mueller, Samuel Marks, Arnab Sen Sharma, Francesca Lucchetti, Nikhil Prakash, Carla E. Brodley, Arjun Guha, Jonathan Bell, Byron C. Wallace, David Bau |
| 2025 | NRGBoost: Energy-Based Generative Boosted Trees. João Bravo |
| 2025 | NUDGE: Lightweight Non-Parametric Fine-Tuning of Embeddings for Retrieval. Sepanta Zeighami, Zac Wellmer, Aditya G. Parameswaran |
| 2025 | NV-Embed: Improved Techniques for Training LLMs as Generalist Embedding Models. Chankyu Lee, Rajarshi Roy, Mengyao Xu, Jonathan Raiman, Mohammad Shoeybi, Bryan Catanzaro, Wei Ping |
| 2025 | NVS-Solver: Video Diffusion Model as Zero-Shot Novel View Synthesizer. Meng You, Zhiyu Zhu, Hui Liu, Junhui Hou |
| 2025 | NarrativeBridge: Enhancing Video Captioning with Causal-Temporal Narrative. Asmar Nadeem, Faegheh Sardari, Robert Dawes, Syed Sameed Husain, Adrian Hilton, Armin Mustafa |
| 2025 | Narrowing Information Bottleneck Theory for Multimodal Image-Text Representations Interpretability. Zhiyu Zhu, Zhibo Jin, Jiayu Zhang, Nan Yang, Jiahao Huang, Jianlong Zhou, Fang Chen |
| 2025 | Natural Language Inference Improves Compositionality in Vision-Language Models. Paola Cascante-Bonilla, Yu Hou, Yang Trista Cao, Hal Daumé III, Rachel Rudinger |
| 2025 | NatureLM-audio: an Audio-Language Foundation Model for Bioacoustics. David Robinson, Marius Miron, Masato Hagiwara, Olivier Pietquin |
| 2025 | Navigating Neural Space: Revisiting Concept Activation Vectors to Overcome Directional Divergence. Frederik Pahde, Maximilian Dreyer, Moritz Weckbecker, Leander Weber, Christopher J. Anders, Thomas Wiegand, Wojciech Samek, Sebastian Lapuschkin |
| 2025 | Navigating the Digital World as Humans Do: Universal Visual Grounding for GUI Agents. Boyu Gou, Ruohan Wang, Boyuan Zheng, Yanan Xie, Cheng Chang, Yiheng Shu, Huan Sun, Yu Su |
| 2025 | Navigation-Guided Sparse Scene Representation for End-to-End Autonomous Driving. Peidong Li, Dixiao Cui |
| 2025 | NeRAF: 3D Scene Infused Neural Radiance and Acoustic Fields. Amandine Brunetto, Sascha Hornauer, Fabien Moutarde |
| 2025 | NeSyC: A Neuro-symbolic Continual Learner For Complex Embodied Tasks in Open Domains. Wonje Choi, Jinwoo Park, Sanghyun Ahn, Daehee Lee, Honguk Woo |
| 2025 | Near, far: Patch-ordering enhances vision foundation models' scene understanding. Valentinos Pariza, Mohammadreza Salehi, Gertjan J. Burghouts, Francesco Locatello, Yuki M. Asano |
| 2025 | Near-Exact Privacy Amplification for Matrix Mechanisms. Christopher A. Choquette-Choo, Arun Ganesh, Saminul Haque, Thomas Steinke, Abhradeep Guha Thakurta |
| 2025 | Near-Optimal Online Learning for Multi-Agent Submodular Coordination: Tight Approximation and Communication Efficiency. Qixin Zhang, Zongqi Wan, Yu Yang, Li Shen, Dacheng Tao |
| 2025 | Near-Optimal Policy Identification in Robust Constrained Markov Decision Processes via Epigraph Form. Toshinori Kitamura, Tadashi Kozuno, Wataru Kumagai, Kenta Hoshino, Yohei Hosoe, Kazumi Kasaura, Masashi Hamaya, Paavo Parmas, Yutaka Matsuo |
| 2025 | Near-optimal Active Regression of Single-Index Models. Yi Li, Wai Ming Tai |
| 2025 | Needle In A Video Haystack: A Scalable Synthetic Evaluator for Video MLLMs. Zijia Zhao, Haoyu Lu, Yuqi Huo, Yifan Du, Tongtian Yue, Longteng Guo, Bingning Wang, Weipeng Chen, Jing Liu |
| 2025 | Needle Threading: Can LLMs Follow Threads Through Near-Million-Scale Haystacks? Jonathan Roberts, Kai Han, Samuel Albanie |
| 2025 | Nesterov acceleration in benignly non-convex landscapes. Kanan Gupta, Stephan Wojtowytsch |
| 2025 | NetFormer: An interpretable model for recovering dynamical connectivity in neuronal population dynamics. Ziyu Lu, Wuwei Zhang, Trung Le, Hao Wang, Uygar Sümbül, Eric Todd Shea-Brown, Lu Mi |
| 2025 | NetMoE: Accelerating MoE Training through Dynamic Sample Placement. Xinyi Liu, Yujie Wang, Fangcheng Fu, Xupeng Miao, Shenhan Zhu, Xiaonan Nie, Bin Cui |
| 2025 | NeurFlow: Interpreting Neural Networks through Neuron Groups and Functional Interactions. Tue Minh Cao, Nhat Hoang-Xuan, Hieu H. Pham, Phi Le Nguyen, My T. Thai |
| 2025 | Neural Approximate Mirror Maps for Constrained Diffusion Models. Berthy Feng, Ricardo Baptista, Katherine L. Bouman |
| 2025 | Neural Causal Graph for Interpretable and Intervenable Classification. Jiawei Wang, Shaofei Lu, Da Cao, Dongyu Wang, Yuquan Le, Zhe Quan, Tat-Seng Chua |
| 2025 | Neural Context Flows for Meta-Learning of Dynamical Systems. Roussel Desmond Nzoyem, David A. W. Barton, Tom Deakin |
| 2025 | Neural Dueling Bandits: Preference-Based Optimization with Human Feedback. Arun Verma, Zhongxiang Dai, Xiaoqiang Lin, Patrick Jaillet, Bryan Kian Hsiang Low |
| 2025 | Neural Eulerian Scene Flow Fields. Kyle Vedder, Neehar Peri, Ishan Khatri, Siyi Li, Eric Eaton, Mehmet Kemal Kocamaz, Yue Wang, Zhiding Yu, Deva Ramanan, Joachim Pehserl |
| 2025 | Neural Exploratory Landscape Analysis for Meta-Black-Box-Optimization. Zeyuan Ma, Jiacheng Chen, Hongshu Guo, Yue-Jiao Gong |
| 2025 | Neural Fluid Simulation on Geometric Surfaces. Haoxiang Wang, Tao Yu, Hui Qiao, Qionghai Dai |
| 2025 | Neural Functions for Learning Periodic Signal. Woojin Cho, Minju Jo, Kookjin Lee, Noseong Park |
| 2025 | Neural Interactive Proofs. Lewis Hammond, Sam Adam-Day |
| 2025 | Neural Multi-Objective Combinatorial Optimization via Graph-Image Multimodal Fusion. Jinbiao Chen, Jiahai Wang, Zhiguang Cao, Yaoxin Wu |
| 2025 | Neural ODE Transformers: Analyzing Internal Dynamics and Adaptive Fine-tuning. Anh Tong, Thanh Nguyen-Tang, Dongeun Lee, Duc Nguyen, Toan M. Tran, David Leo Wright Hall, Cheongwoong Kang, Jaesik Choi |
| 2025 | Neural Phylogeny: Fine-Tuning Relationship Detection among Neural Networks. Runpeng Yu, Xinchao Wang |
| 2025 | Neural Sampling from Boltzmann Densities: Fisher-Rao Curves in the Wasserstein Geometry. Jannis Chemseddine, Christian Wald, Richard Duong, Gabriele Steidl |
| 2025 | Neural Spacetimes for DAG Representation Learning. Haitz Sáez de Ocáriz Borde, Anastasis Kratsios, Marc T. Law, Xiaowen Dong, Michael M. Bronstein |
| 2025 | Neural Stochastic Differential Equations for Uncertainty-Aware Offline RL. Cevahir Köprülü, Franck Djeumou, Ufuk Topcu |
| 2025 | Neural Wave Equation for Irregularly Sampled Sequence Data. Arkaprava Majumdar, M. Anand Krishna, P. K. Srijith |
| 2025 | Neural networks on Symmetric Spaces of Noncompact Type. Xuan Son Nguyen, Shuo Yang, Aymeric Histace |
| 2025 | NeuralPlane: Structured 3D Reconstruction in Planar Primitives with Neural Fields. Hanqiao Ye, Yuzhou Liu, Yangdong Liu, Shuhan Shen |
| 2025 | Neuralized Markov Random Field for Interaction-Aware Stochastic Human Trajectory Prediction. Zilin Fang, David Hsu, Gim Hee Lee |
| 2025 | NeuroLM: A Universal Multi-task Foundation Model for Bridging the Gap between Language and EEG Signals. Weibang Jiang, Yansen Wang, Bao-Liang Lu, Dongsheng Li |
| 2025 | Neuron Platonic Intrinsic Representation From Dynamics Using Contrastive Learning. Wei Wu, Can Liao, Zizhen Deng, Zhengrui Guo, Jinzhuo Wang |
| 2025 | Neuron based Personality Trait Induction in Large Language Models. Jia Deng, Tianyi Tang, Yanbin Yin, Wenhao Yang, Xin Zhao, Ji-Rong Wen |
| 2025 | Neuron-based Multifractal Analysis of Neuron Interaction Dynamics in Large Models. Xiongye Xiao, Heng Ping, Chenyu Zhou, Defu Cao, Yaxing Li, Yizhuo Zhou, Shixuan Li, Nikos Kanakaris, Paul Bogdan |
| 2025 | Neuroplastic Expansion in Deep Reinforcement Learning. Jiashun Liu, Johan S. Obando-Ceron, Aaron C. Courville, Ling Pan |
| 2025 | New Algorithms for the Learning-Augmented k-means Problem. Junyu Huang, Qilong Feng, Ziyun Huang, Zhen Zhang, Jinhui Xu, Jianxin Wang |
| 2025 | Newton Meets Marchenko-Pastur: Massively Parallel Second-Order Optimization with Hessian Sketching and Debiasing. Elad Romanov, Fangzhao Zhang, Mert Pilanci |
| 2025 | NextBestPath: Efficient 3D Mapping of Unseen Environments. Shiyao Li, Antoine Guédon, Clémentin Boittiaux, Shizhe Chen, Vincent Lepetit |
| 2025 | No Equations Needed: Learning System Dynamics Without Relying on Closed-Form ODEs. Krzysztof Kacprzyk, Mihaela van der Schaar |
| 2025 | No Free Lunch: Fundamental Limits of Learning Non-Hallucinating Generative Models. Changlong Wu, Ananth Grama, Wojciech Szpankowski |
| 2025 | No Location Left Behind: Measuring and Improving the Fairness of Implicit Representations for Earth Data. Daniel Cai, Randall Balestriero |
| 2025 | No Need to Talk: Asynchronous Mixture of Language Models. Anastasiia Filippova, Angelos Katharopoulos, David Grangier, Ronan Collobert |
| 2025 | No Pose, No Problem: Surprisingly Simple 3D Gaussian Splats from Sparse Unposed Images. Botao Ye, Sifei Liu, Haofei Xu, Xueting Li, Marc Pollefeys, Ming-Hsuan Yang, Songyou Peng |
| 2025 | No Preference Left Behind: Group Distributional Preference Optimization. Binwei Yao, Zefan Cai, Yun-Shiuan Chuang, Shanglin Yang, Ming Jiang, Diyi Yang, Junjie Hu |
| 2025 | No Training, No Problem: Rethinking Classifier-Free Guidance for Diffusion Models. Seyedmorteza Sadat, Manuel Kansy, Otmar Hilliges, Romann M. Weber |
| 2025 | NoVo: Norm Voting off Hallucinations with Attention Heads in Large Language Models. Zheng Yi Ho, Siyuan Liang, Sen Zhang, Yibing Zhan, Dacheng Tao |
| 2025 | Node Identifiers: Compact, Discrete Representations for Efficient Graph Learning. Yuankai Luo, Hongkang Li, Qijiong Liu, Lei Shi, Xiao-Ming Wu |
| 2025 | Node Similarities under Random Projections: Limits and Pathological Cases. Tvrtko Tadic, Cassiano O. Becker, Jennifer Neville |
| 2025 | Node-Time Conditional Prompt Learning in Dynamic Graphs. Xingtong Yu, Zhenghao Liu, Xinming Zhang, Yuan Fang |
| 2025 | Noise Separation guided Candidate Label Reconstruction for Noisy Partial Label Learning. Xiaorui Peng, Yuheng Jia, Fuchao Yang, Ran Wang, Min-Ling Zhang |
| 2025 | Noise-conditioned Energy-based Annealed Rewards (NEAR): A Generative Framework for Imitation Learning from Observation. Anish Abhijit Diwan, Julen Urain, Jens Kober, Jan Peters |
| 2025 | Noisy Test-Time Adaptation in Vision-Language Models. Chentao Cao, Zhun Zhong, Zhanke Zhou, Tongliang Liu, Yang Liu, Kun Zhang, Bo Han |
| 2025 | Non-Adversarial Inverse Reinforcement Learning via Successor Feature Matching. Arnav Kumar Jain, Harley Wiltzer, Jesse Farebrother, Irina Rish, Glen Berseth, Sanjiban Choudhury |
| 2025 | Non-Equilibrium Dynamics of Hybrid Continuous-Discrete Ground-State Sampling. Timothée G. Leleu, Sam Reifenstein |
| 2025 | Non-myopic Generation of Language Models for Reasoning and Planning. Chang Ma, Haiteng Zhao, Junlei Zhang, Junxian He, Lingpeng Kong |
| 2025 | Nonasymptotic Analysis of Stochastic Gradient Descent with the Richardson-Romberg Extrapolation. Marina Sheshukova, Denis Belomestny, Alain Oliviero Durmus, Eric Moulines, Alexey Naumov, Sergey Samsonov |
| 2025 | Nonconvex Stochastic Optimization under Heavy-Tailed Noises: Optimal Convergence without Gradient Clipping. Zijian Liu, Zhengyuan Zhou |
| 2025 | Nonlinear Sequence Embedding by Monotone Variational Inequality. Jonathan Yuyang Zhou, Yao Xie |
| 2025 | Nonlinear multiregion neural dynamics with parametric impulse response communication channels. Matthew Dowling, Cristina Savin |
| 2025 | Not All Heads Matter: A Head-Level KV Cache Compression Method with Integrated Retrieval and Reasoning. Yu Fu, Zefan Cai, Abedelkadir Asi, Wayne Xiong, Yue Dong, Wen Xiao |
| 2025 | Not All LLM-Generated Data Are Equal: Rethinking Data Weighting in Text Classification. Hsun-Yu Kuo, Yin-Hsiang Liao, Yu-Chieh Chao, Wei-Yun Ma, Pu-Jen Cheng |
| 2025 | Not All Language Model Features Are One-Dimensionally Linear. Joshua Engels, Eric J. Michaud, Isaac Liao, Wes Gurnee, Max Tegmark |
| 2025 | Not All Prompts Are Made Equal: Prompt-based Pruning of Text-to-Image Diffusion Models. Alireza Ganjdanesh, Reza Shirkavand, Shangqian Gao, Heng Huang |
| 2025 | Not-So-Optimal Transport Flows for 3D Point Cloud Generation. Ka-Hei Hui, Chao Liu, Xiaohui Zeng, Chi-Wing Fu, Arash Vahdat |
| 2025 | Nova: Generative Language Models for Assembly Code with Hierarchical Attention and Contrastive Learning. Nan Jiang, Chengxiao Wang, Kevin Liu, Xiangzhe Xu, Lin Tan, Xiangyu Zhang, Petr Babkin |
| 2025 | NovelQA: Benchmarking Question Answering on Documents Exceeding 200K Tokens. Cunxiang Wang, Ruoxi Ning, Boqi Pan, Tonghui Wu, Qipeng Guo, Cheng Deng, Guangsheng Bao, Xiangkun Hu, Zheng Zhang, Qian Wang, Yue Zhang |
| 2025 | Null Counterfactual Factor Interactions for Goal-Conditioned Reinforcement Learning. Caleb Chuck, Fan Feng, Carl Qi, Chang Shi, Siddhant Agarwal, Amy Zhang, Scott Niekum |
| 2025 | Number Cookbook: Number Understanding of Language Models and How to Improve It. Haotong Yang, Yi Hu, Shijia Kang, Zhouchen Lin, Muhan Zhang |
| 2025 | NutriBench: A Dataset for Evaluating Large Language Models in Nutrition Estimation from Meal Descriptions. Mehak Preet Dhaliwal, Andong Hua, Laya Pullela, Ryan Burke, Yao Qin |
| 2025 | O(d/T) Convergence Theory for Diffusion Probabilistic Models under Minimal Assumptions. Gen Li, Yuling Yan |
| 2025 | OASIS Uncovers: High-Quality T2I Models, Same Old Stereotypes. Sepehr Dehdashtian, Gautam Sreekumar, Vishnu Boddeti |
| 2025 | OATS: Outlier-Aware Pruning Through Sparse and Low Rank Decomposition. Stephen Zhang, Vardan Papyan |
| 2025 | OBI-Bench: Can LMMs Aid in Study of Ancient Script on Oracle Bones? Zijian Chen, Tingzhu Chen, Wenjun Zhang, Guangtao Zhai |
| 2025 | OCCAM: Towards Cost-Efficient and Accuracy-Aware Classification Inference. Dujian Ding, Bicheng Xu, Laks V. S. Lakshmanan |
| 2025 | OCEAN: Offline Chain-of-thought Evaluation and Alignment in Large Language Models. Junda Wu, Xintong Li, Ruoyu Wang, Yu Xia, Yuxin Xiong, Jianing Wang, Tong Yu, Xiang Chen, Branislav Kveton, Lina Yao, Jingbo Shang, Julian J. McAuley |
| 2025 | ODE-based Smoothing Neural Network for Reinforcement Learning Tasks. Yinuo Wang, Wenxuan Wang, Xujie Song, Tong Liu, Yuming Yin, Liangfa Chen, Likun Wang, Jingliang Duan, Shengbo Eben Li |
| 2025 | OGBench: Benchmarking Offline Goal-Conditioned RL. Seohong Park, Kevin Frans, Benjamin Eysenbach, Sergey Levine |
| 2025 | OLMoE: Open Mixture-of-Experts Language Models. Niklas Muennighoff, Luca Soldaini, Dirk Groeneveld, Kyle Lo, Jacob Morrison, Sewon Min, Weijia Shi, Evan Pete Walsh, Oyvind Tafjord, Nathan Lambert, Yuling Gu, Shane Arora, Akshita Bhagia, Dustin Schwenk, David Wadden, Alexander Wettig, Binyuan Hui, Tim Dettmers, Douwe Kiela, Ali Farhadi, et al. |
| 2025 | OMG: Opacity Matters in Material Modeling with Gaussian Splatting. Silong Yong, Venkata Nagarjun Pudureddiyur Manivannan, Bernhard Kerbl, Zifu Wan, Simon Stepputtis, Katia P. Sycara, Yaqi Xie |
| 2025 | OMNI-EPIC: Open-endedness via Models of human Notions of Interestingness with Environments Programmed in Code. Maxence Faldor, Jenny Zhang, Antoine Cully, Jeff Clune |
| 2025 | OPTAMI: Global Superlinear Convergence of High-order Methods. Dmitry Kamzolov, Artem Agafonov, Dmitry Pasechnyuk, Alexander V. Gasnikov, Martin Takác |
| 2025 | ORSO: Accelerating Reward Design via Online Reward Selection and Policy Optimization. Chen Bo Calvin Zhang, Zhang-Wei Hong, Aldo Pacchiano, Pulkit Agrawal |
| 2025 | OS-ATLAS: Foundation Action Model for Generalist GUI Agents. Zhiyong Wu, Zhenyu Wu, Fangzhi Xu, Yian Wang, Qiushi Sun, Chengyou Jia, Kanzhi Cheng, Zichen Ding, Liheng Chen, Paul Pu Liang, Yu Qiao |
| 2025 | OSCAR: Operating System Control via State-Aware Reasoning and Re-Planning. Xiaoqiang Wang, Bang Liu |
| 2025 | OSDA Agent: Leveraging Large Language Models for De Novo Design of Organic Structure Directing Agents. Zhaolin Hu, Yixiao Zhou, Zhongan Wang, Xin Li, Weimin Yang, Hehe Fan, Yi Yang |
| 2025 | OSTQuant: Refining Large Language Model Quantization with Orthogonal and Scaling Transformations for Better Distribution Fitting. Xing Hu, Yuan Cheng, Dawei Yang, Zhixuan Chen, Zukang Xu, Jiangyong Yu, Chen Xu, Zhihang Yuan, Zhe Jiang, Sifan Zhou |
| 2025 | OVTR: End-to-End Open-Vocabulary Multiple Object Tracking with Transformer. Jinyang Li, En Yu, Sijia Chen, Wenbing Tao |
| 2025 | Object-Centric Pretraining via Target Encoder Bootstrapping. Nikola Dukic, Tim Lebailly, Tinne Tuytelaars |
| 2025 | ObscuraCoder: Powering Efficient Code LM Pre-Training Via Obfuscation Grounding. Indraneil Paul, Haoyi Yang, Goran Glavas, Kristian Kersting, Iryna Gurevych |
| 2025 | OccProphet: Pushing the Efficiency Frontier of Camera-Only 4D Occupancy Forecasting with an Observer-Forecaster-Refiner Framework. Junliang Chen, Huaiyuan Xu, Yi Wang, Lap-Pui Chau |
| 2025 | Occlusion-aware Non-Rigid Point Cloud Registration via Unsupervised Neural Deformation Correntropy. Mingyang Zhao, Gaofeng Meng, Dong-Ming Yan |
| 2025 | Offline Hierarchical Reinforcement Learning via Inverse Optimization. Carolin Schmidt, Daniele Gammelli, James Harrison, Marco Pavone, Filipe Rodrigues |
| 2025 | Offline Model-Based Optimization by Learning to Rank. Rong-Xi Tan, Ke Xue, Shen-Huan Lyu, Haopu Shang, Yao Wang, Yaoyuan Wang, Sheng Fu, Chao Qian |
| 2025 | Offline RL in Regular Decision Processes: Sample Efficiency via Language Metrics. Ahana Deb, Roberto Cipollone, Anders Jonsson, Alessandro Ronca, Mohammad Sadegh Talebi |
| 2025 | Offline RL with Smooth OOD Generalization in Convex Hull and its Neighborhood. Qingmao Yao, Zhichao Lei, Tianyuan Chen, Ziyue Yuan, Xuefan Chen, Jianxiang Liu, Faguo Wu, Xiao Zhang |
| 2025 | Omni-MATH: A Universal Olympiad Level Mathematic Benchmark for Large Language Models. Bofei Gao, Feifan Song, Zhe Yang, Zefan Cai, Yibo Miao, Qingxiu Dong, Lei Li, Chenghao Ma, Liang Chen, Runxin Xu, Zhengyang Tang, Benyou Wang, Daoguang Zan, Shanghaoran Quan, Ge Zhang, Lei Sha, Yichang Zhang, Xuancheng Ren, Tianyu Liu, Baobao Chang |
| 2025 | OmniBind: Large-scale Omni Multimodal Representation via Binding Spaces. Zehan Wang, Ziang Zhang, Minjie Hong, Hang Zhang, Luping Liu, Rongjie Huang, Xize Cheng, Shengpeng Ji, Tao Jin, Hengshuang Zhao, Zhou Zhao |
| 2025 | OmniCorpus: A Unified Multimodal Corpus of 10 Billion-Level Images Interleaved with Text. Qingyun Li, Zhe Chen, Weiyun Wang, Wenhai Wang, Shenglong Ye, Zhenjiang Jin, Guanzhou Chen, Yinan He, Zhangwei Gao, Erfei Cui, Jiashuo Yu, Hao Tian, Jiasheng Zhou, Chao Xu, Bin Wang, Xingjian Wei, Wei Li, Wenjian Zhang, Bo Zhang, Pinlong Cai, et al. |
| 2025 | OmniEdit: Building Image Editing Generalist Models Through Specialist Supervision. Cong Wei, Zheyang Xiong, Weiming Ren, Xeron Du, Ge Zhang, Wenhu Chen |
| 2025 | OmniKV: Dynamic Context Selection for Efficient Long-Context LLMs. Jitai Hao, Yuke Zhu, Tian Wang, Jun Yu, Xin Xin, Bo Zheng, Zhaochun Ren, Sheng Guo |
| 2025 | OmniPhysGS: 3D Constitutive Gaussians for General Physics-Based Dynamics Generation. Yuchen Lin, Chenguo Lin, Jianjin Xu, Yadong Mu |
| 2025 | OmniRe: Omni Urban Scene Reconstruction. Ziyu Chen, Jiawei Yang, Jiahui Huang, Riccardo de Lutio, Janick Martinez Esturo, Boris Ivanovic, Or Litany, Zan Gojcic, Sanja Fidler, Marco Pavone, Li Song, Yue Wang |
| 2025 | OmniSep: Unified Omni-Modality Sound Separation with Query-Mixup. Xize Cheng, Siqi Zheng, Zehan Wang, Minghui Fang, Ziang Zhang, Rongjie Huang, Shengpeng Ji, Jialong Zuo, Tao Jin, Zhou Zhao |
| 2025 | OmnixR: Evaluating Omni-modality Language Models on Reasoning across Modalities. Lichang Chen, Hexiang Hu, Mingda Zhang, Yiwen Chen, Zifeng Wang, Yandong Li, Pranav Shyam, Tianyi Zhou, Heng Huang, Ming-Hsuan Yang, Boqing Gong |
| 2025 | On Bits and Bandits: Quantifying the Regret-Information Trade-off. Itai Shufaro, Nadav Merlis, Nir Weinberger, Shie Mannor |
| 2025 | On Calibration of LLM-based Guard Models for Reliable Content Moderation. Hongfu Liu, Hengguan Huang, Xiangming Gu, Hao Wang, Ye Wang |
| 2025 | On Conformal Isometry of Grid Cells: Learning Distance-Preserving Position Embedding. Dehong Xu, Ruiqi Gao, Wenhao Zhang, Xue-Xin Wei, Ying Nian Wu |
| 2025 | On Designing General and Expressive Quantum Graph Neural Networks with Applications to MILP Instance Representation. Xinyu Ye, Hao Xiong, Jianhao Huang, Ziang Chen, Jia Wang, Junchi Yan |
| 2025 | On Discriminative Probabilistic Modeling for Self-Supervised Representation Learning. Bokun Wang, Yunwen Lei, Yiming Ying, Tianbao Yang |
| 2025 | On Disentangled Training for Nonlinear Transform in Learned Image Compression. Han Li, Shaohui Li, Wenrui Dai, Maida Cao, Nuowen Kan, Chenglin Li, Junni Zou, Hongkai Xiong |
| 2025 | On Evaluating the Durability of Safeguards for Open-Weight LLMs. Xiangyu Qi, Boyi Wei, Nicholas Carlini, Yangsibo Huang, Tinghao Xie, Luxi He, Matthew Jagielski, Milad Nasr, Prateek Mittal, Peter Henderson |
| 2025 | On Generalization Across Environments In Multi-Objective Reinforcement Learning. Jayden Teoh, Pradeep Varakantham, Peter Vamplew |
| 2025 | On Large Language Model Continual Unlearning. Chongyang Gao, Lixu Wang, Kaize Ding, Chenkai Weng, Xiao Wang, Qi Zhu |
| 2025 | On Linear Representations and Pretraining Data Frequency in Language Models. Jack Merullo, Noah A. Smith, Sarah Wiegreffe, Yanai Elazar |
| 2025 | On Minimizing Adversarial Counterfactual Error in Adversarial Reinforcement Learning. Roman Belaire, Arunesh Sinha, Pradeep Varakantham |
| 2025 | On Quantizing Neural Representation for Variable-Rate Video Coding. Junqi Shi, Zhujia Chen, Hanfei Li, Qi Zhao, Ming Lu, Tong Chen, Zhan Ma |
| 2025 | On Rollouts in Model-Based Reinforcement Learning. Bernd Frauenknecht, Devdutt Subhasish, Friedrich Solowjow, Sebastian Trimpe |
| 2025 | On Scaling Up 3D Gaussian Splatting Training. Hexu Zhao, Haoyang Weng, Daohan Lu, Ang Li, Jinyang Li, Aurojit Panda, Saining Xie |
| 2025 | On Speeding Up Language Model Evaluation. Jin Peng Zhou, Christian K. Belardi, Ruihan Wu, Travis Zhang, Carla P. Gomes, Wen Sun, Kilian Q. Weinberger |
| 2025 | On Statistical Rates of Conditional Diffusion Transformers: Approximation, Estimation and Minimax Optimality. Jerry Yao-Chieh Hu, Weimin Wu, Yi-Chen Lee, Yu-Chao Huang, Minshuo Chen, Han Liu |
| 2025 | On Stochastic Contextual Bandits with Knapsacks in Small Budget Regime. Hengquan Guo, Xin Liu |
| 2025 | On Targeted Manipulation and Deception when Optimizing LLMs for User Feedback. Marcus Williams, Micah Carroll, Adhyyan Narang, Constantin Weisser, Brendan Murphy, Anca D. Dragan |
| 2025 | On a Connection Between Imitation Learning and RLHF. Teng Xiao, Yige Yuan, Mingxiao Li, Zhengyu Chen, Vasant G. Honavar |
| 2025 | On the Adversarial Risk of Test Time Adaptation: An Investigation into Realistic Test-Time Data Poisoning. Yongyi Su, Yushu Li, Nanqing Liu, Kui Jia, XuLei Yang, Chuan-Sheng Foo, Xun Xu |
| 2025 | On the Adversarial Vulnerability of Label-Free Test-Time Adaptation. Shahriar Rifat, Jonathan D. Ashdown, Michael J. De Lucia, Ananthram Swami, Francesco Restuccia |
| 2025 | On the Almost Sure Convergence of the Stochastic Three Points Algorithm. Taha el Bakkali el Kadi, Omar Saadi |
| 2025 | On the Benefits of Attribute-Driven Graph Domain Adaptation. Ruiyi Fang, Bingheng Li, Zhao Kang, Qiuhao Zeng, Nima Hosseini Dashtbayaz, Ruizhi Pu, Charles Ling, Boyu Wang |
| 2025 | On the Benefits of Memory for Modeling Time-Dependent PDEs. Ricardo Buitrago Ruiz, Tanya Marwah, Albert Gu, Andrej Risteski |
| 2025 | On the Byzantine-Resilience of Distillation-Based Federated Learning. Christophe Roux, Max Zimmer, Sebastian Pokutta |
| 2025 | On the Completeness of Invariant Geometric Deep Learning Models. Zian Li, Xiyuan Wang, Shijia Kang, Muhan Zhang |
| 2025 | On the Convergence of No-Regret Dynamics in Information Retrieval Games with Proportional Ranking Functions. Omer Madmon, Idan Pipano, Itamar Reinman, Moshe Tennenholtz |
| 2025 | On the Crucial Role of Initialization for Matrix Factorization. Bingcong Li, Liang Zhang, Aryan Mokhtari, Niao He |
| 2025 | On the Expressive Power of Sparse Geometric MPNNs. Yonatan Sverdlov, Nadav Dym |
| 2025 | On the Expressiveness of Rational ReLU Neural Networks With Bounded Depth. Gennadiy Averkov, Christopher Hojny, Maximilian Merkert |
| 2025 | On the Feature Learning in Diffusion Models. Andi Han, Wei Huang, Yuan Cao, Difan Zou |
| 2025 | On the Fourier analysis in the SO(3) space : the EquiLoPO Network. Dmitrii Zhemchuzhnikov, Sergei Grudinin |
| 2025 | On the Hölder Stability of Multiset and Graph Neural Networks. Yair Davidson, Nadav Dym |
| 2025 | On the Identification of Temporal Causal Representation with Instantaneous Dependence. Zijian Li, Yifan Shen, Kaitao Zheng, Ruichu Cai, Xiangchen Song, Mingming Gong, Guangyi Chen, Kun Zhang |
| 2025 | On the Importance of Language-driven Representation Learning for Heterogeneous Federated Learning. Yunlu Yan, Chun-Mei Feng, Wangmeng Zuo, Salman H. Khan, Yong Liu, Lei Zhu |
| 2025 | On the Learn-to-Optimize Capabilities of Transformers in In-Context Sparse Recovery. Renpu Liu, Ruida Zhou, Cong Shen, Jing Yang |
| 2025 | On the Linear Speedup of Personalized Federated Reinforcement Learning with Shared Representations. Guojun Xiong, Shufan Wang, Daniel Jiang, Jian Li |
| 2025 | On the Modeling Capabilities of Large Language Models for Sequential Decision Making. Martin Klissarov, R. Devon Hjelm, Alexander T. Toshev, Bogdan Mazoure |
| 2025 | On the Optimal Memorization Capacity of Transformers. Tokio Kajitsuka, Issei Sato |
| 2025 | On the Optimization Landscape of Low Rank Adaptation Methods for Large Language Models. Xu-Hui Liu, Yali Du, Jun Wang, Yang Yu |
| 2025 | On the Optimization and Generalization of Two-layer Transformers with Sign Gradient Descent. Bingrui Li, Wei Huang, Andi Han, Zhanpeng Zhou, Taiji Suzuki, Jun Zhu, Jianfei Chen |
| 2025 | On the Performance Analysis of Momentum Method: A Frequency Domain Perspective. Xianliang Li, Jun Luo, Zhiwei Zheng, Hanxiao Wang, Li Luo, Lingkun Wen, Linlong Wu, Sheng Xu |
| 2025 | On the Price of Differential Privacy for Hierarchical Clustering. Chengyuan Deng, Jie Gao, Jalaj Upadhyay, Chen Wang, Samson Zhou |
| 2025 | On the Relation between Trainability and Dequantization of Variational Quantum Learning Models. Elies Gil-Fuster, Casper Gyurik, Adrián Pérez-Salinas, Vedran Dunjko |
| 2025 | On the Role of Attention Heads in Large Language Model Safety. Zhenhong Zhou, Haiyang Yu, Xinghua Zhang, Rongwu Xu, Fei Huang, Kun Wang, Yang Liu, Junfeng Fang, Yongbin Li |
| 2025 | On the Transfer of Object-Centric Representation Learning. Aniket Rajiv Didolkar, Andrii Zadaianchuk, Anirudh Goyal, Michael Curtis Mozer, Yoshua Bengio, Georg Martius, Maximilian Seitzer |
| 2025 | On the expressiveness and spectral bias of KANs. Yixuan Wang, Jonathan W. Siegel, Ziming Liu, Thomas Y. Hou |
| 2025 | On the self-verification limitations of large language models on reasoning and planning tasks. Kaya Stechly, Karthik Valmeekam, Subbarao Kambhampati |
| 2025 | On-the-fly Preference Alignment via Principle-Guided Decoding. Mingye Zhu, Yi Liu, Lei Zhang, Junbo Guo, Zhendong Mao |
| 2025 | Once-for-All: Controllable Generative Image Compression with Dynamic Granularity Adaptation. Anqi Li, Feng Li, Yuxi Liu, Runmin Cong, Yao Zhao, Huihui Bai |
| 2025 | One Hundred Neural Networks and Brains Watching Videos: Lessons from Alignment. Christina Sartzetaki, Gemma Roig, Cees G. M. Snoek, Iris I. A. Groen |
| 2025 | One Model Transfer to All: On Robust Jailbreak Prompts Generation against LLMs. Linbao Li, Yannan Liu, Daojing He, Yu Li |
| 2025 | One Step Diffusion via Shortcut Models. Kevin Frans, Danijar Hafner, Sergey Levine, Pieter Abbeel |
| 2025 | One for all and all for one: Efficient computation of partial Wasserstein distances on the line. Laetitia Chapel, Romain Tavenard |
| 2025 | One-Prompt-One-Story: Free-Lunch Consistent Text-to-Image Generation Using a Single Prompt. Tao Liu, Kai Wang, Senmao Li, Joost van de Weijer, Fahad Shahbaz Khan, Shiqi Yang, Yaxing Wang, Jian Yang, Ming-Ming Cheng |
| 2025 | One-for-All Few-Shot Anomaly Detection via Instance-Induced Prompt Learning. Wenxi Lv, Qinliang Su, Wenchao Xu |
| 2025 | Online Clustering with Nearly Optimal Consistency. T.-H. Hubert Chan, Shaofeng H.-C. Jiang, Tianyi Wu, Mengshi Zhao |
| 2025 | Online Preference Alignment for Language Models via Count-based Exploration. Chenjia Bai, Yang Zhang, Shuang Qiu, Qiaosheng Zhang, Kang Xu, Xuelong Li |
| 2025 | Online Reinforcement Learning in Non-Stationary Context-Driven Environments. Pouya Hamadanian, Arash Nasr-Esfahany, Malte Schwarzkopf, Siddhartha Sen, Mohammad Alizadeh |
| 2025 | Online Reward-Weighted Fine-Tuning of Flow Matching with Wasserstein Regularization. Jiajun Fan, Shuaike Shen, Chaoran Cheng, Yuxin Chen, Chumeng Liang, Ge Liu |
| 2025 | Online epsilon Net & Piercing Set for Geometric Concepts. Sujoy Bhore, Devdan Dey, Satyam Singh |
| 2025 | Online-to-Offline RL for Agent Alignment. Xu Liu, Haobo Fu, Stefano V. Albrecht, Qiang Fu, Shuai Li |
| 2025 | Open-CK: A Large Multi-Physics Fields Coupling benchmarks in Combustion Kinetics. Zaige Fei, Fan Xu, Junyuan Mao, Yuxuan Liang, Qingsong Wen, Kun Wang, Hao Wu, Yang Wang |
| 2025 | Open-Set Graph Anomaly Detection via Normal Structure Regularisation. Qizhou Wang, Guansong Pang, Mahsa Salehi, Xiaokun Xia, Christopher Leckie |
| 2025 | Open-Vocabulary Customization from CLIP via Data-Free Knowledge Distillation. Yongxian Wei, Zixuan Hu, Li Shen, Zhenyi Wang, Chun Yuan, Dacheng Tao |
| 2025 | Open-World Reinforcement Learning over Long Short-Term Imagination. Jiajian Li, Qi Wang, Yunbo Wang, Xin Jin, Yang Li, Wenjun Zeng, Xiaokang Yang |
| 2025 | Open-YOLO 3D: Towards Fast and Accurate Open-Vocabulary 3D Instance Segmentation. Mohamed El Amine Boudjoghra, Angela Dai, Jean Lahoud, Hisham Cholakkal, Rao Muhammad Anwer, Salman H. Khan, Fahad Shahbaz Khan |
| 2025 | OpenHands: An Open Platform for AI Software Developers as Generalist Agents. Xingyao Wang, Boxuan Li, Yufan Song, Frank F. Xu, Xiangru Tang, Mingchen Zhuge, Jiayi Pan, Yueqi Song, Bowen Li, Jaskirat Singh, Hoang H. Tran, Fuqiang Li, Ren Ma, Mingzhang Zheng, Bill Qian, Yanjun Shao, Niklas Muennighoff, Yizhe Zhang, Binyuan Hui, Junyang Lin, et al. |
| 2025 | OpenMathInstruct-2: Accelerating AI for Math with Massive Open-Source Instruction Data. Shubham Toshniwal, Wei Du, Ivan Moshkov, Branislav Kisacanin, Alexan Ayrapetyan, Igor Gitman |
| 2025 | OpenPRM: Building Open-domain Process-based Reward Models with Preference Trees. Kaiyan Zhang, Jiayuan Zhang, Haoxin Li, Xuekai Zhu, Ermo Hua, Xingtai Lv, Ning Ding, Biqing Qi, Bowen Zhou |
| 2025 | OpenRCA: Can Large Language Models Locate the Root Cause of Software Failures? Junjielong Xu, Qinan Zhang, Zhiqing Zhong, Shilin He, Chaoyun Zhang, Qingwei Lin, Dan Pei, Pinjia He, Dongmei Zhang, Qi Zhang |
| 2025 | OpenVid-1M: A Large-Scale High-Quality Dataset for Text-to-video Generation. Kepan Nan, Rui Xie, Penghao Zhou, Tiehan Fan, Zhenheng Yang, Zhijie Chen, Xiang Li, Jian Yang, Ying Tai |
| 2025 | Operator Deep Smoothing for Implied Volatility. Ruben Wiedemann, Antoine Jacquier, Lukas Gonon |
| 2025 | OptiBench Meets ReSocratic: Measure and Improve LLMs for Optimization Modeling. Zhicheng Yang, Yiwei Wang, Yinya Huang, Zhijiang Guo, Wei Shi, Xiongwei Han, Liang Feng, Linqi Song, Xiaodan Liang, Jing Tang |
| 2025 | Optimal Brain Apoptosis. Mingyuan Sun, Zheng Fang, Jiaxu Wang, Junjie Jiang, Delei Kong, Chenming Hu, Yuetong Fang, Renjing Xu |
| 2025 | Optimal Flow Transport and its Entropic Regularization: a GPU-friendly Matrix Iterative Algorithm for Flow Balance Satisfaction. Liangliang Shi, Yufeng Li, Kaipeng Zeng, Yihui Tu, Junchi Yan |
| 2025 | Optimal Learning of Kernel Logistic Regression for Complex Classification Scenarios. Hongwei Wen, Annika Betken, Hanyuan Hang |
| 2025 | Optimal Non-Asymptotic Rates of Value Iteration for Average-Reward Markov Decision Processes. Jongmin Lee, Ernest K. Ryu |
| 2025 | Optimal Protocols for Continual Learning via Statistical Physics and Control Theory. Francesco Mori, Stefano Sarao Mannelli, Francesca Mignacco |
| 2025 | Optimal Strong Regret and Violation in Constrained MDPs via Policy Optimization. Francesco Emanuele Stradi, Matteo Castiglioni, Alberto Marchesi, Nicola Gatti |
| 2025 | Optimal Transport for Time Series Imputation. Hao Wang, Zhengnan Li, Haoxuan Li, Xu Chen, Mingming Gong, BinChen, Zhichao Chen |
| 2025 | Optimality and Adaptivity of Deep Neural Features for Instrumental Variable Regression. Juno Kim, Dimitri Meunier, Arthur Gretton, Taiji Suzuki, Zhu Li |
| 2025 | Optimality of Matrix Mechanism on ℓpp-metric. Zongrui Zou, Jingcheng Liu, Jalaj Upadhyay |
| 2025 | Optimistic Games for Combinatorial Bayesian Optimization with Application to Protein Design. Melis Ilayda Bal, Pier Giuseppe Sessa, Mojmir Mutny, Andreas Krause |
| 2025 | Optimization by Parallel Quasi-Quantum Annealing with Gradient-Based Sampling. Yuma Ichikawa, Yamato Arai |
| 2025 | Optimized Multi-Token Joint Decoding With Auxiliary Model for LLM Inference. Zongyue Qin, Ziniu Hu, Zifan He, Neha Prakriya, Jason Cong, Yizhou Sun |
| 2025 | Optimizing (L0, L1)-Smooth Functions by Gradient Methods. Daniil Vankov, Anton Rodomanov, Angelia Nedich, Lalitha Sankar, Sebastian U. Stich |
| 2025 | Optimizing 4D Gaussians for Dynamic Scene Video from Single Landscape Images. In-Hwan Jin, Haesoo Choo, Seong-Hun Jeong, Park Heemoon, Junghwan Kim, Oh-joon Kwon, Kyeongbo Kong |
| 2025 | Optimizing Backward Policies in GFlowNets via Trajectory Likelihood Maximization. Timofei Gritsaev, Nikita Morozov, Sergey Samsonov, Daniil Tiapkin |
| 2025 | Optimizing Neural Network Representations of Boolean Networks. Joshua Russell, Ignacio Gavier, Devdhar Patel, Edward A. Rietman, Hava T. Siegelmann |
| 2025 | Optimizing Posterior Samples for Bayesian Optimization via Rootfinding. Taiwo A. Adebiyi, Bach Do, Ruda Zhang |
| 2025 | Optimizing importance weighting in the presence of sub-population shifts. Floris Holstege, Bram Wouters, Noud P. A. van Giersbergen, Cees G. H. Diks |
| 2025 | OptionZero: Planning with Learned Options. Po-Wei Huang, Pei-Chiun Peng, Hung Guei, Ti-Rong Wu |
| 2025 | Oracle efficient truncated statistics. Konstantinos Karatapanis, Vasilis Kontonis, Christos Tzamos |
| 2025 | Order-aware Interactive Segmentation. Bin Wang, Anwesa Choudhuri, Meng Zheng, Zhongpai Gao, Benjamin Planche, Andong Deng, Qin Liu, Terrence Chen, Ulas Bagci, Ziyan Wu |
| 2025 | Oryx MLLM: On-Demand Spatial-Temporal Understanding at Arbitrary Resolution. Zuyan Liu, Yuhao Dong, Ziwei Liu, Winston Hu, Jiwen Lu, Yongming Rao |
| 2025 | Oscillatory State-Space Models. T. Konstantin Rusch, Daniela Rus |
| 2025 | Out-of-distribution Generalization for Total Variation based Invariant Risk Minimization. Yuanchao Wang, Zhao-Rong Lai, Tianqi Zhong |
| 2025 | Outlier Synthesis via Hamiltonian Monte Carlo for Out-of-Distribution Detection. Hengzhuang Li, Teng Zhang |
| 2025 | Overcoming False Illusions in Real-World Face Restoration with Multi-Modal Guided Diffusion Model. Keda Tao, Jinjin Gu, Yulun Zhang, Xiucheng Wang, Nan Cheng |
| 2025 | Overcoming Lower-Level Constraints in Bilevel Optimization: A Novel Approach with Regularized Gap Functions. Wei Yao, Haian Yin, Shangzhi Zeng, Jin Zhang |
| 2025 | Overcoming Slow Decision Frequencies in Continuous Control: Model-Based Sequence Reinforcement Learning for Model-Free Control. Devdhar Patel, Hava T. Siegelmann |
| 2025 | OvercookedV2: Rethinking Overcooked for Zero-Shot Coordination. Tobias Gessler, Tin Dizdarevic, Ani Calinescu, Benjamin Ellis, Andrei Lupu, Jakob Nicolaus Foerster |
| 2025 | P-Spikessm: Harnessing Probabilistic Spiking State Space Models for Long-Range Dependency Tasks. Malyaban Bal, Abhronil Sengupta |
| 2025 | PABBO: Preferential Amortized Black-Box Optimization. Xinyu Zhang, Daolang Huang, Samuel Kaski, Julien Martinelli |
| 2025 | PAD: Personalized Alignment of LLMs at Decoding-time. Ruizhe Chen, Xiaotian Zhang, Meng Luo, Wenhao Chai, Zuozhu Liu |
| 2025 | PADRe: A Unifying Polynomial Attention Drop-in Replacement for Efficient Vision Transformer. Pierre-David Letourneau, Manish Kumar Singh, Hsin-Pai Cheng, Shizhong Han, Yunxiao Shi, Dalton Jones, Matthew Harper Langston, Hong Cai, Fatih Porikli |
| 2025 | PAL: Sample-Efficient Personalized Reward Modeling for Pluralistic Alignment. Daiwei Chen, Yi Chen, Aniket Rege, Zhi Wang, Ramya Korlakai Vinayak |
| 2025 | PARTNR: A Benchmark for Planning and Reasoning in Embodied Multi-agent Tasks. Matthew Chang, Gunjan Chhablani, Alexander Clegg, Mikael Dallaire Cote, Ruta Desai, Michal Hlavac, Vladimir Karashchuk, Jacob Krantz, Roozbeh Mottaghi, Priyam Parashar, Siddharth Patki, Ishita Prasad, Xavier Puig, Akshara Rai, Ram Ramrakhya, Daniel Tran, Joanne Truong, John M. Turner, Eric Undersander, Tsung-Yen Yang |
| 2025 | PEAR: Primitive Enabled Adaptive Relabeling for Boosting Hierarchical Reinforcement Learning. Utsav Singh, Vinay P. Namboodiri |
| 2025 | PEARL: Parallel Speculative Decoding with Adaptive Draft Length. Tianyu Liu, Yun Li, Qitan Lv, Kai Liu, Jianchen Zhu, Winston Hu, Xiao Sun |
| 2025 | PEARL: Towards Permutation-Resilient LLMs. Liang Chen, Li Shen, Yang Deng, Xiaoyan Zhao, Bin Liang, Kam-Fai Wong |
| 2025 | PETRA: Parallel End-to-end Training with Reversible Architectures. Stéphane Rivaud, Louis Fournier, Thomas Pumir, Eugene Belilovsky, Michael Eickenberg, Edouard Oyallon |
| 2025 | PFDiff: Training-Free Acceleration of Diffusion Models Combining Past and Future Scores. Guangyi Wang, Yuren Cai, Lijiang Li, Wei Peng, Song-Zhi Su |
| 2025 | PFGuard: A Generative Framework with Privacy and Fairness Safeguards. Soyeon Kim, Yuji Roh, Geon Heo, Steven Euijong Whang |
| 2025 | PICASO: Permutation-Invariant Context Composition with State Space Models. Tian Yu Liu, Alessandro Achille, Matthew Trager, Aditya Golatkar, Luca Zancato, Stefano Soatto |
| 2025 | PIED: Physics-Informed Experimental Design for Inverse Problems. Apivich Hemachandra, Gregory Kang Ruey Lau, See-Kiong Ng, Bryan Kian Hsiang Low |
| 2025 | PIG: Physics-Informed Gaussians as Adaptive Parametric Mesh Representations. Namgyu Kang, Jaemin Oh, Youngjoon Hong, Eunbyung Park |
| 2025 | PIN: Prolate Spheroidal Wave Function-based Implicit Neural Representations. Dhananjaya Jayasundara, Heng Zhao, Demetrio Labate, Vishal M. Patel |
| 2025 | PINP: Physics-Informed Neural Predictor with latent estimation of fluid flows. Huaguan Chen, Yang Liu, Hao Sun |
| 2025 | PIORF: Physics-Informed Ollivier-Ricci Flow for Long-Range Interactions in Mesh Graph Neural Networks. Youn-Yeol Yu, Jeongwhan Choi, Jaehyeon Park, Kookjin Lee, Noseong Park |
| 2025 | PN-GAIL: Leveraging Non-optimal Information from Imperfect Demonstrations. Qiang Liu, Huiqiao Fu, Kaiqiang Tang, Chunlin Chen, Daoyi Dong |
| 2025 | POGEMA: A Benchmark Platform for Cooperative Multi-Agent Pathfinding. Alexey Skrynnik, Anton Andreychuk, Anatolii Borzilov, Alexander Chernyavskiy, Konstantin S. Yakovlev, Aleksandr Panov |
| 2025 | POTEC: Off-Policy Contextual Bandits for Large Action Spaces via Policy Decomposition. Yuta Saito, Jihan Yao, Thorsten Joachims |
| 2025 | PPT: Patch Order Do Matters In Time Series Pretext Task. Jaeho Kim, Kwangryeol Park, Sukmin Yun, Seulki Lee |
| 2025 | PQMass: Probabilistic Assessment of the Quality of Generative Models using Probability Mass Estimation. Pablo Lemos, Sammy Nasser Sharief, Nikolay Malkin, Salma Salhi, Connor Stone, Laurence Perreault Levasseur, Yashar Hezaveh |
| 2025 | PRDP: Progressively Refined Differentiable Physics. Kanishk Bhatia, Felix Koehler, Nils Thuerey |
| 2025 | PRISM: Privacy-Preserving Improved Stochastic Masking for Federated Generative Models. Kyeongkook Seo, Dong-Jun Han, Jaejun Yoo |
| 2025 | PT-T2I/V: An Efficient Proxy-Tokenized Diffusion Transformer for Text-to-Image/Video-Task. Jing Wang, Ao Ma, Jiasong Feng, Dawei Leng, Yuhui Yin, Xiaodan Liang |
| 2025 | PWM: Policy Learning with Multi-Task World Models. Ignat Georgiev, Varun Giridhar, Nicklas Hansen, Animesh Garg |
| 2025 | PaCA: Partial Connection Adaptation for Efficient Fine-Tuning. Sunghyeon Woo, Sol Namkung, Sunwoo Lee, Inho Jeong, Beomseok Kim, Dongsuk Jeon |
| 2025 | PaLD: Detection of Text Partially Written by Large Language Models. Eric Lei, Hsiang Hsu, Chun-Fu Chen |
| 2025 | PaPaGei: Open Foundation Models for Optical Physiological Signals. Arvind Pillai, Dimitris Spathis, Fahim Kawsar, Mohammad Malekzadeh |
| 2025 | PaRa: Personalizing Text-to-Image Diffusion via Parameter Rank Reduction. Shangyu Chen, Zizheng Pan, Jianfei Cai, Dinh Q. Phung |
| 2025 | Pacmann: Efficient Private Approximate Nearest Neighbor Search. Mingxun Zhou, Elaine Shi, Giulia Fanti |
| 2025 | Painting with Words: Elevating Detailed Image Captioning with Benchmark and Alignment Learning. Qinghao Ye, Xianhan Zeng, Fu Li, Chunyuan Li, Haoqi Fan |
| 2025 | Pairwise Elimination with Instance-Dependent Guarantees for Bandits with Cost Subsidy. Ishank Juneja, Carlee Joe-Wong, Osman Yagan |
| 2025 | Palmbench: a comprehensive Benchmark of Compressed Large Language Models on Mobile Platforms. Yilong Li, Jingyu Liu, Hao Zhang, M. Badri Narayanan, Utkarsh Sharma, Shuai Zhang, Yijing Zeng, Jayaram Raghuram, Suman Banerjee |
| 2025 | Palu: KV-Cache Compression with Low-Rank Projection. Chi-Chih Chang, Wei-Cheng Lin, Chien-Yu Lin, Chong-Yan Chen, Yu-Fang Hu, Pei-Shuo Wang, Ning-Chi Huang, Luis Ceze, Mohamed S. Abdelfattah, Kai-Chiang Wu |
| 2025 | Pangea: A Fully Open Multilingual Multimodal LLM for 39 Languages. Xiang Yue, Yueqi Song, Akari Asai, Seungone Kim, Jean de Dieu Nyandwi, Simran Khanuja, Anjali Kantharuban, Lintang Sutawika, Sathyanarayanan Ramamoorthy, Graham Neubig |
| 2025 | ParFam - (Neural Guided) Symbolic Regression via Continuous Global Optimization. Philipp Scholl, Katharina Bieker, Hillary Hauger, Gitta Kutyniok |
| 2025 | ParaSolver: A Hierarchical Parallel Integral Solver for Diffusion Models. Jianrong Lu, Zhiyu Zhu, Junhui Hou |
| 2025 | Parameter Expanded Stochastic Gradient Markov Chain Monte Carlo. Hyunsu Kim, Giung Nam, Chulhee Yun, Hongseok Yang, Juho Lee |
| 2025 | Parameter and Memory Efficient Pretraining via Low-rank Riemannian Optimization. Zhanfeng Mo, Long-Kai Huang, Sinno Jialin Pan |
| 2025 | ParamΔ for Direct Mixing: Post-Train Large Language Model At Zero Cost. Sheng Cao, Mingrui Wu, Karthik Prasad, Yuandong Tian, Zechun Liu |
| 2025 | Pareto Low-Rank Adapters: Efficient Multi-Task Learning with Preferences. Nikolaos Dimitriadis, Pascal Frossard, François Fleuret |
| 2025 | Pareto Prompt Optimization. Guang Zhao, Byung-Jun Yoon, Gilchan Park, Shantenu Jha, Shinjae Yoo, Xiaoning Qian |
| 2025 | ParetoFlow: Guided Flows in Multi-Objective Optimization. Ye Yuan, Can Chen, Christopher Pal, Xue Liu |
| 2025 | Partial Gromov-Wasserstein Metric. Yikun Bai, Rocio Diaz Martin, Abihith Kothapalli, Hengrong Du, Xinran Liu, Soheil Kolouri |
| 2025 | Partially Observed Trajectory Inference using Optimal Transport and a Dynamics Prior. Anming Gu, Edward Chien, Kristjan H. Greenewald |
| 2025 | PathGen-1.6M: 1.6 Million Pathology Image-text Pairs Generation through Multi-agent Collaboration. Yuxuan Sun, Yunlong Zhang, Yixuan Si, Chenglu Zhu, Kai Zhang, Zhongyi Shui, Jingxiong Li, Xuan Gong, Xinheng Lyu, Tao Lin, Lin Yang |
| 2025 | Pedestrian Motion Reconstruction: A Large-scale Benchmark via Mixed Reality Rendering with Multiple Perspectives and Modalities. Yichen Wang, Yiyi Zhang, Xinhao Hu, Li Niu, Jianfu Zhang, Yasushi Makihara, Yasushi Yagi, Pai Peng, Wenlong Liao, Tao He, Junchi Yan, Liqing Zhang |
| 2025 | PeriodWave: Multi-Period Flow Matching for High-Fidelity Waveform Generation. Sang-Hoon Lee, Ha-Yeong Choi, Seong-Whan Lee |
| 2025 | Periodic Materials Generation using Text-Guided Joint Diffusion Model. Kishalay Das, Subhojyoti Khastagir, Pawan Goyal, Seung-Cheol Lee, Satadeep Bhattacharjee, Niloy Ganguly |
| 2025 | Perm: A Parametric Representation for Multi-Style 3D Hair Modeling. Chengan He, Xin Sun, Zhixin Shu, Fujun Luan, Sören Pirk, Jorge Alejandro Amador Herrera, Dominik Ludewig Michels, Tuanfeng Yang Wang, Meng Zhang, Holly E. Rushmeier, Yi Zhou |
| 2025 | Permute-and-Flip: An optimally stable and watermarkable decoder for LLMs. Xuandong Zhao, Lei Li, Yu-Xiang Wang |
| 2025 | Perplexed by Perplexity: Perplexity-Based Data Pruning With Small Reference Models. Zachary Ankner, Cody Blakeney, Kartik Sreenivasan, Max Marion, Matthew L. Leavitt, Mansheej Paul |
| 2025 | Perplexity Trap: PLM-Based Retrievers Overrate Low Perplexity Documents. Haoyu Wang, Sunhao Dai, Haiyuan Zhao, Liang Pang, Xiao Zhang, Gang Wang, Zhenhua Dong, Jun Xu, Ji-Rong Wen |
| 2025 | Persistent Pre-training Poisoning of LLMs. Yiming Zhang, Javier Rando, Ivan Evtimov, Jianfeng Chi, Eric Michael Smith, Nicholas Carlini, Florian Tramèr, Daphne Ippolito |
| 2025 | PersonalLLM: Tailoring LLMs to Individual Preferences. Thomas P. Zollo, Andrew Wei Tung Siah, Naimeng Ye, Ang Li, Hongseok Namkoong |
| 2025 | Personality Alignment of Large Language Models. Minjun Zhu, Yixuan Weng, Linyi Yang, Yue Zhang |
| 2025 | Personalized Representation from Personalized Generation. Shobhita Sundaram, Julia Chae, Yonglong Tian, Sara Beery, Phillip Isola |
| 2025 | Personalized Visual Instruction Tuning. Renjie Pi, Jianshu Zhang, Tianyang Han, Jipeng Zhang, Rui Pan, Tong Zhang |
| 2025 | Perturbation-Restrained Sequential Model Editing. Jun-Yu Ma, Hong Wang, Hao-Xiang Xu, Zhen-Hua Ling, Jia-Chen Gu |
| 2025 | PerturboLLaVA: Reducing Multimodal Hallucinations with Perturbative Visual Training. Cong Chen, Mingyu Liu, Chenchen Jing, Yizhou Zhou, Fengyun Rao, Hao Chen, Bo Zhang, Chunhua Shen |
| 2025 | PharmacoMatch: Efficient 3D Pharmacophore Screening via Neural Subgraph Matching. Daniel Rose, Oliver Wieder, Thomas Seidel, Thierry Langer |
| 2025 | PhiNets: Brain-inspired Non-contrastive Learning Based on Temporal Prediction Hypothesis. Satoki Ishikawa, Makoto Yamada, Han Bao, Yuki Takezawa |
| 2025 | Phidias: A Generative Model for Creating 3D Content from Text, Image, and 3D Conditions with Reference-Augmented Diffusion. Zhenwei Wang, Tengfei Wang, Zexin He, Gerhard Petrus Hancke, Ziwei Liu, Rynson W. H. Lau |
| 2025 | PhyMPGN: Physics-encoded Message Passing Graph Network for spatiotemporal PDE systems. Bocheng Zeng, Qi Wang, Mengtao Yan, Yang Liu, Ruizhi Chengze, Yi Zhang, Hongsheng Liu, Zidong Wang, Hao Sun |
| 2025 | PhyloLM: Inferring the Phylogeny of Large Language Models and Predicting their Performances in Benchmarks. Nicolas Yax, Pierre-Yves Oudeyer, Stefano Palminteri |
| 2025 | PhyloVAE: Unsupervised Learning of Phylogenetic Trees via Variational Autoencoders. Tianyu Xie, Harry Richman, Jiansi Gao, Frederick A. Matsen IV, Cheng Zhang |
| 2025 | PhysBench: Benchmarking and Enhancing Vision-Language Models for Physical World Understanding. Wei Chow, Jiageng Mao, Boyi Li, Daniel Seita, Vitor Campagnolo Guizilini, Yue Wang |
| 2025 | PhysPDE: Rethinking PDE Discovery and a Physical Hypothesis Selection Benchmark. Mingquan Feng, Yixin Huang, Yizhou Liu, Bofang Jiang, Junchi Yan |
| 2025 | Physics of Language Models: Part 2.1, Grade-School Math and the Hidden Reasoning Process. Tian Ye, Zicheng Xu, Yuanzhi Li, Zeyuan Allen-Zhu |
| 2025 | Physics of Language Models: Part 2.2, How to Learn From Mistakes on Grade-School Math Problems. Tian Ye, Zicheng Xu, Yuanzhi Li, Zeyuan Allen-Zhu |
| 2025 | Physics of Language Models: Part 3.2, Knowledge Manipulation. Zeyuan Allen-Zhu, Yuanzhi Li |
| 2025 | Physics of Language Models: Part 3.3, Knowledge Capacity Scaling Laws. Zeyuan Allen-Zhu, Yuanzhi Li |
| 2025 | Physics-Informed Deep Inverse Operator Networks for Solving PDE Inverse Problems. Sung Woong Cho, Hwijae Son |
| 2025 | Physics-Informed Diffusion Models. Jan-Hendrik Bastek, WaiChing Sun, Dennis M. Kochmann |
| 2025 | Physics-aligned field reconstruction with diffusion bridge. Zeyu Li, Hongkun Dou, Shen Fang, Wang Han, Yue Deng, Lijun Yang |
| 2025 | Physics-informed Temporal Difference Metric Learning for Robot Motion Planning. Ruiqi Ni, Zherong Pan, Ahmed H. Qureshi |
| 2025 | Physiome-ODE: A Benchmark for Irregularly Sampled Multivariate Time-Series Forecasting Based on Biological ODEs. Christian Klötergens, Vijaya Krishna Yalavarthi, Randolf Scholz, Maximilian Stubbemann, Stefan Born, Lars Schmidt-Thieme |
| 2025 | PiCO: Peer Review in LLMs based on Consistency Optimization. Kun-Peng Ning, Shuo Yang, Yuyang Liu, Jia-Yu Yao, Zhen-Hui Liu, Yonghong Tian, Yibing Song, Li Yuan |
| 2025 | PianoMotion10M: Dataset and Benchmark for Hand Motion Generation in Piano Performance. Qijun Gan, Song Wang, Shengtao Wu, Jianke Zhu |
| 2025 | PivotMesh: Generic 3D Mesh Generation via Pivot Vertices Guidance. Haohan Weng, Yikai Wang, Tong Zhang, C. L. Philip Chen, Jun Zhu |
| 2025 | PixWizard: Versatile Image-to-Image Visual Assistant with Open-Language Instructions. Weifeng Lin, Xinyu Wei, Renrui Zhang, Le Zhuo, Shitian Zhao, Siyuan Huang, Junlin Xie, Peng Gao, Hongsheng Li |
| 2025 | Planning Anything with Rigor: General-Purpose Zero-Shot Planning with LLM-based Formalized Programming. Yilun Hao, Yang Zhang, Chuchu Fan |
| 2025 | Planning in Natural Language Improves LLM Search for Code Generation. Evan Z. Wang, Federico Cassano, Catherine Wu, Yunfeng Bai, William Song, Vaskar Nath, Ziwen Han, Sean M. Hendryx, Summer Yue, Hugh Zhang |
| 2025 | Plastic Learning with Deep Fourier Features. Alex Lewandowski, Dale Schuurmans, Marlos C. Machado |
| 2025 | PnP-Flow: Plug-and-Play Image Restoration with Flow Matching. Ségolène Tiffany Martin, Anne Gagneux, Paul Hagemann, Gabriele Steidl |
| 2025 | Point Cluster: A Compact Message Unit for Communication-Efficient Collaborative Perception. Zihan Ding, Jiahui Fu, Si Liu, Hongyu Li, Siheng Chen, Hongsheng Li, Shifeng Zhang, Xu Zhou |
| 2025 | Point-SAM: Promptable 3D Segmentation Model for Point Clouds. Yuchen Zhou, Jiayuan Gu, Tung Yen Chiang, Fanbo Xiang, Hao Su |
| 2025 | Point-based Instance Completion with Scene Constraints. Wesley Khademi, Fuxin Li |
| 2025 | PointOBB-v2: Towards Simpler, Faster, and Stronger Single Point Supervised Oriented Object Detection. Botao Ren, Xue Yang, Yi Yu, Junwei Luo, Zhidong Deng |
| 2025 | Poison-splat: Computation Cost Attack on 3D Gaussian Splatting. Jiahao Lu, Yifan Zhang, Qiuhong Shen, Xinchao Wang, Shuicheng Yan |
| 2025 | Poisson-Dirac Neural Networks for Modeling Coupled Dynamical Systems across Domains. Razmik Arman Khosrovian, Takaharu Yaguchi, Hiroaki Yoshimura, Takashi Matsubara |
| 2025 | PolaFormer: Polarity-aware Linear Attention for Vision Transformers. Weikang Meng, Yadan Luo, Xin Li, Dongmei Jiang, Zheng Zhang |
| 2025 | Policy Decorator: Model-Agnostic Online Refinement for Large Policy Model. Xiu Yuan, Tongzhou Mu, Stone Tao, Yunhao Fang, Mengke Zhang, Hao Su |
| 2025 | Policy Design in Long-run Welfare Dynamics. Jiduan Wu, Rediet Abebe, Moritz Hardt, Ana-Andreea Stoica |
| 2025 | Policy Optimization under Imperfect Human Interactions with Agent-Gated Shared Autonomy. Zhenghai Xue, Bo An, Shuicheng Yan |
| 2025 | PolyNet: Learning Diverse Solution Strategies for Neural Combinatorial Optimization. André Hottung, Mridul Mahajan, Kevin Tierney |
| 2025 | PolyPythias: Stability and Outliers across Fifty Language Model Pre-Training Runs. Oskar van der Wal, Pietro Lesci, Max Müller-Eberstein, Naomi Saphra, Hailey Schoelkopf, Willem H. Zuidema, Stella Biderman |
| 2025 | PolyhedronNet: Representation Learning for Polyhedra with Surface-attributed Graph. Dazhou Yu, Genpei Zhang, Liang Zhao |
| 2025 | Polynomial Composition Activations: Unleashing the Dynamics of Large Language Models. Zhijian Zhuo, Ya Wang, Yutao Zeng, Xiaoqing Li, Xun Zhou, Jinwen Ma |
| 2025 | Polyrating: A Cost-Effective and Bias-Aware Rating System for LLM Evaluation. Jasper Dekoninck, Maximilian Baader, Martin T. Vechev |
| 2025 | PooDLe🐩: Pooled and dense self-supervised learning from naturalistic videos. Alex N. Wang, Christopher Hoang, Yuwen Xiong, Yann LeCun, Mengye Ren |
| 2025 | Population Transformer: Learning Population-level Representations of Neural Activity. Geeling Chau, Christopher Wang, Sabera J. Talukder, Vighnesh Subramaniam, Saraswati Soedarmadji, Yisong Yue, Boris Katz, Andrei Barbu |
| 2025 | Port-Hamiltonian Architectural Bias for Long-Range Propagation in Deep Graph Networks. Simon Heilig, Alessio Gravina, Alessandro Trenta, Claudio Gallicchio, Davide Bacciu |
| 2025 | PortLLM: Personalizing Evolving Large Language Models with Training-Free and Portable Model Patches. Rana Muhammad Shahroz, Pingzhi Li, Sukwon Yun, Zhenyu Wang, Shahriar Nirjon, Chau-Wai Wong, Tianlong Chen |
| 2025 | Positive-Unlabeled Diffusion Models for Preventing Sensitive Data Generation. Hiroshi Takahashi, Tomoharu Iwata, Atsutoshi Kumagai, Yuuki Yamanaka, Tomoya Yamashita |
| 2025 | Post-hoc Reward Calibration: A Case Study on Length Bias. Zeyu Huang, Zihan Qiu, Zili Wang, Edoardo M. Ponti, Ivan Titov |
| 2025 | PostCast: Generalizable Postprocessing for Precipitation Nowcasting via Unsupervised Blurriness Modeling. Junchao Gong, Siwei Tu, Weidong Yang, Ben Fei, Kun Chen, Wenlong Zhang, Xiaokang Yang, Wanli Ouyang, Lei Bai |
| 2025 | PostEdit: Posterior Sampling for Efficient Zero-Shot Image Editing. Feng Tian, Yixuan Li, Yichao Yan, Shanyan Guan, Yanhao Ge, Xiaokang Yang |
| 2025 | Posterior-Mean Rectified Flow: Towards Minimum MSE Photo-Realistic Image Restoration. Guy Ohayon, Tomer Michaeli, Michael Elad |
| 2025 | Preble: Efficient Distributed Prompt Scheduling for LLM Serving. Vikranth Srivatsa, Zijian He, Reyna Abhyankar, Dongming Li, Yiying Zhang |
| 2025 | Precedence-Constrained Winter Value for Effective Graph Data Valuation. Hongliang Chi, Wei Jin, Charu C. Aggarwal, Yao Ma |
| 2025 | Precise Localization of Memories: A Fine-grained Neuron-level Knowledge Editing Technique for LLMs. Haowen Pan, Xiaozhi Wang, Yixin Cao, Zenglin Shi, Xun Yang, Juanzi Li, Meng Wang |
| 2025 | Precise Parameter Localization for Textual Generation in Diffusion Models. Lukasz Staniszewski, Bartosz Cywinski, Franziska Boenisch, Kamil Deja, Adam Dziedzic |
| 2025 | Predicate Hierarchies Improve Few-Shot State Classification. Emily Jin, Joy Hsu, Jiajun Wu |
| 2025 | Predicting the Energy Landscape of Stochastic Dynamical System via Physics-informed Self-supervised Learning. Ruikun Li, Huandong Wang, Qingmin Liao, Yong Li |
| 2025 | Prediction Risk and Estimation Risk of the Ridgeless Least Squares Estimator under General Assumptions on Regression Errors. Sungyoon Lee, Sokbae Lee |
| 2025 | Predictive Inverse Dynamics Models are Scalable Learners for Robotic Manipulation. Yang Tian, Sizhe Yang, Jia Zeng, Ping Wang, Dahua Lin, Hao Dong, Jiangmiao Pang |
| 2025 | Predictive Uncertainty Quantification for Bird's Eye View Segmentation: A Benchmark and Novel Loss Function. Linlin Yu, Bowen Yang, Tianhao Wang, Kangshuo Li, Feng Chen |
| 2025 | Preference Diffusion for Recommendation. Shuo Liu, An Zhang, Guoqing Hu, Hong Qian, Tat-Seng Chua |
| 2025 | Preference Elicitation for Offline Reinforcement Learning. Alizée Pace, Bernhard Schölkopf, Gunnar Rätsch, Giorgia Ramponi |
| 2025 | Preference Optimization for Reasoning with Pseudo Feedback. Fangkai Jiao, Geyang Guo, Xingxing Zhang, Nancy F. Chen, Shafiq Joty, Furu Wei |
| 2025 | Preserving Deep Representations in One-Shot Pruning: A Hessian-Free Second-Order Optimization Framework. Ryan Lucas, Rahul Mazumder |
| 2025 | Preserving Diversity in Supervised Fine-Tuning of Large Language Models. Ziniu Li, Congliang Chen, Tian Xu, Zeyu Qin, Jiancong Xiao, Zhi-Quan Luo, Ruoyu Sun |
| 2025 | Presto! Distilling Steps and Layers for Accelerating Music Generation. Zachary Novack, Ge Zhu, Jonah Casebeer, Julian J. McAuley, Taylor Berg-Kirkpatrick, Nicholas J. Bryan |
| 2025 | Prevalence of Negative Transfer in Continual Reinforcement Learning: Analyses and a Simple Baseline. Hongjoon Ahn, Jinu Hyeon, Youngmin Oh, Bosun Hwang, Taesup Moon |
| 2025 | Prioritized Generative Replay. Renhao Wang, Kevin Frans, Pieter Abbeel, Sergey Levine, Alexei A. Efros |
| 2025 | Privacy Auditing of Large Language Models. Ashwinee Panda, Xinyu Tang, Christopher A. Choquette-Choo, Milad Nasr, Prateek Mittal |
| 2025 | Privacy-Aware Lifelong Learning. Ozan Özdenizci, Elmar Rueckert, Robert Legenstein |
| 2025 | Privacy-Preserving Personalized Federated Prompt Learning for Multimodal Large Language Models. Linh Tran, Wei Sun, Stacy Patterson, Ana L. Milanova |
| 2025 | Private Mechanism Design via Quantile Estimation. Yuanyuan Yang, Tao Xiao, Bhuvesh Kumar, Jamie H. Morgenstern |
| 2025 | Privately Counting Partially Ordered Data. Matthew Joseph, Mónica Ribero, Alexander Yu |
| 2025 | ProAdvPrompter: A Two-Stage Journey to Effective Adversarial Prompting for LLMs. Hao Di, Tong He, Haishan Ye, Yinghui Huang, Xiangyu Chang, Guang Dai, Ivor W. Tsang |
| 2025 | Proactive Agent: Shifting LLM Agents from Reactive Responses to Active Assistance. Yaxi Lu, Shenzhi Yang, Cheng Qian, Guirong Chen, Qinyu Luo, Yesai Wu, Huadong Wang, Xin Cong, Zhong Zhang, Yankai Lin, Weiwen Liu, Yasheng Wang, Zhiyuan Liu, Fangming Liu, Maosong Sun |
| 2025 | Proactive Privacy Amnesia for Large Language Models: Safeguarding PII with Negligible Impact on Model Utility. Martin Kuo, Jingyang Zhang, Jianyi Zhang, Minxue Tang, Louis DiValentin, Aolin Ding, Jingwei Sun, William Chen, Amin Hass, Tianlong Chen, Yiran Chen, Hai Li |
| 2025 | Probabilistic Conformal Prediction with Approximate Conditional Validity. Vincent Plassier, Alexander Fishkov, Mohsen Guizani, Maxim Panov, Eric Moulines |
| 2025 | Probabilistic Geometric Principal Component Analysis with application to neural data. Han-Lin Hsieh, Maryam Shanechi |
| 2025 | Probabilistic Language-Image Pre-Training. Sanghyuk Chun, Wonjae Kim, Song Park, Sangdoo Yun |
| 2025 | Probabilistic Learning to Defer: Handling Missing Expert Annotations and Controlling Workload Distribution. Cuong C. Nguyen, Thanh-Toan Do, Gustavo Carneiro |
| 2025 | Probabilistic Neural Pruning via Sparsity Evolutionary Fokker-Planck-Kolmogorov Equation. Zhanfeng Mo, Haosen Shi, Sinno Jialin Pan |
| 2025 | Probe Pruning: Accelerating LLMs through Dynamic Pruning via Model-Probing. Qi Le, Enmao Diao, Ziyan Wang, Xinran Wang, Jie Ding, Li Yang, Ali Anwar |
| 2025 | Probe before You Talk: Towards Black-box Defense against Backdoor Unalignment for Large Language Models. Biao Yi, Tiansheng Huang, Sishuo Chen, Tong Li, Zheli Liu, Zhixuan Chu, Yiming Li |
| 2025 | Probing the Latent Hierarchical Structure of Data via Diffusion Models. Antonio Sclocchi, Alessandro Favero, Noam Itzhak Levi, Matthieu Wyart |
| 2025 | Problem-Parameter-Free Federated Learning. Wenjing Yan, Kai Zhang, Xiaolu Wang, Xuanyu Cao |
| 2025 | Procedural Knowledge in Pretraining Drives Reasoning in Large Language Models. Laura Ruis, Maximilian Mozes, Juhan Bae, Siddhartha Rao Kamalakara, Dwaraknath Gnaneshwar, Acyr Locatelli, Robert Kirk, Tim Rocktäschel, Edward Grefenstette, Max Bartolo |
| 2025 | Procedural Synthesis of Synthesizable Molecules. Michael Sun, Alston Lo, Minghao Guo, Jie Chen, Connor W. Coley, Wojciech Matusik |
| 2025 | Process Reward Model with Q-value Rankings. Wendi Li, Yixuan Li |
| 2025 | Programming Refusal with Conditional Activation Steering. Bruce W. Lee, Inkit Padhi, Karthikeyan Natesan Ramamurthy, Erik Miehling, Pierre L. Dognin, Manish Nagireddy, Amit Dhurandhar |
| 2025 | Progress or Regress? Self-Improvement Reversal in Post-training. Ting Wu, Xuefeng Li, Pengfei Liu |
| 2025 | Progressive Compositionality in Text-to-Image Generative Models. Xu Han, Linghao Jin, Xiaofeng Liu, Paul Pu Liang |
| 2025 | Progressive Compression with Universally Quantized Diffusion Models. Yibo Yang, Justus C. Will, Stephan Mandt |
| 2025 | Progressive Mixed-Precision Decoding for Efficient LLM Inference. Hao Mark Chen, Fuwen Tan, Alexandros Kouris, Royson Lee, Hongxiang Fan, Stylianos I. Venieris |
| 2025 | Progressive Parameter Efficient Transfer Learning for Semantic Segmentation. Nan Zhou, Huiqun Wang, Yaoyan Zheng, Di Huang |
| 2025 | Progressive Token Length Scaling in Transformer Encoders for Efficient Universal Segmentation. Abhishek Aich, Yumin Suh, Samuel Schulter, Manmohan Chandraker |
| 2025 | Progressive distillation induces an implicit curriculum. Abhishek Panigrahi, Bingbin Liu, Sadhika Malladi, Andrej Risteski, Surbhi Goel |
| 2025 | Projection Head is Secretly an Information Bottleneck. Zhuo Ouyang, Kaiwen Hu, Qi Zhang, Yifei Wang, Yisen Wang |
| 2025 | Prompt as Knowledge Bank: Boost Vision-language model via Structural Representation for zero-shot medical detection. Yuguang Yang, Tongfei Chen, Haoyu Huang, Linlin Yang, Chunyu Xie, Dawei Leng, Xianbin Cao, Baochang Zhang |
| 2025 | Prompting Fairness: Integrating Causality to Debias Large Language Models. Jingling Li, Zeyu Tang, Xiaoyu Liu, Peter Spirtes, Kun Zhang, Liu Leqi, Yang Liu |
| 2025 | Promptriever: Instruction-Trained Retrievers Can Be Prompted Like Language Models. Orion Weller, Benjamin Van Durme, Dawn J. Lawrie, Ashwin Paranjape, Yuhao Zhang, Jack Hessel |
| 2025 | ProtComposer: Compositional Protein Structure Generation with 3D Ellipsoids. Hannes Stärk, Bowen Jing, Tomas Geffner, Jason Yim, Tommi S. Jaakkola, Arash Vahdat, Karsten Kreis |
| 2025 | ProtPainter: Draw or Drag Protein via Topology-guided Diffusion. Zhengxi Lu, Shizhuo Cheng, Tintin Jiang, Yan Zhang, Min Zhang |
| 2025 | Protecting against simultaneous data poisoning attacks. Neel Alex, Shoaib Ahmed Siddiqui, Amartya Sanyal, David Krueger |
| 2025 | Protein Language Model Fitness is a Matter of Preference. Cade W. Gordon, Amy X. Lu, Pieter Abbeel |
| 2025 | ProteinBench: A Holistic Evaluation of Protein Foundation Models. Fei Ye, Zaixiang Zheng, Dongyu Xue, Yuning Shen, Lihao Wang, Yiming Ma, Yan Wang, Xinyou Wang, Xiangxin Zhou, Quanquan Gu |
| 2025 | Proteina: Scaling Flow-based Protein Structure Generative Models. Tomas Geffner, Kieran Didi, Zuobai Zhang, Danny Reidenbach, Zhonglin Cao, Jason Yim, Mario Geiger, Christian Dallago, Emine Küçükbenli, Arash Vahdat, Karsten Kreis |
| 2025 | ProtoSnap: Prototype Alignment For Cuneiform Signs. Rachel Mikulinsky, Morris Alper, Shai Gordin, Enrique Jiménez, Yoram Cohen, Hadar Averbuch-Elor |
| 2025 | Prototype antithesis for biological few-shot class-incremental learning. Binghao Liu, Han Yang, Fang Wan, Fei Gu |
| 2025 | Provable Benefit of Annealed Langevin Monte Carlo for Non-log-concave Sampling. Wei Guo, Molei Tao, Yongxin Chen |
| 2025 | Provable Convergence Bounds for Hybrid Dynamical Sampling and Optimization. Matthew X. Burns, Qingyuan Hou, Michael C. Huang |
| 2025 | Provable Convergence and Limitations of Geometric Tempering for Langevin Dynamics. Omar Chehab, Anna Korba, Austin J. Stromme, Adrien Vacher |
| 2025 | Provable Robust Overfitting Mitigation in Wasserstein Distributionally Robust Optimization. Shuang Liu, Yihan Wang, Yifan Zhu, Yibo Miao, Xiao-Shan Gao |
| 2025 | Provable Uncertainty Decomposition via Higher-Order Calibration. Gustaf Ahdritz, Aravind Gollakota, Parikshit Gopalan, Charlotte Peale, Udi Wieder |
| 2025 | Provable unlearning in topic modeling and downstream tasks. Stanley Wei, Sadhika Malladi, Sanjeev Arora, Amartya Sanyal |
| 2025 | Provable weak-to-strong generalization via benign overfitting. David Xing Wu, Anant Sahai |
| 2025 | Provably Accurate Shapley Value Estimation via Leverage Score Sampling. Christopher Musco, R. Teal Witter |
| 2025 | Provably Reliable Conformal Prediction Sets in the Presence of Data Poisoning. Yan Scholten, Stephan Günnemann |
| 2025 | Provably Robust Explainable Graph Neural Networks against Graph Perturbation Attacks. Jiate Li, Meng Pang, Yun Dong, Jinyuan Jia, Binghui Wang |
| 2025 | Provably Safeguarding a Classifier from OOD and Adversarial Samples. Nicolas Atienza, Johanne Cohen, Christophe Labreuche, Michèle Sebag |
| 2025 | Provence: efficient and robust context pruning for retrieval-augmented generation. Nadezhda Chirkova, Thibault Formal, Vassilina Nikoulina, Stéphane Clinchant |
| 2025 | Proving Olympiad Inequalities by Synergizing LLMs and Symbolic Reasoning. Zenan Li, Zhaoyu Li, Wen Tang, Xian Zhang, Yuan Yao, Xujie Si, Fan Yang, Kaiyu Yang, Xiaoxing Ma |
| 2025 | Proximal Mapping Loss: Understanding Loss Functions in Crowd Counting & Localization. Wei Lin, Jia Wan, Antoni B. Chan |
| 2025 | Proxy Denoising for Source-Free Domain Adaptation. Song Tang, Wenxin Su, Yan Gan, Mao Ye, Jianwei Zhang, Xiatian Zhu |
| 2025 | PseDet: Revisiting the Power of Pseudo Label in Incremental Object Detection. Qiuchen Wang, Zehui Chen, Chenhongyi Yang, Jiaming Liu, Zhenyu Li, Feng Zhao |
| 2025 | Pursuing Better Decision Boundaries for Long-Tailed Object Detection via Category Information Amount. Yanbiao Ma, Wei Dai, Jiayi Chen |
| 2025 | Pursuing Feature Separation based on Neural Collapse for Out-of-Distribution Detection. Yingwen Wu, Ruiji Yu, Xinwen Cheng, Zhengbao He, Xiaolin Huang |
| 2025 | Pushing the Limits of All-Atom Geometric Graph Neural Networks: Pre-Training, Scaling, and Zero-Shot Transfer. Zihan Pengmei, Zhengyuan Shen, Zichen Wang, Marcus D. Collins, Huzefa Rangwala |
| 2025 | PuzzleFusion++: Auto-agglomerative 3D Fracture Assembly by Denoise and Verify. Zhengqing Wang, Jiacheng Chen, Yasutaka Furukawa |
| 2025 | PvNeXt: Rethinking Network Design and Temporal Motion for Point Cloud Video Recognition. Jie Wang, Tingfa Xu, Lihe Ding, Xinjie Zhang, Long Bai, Jianan Li |
| 2025 | Pyramidal Flow Matching for Efficient Video Generative Modeling. Yang Jin, Zhicheng Sun, Ningyuan Li, Kun Xu, Hao Jiang, Nan Zhuang, Quzhe Huang, Yang Song, Yadong Mu, Zhouchen Lin |
| 2025 | Q-Adapter: Customizing Pre-trained LLMs to New Preferences with Forgetting Mitigation. Yi-Chen Li, Fuxiang Zhang, Wenjie Qiu, Lei Yuan, Chengxing Jia, Zongzhang Zhang, Yang Yu, Bo An |
| 2025 | Q-SFT: Q-Learning for Language Models via Supervised Fine-Tuning. Joey Hong, Anca D. Dragan, Sergey Levine |
| 2025 | QA-Calibration of Language Model Confidence Scores. Putra Manggala, Atalanti-Anastasia Mastakouri, Elke Kirschbaum, Shiva Prasad Kasiviswanathan, Aaditya Ramdas |
| 2025 | QERA: an Analytical Framework for Quantization Error Reconstruction. Cheng Zhang, Jeffrey T. H. Wong, Can Xiao, George Anthony Constantinides, Yiren Zhao |
| 2025 | QMP: Q-switch Mixture of Policies for Multi-Task Behavior Sharing. Grace Zhang, Ayush Jain, Injune Hwang, Shao-Hua Sun, Joseph J. Lim |
| 2025 | QP-SNN: Quantized and Pruned Spiking Neural Networks. Wenjie Wei, Malu Zhang, Zijian Zhou, Ammar Belatreche, Yimeng Shan, Yu Liang, Honglin Cao, Jieyuan Zhang, Yang Yang |
| 2025 | QPM: Discrete Optimization for Globally Interpretable Image Classification. Thomas Norrenbrock, Timo Kaiser, Sovan Biswas, Ramesh Manuvinakurike, Bodo Rosenhahn |
| 2025 | Qinco2: Vector Compression and Search with Improved Implicit Neural Codebooks. Théophane Vallaeys, Matthew J. Muckley, Jakob Verbeek, Matthijs Douze |
| 2025 | QuaDiM: A Conditional Diffusion Model For Quantum State Property Estimation. Yehui Tang, Mabiao Long, Junchi Yan |
| 2025 | Quality Measures for Dynamic Graph Generative Models. Ryien Hosseini, Filippo Simini, Venkatram Vishwanath, Rebecca Willett, Henry Hoffmann |
| 2025 | Quality over Quantity in Attention Layers: When Adding More Heads Hurts. Noah Amsel, Gilad Yehudai, Joan Bruna |
| 2025 | Quamba: A Post-Training Quantization Recipe for Selective State Space Models. Hung-Yueh Chiang, Chi-Chih Chang, Natalia Frumkin, Kai-Chiang Wu, Diana Marculescu |
| 2025 | Quantifying Generalization Complexity for Large Language Models. Zhenting Qi, Hongyin Luo, Xuliang Huang, Zhuokai Zhao, Yibo Jiang, Xiangjun Fan, Himabindu Lakkaraju, James R. Glass |
| 2025 | Quantitative Approximation for Neural Operators in Nonlinear Parabolic Equations. Takashi Furuya, Koichi Taniguchi, Satoshi Okuda |
| 2025 | Quantized Spike-driven Transformer. Xuerui Qiu, Malu Zhang, Jieyuan Zhang, Wenjie Wei, Honglin Cao, Junsheng Guo, Rui-Jie Zhu, Yimeng Shan, Yang Yang, Haizhou Li |
| 2025 | Quantum (Inspired) D2-sampling with Applications. Poojan Chetan Shah, Ragesh Jaiswal |
| 2025 | Quantum-PEFT: Ultra parameter-efficient fine-tuning. Toshiaki Koike-Akino, Francesco Tonin, Yongtao Wu, Frank Zhengqing Wu, Leyla Naz Candogan, Volkan Cevher |
| 2025 | Query-based Knowledge Transfer for Heterogeneous Learning Environments. Norah Alballa, Wenxuan Zhang, Ziquan Liu, Ahmed M. Abdelmoniem, Mohamed Elhoseiny, Marco Canini |
| 2025 | Quest: Query-centric Data Synthesis Approach for Long-context Scaling of Large Language Model. Chaochen Gao, Xing Wu, Qi Fu, Songlin Hu |
| 2025 | R-Sparse: Rank-Aware Activation Sparsity for Efficient LLM Inference. Zhenyu Zhang, Zechun Liu, Yuandong Tian, Harshit Khaitan, Zhangyang Wang, Steven Li |
| 2025 | R2-Guard: Robust Reasoning Enabled LLM Guardrail via Knowledge-Enhanced Logical Reasoning. Mintong Kang, Bo Li |
| 2025 | R2Det: Exploring Relaxed Rotation Equivariance in 2D Object Detection. Zhiqiang Wu, Yingjie Liu, Hanlin Dong, Xuan Tang, Jian Yang, Bo Jin, Mingsong Chen, Xian Wei |
| 2025 | RA-TTA: Retrieval-Augmented Test-Time Adaptation for Vision-Language Models. Youngjun Lee, Doyoung Kim, Junhyeok Kang, Jihwan Bang, Hwanjun Song, Jae-Gil Lee |
| 2025 | RAG-DDR: Optimizing Retrieval-Augmented Generation Using Differentiable Data Rewards. Xinze Li, Sen Mei, Zhenghao Liu, Yukun Yan, Shuo Wang, Shi Yu, Zheni Zeng, Hao Chen, Ge Yu, Zhiyuan Liu, Maosong Sun, Chenyan Xiong |
| 2025 | RAG-SR: Retrieval-Augmented Generation for Neural Symbolic Regression. Hengzhe Zhang, Qi Chen, Bing Xue, Wolfgang Banzhaf, Mengjie Zhang |
| 2025 | RAPID: Retrieval Augmented Training of Differentially Private Diffusion Models. Tanqiu Jiang, Changjiang Li, Fenglong Ma, Ting Wang |
| 2025 | RB-Modulation: Training-Free Stylization using Reference-Based Modulation. Litu Rout, Yujia Chen, Nataniel Ruiz, Abhishek Kumar, Constantine Caramanis, Sanjay Shakkottai, Wen-Sheng Chu |
| 2025 | RDT-1B: a Diffusion Foundation Model for Bimanual Manipulation. Songming Liu, Lingxuan Wu, Bangguo Li, Hengkai Tan, Huayu Chen, Zhengyi Wang, Ke Xu, Hang Su, Jun Zhu |
| 2025 | REBIND: Enhancing Ground-state Molecular Conformation Prediction via Force-Based Graph Rewiring. Taewon Kim, Hyunjin Seo, Sungsoo Ahn, Eunho Yang |
| 2025 | RECAST: Reparameterized, Compact weight Adaptation for Sequential Tasks. Nazia Tasnim, Bryan A. Plummer |
| 2025 | REEF: Representation Encoding Fingerprints for Large Language Models. Jie Zhang, Dongrui Liu, Chen Qian, Linfeng Zhang, Yong Liu, Yu Qiao, Jing Shao |
| 2025 | REFINE: Inversion-Free Backdoor Defense via Model Reprogramming. Yukun Chen, Shuo Shao, Enhao Huang, Yiming Li, Pin-Yu Chen, Zhan Qin, Kui Ren |
| 2025 | REGENT: A Retrieval-Augmented Generalist Agent That Can Act In-Context in New Environments. Kaustubh Sridhar, Souradeep Dutta, Dinesh Jayaraman, Insup Lee |
| 2025 | REMEDY: Recipe Merging Dynamics in Large Vision-Language Models. Didi Zhu, Yibing Song, Tao Shen, Ziyu Zhao, Jinluan Yang, Min Zhang, Chao Wu |
| 2025 | RESfM: Robust Deep Equivariant Structure from Motion. Fadi Khatib, Yoni Kasten, Dror Moran, Meirav Galun, Ronen Basri |
| 2025 | RESuM: A Rare Event Surrogate Model for Physics Detector Design. Ann-Kathrin Schuetz, Alan W. P. Poon, Aobo Li |
| 2025 | REvolve: Reward Evolution with Large Language Models using Human Feedback. Rishi Hazra, Alkis Sygkounas, Andreas Persson, Amy Loutfi, Pedro Zuidberg Dos Martires |
| 2025 | RFMamba: Frequency-Aware State Space Model for RF-Based Human-Centric Perception. Rui Zhang, Ruixu Geng, Yadong Li, Ruiyuan Song, Hanqin Gong, Dongheng Zhang, Yang Hu, Yan Chen |
| 2025 | RFWave: Multi-band Rectified Flow for Audio Waveform Reconstruction. Peng Liu, Dongyang Dai, Zhiyong Wu |
| 2025 | RGB-Event ISP: The Dataset and Benchmark. Yunfan Lu, Yanlin Qian, Ziyang Rao, Junren Xiao, Liming Chen, Hui Xiong |
| 2025 | RM-Bench: Benchmarking Reward Models of Language Models with Subtlety and Style. Yantao Liu, Zijun Yao, Rui Min, Yixin Cao, Lei Hou, Juanzi Li |
| 2025 | RMB: Comprehensively benchmarking reward models in LLM alignment. Enyu Zhou, Guodong Zheng, Binghai Wang, Zhiheng Xi, Shihan Dou, Rong Bao, Wei Shen, Limao Xiong, Jessica Fan, Yurong Mou, Rui Zheng, Tao Gui, Qi Zhang, Xuanjing Huang |
| 2025 | RMP-SAM: Towards Real-Time Multi-Purpose Segment Anything. Shilin Xu, Haobo Yuan, Qingyu Shi, Lu Qi, Jingbo Wang, Yibo Yang, Yining Li, Kai Chen, Yunhai Tong, Bernard Ghanem, Xiangtai Li, Ming-Hsuan Yang |
| 2025 | RNNs are not Transformers (Yet): The Key Bottleneck on In-Context Retrieval. Kaiyue Wen, Xingyu Dang, Kaifeng Lyu |
| 2025 | ROUTE: Robust Multitask Tuning and Collaboration for Text-to-SQL. Yang Qin, Chao Chen, Zhihang Fu, Ze Chen, Dezhong Peng, Peng Hu, Jieping Ye |
| 2025 | RRM: Robust Reward Model Training Mitigates Reward Hacking. Tianqi Liu, Wei Xiong, Jie Ren, Lichang Chen, Junru Wu, Rishabh Joshi, Yang Gao, Jiaming Shen, Zhen Qin, Tianhe Yu, Daniel Sohn, Anastasia Makarova, Jeremiah Zhe Liu, Yuan Liu, Bilal Piot, Abe Ittycheriah, Aviral Kumar, Mohammad Saleh |
| 2025 | RTDiff: Reverse Trajectory Synthesis via Diffusion for Offline Reinforcement Learning. Qianlan Yang, Yu-Xiong Wang |
| 2025 | RTop-K: Ultra-Fast Row-Wise Top-K Selection for Neural Network Acceleration on GPUs. Xi Xie, Yuebo Luo, Hongwu Peng, Caiwen Ding |
| 2025 | RaSA: Rank-Sharing Low-Rank Adaptation. Zhiwei He, Zhaopeng Tu, Xing Wang, Xingyu Chen, Zhijie Wang, Jiahao Xu, Tian Liang, Wenxiang Jiao, Zhuosheng Zhang, Rui Wang |
| 2025 | Radar: Fast Long-Context Decoding for Any Transformer. Yongchang Hao, Mengyao Zhai, Hossein Hajimirsadeghi, Sepidehsadat Hosseini, Frederick Tung |
| 2025 | RainbowPO: A Unified Framework for Combining Improvements in Preference Optimization. Hanyang Zhao, Genta Indra Winata, Anirban Das, Shi-Xiong Zhang, David D. Yao, Wenpin Tang, Sambit Sahu |
| 2025 | RandLoRA: Full rank parameter-efficient fine-tuning of large models. Paul Albert, Frederic Z. Zhang, Hemanth Saratchandran, Cristian Rodriguez Opazo, Anton van den Hengel, Ehsan Abbasnejad |
| 2025 | Random Is All You Need: Random Noise Injection on Feature Statistics for Generalizable Deep Image Denoising. Zhengwei Yin, Hongjun Wang, Guixu Lin, Weihang Ran, Yinqiang Zheng |
| 2025 | Random-Set Neural Networks. Shireen Kudukkil Manchingal, Muhammad Mubashar, Kaizheng Wang, Keivan Shariatmadar, Fabio Cuzzolin |
| 2025 | Range, not Independence, Drives Modularity in Biologically Inspired Representations. Will Dorrell, Kyle Hsu, Luke Hollingsworth, Jin Hwa Lee, Jiajun Wu, Chelsea Finn, Peter E. Latham, Timothy Edward John Behrens, James C. R. Whittington |
| 2025 | RankSHAP: Shapley Value Based Feature Attributions for Learning to Rank. Tanya Chowdhury, Yair Zick, James Allan |
| 2025 | Ranking-aware adapter for text-driven image ordering with CLIP. Wei-Hsiang Yu, Yen-Yu Lin, Ming-Hsuan Yang, Yi-Hsuan Tsai |
| 2025 | Rapid Selection and Ordering of In-Context Demonstrations via Prompt Embedding Clustering. Kha Pham, Hung Le, Man Ngo, Truyen Tran |
| 2025 | Rapidly Adapting Policies to the Real-World via Simulation-Guided Fine-Tuning. Patrick Yin, Tyler Westenbroek, Ching-An Cheng, Andrey Kolobov, Abhishek Gupta |
| 2025 | Rare event modeling with self-regularized normalizing flows: what can we learn from a single failure? Charles Dawson, Van Tran, Max Z. Li, Chuchu Fan |
| 2025 | Rare-to-Frequent: Unlocking Compositional Generation Power of Diffusion Models on Rare Concepts with LLM Guidance. Dongmin Park, Sebin Kim, Taehong Moon, Minkyu Kim, Kangwook Lee, Jaewoong Cho |
| 2025 | Rational Decision-Making Agent with Learning Internal Utility Judgment. Yining Ye, Xin Cong, Shizuo Tian, Yujia Qin, Chong Liu, Yankai Lin, Zhiyuan Liu, Maosong Sun |
| 2025 | Rationalizing and Augmenting Dynamic Graph Neural Networks. Guibin Zhang, Yiyan Qi, Ziyang Cheng, Yanwei Yue, Dawei Cheng, Jian Guo |
| 2025 | RazorAttention: Efficient KV Cache Compression Through Retrieval Heads. Hanlin Tang, Yang Lin, Jing Lin, Qingsen Han, Danning Ke, Shikuan Hong, Yiwu Yao, Gongyi Wang |
| 2025 | Re-Aligning Language to Visual Objects with an Agentic Workflow. Yuming Chen, Jiangyan Feng, Haodong Zhang, Lijun Gong, Feng Zhu, Rui Zhao, Qibin Hou, Ming-Ming Cheng, Yibing Song |
| 2025 | Re-Evaluating the Impact of Unseen-Class Unlabeled Data on Semi-Supervised Learning Model. Rundong He, Yicong Dong, Lanzhe Guo, Yilong Yin, Tailin Wu |
| 2025 | Re-Imagining Multimodal Instruction Tuning: A Representation View. Yiyang Liu, James Chenhao Liang, Ruixiang Tang, Yugyung Lee, Majid Rabbani, Sohail A. Dianat, Raghuveer Rao, Lifu Huang, Dongfang Liu, Qifan Wang, Cheng Han |
| 2025 | Re-evaluating Open-ended Evaluation of Large Language Models. Siqi Liu, Ian Gemp, Luke Marris, Georgios Piliouras, Nicolas Heess, Marc Lanctot |
| 2025 | ReAttention: Training-Free Infinite Context with Finite Attention Scope. Xiaoran Liu, Ruixiao Li, Zhigeng Liu, Qipeng Guo, Yuerong Song, Kai Lv, Hang Yan, Linlin Li, Qun Liu, Xipeng Qiu |
| 2025 | ReCogLab: a framework testing relational reasoning & cognitive hypotheses on LLMs. Andrew Liu, Henry Prior, Gargi Balasubramaniam, Rivka Moroshko, Amir Zait, Ilia Labzovsky, Danny Karmon, Ishita Dasgupta, Kim Stachenfeld, Kenneth Marino |
| 2025 | ReDeEP: Detecting Hallucination in Retrieval-Augmented Generation via Mechanistic Interpretability. Zhongxiang Sun, Xiaoxue Zang, Kai Zheng, Jun Xu, Xiao Zhang, Weijie Yu, Yang Song, Han Li |
| 2025 | ReGen: Generative Robot Simulation via Inverse Design. Phat Nguyen, Tsun-Hsuan Wang, Zhang-Wei Hong, Erfan Aasi, Andrew Silva, Guy Rosman, Sertac Karaman, Daniela Rus |
| 2025 | ReGenesis: LLMs can Grow into Reasoning Generalists via Self-Improvement. Xiangyu Peng, Congying Xia, Xinyi Yang, Caiming Xiong, Chien-Sheng Wu, Chen Xing |
| 2025 | ReMatching Dynamic Reconstruction Flow. Sara Oblak, Despoina Paschalidou, Sanja Fidler, Matan Atzmon |
| 2025 | ReMoE: Fully Differentiable Mixture-of-Experts with ReLU Routing. Ziteng Wang, Jun Zhu, Jianfei Chen |
| 2025 | ReNovo: Retrieval-Based \emph{De Novo} Mass Spectrometry Peptide Sequencing. Shaorong Chen, Jun Xia, Jingbo Zhou, Lecheng Zhang, Zhangyang Gao, Bozhen Hu, Cheng Tan, Wenjie Du, Stan Z. Li |
| 2025 | ReSi: A Comprehensive Benchmark for Representational Similarity Measures. Max Klabunde, Tassilo Wald, Tobias Schumacher, Klaus H. Maier-Hein, Markus Strohmaier, Florian Lemmerich |
| 2025 | Reading Your Heart: Learning ECG Words and Sentences via Pre-training ECG Language Model. Jiarui Jin, Haoyu Wang, Hongyan Li, Jun Li, Jiahui Pan, Shenda Hong |
| 2025 | Ready-to-React: Online Reaction Policy for Two-Character Interaction Generation. Zhi Cen, Huaijin Pi, Sida Peng, Qing Shuai, Yujun Shen, Hujun Bao, Xiaowei Zhou, Ruizhen Hu |
| 2025 | Real-Time Video Generation with Pyramid Attention Broadcast. Xuanlei Zhao, Xiaolong Jin, Kai Wang, Yang You |
| 2025 | Real-time design of architectural structures with differentiable mechanics and neural networks. Rafael Pastrana, Eder Medina, Isabel M. de Oliveira, Sigrid Adriaenssens, Ryan P. Adams |
| 2025 | Real2Code: Reconstruct Articulated Objects via Code Generation. Zhao Mandi, Yijia Weng, Dominik Bauer, Shuran Song |
| 2025 | Realistic Evaluation of Deep Partial-Label Learning Algorithms. Wei Wang, Dong-Dong Wu, Jindong Wang, Gang Niu, Min-Ling Zhang, Masashi Sugiyama |
| 2025 | Reasoning Elicitation in Language Models via Counterfactual Feedback. Alihan Hüyük, Xinnuo Xu, Jacqueline R. M. A. Maasch, Aditya V. Nori, Javier González |
| 2025 | Reasoning of Large Language Models over Knowledge Graphs with Super-Relations. Song Wang, Junhong Lin, Xiaojie Guo, Julian Shun, Jundong Li, Yada Zhu |
| 2025 | Reasoning with Latent Thoughts: On the Power of Looped Transformers. Nikunj Saunshi, Nishanth Dikkala, Zhiyuan Li, Sanjiv Kumar, Sashank J. Reddi |
| 2025 | Reasoning-Enhanced Healthcare Predictions with Knowledge Graph Community Retrieval. Pengcheng Jiang, Cao Xiao, Minhao Jiang, Parminder Bhatia, Taha A. Kass-Hout, Jimeng Sun, Jiawei Han |
| 2025 | Reassessing How to Compare and Improve the Calibration of Machine Learning Models. Muthu Chidambaram, Rong Ge |
| 2025 | RecDreamer: Consistent Text-to-3D Generation via Uniform Score Distillation. Chenxi Zheng, Yihong Lin, Bangzhen Liu, Xuemiao Xu, Yongwei Nie, Shengfeng He |
| 2025 | RecFlow: An Industrial Full Flow Recommendation Dataset. Qi Liu, Kai Zheng, Rui Huang, Wuchao Li, Kuo Cai, Yuan Chai, Yanan Niu, Yiqun Hui, Bing Han, Na Mou, Hongning Wang, Wentian Bao, Yunen Yu, Guorui Zhou, Han Li, Yang Song, Defu Lian, Kun Gai |
| 2025 | Recite, Reconstruct, Recollect: Memorization in LMs as a Multifaceted Phenomenon. USVSN Sai Prashanth, Alvin Deng, Kyle O'Brien, Jyothir S. V, Mohammad Aflah Khan, Jaydeep Borkar, Christopher A. Choquette-Choo, Jacob Ray Fuehne, Stella Biderman, Tracy Ke, Katherine Lee, Naomi Saphra |
| 2025 | Recognize Any Surgical Object: Unleashing the Power of Weakly-Supervised Data. Jiajie Li, Brian R. Quaranto, Chenhui Xu, Ishan Mishra, Ruiyang Qin, Dancheng Liu, Peter C. W. Kim, Jinjun Xiong |
| 2025 | Reconciling Model Multiplicity for Downstream Decision Making. Ally Yalei Du, Dung Daniel T. Ngo, Zhiwei Steven Wu |
| 2025 | Reconsidering Faithfulness in Regular, Self-Explainable and Domain Invariant GNNs. Steve Azzolin, Antonio Longa, Stefano Teso, Andrea Passerini |
| 2025 | Reconstruction-Guided Policy: Enhancing Decision-Making through Agent-Wise State Consistency. Qifan Liang, Yixiang Shan, Haipeng Liu, Zhengbang Zhu, Ting Long, Weinan Zhang, Yuan Tian |
| 2025 | Reconstructive Visual Instruction Tuning. Haochen Wang, Anlin Zheng, Yucheng Zhao, Tiancai Wang, Zheng Ge, Xiangyu Zhang, Zhaoxiang Zhang |
| 2025 | Recovering Manifold Structure Using Ollivier Ricci Curvature. Tristan Luca Saidi, Abigail Hickok, Andrew J. Blumberg |
| 2025 | Recovery of Causal Graph Involving Latent Variables via Homologous Surrogates. Xiu-Chuan Li, Jun Wang, Tongliang Liu |
| 2025 | Rectified Diffusion: Straightness Is Not Your Need in Rectified Flow. Fu-Yun Wang, Ling Yang, Zhaoyang Huang, Mengdi Wang, Hongsheng Li |
| 2025 | Redefining the task of Bioactivity Prediction. Yanwen Huang, Bowen Gao, Yinjun Jia, Hongbo Ma, Wei-Ying Ma, Ya-Qin Zhang, Yanyan Lan |
| 2025 | Reducing Hallucinations in Large Vision-Language Models via Latent Space Steering. Sheng Liu, Haotian Ye, James Zou |
| 2025 | RefactorBench: Evaluating Stateful Reasoning in Language Agents Through Code. Dhruv Gautam, Spandan Garg, Jinu Jang, Neel Sundaresan, Roshanak Zilouchian Moghaddam |
| 2025 | Refine Knowledge of Large Language Models via Adaptive Contrastive Learning. Yinghui Li, Haojing Huang, Jiayi Kuang, Yangning Li, Shu-Yu Guo, Chao Qu, Xiaoyu Tan, Hai-Tao Zheng, Ying Shen, Philip S. Yu |
| 2025 | Refine-by-Align: Reference-Guided Artifacts Refinement through Semantic Alignment. Yizhi Song, Liu He, Zhifei Zhang, Soo Ye Kim, He Zhang, Wei Xiong, Zhe Lin, Brian L. Price, Scott Cohen, Jianming Zhang, Daniel G. Aliaga |
| 2025 | Refining CLIP's Spatial Awareness: A Visual-Centric Perspective. Congpei Qiu, Yanhao Wu, Wei Ke, Xiuxiu Bai, Tong Zhang |
| 2025 | Reflective Gaussian Splatting. Yuxuan Yao, Zixuan Zeng, Chun Gu, Xiatian Zhu, Li Zhang |
| 2025 | Reflexive Guidance: Improving OoDD in Vision-Language Models via Self-Guided Image-Adaptive Concept Generation. Jihyo Kim, Seulbi Lee, Sangheum Hwang |
| 2025 | Reframing Structure-Based Drug Design Model Evaluation via Metrics Correlated to Practical Needs. Bowen Gao, Haichuan Tan, Yanwen Huang, Minsi Ren, Xiao Huang, Wei-Ying Ma, Ya-Qin Zhang, Yanyan Lan |
| 2025 | RegMix: Data Mixture as Regression for Language Model Pre-training. Qian Liu, Xiaosen Zheng, Niklas Muennighoff, Guangtao Zeng, Longxu Dou, Tianyu Pang, Jing Jiang, Min Lin |
| 2025 | Regressing the Relative Future: Efficient Policy Optimization for Multi-turn RLHF. Zhaolin Gao, Wenhao Zhan, Jonathan Daniel Chang, Gokul Swamy, Kianté Brantley, Jason D. Lee, Wen Sun |
| 2025 | Regret Bounds for Episodic Risk-Sensitive Linear Quadratic Regulator. Wenhao Xu, Xuefeng Gao, Xuedong He |
| 2025 | Regret-Optimal List Replicable Bandit Learning: Matching Upper and Lower Bounds. Michael Chen, Aduri Pavan, N. V. Vinodchandran, Ruosong Wang, Lin Yang |
| 2025 | Regretful Decisions under Label Noise. Sujay Nagaraj, Yang Liu, Flávio P. Calmon, Berk Ustun |
| 2025 | Regularization by Texts for Latent Diffusion Inverse Solvers. Jeongsol Kim, Geon Yeong Park, Hyungjin Chung, Jong Chul Ye |
| 2025 | Regularizing Energy among Training Samples for Out-of-Distribution Generalization. Yiting Chen, Qitian Wu, Junchi Yan |
| 2025 | Regulatory DNA Sequence Design with Reinforcement Learning. Zhao Yang, Bing Su, Chuan Cao, Ji-Rong Wen |
| 2025 | Reinforcement Learning for Control of Non-Markovian Cellular Population Dynamics. Josiah C. Kratz, Jacob Adamczyk |
| 2025 | Reinforcement Learning from Imperfect Corrective Actions and Proxy Rewards. Zhaohui Jiang, Xuening Feng, Paul Weng, Yifei Zhu, Yan Song, Tianze Zhou, Yujing Hu, Tangjie Lv, Changjie Fan |
| 2025 | Reinforcement learning with combinatorial actions for coupled restless bandits. Lily Xu, Bryan Wilder, Elias Boutros Khalil, Milind Tambe |
| 2025 | RelCon: Relative Contrastive Learning for a Motion Foundation Model for Wearable Data. Maxwell A. Xu, Jaya Narain, Gregory Darnell, Haraldur Tómas Hallgrímsson, Hyewon Jeong, Darren Forde, Richard Andres Fineman, Karthik Jayaraman Raghuram, James Matthew Rehg, Shirley You Ren |
| 2025 | Relation-Aware Diffusion for Heterogeneous Graphs with Partially Observed Features. Daeho Um, Yoonji Lee, Jiwoong Park, Seulki Park, Yuneil Yeo, Seong-Jin Ahn |
| 2025 | Relax and Merge: A Simple Yet Effective Framework for Solving Fair k-Means and k-sparse Wasserstein Barycenter Problems. Shihong Song, Guanlin Mo, Hu Ding |
| 2025 | Relaxed Recursive Transformers: Effective Parameter Sharing with Layer-wise LoRA. Sangmin Bae, Adam Fisch, Hrayr Harutyunyan, Ziwei Ji, Seungyeon Kim, Tal Schuster |
| 2025 | Release the Powers of Prompt Tuning: Cross-Modality Prompt Transfer. Ningyuan Zhang, Jie Lu, Keqiuyin Li, Zhen Fang, Guangquan Zhang |
| 2025 | Reliable and Diverse Evaluation of LLM Medical Knowledge Mastery. Yuxuan Zhou, Xien Liu, Chen Ning, Xiao Zhang, Ji Wu |
| 2025 | RelitLRM: Generative Relightable Radiance for Large Reconstruction Models. Tianyuan Zhang, Zhengfei Kuang, Haian Jin, Zexiang Xu, Sai Bi, Hao Tan, He Zhang, Yiwei Hu, Milos Hasan, William T. Freeman, Kai Zhang, Fujun Luan |
| 2025 | Remove Symmetries to Control Model Expressivity and Improve Optimization. Liu Ziyin, Yizhou Xu, Isaac L. Chuang |
| 2025 | Repetition Improves Language Model Embeddings. Jacob Mitchell Springer, Suhas Kotha, Daniel Fried, Graham Neubig, Aditi Raghunathan |
| 2025 | RepoGraph: Enhancing AI Software Engineering with Repository-level Code Graph. Siru Ouyang, Wenhao Yu, Kaixin Ma, Zilin Xiao, Zhihan Zhang, Mengzhao Jia, Jiawei Han, Hongming Zhang, Dong Yu |
| 2025 | Representation Alignment for Generation: Training Diffusion Transformers Is Easier Than You Think. Sihyun Yu, Sangkyung Kwak, Huiwon Jang, Jongheon Jeong, Jonathan Huang, Jinwoo Shin, Saining Xie |
| 2025 | Representational Similarity via Interpretable Visual Concepts. Neehar Kondapaneni, Oisin Mac Aodha, Pietro Perona |
| 2025 | Representative Guidance: Diffusion Model Sampling with Coherence. Anh-Dung Dinh, Daochang Liu, Chang Xu |
| 2025 | Repulsive Latent Score Distillation for Solving Inverse Problems. Nicolas Zilberstein, Morteza Mardani, Santiago Segarra |
| 2025 | Residual Connections and Normalization Can Provably Prevent Oversmoothing in GNNs. Michael Scholkemper, Xinyi Wu, Ali Jadbabaie, Michael T. Schaub |
| 2025 | Residual Deep Gaussian Processes on Manifolds. Kacper Wyrwal, Andreas Krause, Viacheslav Borovitskiy |
| 2025 | Residual Kernel Policy Network: Enhancing Stability and Robustness in RKHS-Based Reinforcement Learning. Yixian Zhang, Huaze Tang, Huijing Lin, Wenbo Ding |
| 2025 | Residual Stream Analysis with Multi-Layer SAEs. Tim Lawson, Lucy Farnik, Conor J. Houghton, Laurence Aitchison |
| 2025 | Residual-MPPI: Online Policy Customization for Continuous Control. Pengcheng Wang, Chenran Li, Catherine Weaver, Kenta Kawamoto, Masayoshi Tomizuka, Chen Tang, Wei Zhan |
| 2025 | Resolution Attack: Exploiting Image Compression to Deceive Deep Neural Networks. Wangjia Yu, Xiaomeng Fu, Qiao Li, Jizhong Han, Xiaodan Zhang |
| 2025 | Restructuring Vector Quantization with the Rotation Trick. Christopher Fifty, Ronald Guenther Junkins, Dennis Duan, Aniketh Iyengar, Jerry Weihong Liu, Ehsan Amid, Sebastian Thrun, Christopher Ré |
| 2025 | Restyling Unsupervised Concept Based Interpretable Networks with Generative Models. Jayneel Parekh, Quentin Bouniot, Pavlo Mozharovskyi, Alasdair Newson, Florence d'Alché-Buc |
| 2025 | Rethinking Artistic Copyright Infringements In the Era Of Text-to-Image Generative Models. Mazda Moayeri, Sriram Balasubramanian, Samyadeep Basu, Priyatham Kattakinda, Atoosa Malemir Chegini, Robert Brauneis, Soheil Feizi |
| 2025 | Rethinking Audio-Visual Adversarial Vulnerability from Temporal and Modality Perspectives. Zeliang Zhang, Susan Liang, Daiki Shimada, Chenliang Xu |
| 2025 | Rethinking Classifier Re-Training in Long-Tailed Recognition: Label Over-Smooth Can Balance. Siyu Sun, Han Lu, Jiangtong Li, Yichen Xie, Tianjiao Li, Xiaokang Yang, Liqing Zhang, Junchi Yan |
| 2025 | Rethinking Diffusion Posterior Sampling: From Conditional Score Estimator to Maximizing a Posterior. Tongda Xu, Xiyan Cai, Xinjie Zhang, Xingtong Ge, Dailan He, Ming Sun, Jingjing Liu, Ya-Qin Zhang, Jian Li, Yan Wang |
| 2025 | Rethinking Evaluation of Sparse Autoencoders through the Representation of Polysemous Words. Gouki Minegishi, Hiroki Furuta, Yusuke Iwasawa, Yutaka Matsuo |
| 2025 | Rethinking Fair Representation Learning for Performance-Sensitive Tasks. Charles Jones, Fabio De Sousa Ribeiro, Mélanie Roschewitz, Daniel C. Castro, Ben Glocker |
| 2025 | Rethinking Graph Neural Networks From A Geometric Perspective Of Node Features. Feng Ji, Yanan Zhao, Kai Zhao, Hanyang Meng, Jielong Yang, Wee Peng Tay |
| 2025 | Rethinking Invariance Regularization in Adversarial Training to Improve Robustness-Accuracy Trade-off. Futa Kai Waseda, Ching-Chun Chang, Isao Echizen |
| 2025 | Rethinking Invariance in In-context Learning. Lizhe Fang, Yifei Wang, Khashayar Gatmiry, Lei Fang, Yisen Wang |
| 2025 | Rethinking LLM Unlearning Objectives: A Gradient Perspective and Go Beyond. Qizhou Wang, Jin Peng Zhou, Zhanke Zhou, Saebyeol Shin, Bo Han, Kilian Q. Weinberger |
| 2025 | Rethinking Light Decoder-based Solvers for Vehicle Routing Problems. Ziwei Huang, Jianan Zhou, Zhiguang Cao, Yixin Xu |
| 2025 | Rethinking Multiple-Instance Learning From Feature Space to Probability Space. Zhaolong Du, Shasha Mao, Xuequan Lu, Mengnan Qi, Yimeng Zhang, Jing Gu, Licheng Jiao |
| 2025 | Rethinking Neural Multi-Objective Combinatorial Optimization via Neat Weight Embedding. Jinbiao Chen, Zhiguang Cao, Jiahai Wang, Yaoxin Wu, Hanzhang Qin, Zizhen Zhang, Yue-Jiao Gong |
| 2025 | Rethinking Reward Model Evaluation: Are We Barking up the Wrong Tree? Xueru Wen, Jie Lou, Yaojie Lu, Hongyu Lin, XingYu, Xinyu Lu, Ben He, Xianpei Han, Debing Zhang, Le Sun |
| 2025 | Rethinking Reward Modeling in Preference-based Large Language Model Alignment. Hao Sun, Yunyi Shen, Jean-Francois Ton |
| 2025 | Rethinking Self-Distillation: Label Averaging and Enhanced Soft Label Refinement with Partial Labels. Hyeonsu Jeong, Hye Won Chung |
| 2025 | Rethinking Shapley Value for Negative Interactions in Non-convex Games. Wonjoon Chang, Myeongjin Lee, Jaesik Choi |
| 2025 | Rethinking Spiking Neural Networks from an Ensemble Learning Perspective. Yongqi Ding, Lin Zuo, Mengmeng Jing, Pei He, Hanpu Deng |
| 2025 | Rethinking Visual Counterfactual Explanations Through Region Constraint. Bartlomiej Sobieski, Jakub Grzywaczewski, Bartlomiej Sadlej, Matthew Tivnan, Przemyslaw Biecek |
| 2025 | Rethinking and Improving Autoformalization: Towards a Faithful Metric and a Dependency Retrieval-based Approach. Qi Liu, Xinhao Zheng, Xudong Lu, Qinxiang Cao, Junchi Yan |
| 2025 | Rethinking the generalization of drug target affinity prediction algorithms via similarity aware evaluation. Chenbin Zhang, Zhiqiang Hu, Chuchu Jiang, Wen Chen, Jie Xu, Shaoting Zhang |
| 2025 | Rethinking the role of frames for SE(3)-invariant crystal structure modeling. Yusei Ito, Tatsunori Taniai, Ryo Igarashi, Yoshitaka Ushiku, Kanta Ono |
| 2025 | Reti-Diff: Illumination Degradation Image Restoration with Retinex-based Latent Diffusion Model. Chunming He, Chengyu Fang, Yulun Zhang, Longxiang Tang, Jinfa Huang, Kai Li, Zhenhua Guo, Xiu Li, Sina Farsiu |
| 2025 | Retri3D: 3D Neural Graphics Representation Retrieval. Yushi Guan, Daniel Kwan, Jean Sebastien Dandurand, Xi Yan, Ruofan Liang, Yuxuan Zhang, Nilesh Jain, Nilesh A. Ahuja, Selvakumar Panneer, Nandita Vijaykumar |
| 2025 | Retrieval Augmented Diffusion Model for Structure-informed Antibody Design and Optimization. Zichen Wang, Yaokun Ji, Jianing Tian, Shuangjia Zheng |
| 2025 | Retrieval Head Mechanistically Explains Long-Context Factuality. Wenhao Wu, Yizhong Wang, Guangxuan Xiao, Hao Peng, Yao Fu |
| 2025 | RetroInText: A Multimodal Large Language Model Enhanced Framework for Retrosynthetic Planning via In-Context Representation Learning. Chenglong Kang, Xiaoyi Liu, Fei Guo |
| 2025 | Reveal Object in Lensless Photography via Region Gaze and Amplification. Xiangjun Yin, HuiHui Yue |
| 2025 | Revealing and Mitigating Over-Attention in Knowledge Editing. Pinzheng Wang, Zecheng Tang, Keyan Zhou, Juntao Li, Qiaoming Zhu, Min Zhang |
| 2025 | Revealing and Reducing Gender Biases in Vision and Language Assistants (VLAs). Leander Girrbach, Stephan Alaniz, Yiran Huang, Trevor Darrell, Zeynep Akata |
| 2025 | Revealing the 3D Cosmic Web through Gravitationally Constrained Neural Fields. Brandon Zhao, Aviad Levis, Liam Connor, Pratul P. Srinivasan, Katherine L. Bouman |
| 2025 | RevisEval: Improving LLM-as-a-Judge via Response-Adapted References. Qiyuan Zhang, Yufei Wang, Tiezheng Yu, Yuxin Jiang, Chuhan Wu, Liangyou Li, Yasheng Wang, Xin Jiang, Lifeng Shang, Ruiming Tang, Fuyuan Lyu, Chen Ma |
| 2025 | Revisit Large-Scale Image-Caption Data in Pre-training Multimodal Foundation Models. Zhengfeng Lai, Vasileios Saveris, Chen Chen, Hong-You Chen, Haotian Zhang, Bowen Zhang, Wenze Hu, Juan Lao Tebar, Zhe Gan, Peter Grasch, Meng Cao, Yinfei Yang |
| 2025 | Revisit Micro-batch Clipping: Adaptive Data Pruning via Gradient Manipulation. Lun Wang |
| 2025 | Revisit the Open Nature of Open Vocabulary Semantic Segmentation. Qiming Huang, Han Hu, Jianbo Jiao |
| 2025 | Revisiting Convolution Architecture in the Realm of DNA Foundation Models. Yu Bo, Weian Mao, Yanjun Shao, Weiqiang Bai, Peng Ye, Xinzhu Ma, Junbo Zhao, Hao Chen, Chunhua Shen |
| 2025 | Revisiting In-context Learning Inference Circuit in Large Language Models. Hakaze Cho, Mariko Kato, Yoshihiro Sakai, Naoya Inoue |
| 2025 | Revisiting Large-Scale Non-convex Distributionally Robust Optimization. Qi Zhang, Yi Zhou, Simon Khan, Ashley Prater-Bennette, Lixin Shen, Shaofeng Zou |
| 2025 | Revisiting Mode Connectivity in Neural Networks with Bezier Surface. Jie Ren, Pin-Yu Chen, Ren Wang |
| 2025 | Revisiting Multi-Permutation Equivariance through the Lens of irreducible Representations. Yonatan Sverdlov, Ido Springer, Nadav Dym |
| 2025 | Revisiting Nearest Neighbor for Tabular Data: A Deep Tabular Baseline Two Decades Later. Han-Jia Ye, Huai-Hong Yin, De-Chuan Zhan, Wei-Lun Chao |
| 2025 | Revisiting Prefix-tuning: Statistical Benefits of Reparameterization among Prompts. Minh Le, Chau Nguyen, Huy Nguyen, Quyen Tran, Trung Le, Nhat Ho |
| 2025 | Revisiting Random Walks for Learning on Graphs. Jinwoo Kim, Olga Zaghen, Ayhan Suleymanzade, Youngmin Ryou, Seunghoon Hong |
| 2025 | Revisiting Source-Free Domain Adaptation: a New Perspective via Uncertainty Control. Gezheng Xu, Hui Guo, Li Yi, Charles Ling, Boyu Wang, Grace Yi |
| 2025 | Revisiting Zeroth-Order Optimization: Minimum-Variance Two-Point Estimators and Directionally Aligned Perturbations. Shaocong Ma, Heng Huang |
| 2025 | Revisiting a Design Choice in Gradient Temporal Difference Learning. Xiaochi Qian, Shangtong Zhang |
| 2025 | Revisiting text-to-image evaluation with Gecko: on metrics, prompts, and human rating. Olivia Wiles, Chuhan Zhang, Isabela Albuquerque, Ivana Kajic, Su Wang, Emanuele Bugliarello, Yasumasa Onoe, Pinelopi Papalampidi, Ira Ktena, Christopher Knutsen, Cyrus Rashtchian, Anant Nawalgaria, Jordi Pont-Tuset, Aida Nematzadeh |
| 2025 | Revolutionizing EMCCD Denoising through a Novel Physics-Based Learning Framework for Noise Modeling. Haiyang Jiang, Tetsuichi Wazawa, Imari Sato, Takeharu Nagai, Yinqiang Zheng |
| 2025 | Reward Dimension Reduction for Scalable Multi-Objective Reinforcement Learning. Giseung Park, Youngchul Sung |
| 2025 | Reward Learning from Multiple Feedback Types. Yannick Metz, András Geiszl, Raphaël Baur, Mennatallah El-Assady |
| 2025 | Rewarding Progress: Scaling Automated Process Verifiers for LLM Reasoning. Amrith Setlur, Chirag Nagpal, Adam Fisch, Xinyang Geng, Jacob Eisenstein, Rishabh Agarwal, Alekh Agarwal, Jonathan Berant, Aviral Kumar |
| 2025 | Risk-Sensitive Diffusion: Robustly Optimizing Diffusion Models with Noisy Samples. Yangming Li, Max Ruiz Luyten, Mihaela van der Schaar |
| 2025 | Risk-Sensitive Variational Actor-Critic: A Model-Based Approach. Alonso Granados Baca, Reza Ebrahimi, Jason Pacheco |
| 2025 | Robotouille: An Asynchronous Planning Benchmark for LLM Agents. Gonzalo Gonzalez-Pumariega, Leong Su Yean, Neha Sunkara, Sanjiban Choudhury |
| 2025 | Robots Pre-train Robots: Manipulation-Centric Robotic Representation from Large-Scale Robot Datasets. Guangqi Jiang, Yifei Sun, Tao Huang, Huanyu Li, Yongyuan Liang, Huazhe Xu |
| 2025 | RobuRCDet: Enhancing Robustness of Radar-Camera Fusion in Bird's Eye View for 3D Object Detection. Jingtong Yue, Zhiwei Lin, Xin Lin, Xiaoyu Zhou, Xiangtai Li, Lu Qi, Yongtao Wang, Ming-Hsuan Yang |
| 2025 | Robust Barycenter Estimation using Semi-Unbalanced Neural Optimal Transport. Milena Gazdieva, Jaemoo Choi, Alexander Kolesov, Jaewoong Choi, Petr Mokrov, Alexander Korotin |
| 2025 | Robust Conformal Prediction with a Single Binary Certificate. Soroush H. Zargarbashi, Aleksandar Bojchevski |
| 2025 | Robust Feature Learning for Multi-Index Models in High Dimensions. Alireza Mousavi Hosseini, Adel Javanmard, Murat A. Erdogdu |
| 2025 | Robust Function-Calling for On-Device Language Model via Function Masking. Qiqiang Lin, Muning Wen, Qiuying Peng, Guanyu Nie, Junwei Liao, Jun Wang, Xiaoyun Mo, Jiamu Zhou, Cheng Cheng, Yin Zhao, Weinan Zhang |
| 2025 | Robust Gymnasium: A Unified Modular Benchmark for Robust Reinforcement Learning. Shangding Gu, Laixi Shi, Muning Wen, Ming Jin, Eric Mazumdar, Yuejie Chi, Adam Wierman, Costas J. Spanos |
| 2025 | Robust LLM safeguarding via refusal feature adversarial training. Lei Yu, Virginie Do, Karen Hambardzumyan, Nicola Cancedda |
| 2025 | Robust Representation Consistency Model via Contrastive Denoising. Jiachen Lei, Julius Berner, Jiongxiao Wang, Zhongzhu Chen, Chaowei Xiao, Zhongjie Ba, Kui Ren, Jun Zhu, Anima Anandkumar |
| 2025 | Robust Root Cause Diagnosis using In-Distribution Interventions. Lokesh Nagalapatti, Ashutosh Srivastava, Sunita Sarawagi, Amit Sharma |
| 2025 | Robust Simulation-Based Inference under Missing Data via Neural Processes. Yogesh Verma, Ayush Bharti, Vikas Garg |
| 2025 | Robust System Identification: Finite-sample Guarantees and Connection to Regularization. Hyuk Park, Grani A. Hanasusanto, Yingying Li |
| 2025 | Robust Transfer of Safety-Constrained Reinforcement Learning Agents. Markel Zubia, Thiago D. Simão, Nils Jansen |
| 2025 | Robust Watermarking Using Generative Priors Against Image Editing: From Benchmarking to Advances. Shilin Lu, Zihan Zhou, Jiayou Lu, Yuanzhi Zhu, Adams Wai-Kin Kong |
| 2025 | Robust Weight Initialization for Tanh Neural Networks with Fixed Point Analysis. Hyunwoo Lee, Hayoung Choi, Hyunju Kim |
| 2025 | Robust-PIFu: Robust Pixel-aligned Implicit Function for 3D Human Digitalization from a Single Image. Kennard Yanting Chan, Fayao Liu, Guosheng Lin, Chuan-Sheng Foo, Weisi Lin |
| 2025 | RobustKV: Defending Large Language Models against Jailbreak Attacks via KV Eviction. Tanqiu Jiang, Zian Wang, Jiacheng Liang, Changjiang Li, Yuhui Wang, Ting Wang |
| 2025 | Robustness Auditing for Linear Regression: To Singularity and Beyond. Ittai Rubinstein, Samuel B. Hopkins |
| 2025 | Robustness Inspired Graph Backdoor Defense. Zhiwei Zhang, Minhua Lin, Junjie Xu, Zongyu Wu, Enyan Dai, Suhang Wang |
| 2025 | Robustness Reprogramming for Representation Learning. Zhichao Hou, MohamadAli Torkamani, Hamid Krim, Xiaorui Liu |
| 2025 | Robustness of Quantum Algorithms for Nonconvex Optimization. Weiyuan Gong, Chenyi Zhang, Tongyang Li |
| 2025 | RocketEval: Efficient automated LLM evaluation via grading checklist. Tianjun Wei, Wei Wen, Ruizhi Qiao, Xing Sun, Jianghong Ma |
| 2025 | Rodimus*: Breaking the Accuracy-Efficiency Trade-Off with Efficient Attentions. Zhihao He, Hang Yu, Zi Gong, Shizhan Liu, Jianguo Li, Weiyao Lin |
| 2025 | Root Cause Analysis of Anomalies in Multivariate Time Series through Granger Causal Discovery. Xiao Han, Saima Absar, Lu Zhang, Shuhan Yuan |
| 2025 | Rotated Runtime Smooth: Training-Free Activation Smoother for accurate INT4 inference. Ke Yi, Zengke Liu, Jianwei Zhang, Chengyuan Li, Tong Zhang, Junyang Lin, Jingren Zhou |
| 2025 | Round and Round We Go! What makes Rotary Positional Encodings useful? Federico Barbero, Alex Vitvitskyi, Christos Perivolaropoulos, Razvan Pascanu, Petar Velickovic |
| 2025 | RouteLLM: Learning to Route LLMs from Preference Data. Isaac Ong, Amjad Almahairi, Vincent Wu, Wei-Lin Chiang, Tianhao Wu, Joseph E. Gonzalez, M. Waleed Kadous, Ion Stoica |
| 2025 | Routing Experts: Learning to Route Dynamic Experts in Existing Multi-modal Large Language Models. Qiong Wu, Zhaoxi Ke, Yiyi Zhou, Xiaoshuai Sun, Rongrong Ji |
| 2025 | RuAG: Learned-rule-augmented Generation for Large Language Models. Yudi Zhang, Pei Xiao, Lu Wang, Chaoyun Zhang, Meng Fang, Yali Du, Yevgeniy Puzyrev, Randolph Yao, Si Qin, Qingwei Lin, Mykola Pechenizkiy, Dongmei Zhang, Saravan Rajmohan, Qi Zhang |
| 2025 | S4M: S4 for multivariate time series forecasting with Missing values. Peng Jing, Meiqi Yang, Qiong Zhang, Xiaoxiao Li |
| 2025 | SAFREE: Training-Free and Adaptive Guard for Safe Text-to-Image And Video Generation. Jaehong Yoon, Shoubin Yu, Vaidehi Patil, Huaxiu Yao, Mohit Bansal |
| 2025 | SAGEPhos: Sage Bio-Coupled and Augmented Fusion for Phosphorylation Site Detection. Jingjie Zhang, Hanqun Cao, Zijun Gao, Xiaorui Wang, Chunbin Gu |
| 2025 | SAM 2: Segment Anything in Images and Videos. Nikhila Ravi, Valentin Gabeur, Yuan-Ting Hu, Ronghang Hu, Chaitanya Ryali, Tengyu Ma, Haitham Khedr, Roman Rädle, Chloé Rolland, Laura Gustafson, Eric Mintun, Junting Pan, Kalyan Vasudev Alwala, Nicolas Carion, Chao-Yuan Wu, Ross B. Girshick, Piotr Dollár, Christoph Feichtenhofer |
| 2025 | SAM-CP: Marrying SAM with Composable Prompts for Versatile Segmentation. Pengfei Chen, Lingxi Xie, Xinyue Huo, Xuehui Yu, Xiaopeng Zhang, Yingfei Sun, Zhenjun Han, Qi Tian |
| 2025 | SAMRefiner: Taming Segment Anything Model for Universal Mask Refinement. Yuqi Lin, Hengjia Li, Wenqi Shao, Zheng Yang, Jun Zhao, Xiaofei He, Ping Luo, Kaipeng Zhang |
| 2025 | SANA: Efficient High-Resolution Text-to-Image Synthesis with Linear Diffusion Transformers. Enze Xie, Junsong Chen, Junyu Chen, Han Cai, Haotian Tang, Yujun Lin, Zhekai Zhang, Muyang Li, Ligeng Zhu, Yao Lu, Song Han |
| 2025 | SANER: Annotation-free Societal Attribute Neutralizer for Debiasing CLIP. Yusuke Hirota, Min-Hung Chen, Chien-Yi Wang, Yuta Nakashima, Yu-Chiang Frank Wang, Ryo Hachiuma |
| 2025 | SAVA: Scalable Learning-Agnostic Data Valuation. Samuel Kessler, Tam Le, Vu Nguyen |
| 2025 | SBSC: Step-by-Step Coding for Improving Mathematical Olympiad Performance. Kunal Singh, Ankan Biswas, Sayandeep Bhowmick, Pradeep Moturi, Siva Kishore Gollapalli |
| 2025 | SC-OmniGS: Self-Calibrating Omnidirectional Gaussian Splatting. Huajian Huang, Yingshu Chen, Longwei Li, Hui Cheng, Tristan Braud, Yajie Zhao, Sai-Kit Yeung |
| 2025 | SCBench: A KV Cache-Centric Analysis of Long-Context Methods. Yucheng Li, Huiqiang Jiang, Qianhui Wu, Xufang Luo, Surin Ahn, Chengruidong Zhang, Amir H. Abdi, Dongsheng Li, Jianfeng Gao, Yuqing Yang, Lili Qiu |
| 2025 | SCOPE: A Self-supervised Framework for Improving Faithfulness in Conditional Text Generation. Song Duong, Florian Le Bronnec, Alexandre Allauzen, Vincent Guigue, Alberto Lumbreras, Laure Soulier, Patrick Gallinari |
| 2025 | SD-LoRA: Scalable Decoupled Low-Rank Adaptation for Class Incremental Learning. Yichen Wu, Hongming Piao, Long-Kai Huang, Renzhen Wang, Wanhua Li, Hanspeter Pfister, Deyu Meng, Kede Ma, Ying Wei |
| 2025 | SEAL: Safety-enhanced Aligned LLM Fine-tuning via Bilevel Data Selection. Han Shen, Pin-Yu Chen, Payel Das, Tianyi Chen |
| 2025 | SEBRA : Debiasing through Self-Guided Bias Ranking. Adarsh Kappiyath, Abhra Chaudhuri, Ajay Kumar Jaiswal, Ziquan Liu, Yunpeng Li, Xiatian Zhu, Lu Yin |
| 2025 | SEMDICE: Off-policy State Entropy Maximization via Stationary Distribution Correction Estimation. Jongmin Lee, Meiqi Sun, Pieter Abbeel |
| 2025 | SEPARATE: A Simple Low-rank Projection for Gradient Compression in Modern Large-scale Model Training Process. Hanzhen Zhao, Xingyu Xie, Cong Fang, Zhouchen Lin |
| 2025 | SFESS: Score Function Estimators for k-Subset Sampling. Klas Wijk, Ricardo Vinuesa, Hossein Azizpour |
| 2025 | SFS: Smarter Code Space Search improves LLM Inference Scaling. Jonathan Light, Yue Wu, Yiyou Sun, Wenchao Yu, Yanchi Liu, Xujiang Zhao, Ziniu Hu, Haifeng Chen, Wei Cheng |
| 2025 | SG-I2V: Self-Guided Trajectory Control in Image-to-Video Generation. Koichi Namekata, Sherwin Bahmani, Ziyi Wu, Yash Kant, Igor Gilitschenski, David B. Lindell |
| 2025 | SGD with memory: fundamental properties and stochastic acceleration. Dmitry Yarotsky, Maksim Velikanov |
| 2025 | SIM: Surface-based fMRI Analysis for Inter-Subject Multimodal Decoding from Movie-Watching Experiments. Simon Dahan, Gabriel Bénédict, Logan Zane John Williams, Yourong Guo, Daniel Rueckert, Robert Leech, Emma Claire Robinson |
| 2025 | SIMPL: Scalable and hassle-free optimisation of neural representations from behaviour. Tom M. George, Pierre Glaser, Kim Stachenfeld, Caswell Barry, Claudia Clopath |
| 2025 | SINGAPO: Single Image Controlled Generation of Articulated Parts in Objects. Jiayi Liu, Denys Iliash, Angel X. Chang, Manolis Savva, Ali Mahdavi Amiri |
| 2025 | SINGER: Stochastic Network Graph Evolving Operator for High Dimensional PDEs. Mingquan Feng, Yixin Huang, Weixin Liao, Yuhong Liu, Yizhou Liu, Junchi Yan |
| 2025 | SLMRec: Distilling Large Language Models into Small for Sequential Recommendation. Wujiang Xu, Qitian Wu, Zujie Liang, Jiaojiao Han, Xuying Ning, Yunxiao Shi, Wenfang Lin, Yongfeng Zhang |
| 2025 | SLoPe: Double-Pruned Sparse Plus Lazy Low-Rank Adapter Pretraining of LLMs. Mohammad Mozaffari, Amir Yazdanbakhsh, Zhao Zhang, Maryam Mehri Dehnavi |
| 2025 | SMI-Editor: Edit-based SMILES Language Model with Fragment-level Supervision. Kangjie Zheng, Siyue Liang, Junwei Yang, Bin Feng, Zequn Liu, Wei Ju, Zhiping Xiao, Ming Zhang |
| 2025 | SMITE: Segment Me In TimE. Amirhossein Alimohammadi, Sauradip Nag, Saeid Asgari Taghanaki, Andrea Tagliasacchi, Ghassan Hamarneh, Ali Mahdavi-Amiri |
| 2025 | SMT: Fine-Tuning Large Language Models with Sparse Matrices. Haoze He, Juncheng B. Li, Xuan Jiang, Heather Miller |
| 2025 | SOAP: Improving and Stabilizing Shampoo using Adam for Language Modeling. Nikhil Vyas, Depen Morwani, Rosie Zhao, Itai Shapira, David Brandfonbrener, Lucas Janson, Sham M. Kakade |
| 2025 | SONICS: Synthetic Or Not - Identifying Counterfeit Songs. Md Awsafur Rahman, Zaber Ibn Abdul Hakim, Najibul Haque Sarker, Bishmoy Paul, Shaikh Anowarul Fattah |
| 2025 | SOO-Bench: Benchmarks for Evaluating the Stability of Offline Black-Box Optimization. Hong Qian, Yiyi Zhu, Xiang Shu, Shuo Liu, Yaolin Wen, Xin An, Huakang Lu, Aimin Zhou, Ke Tang, Yang Yu |
| 2025 | SOREL: A Stochastic Algorithm for Spectral Risks Minimization. Yuze Ge, Rujun Jiang |
| 2025 | SORRY-Bench: Systematically Evaluating Large Language Model Safety Refusal. Tinghao Xie, Xiangyu Qi, Yi Zeng, Yangsibo Huang, Udari Madhushani Sehwag, Kaixuan Huang, Luxi He, Boyi Wei, Dacheng Li, Ying Sheng, Ruoxi Jia, Bo Li, Kai Li, Danqi Chen, Peter Henderson, Prateek Mittal |
| 2025 | SPA: 3D Spatial-Awareness Enables Effective Embodied Representation. Haoyi Zhu, Honghui Yang, Yating Wang, Jiange Yang, Limin Wang, Tong He |
| 2025 | SPAM: Spike-Aware Adam with Momentum Reset for Stable LLM Training. Tianjin Huang, Ziquan Zhu, Gaojie Jin, Lu Liu, Zhangyang Wang, Shiwei Liu |
| 2025 | SPARTUN3D: Situated Spatial Understanding of 3D World in Large Language Model. Yue Zhang, Zhiyang Xu, Ying Shen, Parisa Kordjamshidi, Lifu Huang |
| 2025 | SPDIM: Source-Free Unsupervised Conditional and Label Shift Adaptation in EEG. Shanglin Li, Motoaki Kawanabe, Reinmar J. Kobler |
| 2025 | SPORTU: A Comprehensive Sports Understanding Benchmark for Multimodal Large Language Models. Haotian Xia, Zhengbang Yang, Junbo Zou, Rhys Tracy, Yuqing Wang, Chi Lu, Christopher Lai, Yanjun He, Xun Shao, Zhuoqing Xie, Yuan-Fang Wang, Weining Shen, Hanjie Chen |
| 2025 | SPaR: Self-Play with Tree-Search Refinement to Improve Instruction-Following in Large Language Models. Jiale Cheng, Xiao Liu, Cunxiang Wang, Xiaotao Gu, Yida Lu, Dan Zhang, Yuxiao Dong, Jie Tang, Hongning Wang, Minlie Huang |
| 2025 | SRSA: Skill Retrieval and Adaptation for Robotic Assembly Tasks. Yijie Guo, Bingjie Tang, Iretiayo Akinola, Dieter Fox, Abhishek Gupta, Yashraj Narang |
| 2025 | SSLAM: Enhancing Self-Supervised Models with Audio Mixtures for Polyphonic Soundscapes. Tony Alex, Sara Atito, Armin Mustafa, Muhammad Awais, Philip J. B. Jackson |
| 2025 | SSOLE: Rethinking Orthogonal Low-rank Embedding for Self-Supervised Learning. Lun Huang, Qiang Qiu, Guillermo Sapiro |
| 2025 | ST-GCond: Self-supervised and Transferable Graph Dataset Condensation. Beining Yang, Qingyun Sun, Cheng Ji, Xingcheng Fu, Jianxin Li |
| 2025 | STAFF: Speculative Coreset Selection for Task-Specific Fine-tuning. Xiaoyu Zhang, Juan Zhai, Shiqing Ma, Chao Shen, Tianlin Li, Weipeng Jiang, Yang Liu |
| 2025 | STAMP: Scalable Task- And Model-agnostic Collaborative Perception. Xiangbo Gao, Runsheng Xu, Jiachen Li, Ziran Wang, Zhiwen Fan, Zhengzhong Tu |
| 2025 | STAR: Stability-Inducing Weight Perturbation for Continual Learning. Masih Eskandar, Tooba Imtiaz, Davin Hill, Zifeng Wang, Jennifer G. Dy |
| 2025 | STAR: Synthesis of Tailored Architectures. Armin W. Thomas, Rom N. Parnichkun, Alexander Amini, Stefano Massaroli, Michael Poli |
| 2025 | STBLLM: Breaking the 1-Bit Barrier with Structured Binary LLMs. Peijie Dong, Lujun Li, Yuedong Zhong, Dayou Du, Ruibo Fan, Yuhan Chen, Zhenheng Tang, Qiang Wang, Wei Xue, Yike Guo, Xiaowen Chu |
| 2025 | STORM: Spatio-TempOral Reconstruction Model For Large-Scale Outdoor Scenes. Jiawei Yang, Jiahui Huang, Boris Ivanovic, Yuxiao Chen, Yan Wang, Boyi Li, Yurong You, Apoorva Sharma, Maximilian Igl, Péter Karkus, Danfei Xu, Yue Wang, Marco Pavone |
| 2025 | STRAP: Robot Sub-Trajectory Retrieval for Augmented Policy Learning. Marius Memmel, Jacob Berg, Bingqing Chen, Abhishek Gupta, Jonathan Francis |
| 2025 | SV-RAG: LoRA-Contextualizing Adaptation of MLLMs for Long Document Understanding. Jian Chen, Ruiyi Zhang, Yufan Zhou, Tong Yu, Franck Dernoncourt, Jiuxiang Gu, Ryan A. Rossi, Changyou Chen, Tong Sun |
| 2025 | SV4D: Dynamic 3D Content Generation with Multi-Frame and Multi-View Consistency. Yiming Xie, Chun-Han Yao, Vikram Voleti, Huaizu Jiang, Varun Jampani |
| 2025 | SVBench: A Benchmark with Temporal Multi-Turn Dialogues for Streaming Video Understanding. Zhenyu Yang, Yuhang Hu, Zemin Du, Dizhan Xue, Shengsheng Qian, Jiahong Wu, Fan Yang, Weiming Dong, Changsheng Xu |
| 2025 | SVD-LLM: Truncation-aware Singular Value Decomposition for Large Language Model Compression. Xin Wang, Yu Zheng, Zhongwei Wan, Mi Zhang |
| 2025 | SVDQuant: Absorbing Outliers by Low-Rank Component for 4-Bit Diffusion Models. Muyang Li, Yujun Lin, Zhekai Zhang, Tianle Cai, Xiuyu Li, Junxian Guo, Enze Xie, Chenlin Meng, Jun-Yan Zhu, Song Han |
| 2025 | SVG: 3D Stereoscopic Video Generation via Denoising Frame Matrix. Peng Dai, Feitong Tan, Qiangeng Xu, David Futschik, Ruofei Du, Sean Fanello, Xiaojuan Qi, Yinda Zhang |
| 2025 | SWE-Search: Enhancing Software Agents with Monte Carlo Tree Search and Iterative Refinement. Antonis Antoniades, Albert Örwall, Kexun Zhang, Yuxi Xie, Anirudh Goyal, William Yang Wang |
| 2025 | SWE-bench Multimodal: Do AI Systems Generalize to Visual Software Domains? John Yang, Carlos E. Jimenez, Alex L. Zhang, Kilian Lieret, Joyce Yang, Xindi Wu, Ori Press, Niklas Muennighoff, Gabriel Synnaeve, Karthik R. Narasimhan, Diyi Yang, Sida Wang, Ofir Press |
| 2025 | SWEb: A Large Web Dataset for the Scandinavian Languages. Tobias Norlund, Tim Isbister, Amaru Cuba Gyllensten, Paul Gabriel dos Santos, Danila Petrelli, Ariel Ekgren, Magnus Sahlgren |
| 2025 | SWIFT: On-the-Fly Self-Speculative Decoding for LLM Inference Acceleration. Heming Xia, Yongqi Li, Jun Zhang, Cunxiao Du, Wenjie Li |
| 2025 | SaLoRA: Safety-Alignment Preserved Low-Rank Adaptation. Mingjie Li, Wai Man Si, Michael Backes, Yang Zhang, Yisen Wang |
| 2025 | SaMer: A Scenario-aware Multi-dimensional Evaluator for Large Language Models. Kehua Feng, Keyan Ding, Jing Yu, Yiwen Qu, Zhiwen Chen, Chengfei Lv, Gang Yu, Qiang Zhang, Huajun Chen |
| 2025 | SaRA: High-Efficient Diffusion Model Fine-tuning with Progressive Sparse Low-Rank Adaptation. Teng Hu, Jiangning Zhang, Ran Yi, Hongrui Huang, Yabiao Wang, Lizhuang Ma |
| 2025 | SafeDiffuser: Safe Planning with Diffusion Probabilistic Models. Wei Xiao, Tsun-Hsuan Wang, Chuang Gan, Ramin M. Hasani, Mathias Lechner, Daniela Rus |
| 2025 | SafeWatch: An Efficient Safety-Policy Following Video Guardrail Model with Transparent Explanations. Zhaorun Chen, Francesco Pinto, Minzhou Pan, Bo Li |
| 2025 | Safety Alignment Should be Made More Than Just a Few Tokens Deep. Xiangyu Qi, Ashwinee Panda, Kaifeng Lyu, Xiao Ma, Subhrajit Roy, Ahmad Beirami, Prateek Mittal, Peter Henderson |
| 2025 | Safety Layers in Aligned Large Language Models: The Key to LLM Security. Shen Li, Liuyi Yao, Lan Zhang, Yaliang Li |
| 2025 | Safety Representations for Safer Policy Learning. Kaustubh Mani, Vincent Mai, Charlie Gauthier, Annie S. Chen, Samer B. Nashed, Liam Paull |
| 2025 | Safety-Prioritizing Curricula for Constrained Reinforcement Learning. Cevahir Köprülü, Thiago D. Simão, Nils Jansen, Ufuk Topcu |
| 2025 | SageAttention: Accurate 8-Bit Attention for Plug-and-play Inference Acceleration. Jintao Zhang, Jia Wei, Pengle Zhang, Jun Zhu, Jianfei Chen |
| 2025 | Sail into the Headwind: Alignment via Robust Rewards and Dynamic Labels against Reward Hacking. Paria Rashidinejad, Yuandong Tian |
| 2025 | Salvage: Shapley-distribution Approximation Learning Via Attribution Guided Exploration for Explainable Image Classification. Mehdi Naouar, Hanne Raum, Jens Rahnfeld, Yannick Vogt, Joschka Boedecker, Gabriel Kalweit, Maria Kalweit |
| 2025 | Samba: Simple Hybrid State Space Models for Efficient Unlimited Context Language Modeling. Liliang Ren, Yang Liu, Yadong Lu, Yelong Shen, Chen Liang, Weizhu Chen |
| 2025 | Samba: Synchronized Set-of-Sequences Modeling for Multiple Object Tracking. Mattia Segù, Luigi Piccinelli, Siyuan Li, Yung-Hsu Yang, Luc Van Gool, Bernt Schiele |
| 2025 | Sample then Identify: A General Framework for Risk Control and Assessment in Multimodal Large Language Models. Qingni Wang, Tiantian Geng, Zhiyuan Wang, Teng Wang, Bo Fu, Feng Zheng |
| 2025 | Satisficing Regret Minimization in Bandits. Qing Feng, Tianyi Ma, Ruihao Zhu |
| 2025 | ScImage: How good are multimodal large language models at scientific text-to-image generation? Leixin Zhang, Steffen Eger, Yinjie Cheng, Weihe Zhai, Jonas Belouadi, Fahimeh Moafian, Zhixue Zhao |
| 2025 | Scalable Bayesian Learning with posteriors. Samuel Duffield, Kaelan Donatella, Johnathan Chiu, Phoebe Klett, Daniel Simpson |
| 2025 | Scalable Benchmarking and Robust Learning for Noise-Free Ego-Motion and 3D Reconstruction from Noisy Video. Xiaohao Xu, Tianyi Zhang, Shibo Zhao, Xiang Li, Sibo Wang, Yongqi Chen, Ye Li, Bhiksha Raj, Matthew Johnson-Roberson, Sebastian A. Scherer, Xiaonan Huang |
| 2025 | Scalable Decentralized Learning with Teleportation. Yuki Takezawa, Sebastian U. Stich |
| 2025 | Scalable Decision-Making in Stochastic Environments through Learned Temporal Abstraction. Baiting Luo, Ava Pettet, Aron Laszka, Abhishek Dubey, Ayan Mukhopadhyay |
| 2025 | Scalable Discrete Diffusion Samplers: Combinatorial Optimization and Statistical Physics. Sebastian Sanokowski, Wilhelm Franz Berghammer, Haoyu Peter Wang, Martin Ennemoser, Sepp Hochreiter, Sebastian Lehner |
| 2025 | Scalable Extraction of Training Data from Aligned, Production Language Models. Milad Nasr, Javier Rando, Nicholas Carlini, Jonathan Hayase, Matthew Jagielski, A. Feder Cooper, Daphne Ippolito, Christopher A. Choquette-Choo, Florian Tramèr, Katherine Lee |
| 2025 | Scalable Influence and Fact Tracing for Large Language Model Pretraining. Tyler A. Chang, Dheeraj Rajagopal, Tolga Bolukbasi, Lucas Dixon, Ian Tenney |
| 2025 | Scalable Mechanistic Neural Networks. Jiale Chen, Dingling Yao, Adeel Pervez, Dan Alistarh, Francesco Locatello |
| 2025 | Scalable Universal T-Cell Receptor Embeddings from Adaptive Immune Repertoires. Paidamoyo Chapfuwa, Ilker Demirel, Lorenzo Pisani, Javier Zazo, Elon Portugaly, H. Jabran Zahid, Julia Greissl |
| 2025 | Scalable and Certifiable Graph Unlearning: Overcoming the Approximation Error Barrier. Lu Yi, Zhewei Wei |
| 2025 | Scale-Aware Contrastive Reverse Distillation for Unsupervised Medical Anomaly Detection. Chunlei Li, Yilei Shi, Jingliang Hu, Xiao Xiang Zhu, Lichao Mou |
| 2025 | Scale-Free Graph-Language Models. Jianglin Lu, Yixuan Liu, Yitian Zhang, Yun Fu |
| 2025 | Scale-aware Recognition in Satellite Images under Resource Constraints. Shreelekha Revankar, Cheng Perng Phoo, Utkarsh Mall, Bharath Hariharan, Kavita Bala |
| 2025 | Scaling Autonomous Agents via Automatic Reward Modeling And Planning. Zhenfang Chen, Delin Chen, Rui Sun, Wenjun Liu, Chuang Gan |
| 2025 | Scaling Diffusion Language Models via Adaptation from Autoregressive Models. Shansan Gong, Shivam Agarwal, Yizhe Zhang, Jiacheng Ye, Lin Zheng, Mukai Li, Chenxin An, Peilin Zhao, Wei Bi, Jiawei Han, Hao Peng, Lingpeng Kong |
| 2025 | Scaling FP8 training to trillion-token LLMs. Maxim Fishman, Brian Chmiel, Ron Banner, Daniel Soudry |
| 2025 | Scaling In-the-Wild Training for Diffusion-based Illumination Harmonization and Editing by Imposing Consistent Light Transport. Lvmin Zhang, Anyi Rao, Maneesh Agrawala |
| 2025 | Scaling Instruction-tuned LLMs to Million-token Contexts via Hierarchical Synthetic Data Generation. Linda He, Jue Wang, Maurice Weber, Shang Zhu, Ben Athiwaratkun, Ce Zhang |
| 2025 | Scaling LLM Test-Time Compute Optimally Can be More Effective than Scaling Parameters for Reasoning. Charlie Victor Snell, Jaehoon Lee, Kelvin Xu, Aviral Kumar |
| 2025 | Scaling Large Language Model-based Multi-Agent Collaboration. Chen Qian, Zihao Xie, Yifei Wang, Wei Liu, Kunlun Zhu, Hanchen Xia, Yufan Dang, Zhuoyun Du, Weize Chen, Cheng Yang, Zhiyuan Liu, Maosong Sun |
| 2025 | Scaling Laws for Adversarial Attacks on Language Model Activations and Tokens. Stanislav Fort |
| 2025 | Scaling Laws for Downstream Task Performance in Machine Translation. Berivan Isik, Natalia Ponomareva, Hussein Hazimeh, Dimitris Paparas, Sergei Vassilvitskii, Sanmi Koyejo |
| 2025 | Scaling Laws for Precision. Tanishq Kumar, Zachary Ankner, Benjamin Frederick Spector, Blake Bordelon, Niklas Muennighoff, Mansheej Paul, Cengiz Pehlevan, Christopher Ré, Aditi Raghunathan |
| 2025 | Scaling Long Context Training Data by Long-Distance Referrals. Yonghao Zhuang, Lanxiang Hu, Longfei Yun, Souvik Kundu, Zhengzhong Liu, Eric P. Xing, Hao Zhang |
| 2025 | Scaling Offline Model-Based RL via Jointly-Optimized World-Action Model Pretraining. Jie Cheng, Ruixi Qiao, Yingwei Ma, Binhua Li, Gang Xiong, Qinghai Miao, Yongbin Li, Yisheng Lv |
| 2025 | Scaling Optimal LR Across Token Horizons. Johan Bjorck, Alon Benhaim, Vishrav Chaudhary, Furu Wei, Xia Song |
| 2025 | Scaling Speech-Text Pre-training with Synthetic Interleaved Data. Aohan Zeng, Zhengxiao Du, Mingdao Liu, Lei Zhang, Shengmin Jiang, Yuxiao Dong, Jie Tang |
| 2025 | Scaling Stick-Breaking Attention: An Efficient Implementation and In-depth Study. Shawn Tan, Songlin Yang, Aaron C. Courville, Rameswar Panda, Yikang Shen |
| 2025 | Scaling Transformers for Low-Bitrate High-Quality Speech Coding. Julian D. Parker, Anton Smirnov, Jordi Pons, CJ Carr, Zack Zukowski, Zach Evans, Xubo Liu |
| 2025 | Scaling Wearable Foundation Models. Girish Narayanswamy, Xin Liu, Kumar Ayush, Yuzhe Yang, Xuhai Xu, Shun Liao, Jake Garrison, Shyam A. Tailor, Jacob E. Sunshine, Yun Liu, Tim Althoff, Shrikanth Narayanan, Pushmeet Kohli, Jiening Zhan, Mark Malhotra, Shwetak N. Patel, Samy Abdel-Ghaffar, Daniel McDuff |
| 2025 | Scaling and evaluating sparse autoencoders. Leo Gao, Tom Dupré la Tour, Henk Tillman, Gabriel Goh, Rajan Troll, Alec Radford, Ilya Sutskever, Jan Leike, Jeffrey Wu |
| 2025 | Scaling up Masked Diffusion Models on Text. Shen Nie, Fengqi Zhu, Chao Du, Tianyu Pang, Qian Liu, Guangtao Zeng, Min Lin, Chongxuan Li |
| 2025 | Scaling up the Banded Matrix Factorization Mechanism for Large Scale Differentially Private ML. Ryan McKenna |
| 2025 | Schur's Positive-Definite Network: Deep Learning in the SPD cone with structure. Can Pouliquen, Mathurin Massias, Titouan Vayer |
| 2025 | SciLitLLM: How to Adapt LLMs for Scientific Literature Understanding. Sihang Li, Jin Huang, Jiaxi Zhuang, Yaorui Shi, Xiaochen Cai, Mingjun Xu, Xiang Wang, Linfeng Zhang, Guolin Ke, Hengxing Cai |
| 2025 | ScienceAgentBench: Toward Rigorous Assessment of Language Agents for Data-Driven Scientific Discovery. Ziru Chen, Shijie Chen, Yuting Ning, Qianheng Zhang, Boshi Wang, Botao Yu, Yifei Li, Zeyi Liao, Chen Wei, Zitong Lu, Vishal Dey, Mingyi Xue, Frazier N. Baker, Benjamin Burns, Daniel Adu-Ampratwum, Xuhui Huang, Xia Ning, Song Gao, Yu Su, Huan Sun |
| 2025 | Score Forgetting Distillation: A Swift, Data-Free Method for Machine Unlearning in Diffusion Models. Tianqi Chen, Shujian Zhang, Mingyuan Zhou |
| 2025 | Score-based Self-supervised MRI Denoising. Jiachen Tu, Yaokun Shi, Fan Lam |
| 2025 | Score-based free-form architectures for high-dimensional Fokker-Planck equations. Feng Liu, Faguo Wu, Xiao Zhang |
| 2025 | Scrutinize What We Ignore: Reining In Task Representation Shift Of Context-Based Offline Meta Reinforcement Learning. Hai Zhang, Boyuan Zheng, Tianying Ji, Jinhang Liu, Anqi Guo, Junqiao Zhao, Lanqing Li |
| 2025 | SeCom: On Memory Construction and Retrieval for Personalized Conversational Agents. Zhuoshi Pan, Qianhui Wu, Huiqiang Jiang, Xufang Luo, Hao Cheng, Dongsheng Li, Yuqing Yang, Chin-Yew Lin, H. Vicky Zhao, Lili Qiu, Jianfeng Gao |
| 2025 | SePer: Measure Retrieval Utility Through The Lens Of Semantic Perplexity Reduction. Lu Dai, Yijie Xu, Jinhui Ye, Hao Liu, Hui Xiong |
| 2025 | SeRA: Self-Reviewing and Alignment of LLMs using Implicit Reward Margins. Jongwoo Ko, Saket Dingliwal, Bhavana Ganesh, Sailik Sengupta, Sravan Babu Bodapati, Aram Galstyan |
| 2025 | Searching for Optimal Solutions with LLMs via Bayesian Optimization. Dhruv Agarwal, Manoj Ghuhan Arivazhagan, Rajarshi Das, Sandesh Swamy, Sopan Khosla, Rashmi Gangadharaiah |
| 2025 | Second Order Bounds for Contextual Bandits with Function Approximation. Aldo Pacchiano |
| 2025 | Second-Order Fine-Tuning without Pain for LLMs: A Hessian Informed Zeroth-Order Optimizer. Yanjun Zhao, Sizhe Dang, Haishan Ye, Guang Dai, Yi Qian, Ivor W. Tsang |
| 2025 | Second-Order Min-Max Optimization with Lazy Hessians. Lesi Chen, Chengchang Liu, Jingzhao Zhang |
| 2025 | SecureGS: Boosting the Security and Fidelity of 3D Gaussian Splatting Steganography. Xuanyu Zhang, Jiarui Meng, Zhipei Xu, Shuzhou Yang, Yanmin Wu, Ronggang Wang, Jian Zhang |
| 2025 | See It from My Perspective: How Language Affects Cultural Bias in Image Understanding. Amith Ananthram, Elias Stengel-Eskin, Mohit Bansal, Kathleen McKeown |
| 2025 | See What You Are Told: Visual Attention Sink in Large Multimodal Models. Seil Kang, Jinyeong Kim, Junhyeok Kim, Seong Jae Hwang |
| 2025 | SeedLM: Compressing LLM Weights into Seeds of Pseudo-Random Generators. Rasoul Shafipour, David Harrison, Maxwell Horton, Jeffrey Marker, Houman Bedayat, Sachin Mehta, Mohammad Rastegari, Mahyar Najibi, Saman Naderiparizi |
| 2025 | Seeing Eye to AI: Human Alignment via Gaze-Based Response Rewards for Large Language Models. Ángela López-Cardona, Carlos Segura, Alexandros Karatzoglou, Sergi Abadal, Ioannis Arapakis |
| 2025 | SegLLM: Multi-round Reasoning Segmentation with Large Language Models. Xudong Wang, Shaolun Zhang, Shufan Li, Kehan Li, Konstantinos Kallidromitis, Yusuke Kato, Kazuki Kozuka, Trevor Darrell |
| 2025 | Segment Any 3D Object with Language. Seungjun Lee, Yuyang Zhao, Gim Hee Lee |
| 2025 | SelKD: Selective Knowledge Distillation via Optimal Transport Perspective. Liangliang Shi, Zhengyan Shi, Junchi Yan |
| 2025 | Select before Act: Spatially Decoupled Action Repetition for Continuous Control. Buqing Nie, Yangqing Fu, Yue Gao |
| 2025 | SelectFormer in Data Markets: Privacy-Preserving and Efficient Data Selection for Transformers with Multi-Party Computation. Xu Ouyang, Felix Xiaozhu Lin, Yangfeng Ji |
| 2025 | Selective Aggregation for Low-Rank Adaptation in Federated Learning. Pengxin Guo, Shuang Zeng, Yanran Wang, Huijie Fan, Feifei Wang, Liangqiong Qu |
| 2025 | Selective Attention Improves Transformer. Yaniv Leviathan, Matan Kalman, Yossi Matias |
| 2025 | Selective Label Enhancement Learning for Test-Time Adaptation. Yihao Hu, Congyu Qiao, Xin Geng, Ning Xu |
| 2025 | Selective Task Group Updates for Multi-Task Optimization. Wooseong Jeong, Kuk-Jin Yoon |
| 2025 | Selective Unlearning via Representation Erasure Using Domain Adversarial Training. Nazanin Mohammadi Sepahvand, Eleni Triantafillou, Hugo Larochelle, Doina Precup, James J. Clark, Daniel M. Roy, Gintare Karolina Dziugaite |
| 2025 | Selective induction Heads: How Transformers Select Causal Structures in Context. Francesco D'Angelo, Francesco Croce, Nicolas Flammarion |
| 2025 | Self-Attention-Based Contextual Modulation Improves Neural System Identification. Isaac Lin, Tianye Wang, Shang Gao, Shiming Tang, Tai Sing Lee |
| 2025 | Self-Boosting Large Language Models with Synthetic Preference Data. Qingxiu Dong, Li Dong, Xingxing Zhang, Zhifang Sui, Furu Wei |
| 2025 | Self-Correcting Decoding with Generative Feedback for Mitigating Hallucinations in Large Vision-Language Models. Ce Zhang, Zifu Wan, Zhehan Kan, Martin Q. Ma, Simon Stepputtis, Deva Ramanan, Russ Salakhutdinov, Louis-Philippe Morency, Katia P. Sycara, Yaqi Xie |
| 2025 | Self-Evolved Reward Learning for LLMS. Chenghua Huang, Zhizhen Fan, Lu Wang, Fangkai Yang, Pu Zhao, Zeqi Lin, Qingwei Lin, Dongmei Zhang, Saravan Rajmohan, Qi Zhang |
| 2025 | Self-Evolving Multi-Agent Collaboration Networks for Software Development. Yue Hu, Yuzhu Cai, Yaxin Du, Xinyu Zhu, Xiangrui Liu, Zijie Yu, Yuchen Hou, Shuo Tang, Siheng Chen |
| 2025 | Self-Improvement in Language Models: The Sharpening Mechanism. Audrey Huang, Adam Block, Dylan J. Foster, Dhruv Rohatgi, Cyril Zhang, Max Simchowitz, Jordan T. Ash, Akshay Krishnamurthy |
| 2025 | Self-Improving Robust Preference Optimization. Eugene Choi, Arash Ahmadian, Matthieu Geist, Olivier Pietquin, Mohammad Gheshlaghi Azar |
| 2025 | Self-Introspective Decoding: Alleviating Hallucinations for Large Vision-Language Models. Fushuo Huo, Wenchao Xu, Zhong Zhang, Haozhao Wang, Zhicheng Chen, Peilin Zhao |
| 2025 | Self-MoE: Towards Compositional Large Language Models with Self-Specialized Experts. Junmo Kang, Leonid Karlinsky, Hongyin Luo, Zhen Wang, Jacob A. Hansen, James R. Glass, David Daniel Cox, Rameswar Panda, Rogério Feris, Alan Ritter |
| 2025 | Self-Normalized Resets for Plasticity in Continual Learning. Vivek F. Farias, Adam Daniel Jozefiak |
| 2025 | Self-Play Preference Optimization for Language Model Alignment. Yue Wu, Zhiqing Sun, Huizhuo Yuan, Kaixuan Ji, Yiming Yang, Quanquan Gu |
| 2025 | Self-Supervised Diffusion MRI Denoising via Iterative and Stable Refinement. Chenxu Wu, Qingpeng Kong, Zihang Jiang, S. Kevin Zhou |
| 2025 | Self-Supervised Diffusion Models for Electron-Aware Molecular Representation Learning. Gyoung S. Na, Chanyoung Park |
| 2025 | Self-Updatable Large Language Models by Integrating Context into Model Parameters. Yu Wang, Xinshuang Liu, Xiusi Chen, Sean O'Brien, Junda Wu, Julian J. McAuley |
| 2025 | Self-play with Execution Feedback: Improving Instruction-following Capabilities of Large Language Models. Guanting Dong, Keming Lu, Chengpeng Li, Tingyu Xia, Bowen Yu, Chang Zhou, Jingren Zhou |
| 2025 | Self-supervised Monocular Depth Estimation Robust to Reflective Surface Leveraged by Triplet Mining. Wonhyeok Choi, Kyumin Hwang, Wei Peng, Minwoo Choi, Sunghoon Im |
| 2025 | Self-supervised contrastive learning performs non-linear system identification. Rodrigo González Laiz, Tobias Schmidt, Steffen Schneider |
| 2025 | Semantic Aware Representation Learning for Lifelong Learning. Fahad Sarfraz, Elahe Arani, Bahram Zonooz |
| 2025 | Semantic Image Inversion and Editing using Rectified Stochastic Differential Equations. Litu Rout, Yujia Chen, Nataniel Ruiz, Constantine Caramanis, Sanjay Shakkottai, Wen-Sheng Chu |
| 2025 | Semantic Loss Guided Data Efficient Supervised Fine Tuning for Safe Responses in LLMs. Yuxiao Lu, Arunesh Sinha, Pradeep Varakantham |
| 2025 | Semantic Temporal Abstraction via Vision-Language Model Guidance for Efficient Reinforcement Learning. Tian-Shuo Liu, Xu-Hui Liu, Ruifeng Chen, Lixuan Jin, Pengyuan Wang, Zhilong Zhang, Yang Yu |
| 2025 | Semantics-Adaptive Activation Intervention for LLMs via Dynamic Steering Vectors. Weixuan Wang, Jingyuan Yang, Wei Peng |
| 2025 | Semantix: An Energy-guided Sampler for Semantic Style Transfer. Huiang He, Minghui Hu, Chuanxia Zheng, Chaoyue Wang, Tat-Jen Cham |
| 2025 | Semi-Parametric Retrieval via Binary Bag-of-Tokens Index. Jiawei Zhou, Li Dong, Furu Wei, Lei Chen |
| 2025 | Semi-Supervised CLIP Adaptation by Enforcing Semantic and Trapezoidal Consistency. Kai Gan, Bo Ye, Min-Ling Zhang, Tong Wei |
| 2025 | Semi-Supervised Vision-Centric 3D Occupancy World Model for Autonomous Driving. Xiang Li, Pengfei Li, Yupeng Zheng, Wei Sun, Yan Wang, Yilun Chen |
| 2025 | Semialgebraic Neural Networks: From roots to representations. S. David Mis, Matti Lassas, Maarten V. de Hoop |
| 2025 | Sensitivity Verification for Additive Decision Tree Ensembles. Arhaan Ahmad, Tanay Vineet Tayal, Ashutosh Gupta, S. Akshay |
| 2025 | Sensitivity-Constrained Fourier Neural Operators for Forward and Inverse Problems in Parametric Differential Equations. Abdolmehdi Behroozi, Chaopeng Shen, Daniel Kifer |
| 2025 | Sensor-Invariant Tactile Representation. Harsh Gupta, Yuchen Mo, Shengmiao Jin, Wenzhen Yuan |
| 2025 | Separation Power of Equivariant Neural Networks. Marco Pacini, Xiaowen Dong, Bruno Lepri, Gabriele Santin |
| 2025 | Seq-VCR: Preventing Collapse in Intermediate Transformer Representations for Enhanced Reasoning. Md Rifat Arefin, Gopeshh Subbaraj, Nicolas Gontier, Yann LeCun, Irina Rish, Ravid Shwartz-Ziv, Christopher Pal |
| 2025 | Sequential Controlled Langevin Diffusions. Junhua Chen, Lorenz Richter, Julius Berner, Denis Blessing, Gerhard Neumann, Anima Anandkumar |
| 2025 | Sequential Stochastic Combinatorial Optimization Using Hierarchal Reinforcement Learning. Xinsong Feng, Zihan Yu, Yanhai Xiong, Haipeng Chen |
| 2025 | Severing Spurious Correlations with Data Pruning. Varun Mulchandani, Jung-Eun Kim |
| 2025 | ShEPhERD: Diffusing shape, electrostatics, and pharmacophores for bioisosteric drug design. Keir Adams, Kento Abeywardane, Jenna C. Fromer, Connor W. Coley |
| 2025 | Shallow diffusion networks provably learn hidden low-dimensional structure. Nicholas Matthew Boffi, Arthur Jacot, Stephen Tu, Ingvar M. Ziemann |
| 2025 | Shape as Line Segments: Accurate and Flexible Implicit Surface Representation. Siyu Ren, Junhui Hou |
| 2025 | Shapley-Guided Utility Learning for Effective Graph Inference Data Valuation. Hongliang Chi, Qiong Wu, Zhengyi Zhou, Yao Ma |
| 2025 | Shared-AE: Automatic Identification of Shared Subspaces in High-dimensional Neural and Behavioral Activity. Daiyao Yi, Hao Dong, Michael James Higley, Anne Churchland, Shreya Saxena |
| 2025 | Sharper Guarantees for Learning Neural Network Classifiers with Gradient Methods. Hossein Taheri, Christos Thrampoulidis, Arya Mazumdar |
| 2025 | Sharpness-Aware Black-Box Optimization. Feiyang Ye, Yueming Lyu, Xuehao Wang, Masashi Sugiyama, Yu Zhang, Ivor W. Tsang |
| 2025 | Sharpness-Aware Minimization Efficiently Selects Flatter Minima Late In Training. Zhanpeng Zhou, Mingze Wang, Yuchen Mao, Bingrui Li, Junchi Yan |
| 2025 | Sharpness-Aware Minimization: General Analysis and Improved Rates. Dimitris Oikonomou, Nicolas Loizou |
| 2025 | Shedding Light on Time Series Classification using Interpretability Gated Networks. Yunshi Wen, Tengfei Ma, Ronny Luss, Debarun Bhattacharjya, Achille Fokoue, Anak Agung Julius |
| 2025 | Shh, don't say that! Domain Certification in LLMs. Cornelius Emde, Alasdair Paren, Preetham Arvind, Maxime Guillaume Kayser, Tom Rainforth, Thomas Lukasiewicz, Philip Torr, Adel Bibi |
| 2025 | Shifting the Paradigm: A Diffeomorphism Between Time Series Data Manifolds for Achieving Shift-Invariancy in Deep Learning. Berken Utku Demirel, Christian Holz |
| 2025 | ShortcutsBench: A Large-Scale Real-world Benchmark for API-based Agents. Haiyang Shen, Yue Li, Desong Meng, Dongqi Cai, Sheng Qi, Li Zhang, Mengwei Xu, Yun Ma |
| 2025 | Shot2Story: A New Benchmark for Comprehensive Understanding of Multi-shot Videos. Mingfei Han, Linjie Yang, Xiaojun Chang, Lina Yao, Heng Wang |
| 2025 | Should VLMs be Pre-trained with Image Data? Sedrick Keh, Jean Mercat, Samir Yitzhak Gadre, Kushal Arora, Igor Vasiljevic, Benjamin Burchfiel, Shuran Song, Russ Tedrake, Thomas Kollar, Ludwig Schmidt, Achal Dave |
| 2025 | Show-o: One Single Transformer to Unify Multimodal Understanding and Generation. Jinheng Xie, Weijia Mao, Zechen Bai, David Junhao Zhang, Weihao Wang, Kevin Qinghong Lin, Yuchao Gu, Zhijie Chen, Zhenheng Yang, Mike Zheng Shou |
| 2025 | SiMHand: Mining Similar Hands for Large-Scale 3D Hand Pose Pre-training. Nie Lin, Takehiko Ohkawa, Yifei Huang, Mingfang Zhang, Minjie Cai, Ming Li, Ryosuke Furuta, Yoichi Sato |
| 2025 | SiReRAG: Indexing Similar and Related Information for Multihop Reasoning. Nan Zhang, Prafulla Kumar Choubey, Alexander R. Fabbri, Gabriel Bernadett-Shapiro, Rui Zhang, Prasenjit Mitra, Caiming Xiong, Chien-Sheng Wu |
| 2025 | SigDiffusions: Score-Based Diffusion Models for Time Series via Log-Signature Embeddings. Barbora Barancikova, Zhuoyue Huang, Cristopher Salvi |
| 2025 | Signature Kernel Conditional Independence Tests in Causal Discovery for Stochastic Processes. Georg Manten, Cecilia Casolo, Emilio Ferrucci, Søren Wengel Mogensen, Cristopher Salvi, Niki Kilbertus |
| 2025 | SimBa: Simplicity Bias for Scaling Up Parameters in Deep Reinforcement Learning. Hojoon Lee, Dongyoon Hwang, Donghu Kim, Hyunseung Kim, Jun Jet Tai, Kaushik Subramanian, Peter R. Wurman, Jaegul Choo, Peter Stone, Takuma Seno |
| 2025 | SimPER: A Minimalist Approach to Preference Alignment without Hyperparameters. Teng Xiao, Yige Yuan, Zhengyu Chen, Mingxiao Li, Shangsong Liang, Zhaochun Ren, Vasant G. Honavar |
| 2025 | SimXRD-4M: Big Simulated X-ray Diffraction Data and Crystal Symmetry Classification Benchmark. Bin Cao, Yang Liu, Zinan Zheng, Ruifeng Tan, Jia Li, Tong-yi Zhang |
| 2025 | Simple Guidance Mechanisms for Discrete Diffusion Models. Yair Schiff, Subham Sekhar Sahoo, Hao Phung, Guanghan Wang, Sam Boshar, Hugo Dalla-torre, Bernardo P. de Almeida, Alexander M. Rush, Thomas Pierrot, Volodymyr Kuleshov |
| 2025 | Simple ReFlow: Improved Techniques for Fast Flow Models. Beomsu Kim, Yu-Guan Hsieh, Michal Klein, Marco Cuturi, Jong Chul Ye, Bahjat Kawar, James Thornton |
| 2025 | Simple is Effective: The Roles of Graphs and Large Language Models in Knowledge-Graph-Based Retrieval-Augmented Generation. Mufei Li, Siqi Miao, Pan Li |
| 2025 | Simple yet Effective Incomplete Multi-view Clustering: Similarity-level Imputation and Intra-view Hybrid-group Prototype Construction. Shengju Yu, Zhibin Dong, Siwei Wang, Pei Zhang, Yi Zhang, Xinwang Liu, Naiyang Guan, Tiejun Li, Yiu-ming Cheung |
| 2025 | Simple, Good, Fast: Self-Supervised World Models Free of Baggage. Jan Robine, Marc Höftmann, Stefan Harmeling |
| 2025 | SimpleTM: A Simple Baseline for Multivariate Time Series Forecasting. Hui Chen, Viet Luong, Lopamudra Mukherjee, Vikas Singh |
| 2025 | Simplifying Deep Temporal Difference Learning. Matteo Gallici, Mattie Fellows, Benjamin Ellis, Bartomeu Pou, Ivan Masmitja, Jakob Nicolaus Foerster, Mario Martin |
| 2025 | Simplifying, Stabilizing and Scaling Continuous-time Consistency Models. Cheng Lu, Yang Song |
| 2025 | SimulPL: Aligning Human Preferences in Simultaneous Machine Translation. Donglei Yu, Yang Zhao, Jie Zhu, Yangyifan Xu, Yu Zhou, Chengqing Zong |
| 2025 | Simulating Human-like Daily Activities with Desire-driven Autonomy. Yiding Wang, Yuxuan Chen, Fangwei Zhong, Long Ma, Yizhou Wang |
| 2025 | Simulating Training Dynamics to Reconstruct Training Data from Deep Neural Networks. Hanling Tian, Yuhang Liu, Mingzhen He, Zhengbao He, Zhehao Huang, Ruikai Yang, Xiaolin Huang |
| 2025 | Single Teacher, Multiple Perspectives: Teacher Knowledge Augmentation for Enhanced Knowledge Distillation. Md. Imtiaz Hossain, Sharmen Akhter, Choong Seon Hong, Eui-Nam Huh |
| 2025 | Single-agent Poisoning Attacks Suffice to Ruin Multi-Agent Learning. Fan Yao, Yuwei Cheng, Ermin Wei, Haifeng Xu |
| 2025 | Singular Subspace Perturbation Bounds via Rectangular Random Matrix Diffusions. Peiyao Lai, Oren Mangoubi |
| 2025 | Sitcom-Crafter: A Plot-Driven Human Motion Generation System in 3D Scenes. Jianqi Chen, Panwen Hu, Xiaojun Chang, Zhenwei Shi, Michael Kampffmeyer, Xiaodan Liang |
| 2025 | Size-Generalizable RNA Structure Evaluation by Exploring Hierarchical Geometries. Zongzhao Li, Jiacheng Cen, Wenbing Huang, Taifeng Wang, Le Song |
| 2025 | Sketch2Diagram: Generating Vector Diagrams from Hand-Drawn Sketches. Itsumi Saito, Haruto Yoshida, Keisuke Sakaguchi |
| 2025 | Sketching for Convex and Nonconvex Regularized Least Squares with Sharp Guarantees. Yingzhen Yang, Ping Li |
| 2025 | Skill Expansion and Composition in Parameter Space. Tenglong Liu, Jianxiong Li, Yinan Zheng, Haoyi Niu, Yixing Lan, Xin Xu, Xianyuan Zhan |
| 2025 | SleepSMC: Ubiquitous Sleep Staging via Supervised Multimodal Coordination. Shuo Ma, Yingwei Zhang, Yiqiang Chen, Hualei Wang, Yuan Jin, Wei Zhang, Ziyu Jia |
| 2025 | Slot-Guided Adaptation of Pre-trained Diffusion Models for Object-Centric Learning and Compositional Generation. Adil Kaan Akan, Yucel Yemez |
| 2025 | SlowFast-VGen: Slow-Fast Learning for Action-Driven Long Video Generation. Yining Hong, Beide Liu, Maxine Wu, Yuanhao Zhai, Kai-Wei Chang, Linjie Li, Kevin Lin, Chung-Ching Lin, Jianfeng Wang, Zhengyuan Yang, Ying Nian Wu, Lijuan Wang |
| 2025 | Small Models are LLM Knowledge Triggers for Medical Tabular Prediction. Jiahuan Yan, Jintai Chen, Chaowen Hu, Bo Zheng, Yaojun Hu, Jimeng Sun, Jian Wu |
| 2025 | Small-to-Large Generalization: Training Data Influences Models Consistently Across Scale. Alaa Khaddaj, Logan Engstrom, Aleksander Madry |
| 2025 | Smaller, Weaker, Yet Better: Training LLM Reasoners via Compute-Optimal Sampling. Hritik Bansal, Arian Hosseini, Rishabh Agarwal, Vinh Q. Tran, Mehran Kazemi |
| 2025 | SmartPretrain: Model-Agnostic and Dataset-Agnostic Representation Learning for Motion Prediction. Yang Zhou, Hao Shao, Letian Wang, Steven L. Waslander, Hongsheng Li, Yu Liu |
| 2025 | SmartRAG: Jointly Learn RAG-Related Tasks From the Environment Feedback. Jingsheng Gao, Linxu Li, Ke Ji, Weiyuan Li, Yixin Lian, Yuzhuo Fu, Bin Dai |
| 2025 | Smoothing the Shift: Towards Stable Test-Time Adaptation under Complex Multimodal Noises. Zirun Guo, Tao Jin |
| 2025 | SoftCVI: Contrastive variational inference with self-generated soft labels. Daniel Ward, Mark Beaumont, Matteo Fasiolo |
| 2025 | SoftMatcha: A Soft and Fast Pattern Matcher for Billion-Scale Corpus Searches. Hiroyuki Deguchi, Go Kamoda, Yusuke Matsushita, Chihiro Taguchi, Kohei Suenaga, Masaki Waga, Sho Yokoi |
| 2025 | Solving Differential Equations with Constrained Learning. Viggo Moro, Luiz F. O. Chamon |
| 2025 | Solving New Tasks by Adapting Internet Video Knowledge. Calvin Luo, Zilai Zeng, Yilun Du, Chen Sun |
| 2025 | Solving Token Gradient Conflict in Mixture-of-Experts for Large Vision-Language Model. Longrong Yang, Dong Shen, Chaoxiang Cai, Fan Yang, Tingting Gao, Di Zhang, Xi Li |
| 2025 | Solving Video Inverse Problems Using Image Diffusion Models. Taesung Kwon, Jong Chul Ye |
| 2025 | Solving hidden monotone variational inequalities with surrogate losses. Ryan D'Orazio, Danilo Vucetic, Zichu Liu, Junhyung Lyle Kim, Ioannis Mitliagkas, Gauthier Gidel |
| 2025 | SonicSim: A customizable simulation platform for speech processing in moving sound source scenarios. Kai Li, Wendi Sang, Chang Zeng, Runxuan Yang, Guo Chen, Xiaolin Hu |
| 2025 | Sort-free Gaussian Splatting via Weighted Sum Rendering. Qiqi Hou, Randall Rauwendaal, Zifeng Li, Hoang Le, Farzad Farhadzadeh, Fatih Porikli, Alexei Bourd, Amir Said |
| 2025 | SoundCTM: Unifying Score-based and Consistency Models for Full-band Text-to-Sound Generation. Koichi Saito, Dongjun Kim, Takashi Shibuya, Chieh-Hsin Lai, Zhi Zhong, Yuhta Takida, Yuki Mitsufuji |
| 2025 | Spa-Bench: a comprehensive Benchmark for Smartphone Agent Evaluation. Jingxuan Chen, Derek Yuen, Bin Xie, Yuhao Yang, Gongwei Chen, Zhihao Wu, Li Yixing, Xurui Zhou, Weiwen Liu, Shuai Wang, Kaiwen Zhou, Rui Shao, Liqiang Nie, Yasheng Wang, Jianye Hao, Jun Wang, Kun Shao |
| 2025 | SpaceGNN: Multi-Space Graph Neural Network for Node Anomaly Detection with Extremely Limited Labels. Xiangyu Dong, Xingyi Zhang, Lei Chen, Mingxuan Yuan, Sibo Wang |
| 2025 | Sparse Autoencoders Do Not Find Canonical Units of Analysis. Patrick Leask, Bart Bussmann, Michael T. Pearce, Joseph Isaac Bloom, Curt Tigges, Noura Al Moubayed, Lee Sharkey, Neel Nanda |
| 2025 | Sparse Autoencoders Reveal Temporal Difference Learning in Large Language Models. Can Demircan, Tankred Saanum, Akshay Kumar Jagadish, Marcel Binz, Eric Schulz |
| 2025 | Sparse Feature Circuits: Discovering and Editing Interpretable Causal Graphs in Language Models. Samuel Marks, Can Rager, Eric J. Michaud, Yonatan Belinkov, David Bau, Aaron Mueller |
| 2025 | Sparse Learning for State Space Models on Mobile. Xuan Shen, Hangyu Zheng, Yifan Gong, Zhenglun Kong, Changdi Yang, Zheng Zhan, Yushu Wu, Xue Lin, Yanzhi Wang, Pu Zhao, Wei Niu |
| 2025 | Sparse autoencoders reveal selective remapping of visual concepts during adaptation. Hyesu Lim, Jinho Choi, Jaegul Choo, Steffen Schneider |
| 2025 | Sparse components distinguish visual pathways & their alignment to neural networks. Ammar I Marvi, Nancy Kanwisher, Meenakshi Khosla |
| 2025 | SparsyFed: Sparse Adaptive Federated Learning. Adriano Guastella, Lorenzo Sani, Alex Iacob, Alessio Mora, Paolo Bellavista, Nicholas Donald Lane |
| 2025 | Spatial-Mamba: Effective Visual State Space Models via Structure-Aware State Fusion. Chaodong Xiao, Minghan Li, Zhengqiang Zhang, Deyu Meng, Lei Zhang |
| 2025 | Specialized Foundation Models Struggle to Beat Supervised Baselines. Zongzhe Xu, Ritvik Gupta, Wenduo Cheng, Alexander Shen, Junhong Shen, Ameet Talwalkar, Mikhail Khodak |
| 2025 | Spectral Compressive Imaging via Unmixing-driven Subspace Diffusion Refinement. Haijin Zeng, Benteng Sun, Yongyong Chen, Jingyong Su, Yong Xu |
| 2025 | Spectral-Refiner: Accurate Fine-Tuning of Spatiotemporal Fourier Neural Operator for Turbulent Flows. Shuhao Cao, Francesco Brarda, Ruipeng Li, Yuanzhe Xi |
| 2025 | Spectro-Riemannian Graph Neural Networks. Karish Grover, Haiyang Yu, Xiang Song, Qi Zhu, Han Xie, Vassilis N. Ioannidis, Christos Faloutsos |
| 2025 | Speculative Knowledge Distillation: Bridging the Teacher-Student Gap Through Interleaved Sampling. Wenda Xu, Rujun Han, Zifeng Wang, Long T. Le, Dhruv Madeka, Lei Li, William Yang Wang, Rishabh Agarwal, Chen-Yu Lee, Tomas Pfister |
| 2025 | Speculative RAG: Enhancing Retrieval Augmented Generation through Drafting. Zilong Wang, Zifeng Wang, Long T. Le, Huaixiu Steven Zheng, Swaroop Mishra, Vincent Perot, Yuwei Zhang, Anush Mattapalli, Ankur Taly, Jingbo Shang, Chen-Yu Lee, Tomas Pfister |
| 2025 | Speech Robust Bench: A Robustness Benchmark For Speech Recognition. Muhammad A. Shah, David Solans Noguero, Mikko A. Heikkilä, Bhiksha Raj, Nicolas Kourtellis |
| 2025 | Spherical Tree-Sliced Wasserstein Distance. Hoang V. Tran, Thanh T. Chu, Minh-Khoi Nguyen-Nhat, Huyen Trang Pham, Tam Le, Tan Minh Nguyen |
| 2025 | Spider 2.0: Evaluating Language Models on Real-World Enterprise Text-to-SQL Workflows. Fangyu Lei, Jixuan Chen, Yuxiao Ye, Ruisheng Cao, Dongchan Shin, Hongjin Su, Zhaoqing Suo, Hongcheng Gao, Wenjing Hu, Pengcheng Yin, Victor Zhong, Caiming Xiong, Ruoxi Sun, Qian Liu, Sida Wang, Tao Yu |
| 2025 | SpikeLLM: Scaling up Spiking Neural Network to Large Language Models via Saliency-based Spiking. Xingrun Xing, Boyan Gao, Zheng Liu, David A. Clifton, Shitao Xiao, Wanpeng Zhang, Li Du, Zheng Zhang, Guoqi Li, Jiajun Zhang |
| 2025 | Spiking Vision Transformer with Saccadic Attention. Shuai Wang, Malu Zhang, Dehao Zhang, Ammar Belatreche, Yichen Xiao, Yu Liang, Yimeng Shan, Qian Sun, Enqi Zhang, Yang Yang |
| 2025 | SpinQuant: LLM Quantization with Learned Rotations. Zechun Liu, Changsheng Zhao, Igor Fedorov, Bilge Soran, Dhruv Choudhary, Raghuraman Krishnamoorthi, Vikas Chandra, Yuandong Tian, Tijmen Blankevoort |
| 2025 | SplatFormer: Point Transformer for Robust 3D Gaussian Splatting. Yutong Chen, Marko Mihajlovic, Xiyi Chen, Yiming Wang, Sergey Prokudin, Siyu Tang |
| 2025 | SplineGS: Learning Smooth Trajectories in Gaussian Splatting for Dynamic Scene Reconstruction. Jihwan Yoon, Sangbeom Han, Jaeseok Oh, Minsik Lee |
| 2025 | Sports-Traj: A Unified Trajectory Generation Model for Multi-Agent Movement in Sports. Yi Xu, Yun Fu |
| 2025 | Spread Preference Annotation: Direct Preference Judgment for Efficient LLM Alignment. Dongyoung Kim, Kimin Lee, Jinwoo Shin, Jaehyung Kim |
| 2025 | Spreading Out-of-Distribution Detection on Graphs. Daeho Um, Jongin Lim, Sunoh Kim, Yuneil Yeo, Yoonho Jung |
| 2025 | Spurious Forgetting in Continual Learning of Language Models. Junhao Zheng, Xidi Cai, Shengjie Qiu, Qianli Ma |
| 2025 | SqueezeAttention: 2D Management of KV-Cache in LLM Inference via Layer-wise Optimal Budget. Zihao Wang, Bin Cui, Shaoduo Gan |
| 2025 | Stabilized Neural Prediction of Potential Outcomes in Continuous Time. Konstantin Hess, Stefan Feuerriegel |
| 2025 | Stabilizing Reinforcement Learning in Differentiable Multiphysics Simulation. Eliot Xing, Vernon Luk, Jean Oh |
| 2025 | Stable Hadamard Memory: Revitalizing Memory-Augmented Agents for Reinforcement Learning. Hung Le, Dung Nguyen, Kien Do, Sunil Gupta, Svetha Venkatesh |
| 2025 | Stable Segment Anything Model. Qi Fan, Xin Tao, Lei Ke, Mingqiao Ye, Di Zhang, Pengfei Wan, Yu-Wing Tai, Chi-Keung Tang |
| 2025 | Standard Gaussian Process is All You Need for High-Dimensional Bayesian Optimization. Zhitong Xu, Haitao Wang, Jeff M. Phillips, Shandian Zhe |
| 2025 | Standardizing Structural Causal Models. Weronika Ormaniec, Scott Sussex, Lars Lorch, Bernhard Schölkopf, Andreas Krause |
| 2025 | Start Smart: Leveraging Gradients For Enhancing Mask-based XAI Methods. Buelent Uendes, Shujian Yu, Mark Hoogendoorn |
| 2025 | State Space Model Meets Transformer: A New Paradigm for 3D Object Detection. Chuxin Wang, Wenfei Yang, Xiang Liu, Tianzhu Zhang |
| 2025 | State Space Models are Provably Comparable to Transformers in Dynamic Token Selection. Naoki Nishikawa, Taiji Suzuki |
| 2025 | Statistical Advantages of Perturbing Cosine Router in Mixture of Experts. Huy Nguyen, Pedram Akbarian, Huyen Trang Pham, Thien Trang Nguyen Vu, Shujian Zhang, Nhat Ho |
| 2025 | Statistical Tractability of Off-policy Evaluation of History-dependent Policies in POMDPs. Yuheng Zhang, Nan Jiang |
| 2025 | Stealthy Shield Defense: A Conditional Mutual Information-Based Approach against Black-Box Model Inversion Attacks. Tianqu Zhuang, Hongyao Yu, Yixiang Qiu, Hao Fang, Bin Chen, Shu-Tao Xia |
| 2025 | Steering Large Language Models between Code Execution and Textual Reasoning. Yongchao Chen, Harsh Jhamtani, Srinagesh Sharma, Chuchu Fan, Chi Wang |
| 2025 | Steering Masked Discrete Diffusion Models via Discrete Denoising Posterior Prediction. Jarrid Rector-Brooks, Mohsin Hasan, Zhangzhi Peng, Cheng-Hao Liu, Sarthak Mittal, Nouha Dziri, Michael M. Bronstein, Pranam Chatterjee, Alexander Tong, Joey Bose |
| 2025 | Steering Protein Family Design through Profile Bayesian Flow. Jingjing Gong, Yu Pei, Siyu Long, Yuxuan Song, Zhe Zhang, Wenhao Huang, Ziyao Cao, Shuyi Zhang, Hao Zhou, Wei-Ying Ma |
| 2025 | Stem-OB: Generalizable Visual Imitation Learning with Stem-Like Convergent Observation through Diffusion Inversion. Kaizhe Hu, Zihang Rui, Yao He, Yuyao Liu, Pu Hua, Huazhe Xu |
| 2025 | Step-by-Step Reasoning for Math Problems via Twisted Sequential Monte Carlo. Shengyu Feng, Xiang Kong, Shuang Ma, Aonan Zhang, Dong Yin, Chong Wang, Ruoming Pang, Yiming Yang |
| 2025 | Stiefel Flow Matching for Moment-Constrained Structure Elucidation. Austin Henry Cheng, Alston Lo, Kin Long Kelvin Lee, Santiago Miret, Alán Aspuru-Guzik |
| 2025 | StochSync: Stochastic Diffusion Synchronization for Image Generation in Arbitrary Spaces. Kyeongmin Yeo, Jaihoon Kim, Minhyuk Sung |
| 2025 | Stochastic Bandits Robust to Adversarial Attacks. Xuchuang Wang, Maoli Liu, Jinhang Zuo, Xutong Liu, John C. S. Lui, Mohammad Hajiesmaili |
| 2025 | Stochastic Polyak Step-sizes and Momentum: Convergence Guarantees and Practical Performance. Dimitris Oikonomou, Nicolas Loizou |
| 2025 | Stochastic Semi-Gradient Descent for Learning Mean Field Games with Population-Aware Function Approximation. Chenyu Zhang, Xu Chen, Xuan Di |
| 2025 | Stochastic variance-reduced Gaussian variational inference on the Bures-Wasserstein manifold. Hoang Phuc Hau Luu, Hanlin Yu, Bernardo Williams, Marcelo Hartmann, Arto Klami |
| 2025 | Storybooth: Training-Free Multi-Subject Consistency for Improved Visual Storytelling. Jaskirat Singh, Junshen K. Chen, Jonas Kohler, Michael F. Cohen |
| 2025 | Straight to Zero: Why Linearly Decaying the Learning Rate to Zero Works Best for LLMs. Shane Bergsma, Nolan Simran Dey, Gurpreet Gosal, Gavia Gray, Daria Soboleva, Joel Hestness |
| 2025 | Strategic Classification With Externalities. Safwan Hossain, Evi Micha, Yiling Chen, Ariel D. Procaccia |
| 2025 | Strategist: Self-improvement of LLM Decision Making via Bi-Level Tree Search. Jonathan Light, Min Cai, Weiqin Chen, Guanzhi Wang, Xiusi Chen, Wei Cheng, Yisong Yue, Ziniu Hu |
| 2025 | Streaming Algorithms For ℓp Flows and ℓp Regression. Amit Chakrabarti, Jeffrey Jiang, David P. Woodruff, Taisuke Yasuda |
| 2025 | Streaming Video Question-Answering with In-context Video KV-Cache Retrieval. Shangzhe Di, Zhelun Yu, Guanghao Zhang, Haoyuan Li, Tao Zhong, Hao Cheng, Bolin Li, Wanggui He, Fangxun Shu, Hao Jiang |
| 2025 | Streaming Video Understanding and Multi-round Interaction with Memory-enhanced Knowledge. Haomiao Xiong, Zongxin Yang, Jiazuo Yu, Yunzhi Zhuge, Lu Zhang, Jiawen Zhu, Huchuan Lu |
| 2025 | Streamlining Prediction in Bayesian Deep Learning. Rui Li, Marcus Klasson, Arno Solin, Martin Trapp |
| 2025 | Streamlining Redundant Layers to Compress Large Language Models. Xiaodong Chen, Yuxuan Hu, Jing Zhang, Yanling Wang, Cuiping Li, Hong Chen |
| 2025 | Strength Estimation and Human-Like Strength Adjustment in Games. Chun Jung Chen, Chung-Chin Shih, Ti-Rong Wu |
| 2025 | StringLLM: Understanding the String Processing Capability of Large Language Models. Xilong Wang, Hao Fu, Jindong Wang, Neil Zhenqiang Gong |
| 2025 | Strong Model Collapse. Elvis Dohmatob, Yunzhen Feng, Arjun Subramonian, Julia Kempe |
| 2025 | Strong Preferences Affect the Robustness of Preference Models and Value Alignment. Ziwei Xu, Mohan S. Kankanhalli |
| 2025 | StructRAG: Boosting Knowledge Intensive Reasoning of LLMs via Inference-time Hybrid Information Structurization. Zhuoqun Li, Xuanang Chen, Haiyang Yu, Hongyu Lin, Yaojie Lu, Qiaoyu Tang, Fei Huang, Xianpei Han, Le Sun, Yongbin Li |
| 2025 | Structural-Entropy-Based Sample Selection for Efficient and Effective Learning. Tianchi Xie, Jiangning Zhu, Guozu Ma, Minzhi Lin, Wei Chen, Weikai Yang, Shixia Liu |
| 2025 | Structure Language Models for Protein Conformation Generation. Jiarui Lu, Xiaoyin Chen, Stephen Zhewen Lu, Chence Shi, Hongyu Guo, Yoshua Bengio, Jian Tang |
| 2025 | Structuring Benchmark into Knowledge Graphs to Assist Large Language Models in Retrieving and Designing Models. Hanmo Liu, Shimin Di, Jialiang Wang, Zhili Wang, Jiachuan Wang, Xiaofang Zhou, Lei Chen |
| 2025 | Student-Informed Teacher Training. Nico Messikommer, Jiaxu Xing, Elie Aljalbout, Davide Scaramuzza |
| 2025 | Studying the Interplay Between the Actor and Critic Representations in Reinforcement Learning. Samuel Garcin, Trevor McInroe, Pablo Samuel Castro, Christopher G. Lucas, David Abel, Prakash Panangaden, Stefano V. Albrecht |
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| 2025 | Subgraph Federated Learning for Local Generalization. Sungwon Kim, Yoonho Lee, Yunhak Oh, Namkyeong Lee, Sukwon Yun, Junseok Lee, Sein Kim, Carl Yang, Chanyoung Park |
| 2025 | Subtask-Aware Visual Reward Learning from Segmented Demonstrations. Changyeon Kim, Minho Heo, Doohyun Lee, Honglak Lee, Jinwoo Shin, Joseph J. Lim, Kimin Lee |
| 2025 | Sufficient Context: A New Lens on Retrieval Augmented Generation Systems. Hailey Joren, Jianyi Zhang, Chun-Sung Ferng, Da-Cheng Juan, Ankur Taly, Cyrus Rashtchian |
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| 2025 | Supervised and Semi-Supervised Diffusion Maps with Label-Driven Diffusion. Harel Mendelman, Ronen Talmon |
| 2025 | Support is All You Need for Certified VAE Training. Changming Xu, Debangshu Banerjee, Deepak Vasisht, Gagandeep Singh |
| 2025 | SurFhead: Affine Rig Blending for Geometrically Accurate 2D Gaussian Surfel Head Avatars. Jaeseong Lee, Taewoong Kang, Marcel C. Bühler, Min-Jung Kim, Sungwon Hwang, Junha Hyung, Hyojin Jang, Jaegul Choo |
| 2025 | Surgical, Cheap, and Flexible: Mitigating False Refusal in Language Models via Single Vector Ablation. Xinpeng Wang, Chengzhi Hu, Paul Röttger, Barbara Plank |
| 2025 | Surprising Effectiveness of pretraining Ternary Language Model at Scale. Ayush Kaushal, Tejas Vaidhya, Arnab Kumar Mondal, Tejas Pandey, Aaryan Bhagat, Irina Rish |
| 2025 | Swift Hydra: Self-Reinforcing Generative Framework for Anomaly Detection with Multiple Mamba Models. Nguyen Hoang Khoi Do, Truc Nguyen, Malik Hassanaly, Raed Alharbi, Jung Taek Seo, My T. Thai |
| 2025 | Swift4D: Adaptive divide-and-conquer Gaussian Splatting for compact and efficient reconstruction of dynamic scene. Jiahao Wu, Rui Peng, Zhiyan Wang, Lu Xiao, Luyang Tang, Jinbo Yan, Kaiqiang Xiong, Ronggang Wang |
| 2025 | Swing-by Dynamics in Concept Learning and Compositional Generalization. Yongyi Yang, Core Francisco Park, Ekdeep Singh Lubana, Maya Okawa, Wei Hu, Hidenori Tanaka |
| 2025 | Swiss Army Knife: Synergizing Biases in Knowledge from Vision Foundation Models for Multi-Task Learning. Yuxiang Lu, Shengcao Cao, Yu-Xiong Wang |
| 2025 | Sylber: Syllabic Embedding Representation of Speech from Raw Audio. Cheol Jun Cho, Nicholas Lee, Akshat Gupta, Dhruv Agarwal, Ethan Chen, Alan W. Black, Gopala Anumanchipalli |
| 2025 | SyllableLM: Learning Coarse Semantic Units for Speech Language Models. Alan Baade, Puyuan Peng, David Harwath |
| 2025 | SymDiff: Equivariant Diffusion via Stochastic Symmetrisation. Leo Zhang, Kianoosh Ashouritaklimi, Yee Whye Teh, Rob Cornish |
| 2025 | Symbolic regression via MDLformer-guided search: from minimizing prediction error to minimizing description length. Zihan Yu, Jingtao Ding, Yong Li, Depeng Jin |
| 2025 | SymmCD: Symmetry-Preserving Crystal Generation with Diffusion Models. Daniel Levy, Siba Smarak Panigrahi, Sékou-Oumar Kaba, Qiang Zhu, Kin Long Kelvin Lee, Mikhail Galkin, Santiago Miret, Siamak Ravanbakhsh |
| 2025 | SymmetricDiffusers: Learning Discrete Diffusion on Finite Symmetric Groups. Yongxing Zhang, Donglin Yang, Renjie Liao |
| 2025 | SynCamMaster: Synchronizing Multi-Camera Video Generation from Diverse Viewpoints. Jianhong Bai, Menghan Xia, Xintao Wang, Ziyang Yuan, Zuozhu Liu, Haoji Hu, Pengfei Wan, Di Zhang |
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| 2025 | SynQ: Accurate Zero-shot Quantization by Synthesis-aware Fine-tuning. Minjun Kim, Jongjin Kim, U Kang |
| 2025 | Synergy Between Sufficient Changes and Sparse Mixing Procedure for Disentangled Representation Learning. Zijian Li, Shunxing Fan, Yujia Zheng, Ignavier Ng, Shaoan Xie, Guangyi Chen, Xinshuai Dong, Ruichu Cai, Kun Zhang |
| 2025 | Synergy and Diversity in CLIP: Enhancing Performance Through Adaptive Backbone Ensembling. Cristian Rodriguez Opazo, Ehsan Abbasnejad, Damien Teney, Hamed Damirchi, Edison Marrese-Taylor, Anton van den Hengel |
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| 2025 | Synthesizing Realistic fMRI: A Physiological Dynamics-Driven Hierarchical Diffusion Model for Efficient fMRI Acquisition. Yufan Hu, Yu Jiang, Wuyang Li, Yixuan Yuan |
| 2025 | Synthetic continued pretraining. Zitong Yang, Neil Band, Shuangping Li, Emmanuel J. Candès, Tatsunori Hashimoto |
| 2025 | Synthio: Augmenting Small-Scale Audio Classification Datasets with Synthetic Data. Sreyan Ghosh, Sonal Kumar, Zhifeng Kong, Rafael Valle, Bryan Catanzaro, Dinesh Manocha |
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| 2025 | System 1.x: Learning to Balance Fast and Slow Planning with Language Models. Swarnadeep Saha, Archiki Prasad, Justin Chih-Yao Chen, Peter Hase, Elias Stengel-Eskin, Mohit Bansal |
| 2025 | Systematic Outliers in Large Language Models. Yongqi An, Xu Zhao, Tao Yu, Ming Tang, Jinqiao Wang |
| 2025 | Systematic Relational Reasoning With Epistemic Graph Neural Networks. Irtaza Khalid, Steven Schockaert |
| 2025 | Systems with Switching Causal Relations: A Meta-Causal Perspective. Moritz Willig, Tim Nelson Tobiasch, Florian Peter Busch, Jonas Seng, Devendra Singh Dhami, Kristian Kersting |
| 2025 | T-JEPA: Augmentation-Free Self-Supervised Learning for Tabular Data. Hugo Thimonier, José Lucas De Melo Costa, Fabrice Popineau, Arpad Rimmel, Bich-Liên Doan |
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| 2025 | T2V2: A Unified Non-Autoregressive Model for Speech Recognition and Synthesis via Multitask Learning. Nabarun Goswami, Hanqin Wang, Tatsuya Harada |
| 2025 | TAID: Temporally Adaptive Interpolated Distillation for Efficient Knowledge Transfer in Language Models. Makoto Shing, Kou Misaki, Han Bao, Sho Yokoi, Takuya Akiba |
| 2025 | TANGO: Co-Speech Gesture Video Reenactment with Hierarchical Audio Motion Embedding and Diffusion Interpolation. Haiyang Liu, Xingchao Yang, Tomoya Akiyama, Yuantian Huang, Qiaoge Li, Shigeru Kuriyama, Takafumi Taketomi |
| 2025 | TASAR: Transfer-based Attack on Skeletal Action Recognition. Yunfeng Diao, Baiqi Wu, Ruixuan Zhang, Ajian Liu, Xiaoshuai Hao, Xingxing Wei, Meng Wang, He Wang |
| 2025 | TAU-106K: A New Dataset for Comprehensive Understanding of Traffic Accident. Yixuan Zhou, Long Bai, Sijia Cai, Bing Deng, Xing Xu, Heng Tao Shen |
| 2025 | TC-MoE: Augmenting Mixture of Experts with Ternary Expert Choice. Shen Yan, Xingyan Bin, Sijun Zhang, Yisen Wang, Zhouchen Lin |
| 2025 | TD-Paint: Faster Diffusion Inpainting Through Time-Aware Pixel Conditioning. Tsiry Mayet, Pourya Shamsolmoali, Simon Bernard, Eric Granger, Romain Hérault, Clément Chatelain |
| 2025 | TDDBench: A Benchmark for Training data detection. Zhihao Zhu, Yi Yang, Defu Lian |
| 2025 | TEASER: Token Enhanced Spatial Modeling for Expressions Reconstruction. Yunfei Liu, Lei Zhu, Lijian Lin, Ye Zhu, Ailing Zhang, Yu Li |
| 2025 | TEOChat: A Large Vision-Language Assistant for Temporal Earth Observation Data. Jeremy Andrew Irvin, Emily Ruoyu Liu, Joyce Chuyi Chen, Ines Dormoy, Jinyoung Kim, Samar Khanna, Zhuo Zheng, Stefano Ermon |
| 2025 | TFG-Flow: Training-free Guidance in Multimodal Generative Flow. Haowei Lin, Shanda Li, Haotian Ye, Yiming Yang, Stefano Ermon, Yitao Liang, Jianzhu Ma |
| 2025 | TGB-Seq Benchmark: Challenging Temporal GNNs with Complex Sequential Dynamics. Lu Yi, Jie Peng, Yanping Zheng, Fengran Mo, Zhewei Wei, Yuhang Ye, Yue Zixuan, Zengfeng Huang |
| 2025 | TIGER: Time-frequency Interleaved Gain Extraction and Reconstruction for Efficient Speech Separation. Mohan Xu, Kai Li, Guo Chen, Xiaolin Hu |
| 2025 | TIGeR: Unifying Text-to-Image Generation and Retrieval with Large Multimodal Models. Leigang Qu, Haochuan Li, Tan Wang, Wenjie Wang, Yongqi Li, Liqiang Nie, Tat-Seng Chua |
| 2025 | TIPS: Text-Image Pretraining with Spatial awareness. Kevis-Kokitsi Maninis, Kaifeng Chen, Soham Ghosh, Arjun Karpur, Koert Chen, Ye Xia, Bingyi Cao, Daniel Salz, Guangxing Han, Jan Dlabal, Dan Gnanapragasam, Mojtaba Seyedhosseini, Howard Zhou, André Araújo |
| 2025 | TIS-DPO: Token-level Importance Sampling for Direct Preference Optimization With Estimated Weights. Aiwei Liu, Haoping Bai, Zhiyun Lu, Yanchao Sun, Xiang Kong, Xiaoming Simon Wang, Jiulong Shan, Albin Madappally Jose, Xiaojiang Liu, Lijie Wen, Philip S. Yu, Meng Cao |
| 2025 | TLDR: Token-Level Detective Reward Model for Large Vision Language Models. Deqing Fu, Tong Xiao, Rui Wang, Wang Zhu, Pengchuan Zhang, Guan Pang, Robin Jia, Lawrence Chen |
| 2025 | TODO: Enhancing LLM Alignment with Ternary Preferences. Yuxiang Guo, Lu Yin, Bo Jiang, Jiaqi Zhang |
| 2025 | TOMATO: Assessing Visual Temporal Reasoning Capabilities in Multimodal Foundation Models. Ziyao Shangguan, Chuhan Li, Yuxuan Ding, Yanan Zheng, Yilun Zhao, Tesca Fitzgerald, Arman Cohan |
| 2025 | TOP-ERL: Transformer-based Off-Policy Episodic Reinforcement Learning. Ge Li, Dong Tian, Hongyi Zhou, Xinkai Jiang, Rudolf Lioutikov, Gerhard Neumann |
| 2025 | TPO: Aligning Large Language Models with Multi-branch & Multi-step Preference Trees. Weibin Liao, Xu Chu, Yasha Wang |
| 2025 | TRACE: Temporal Grounding Video LLM via Causal Event Modeling. Yongxin Guo, Jingyu Liu, Mingda Li, Qingbin Liu, Xi Chen, Xiaoying Tang |
| 2025 | TRENDy: Temporal Regression of Effective Nonlinear Dynamics. Matthew Ricci, Guy Pelc, Zoe Piran, Noa Moriel, Mor Nitzan |
| 2025 | TS-LIF: A Temporal Segment Spiking Neuron Network for Time Series Forecasting. Shibo Feng, Wanjin Feng, Xingyu Gao, Peilin Zhao, Zhiqi Shen |
| 2025 | TSC-Net: Prediction of Pedestrian Trajectories by Trajectory-Scene-Cell Classification. Bo Hu, Tat-Jen Cham |
| 2025 | TTVD: Towards a Geometric Framework for Test-Time Adaptation Based on Voronoi Diagram. Mingxi Lei, Chunwei Ma, Meng Ding, Yufan Zhou, Ziyun Huang, Jinhui Xu |
| 2025 | TULIP: Token-length Upgraded CLIP. Ivona Najdenkoska, Mohammad Mahdi Derakhshani, Yuki M. Asano, Nanne van Noord, Marcel Worring, Cees G. M. Snoek |
| 2025 | TVNet: A Novel Time Series Analysis Method Based on Dynamic Convolution and 3D-Variation. Chenghan Li, Mingchen Li, Ruisheng Diao |
| 2025 | TabDiff: a Mixed-type Diffusion Model for Tabular Data Generation. Juntong Shi, Minkai Xu, Harper Hua, Hengrui Zhang, Stefano Ermon, Jure Leskovec |
| 2025 | TabM: Advancing tabular deep learning with parameter-efficient ensembling. Yury Gorishniy, Akim Kotelnikov, Artem Babenko |
| 2025 | TabReD: Analyzing Pitfalls and Filling the Gaps in Tabular Deep Learning Benchmarks. Ivan Rubachev, Nikolay Kartashev, Yury Gorishniy, Artem Babenko |
| 2025 | TabWak: A Watermark for Tabular Diffusion Models. Chaoyi Zhu, Jiayi Tang, Jeroen M. Galjaard, Pin-Yu Chen, Robert Birke, Cornelis Bos, Lydia Y. Chen |
| 2025 | Tackling Data Corruption in Offline Reinforcement Learning via Sequence Modeling. Jiawei Xu, Rui Yang, Shuang Qiu, Feng Luo, Meng Fang, Baoxiang Wang, Lei Han |
| 2025 | Tailoring Mixup to Data for Calibration. Quentin Bouniot, Pavlo Mozharovskyi, Florence d'Alché-Buc |
| 2025 | Talking Turns: Benchmarking Audio Foundation Models on Turn-Taking Dynamics. Siddhant Arora, Zhiyun Lu, Chung-Cheng Chiu, Ruoming Pang, Shinji Watanabe |
| 2025 | Taming Overconfidence in LLMs: Reward Calibration in RLHF. Jixuan Leng, Chengsong Huang, Banghua Zhu, Jiaxin Huang |
| 2025 | Taming Transformer Without Using Learning Rate Warmup. Xianbiao Qi, Yelin He, Jiaquan Ye, Chun-Guang Li, Bojia Zi, Xili Dai, Qin Zou, Rong Xiao |
| 2025 | Tamper-Resistant Safeguards for Open-Weight LLMs. Rishub Tamirisa, Bhrugu Bharathi, Long Phan, Andy Zhou, Alice Gatti, Tarun Suresh, Maxwell Lin, Justin Wang, Rowan Wang, Ron Arel, Andy Zou, Dawn Song, Bo Li, Dan Hendrycks, Mantas Mazeika |
| 2025 | Targeted Attack Improves Protection against Unauthorized Diffusion Customization. Boyang Zheng, Chumeng Liang, Xiaoyu Wu |
| 2025 | Task Descriptors Help Transformers Learn Linear Models In-Context. Ruomin Huang, Rong Ge |
| 2025 | Task-Adaptive Pretrained Language Models via Clustered-Importance Sampling. David Grangier, Simin Fan, Skyler Seto, Pierre Ablin |
| 2025 | TaskGalaxy: Scaling Multi-modal Instruction Fine-tuning with Tens of Thousands Vision Task Types. Jiankang Chen, Tianke Zhang, Changyi Liu, Haojie Ding, Yaya Shi, Cheng Feng, Huihui Xiao, Bin Wen, Fan Yang, Tingting Gao, Di Zhang |
| 2025 | Teaching Human Behavior Improves Content Understanding Abilities Of VLMs. Somesh Kumar Singh, Harini S. I, Yaman Kumar Singla, Changyou Chen, Rajiv Ratn Shah, Veeky Baths, Balaji Krishnamurthy |
| 2025 | Teaching LLMs How to Learn with Contextual Fine-Tuning. Younwoo Choi, Muhammad Adil Asif, Ziwen Han, John Willes, Rahul G. Krishnan |
| 2025 | TeaserGen: Generating Teasers for Long Documentaries. Weihan Xu, Paul Pu Liang, Haven Kim, Julian J. McAuley, Taylor Berg-Kirkpatrick, Hao-Wen Dong |
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| 2025 | TempMe: Video Temporal Token Merging for Efficient Text-Video Retrieval. Leqi Shen, Tianxiang Hao, Tao He, Sicheng Zhao, Yifeng Zhang, Pengzhang Liu, Yongjun Bao, Guiguang Ding |
| 2025 | Temporal Difference Learning: Why It Can Be Fast and How It Will Be Faster. Patrick Schnell, Luca Guastoni, Nils Thuerey |
| 2025 | Temporal Flexibility in Spiking Neural Networks: Towards Generalization Across Time Steps and Deployment Friendliness. Kangrui Du, Yuhang Wu, Shikuang Deng, Shi Gu |
| 2025 | Temporal Heterogeneous Graph Generation with Privacy, Utility, and Efficiency. Xinyu He, Dongqi Fu, Hanghang Tong, Ross Maciejewski, Jingrui He |
| 2025 | Temporal Reasoning Transfer from Text to Video. Lei Li, Yuanxin Liu, Linli Yao, Peiyuan Zhang, Chenxin An, Lean Wang, Xu Sun, Lingpeng Kong, Qi Liu |
| 2025 | Test of Time: A Benchmark for Evaluating LLMs on Temporal Reasoning. Bahare Fatemi, Mehran Kazemi, Anton Tsitsulin, Karishma Malkan, Jinyeong Yim, John Palowitch, Sungyong Seo, Jonathan Halcrow, Bryan Perozzi |
| 2025 | Test-Time Adaptation for Combating Missing Modalities in Egocentric Videos. Merey Ramazanova, Alejandro Pardo, Bernard Ghanem, Motasem Alfarra |
| 2025 | Test-Time Ensemble via Linear Mode Connectivity: A Path to Better Adaptation. Byungjai Kim, Chanho Ahn, Wissam J. Baddar, Kikyung Kim, Huijin Lee, Saehyun Ahn, Seungju Han, Sungjoo Suh, Eunho Yang |
| 2025 | Test-time Adaptation for Cross-modal Retrieval with Query Shift. Haobin Li, Peng Hu, Qianjun Zhang, Xi Peng, XitingLiu, Mouxing Yang |
| 2025 | Test-time Adaptation for Image Compression with Distribution Regularization. Kecheng Chen, Pingping Zhang, Tiexin Qin, Shiqi Wang, Hong Yan, Haoliang Li |
| 2025 | Test-time Adaptation for Regression by Subspace Alignment. Kazuki Adachi, Shin'ya Yamaguchi, Atsutoshi Kumagai, Tomoki Hamagami |
| 2025 | Test-time Alignment of Diffusion Models without Reward Over-optimization. Sunwoo Kim, Minkyu Kim, Dongmin Park |
| 2025 | TestGenEval: A Real World Unit Test Generation and Test Completion Benchmark. Kush Jain, Gabriel Synnaeve, Baptiste Rozière |
| 2025 | TetSphere Splatting: Representing High-Quality Geometry with Lagrangian Volumetric Meshes. Minghao Guo, Bohan Wang, Kaiming He, Wojciech Matusik |
| 2025 | TexTailor: Customized Text-aligned Texturing via Effective Resampling. Suin Lee, Daeshik Kim |
| 2025 | Text-to-Image Rectified Flow as Plug-and-Play Priors. Xiaofeng Yang, Cheng Chen, XuLei Yang, Fayao Liu, Guosheng Lin |
| 2025 | Text2PDE: Latent Diffusion Models for Accessible Physics Simulation. Anthony Y. Zhou, Zijie Li, Michael Schneier, John R. Buchanan Jr., Amir Barati Farimani |
| 2025 | Text4Seg: Reimagining Image Segmentation as Text Generation. Mengcheng Lan, Chaofeng Chen, Yue Zhou, Jiaxing Xu, Yiping Ke, Xinjiang Wang, Litong Feng, Wayne Zhang |
| 2025 | The "Law" of the Unconscious Contrastive Learner: Probabilistic Alignment of Unpaired Modalities. Yongwei Che, Benjamin Eysenbach |
| 2025 | The 3D-PC: a benchmark for visual perspective taking in humans and machines. Drew Linsley, Peisen Zhou, Alekh Karkada Ashok, Akash Nagaraj, Gaurav Gaonkar, Francis E. Lewis, Zygmunt Pizlo, Thomas Serre |
| 2025 | The AdEMAMix Optimizer: Better, Faster, Older. Matteo Pagliardini, Pierre Ablin, David Grangier |
| 2025 | The Belief State Transformer. Edward S. Hu, Kwangjun Ahn, Qinghua Liu, Haoran Xu, Manan Tomar, Ada Langford, Dinesh Jayaraman, Alex Lamb, John Langford |
| 2025 | The Breakdown of Gaussian Universality in Classification of High-dimensional Linear Factor Mixtures. Xiaoyi Mai, Zhenyu Liao |
| 2025 | The Case for Cleaner Biosignals: High-fidelity Neural Compressor Enables Transfer from Cleaner iEEG to Noisier EEG. Francesco S. Carzaniga, Gary Tom Hoppeler, Michael Hersche, Kaspar Schindler, Abbas Rahimi |
| 2025 | The Complexity of Two-Team Polymatrix Games with Independent Adversaries. Alexandros Hollender, Gilbert Maystre, Sai Ganesh Nagarajan |
| 2025 | The Computational Complexity of Circuit Discovery for Inner Interpretability. Federico Adolfi, Martina G. Vilas, Todd Wareham |
| 2025 | The Computational Complexity of Positive Non-Clashing Teaching in Graphs. Robert Ganian, Liana Khazaliya, Fionn Mc Inerney, Mathis Rocton |
| 2025 | The Crucial Role of Samplers in Online Direct Preference Optimization. Ruizhe Shi, Runlong Zhou, Simon Shaolei Du |
| 2025 | The Crystal Ball Hypothesis in diffusion models: Anticipating object positions from initial noise. Yuanhao Ban, Ruochen Wang, Tianyi Zhou, Boqing Gong, Cho-Jui Hsieh, Minhao Cheng |
| 2025 | The Directionality of Optimization Trajectories in Neural Networks. Sidak Pal Singh, Bobby He, Thomas Hofmann, Bernhard Schölkopf |
| 2025 | The Effectiveness of Curvature-Based Rewiring and the Role of Hyperparameters in GNNs Revisited. Floriano Tori, Vincent Holst, Vincent Ginis |
| 2025 | The Foundations of Tokenization: Statistical and Computational Concerns. Juan Luis Gastaldi, John Terilla, Luca Malagutti, Brian DuSell, Tim Vieira, Ryan Cotterell |
| 2025 | The Geometry of Categorical and Hierarchical Concepts in Large Language Models. Kiho Park, Yo Joong Choe, Yibo Jiang, Victor Veitch |
| 2025 | The Hidden Cost of Waiting for Accurate Predictions. Ali Shirali, Ariel D. Procaccia, Rediet Abebe |
| 2025 | The Hyperfitting Phenomenon: Sharpening and Stabilizing LLMs for Open-Ended Text Generation. Fredrik Carlsson, Fangyu Liu, Daniel Ward, Murathan Kurfali, Joakim Nivre |
| 2025 | The Journey Matters: Average Parameter Count over Pre-training Unifies Sparse and Dense Scaling Laws. Tian Jin, Ahmed Imtiaz Humayun, Utku Evci, Suvinay Subramanian, Amir Yazdanbakhsh, Dan Alistarh, Gintare Karolina Dziugaite |
| 2025 | The KoLMogorov Test: Compression by Code Generation. Ori Yoran, Kunhao Zheng, Fabian Gloeckle, Jonas Gehring, Gabriel Synnaeve, Taco Cohen |
| 2025 | The Labyrinth of Links: Navigating the Associative Maze of Multi-modal LLMs. Hong Li, Nanxi Li, Yuanjie Chen, Jianbin Zhu, Qinlu Guo, Cewu Lu, Yong-Lu Li |
| 2025 | The Last Iterate Advantage: Empirical Auditing and Principled Heuristic Analysis of Differentially Private SGD. Milad Nasr, Thomas Steinke, Borja Balle, Christopher A. Choquette-Choo, Arun Ganesh, Matthew Jagielski, Jamie Hayes, Abhradeep Guha Thakurta, Adam Smith, Andreas Terzis |
| 2025 | The OMG dataset: An Open MetaGenomic corpus for mixed-modality genomic language modeling. Andre Cornman, Jacob West-Roberts, Antonio Pedro Camargo, Simon Roux, Martin Beracochea, Milot Mirdita, Sergey Ovchinnikov, Yunha Hwang |
| 2025 | The Optimization Landscape of SGD Across the Feature Learning Strength. Alexander B. Atanasov, Alexandru Meterez, James B. Simon, Cengiz Pehlevan |
| 2025 | The Pitfalls of Memorization: When Memorization Hurts Generalization. Reza Bayat, Mohammad Pezeshki, Elvis Dohmatob, David Lopez-Paz, Pascal Vincent |
| 2025 | The Power of LLM-Generated Synthetic Data for Stance Detection in Online Political Discussions. Stefan Sylvius Wagner, Maike Behrendt, Marc Ziegele, Stefan Harmeling |
| 2025 | The Ramanujan Library - Automated Discovery on the Hypergraph of Integer Relations. Itay Beit Halachmi, Ido Kaminer |
| 2025 | The Rise and Down of Babel Tower: Investigating the Evolution Process of Multilingual Code Large Language Model. Jiawei Chen, Wentao Chen, Jing Su, Jingjing Xu, Hongyu Lin, Mengjie Ren, Yaojie Lu, Xianpei Han, Le Sun |
| 2025 | The Same but Different: Structural Similarities and Differences in Multilingual Language Modeling. Ruochen Zhang, Qinan Yu, Matianyu Zang, Carsten Eickhoff, Ellie Pavlick |
| 2025 | The Semantic Hub Hypothesis: Language Models Share Semantic Representations Across Languages and Modalities. Zhaofeng Wu, Xinyan Velocity Yu, Dani Yogatama, Jiasen Lu, Yoon Kim |
| 2025 | The Superposition of Diffusion Models Using the Itô Density Estimator. Marta Skreta, Lazar Atanackovic, Joey Bose, Alexander Tong, Kirill Neklyudov |
| 2025 | The Thirteenth International Conference on Learning Representations, ICLR 2025, Singapore, April 24-28, 2025 |
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| 2025 | The Utility and Complexity of In- and Out-of-Distribution Machine Unlearning. Youssef Allouah, Joshua Kazdan, Rachid Guerraoui, Sanmi Koyejo |
| 2025 | The Value of Sensory Information to a Robot. Arjun Krishna, Edward S. Hu, Dinesh Jayaraman |
| 2025 | The adaptive complexity of parallelized log-concave sampling. Huanjian Zhou, Baoxiang Wang, Masashi Sugiyama |
| 2025 | The impact of allocation strategies in subset learning on the expressive power of neural networks. Ofir Schlisselberg, Ran Darshan |
| 2025 | The robustness of differentiable Causal Discovery in misspecified Scenarios. Huiyang Yi, Yanyan He, Duxin Chen, Mingyu Kang, He Wang, Wenwu Yu |
| 2025 | Theory on Mixture-of-Experts in Continual Learning. Hongbo Li, Sen Lin, Lingjie Duan, Yingbin Liang, Ness B. Shroff |
| 2025 | Theory on Score-Mismatched Diffusion Models and Zero-Shot Conditional Samplers. Yuchen Liang, Peizhong Ju, Yingbin Liang, Ness B. Shroff |
| 2025 | Theory, Analysis, and Best Practices for Sigmoid Self-Attention. Jason Ramapuram, Federico Danieli, Eeshan Gunesh Dhekane, Floris Weers, Dan Busbridge, Pierre Ablin, Tatiana Likhomanenko, Jagrit Digani, Zijin Gu, Amitis Shidani, Russell Webb |
| 2025 | ThermalGaussian: Thermal 3D Gaussian Splatting. Rongfeng Lu, Hangyu Chen, Zunjie Zhu, Yuhang Qin, Ming Lu, Le Zhang, Chenggang Yan, Anke Xue |
| 2025 | ThinK: Thinner Key Cache by Query-Driven Pruning. Yuhui Xu, Zhanming Jie, Hanze Dong, Lei Wang, Xudong Lu, Aojun Zhou, Amrita Saha, Caiming Xiong, Doyen Sahoo |
| 2025 | Think Then React: Towards Unconstrained Action-to-Reaction Motion Generation. Wenhui Tan, Boyuan Li, Chuhao Jin, Wenbing Huang, Xiting Wang, Ruihua Song |
| 2025 | Think Thrice Before You Act: Progressive Thought Refinement in Large Language Models. Chengyu Du, Jinyi Han, Yizhou Ying, Aili Chen, Qianyu He, Haokun Zhao, Haoran Guo, Sirui Xia, Jiaqing Liang, Zulong Chen, Liangyue Li, Yanghua Xiao |
| 2025 | Think while You Generate: Discrete Diffusion with Planned Denoising. Sulin Liu, Juno Nam, Andrew Campbell, Hannes Stärk, Yilun Xu, Tommi S. Jaakkola, Rafael Gómez-Bombarelli |
| 2025 | Think-on-Graph 2.0: Deep and Faithful Large Language Model Reasoning with Knowledge-guided Retrieval Augmented Generation. Shengjie Ma, Chengjin Xu, Xuhui Jiang, Muzhi Li, Huaren Qu, Cehao Yang, Jiaxin Mao, Jian Guo |
| 2025 | ThinkBot: Embodied Instruction Following with Thought Chain Reasoning. Guanxing Lu, Ziwei Wang, Changliu Liu, Jiwen Lu, Yansong Tang |
| 2025 | Three Mechanisms of Feature Learning in a Linear Network. Yizhou Xu, Ziyin Liu |
| 2025 | ThunderKittens: Simple, Fast, and Adorable Kernels. Benjamin Frederick Spector, Simran Arora, Aaryan Singhal, Arjun Parthasarathy, Daniel Y. Fu, Christopher Ré |
| 2025 | TidalDecode: Fast and Accurate LLM Decoding with Position Persistent Sparse Attention. Lijie Yang, Zhihao Zhang, Zhuofu Chen, Zikun Li, Zhihao Jia |
| 2025 | Tight Clusters Make Specialized Experts. Stefan K. Nielsen, Rachel S. Y. Teo, Laziz U. Abdullaev, Tan Minh Nguyen |
| 2025 | Tight Lower Bounds under Asymmetric High-Order Hölder Smoothness and Uniform Convexity. Site Bai, Brian Bullins |
| 2025 | Tight Time Complexities in Parallel Stochastic Optimization with Arbitrary Computation Dynamics. Alexander Tyurin |
| 2025 | Tighter Privacy Auditing of DP-SGD in the Hidden State Threat Model. Tudor Ioan Cebere, Aurélien Bellet, Nicolas Papernot |
| 2025 | Time After Time: Deep-Q Effect Estimation for Interventions on When and What to do. Yoav Wald, Mark Goldstein, Yonathan Efroni, Wouter A. C. van Amsterdam, Rajesh Ranganath |
| 2025 | Time-MoE: Billion-Scale Time Series Foundation Models with Mixture of Experts. Xiaoming Shi, Shiyu Wang, Yuqi Nie, Dianqi Li, Zhou Ye, Qingsong Wen, Ming Jin |
| 2025 | Time-to-Event Pretraining for 3D Medical Imaging. Zepeng Frazier Huo, Jason Alan Fries, Alejandro Lozano, Jeya Maria Jose Valanarasu, Ethan Steinberg, Louis Blankemeier, Akshay S. Chaudhari, Curtis P. Langlotz, Nigam Shah |
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| 2025 | TimeKAN: KAN-based Frequency Decomposition Learning Architecture for Long-term Time Series Forecasting. Songtao Huang, Zhen Zhao, Can Li, Lei Bai |
| 2025 | TimeMixer++: A General Time Series Pattern Machine for Universal Predictive Analysis. Shiyu Wang, Jiawei Li, Xiaoming Shi, Zhou Ye, Baichuan Mo, Wenze Lin, Shengtong Ju, Zhixuan Chu, Ming Jin |
| 2025 | TimeSuite: Improving MLLMs for Long Video Understanding via Grounded Tuning. Xiangyu Zeng, Kunchang Li, Chenting Wang, Xinhao Li, Tianxiang Jiang, Ziang Yan, Songze Li, Yansong Shi, Zhengrong Yue, Yi Wang, Yali Wang, Yu Qiao, Limin Wang |
| 2025 | Timer-XL: Long-Context Transformers for Unified Time Series Forecasting. Yong Liu, Guo Qin, Xiangdong Huang, Jianmin Wang, Mingsheng Long |
| 2025 | To Clip or not to Clip: the Dynamics of SGD with Gradient Clipping in High-Dimensions. Noah Marshall, Ke Liang Xiao, Atish Agarwala, Elliot Paquette |
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| 2025 | ToVE: Efficient Vision-Language Learning via Knowledge Transfer from Vision Experts. Yuanchen Wu, Junlong Du, Ke Yan, Shouhong Ding, Xiaoqiang Li |
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| 2025 | Towards Auto-Regressive Next-Token Prediction: In-context Learning Emerges from Generalization. Zixuan Gong, Xiaolin Hu, Huayi Tang, Yong Liu |
| 2025 | Towards Automated Knowledge Integration From Human-Interpretable Representations. Kasia Kobalczyk, Mihaela van der Schaar |
| 2025 | Towards Bridging Generalization and Expressivity of Graph Neural Networks. Shouheng Li, Floris Geerts, Dongwoo Kim, Qing Wang |
| 2025 | Towards Calibrated Deep Clustering Network. Yuheng Jia, Jianhong Cheng, Hui Liu, Junhui Hou |
| 2025 | Towards Certification of Uncertainty Calibration under Adversarial Attacks. Cornelius Emde, Francesco Pinto, Thomas Lukasiewicz, Philip Torr, Adel Bibi |
| 2025 | Towards Continuous Reuse of Graph Models via Holistic Memory Diversification. Ziyue Qiao, Junren Xiao, Qingqiang Sun, Meng Xiao, Xiao Luo, Hui Xiong |
| 2025 | Towards Domain Adaptive Neural Contextual Bandits. Ziyan Wang, Xiaoming Huo, Hao Wang |
| 2025 | Towards Effective Evaluations and Comparisons for LLM Unlearning Methods. Qizhou Wang, Bo Han, Puning Yang, Jianing Zhu, Tongliang Liu, Masashi Sugiyama |
| 2025 | Towards Empowerment Gain through Causal Structure Learning in Model-Based Reinforcement Learning. Hongye Cao, Fan Feng, Meng Fang, Shaokang Dong, Tianpei Yang, Jing Huo, Yang Gao |
| 2025 | Towards Explaining the Power of Constant-depth Graph Neural Networks for Structured Linear Programming. Qian Li, Minghui Ouyang, Tian Ding, Yuyi Wang, Qingjiang Shi, Ruoyu Sun |
| 2025 | Towards Fast, Specialized Machine Learning Force Fields: Distilling Foundation Models via Energy Hessians. Ishan Amin, Sanjeev Raja, Aditi S. Krishnapriyan |
| 2025 | Towards Faster Decentralized Stochastic Optimization with Communication Compression. Rustem Islamov, Yuan Gao, Sebastian U. Stich |
| 2025 | Towards Federated RLHF with Aggregated Client Preference for LLMs. Feijie Wu, Xiaoze Liu, Haoyu Wang, Xingchen Wang, Lu Su, Jing Gao |
| 2025 | Towards Foundation Models for Mixed Integer Linear Programming. Sirui Li, Janardhan Kulkarni, Ishai Menache, Cathy Wu, Beibin Li |
| 2025 | Towards General-Purpose Model-Free Reinforcement Learning. Scott Fujimoto, Pierluca D'Oro, Amy Zhang, Yuandong Tian, Michael Rabbat |
| 2025 | Towards Generalizable Reinforcement Learning via Causality-Guided Self-Adaptive Representations. Yupei Yang, Biwei Huang, Fan Feng, Xinyue Wang, Shikui Tu, Lei Xu |
| 2025 | Towards Generalization Bounds of GCNs for Adversarially Robust Node Classification. Wen Wen, Han Li, Tieliang Gong, Hong Chen |
| 2025 | Towards Hierarchical Rectified Flow. Yichi Zhang, Yici Yan, Alexander G. Schwing, Zhizhen Zhao |
| 2025 | Towards Homogeneous Lexical Tone Decoding from Heterogeneous Intracranial Recordings. Di Wu, Siyuan Li, Chen Feng, Lu Cao, Yue Zhang, Jie Yang, Mohamad Sawan |
| 2025 | Towards Improving Exploration through Sibling Augmented GFlowNets. Kanika Madan, Alex Lamb, Emmanuel Bengio, Glen Berseth, Yoshua Bengio |
| 2025 | Towards Interpreting Visual Information Processing in Vision-Language Models. Clement Neo, Luke Ong, Philip Torr, Mor Geva, David Krueger, Fazl Barez |
| 2025 | Towards Learning High-Precision Least Squares Algorithms with Sequence Models. Jerry Weihong Liu, Jessica Grogan, Owen M. Dugan, Ashish Rao, Simran Arora, Atri Rudra, Christopher Ré |
| 2025 | Towards Marginal Fairness Sliced Wasserstein Barycenter. Khai Nguyen, Hai Nguyen, Nhat Ho |
| 2025 | Towards Multiple Character Image Animation Through Enhancing Implicit Decoupling. Jingyun Xue, Hongfa Wang, Qi Tian, Yue Ma, Andong Wang, Zhiyuan Zhao, Shaobo Min, Wenzhe Zhao, Kaihao Zhang, Heung-Yeung Shum, Wei Liu, Mengyang Liu, Wenhan Luo |
| 2025 | Towards Neural Scaling Laws for Time Series Foundation Models. Qingren Yao, Chao-Han Huck Yang, Renhe Jiang, Yuxuan Liang, Ming Jin, Shirui Pan |
| 2025 | Towards Optimal Multi-draft Speculative Decoding. Zhengmian Hu, Tong Zheng, Vignesh Viswanathan, Ziyi Chen, Ryan A. Rossi, Yihan Wu, Dinesh Manocha, Heng Huang |
| 2025 | Towards Out-of-Modal Generalization without Instance-level Modal Correspondence. Zhuo Huang, Gang Niu, Bo Han, Masashi Sugiyama, Tongliang Liu |
| 2025 | Towards Principled Evaluations of Sparse Autoencoders for Interpretability and Control. Aleksandar Makelov, Georg Lange, Neel Nanda |
| 2025 | Towards Realistic Data Generation for Real-World Super-Resolution. Long Peng, Wenbo Li, Renjing Pei, Jingjing Ren, Jiaqi Xu, Yang Wang, Yang Cao, Zheng-Jun Zha |
| 2025 | Towards Realistic UAV Vision-Language Navigation: Platform, Benchmark, and Methodology. Xiangyu Wang, Donglin Yang, Ziqin Wang, Hohin Kwan, Jinyu Chen, Wenjun Wu, Hongsheng Li, Yue Liao, Si Liu |
| 2025 | Towards Robust Alignment of Language Models: Distributionally Robustifying Direct Preference Optimization. Junkang Wu, Yuexiang Xie, Zhengyi Yang, Jiancan Wu, Jiawei Chen, Jinyang Gao, Bolin Ding, Xiang Wang, Xiangnan He |
| 2025 | Towards Robust Multimodal Open-set Test-time Adaptation via Adaptive Entropy-aware Optimization. Hao Dong, Eleni N. Chatzi, Olga Fink |
| 2025 | Towards Robust and Parameter-Efficient Knowledge Unlearning for LLMs. Sungmin Cha, Sungjun Cho, Dasol Hwang, Moontae Lee |
| 2025 | Towards Scalable Exact Machine Unlearning Using Parameter-Efficient Fine-Tuning. Somnath Basu Roy Chowdhury, Krzysztof Marcin Choromanski, Arijit Sehanobish, Kumar Avinava Dubey, Snigdha Chaturvedi |
| 2025 | Towards Scalable Topological Regularizers. Hiu-Tung Wong, Darrick Lee, Hong Yan |
| 2025 | Towards Self-Supervised Covariance Estimation in Deep Heteroscedastic Regression. Megh Shukla, Aziz Shameem, Mathieu Salzmann, Alexandre Alahi |
| 2025 | Towards Semantic Equivalence of Tokenization in Multimodal LLM. Shengqiong Wu, Hao Fei, Xiangtai Li, Jiayi Ji, Hanwang Zhang, Tat-Seng Chua, Shuicheng Yan |
| 2025 | Towards Synergistic Path-based Explanations for Knowledge Graph Completion: Exploration and Evaluation. Tengfei Ma, Xiang Song, Wen Tao, Mufei Li, Jiani Zhang, Xiaoqin Pan, Yijun Wang, Bosheng Song, Xiangxiang Zeng |
| 2025 | Towards Unbiased Learning in Semi-Supervised Semantic Segmentation. Rui Sun, Huayu Mai, Wangkai Li, Tianzhu Zhang |
| 2025 | Towards Understanding Text Hallucination of Diffusion Models via Local Generation Bias. Rui Lu, Runzhe Wang, Kaifeng Lyu, Xitai Jiang, Gao Huang, Mengdi Wang |
| 2025 | Towards Understanding Why FixMatch Generalizes Better Than Supervised Learning. Jingyang Li, Jiachun Pan, Vincent Y. F. Tan, Kim-Chuan Toh, Pan Zhou |
| 2025 | Towards Understanding Why Label Smoothing Degrades Selective Classification and How to Fix It. Guoxuan Xia, Olivier Laurent, Gianni Franchi, Christos-Savvas Bouganis |
| 2025 | Towards Understanding the Robustness of Diffusion-Based Purification: A Stochastic Perspective. Yiming Liu, Kezhao Liu, Yao Xiao, Ziyi Dong, Xiaogang Xu, Pengxu Wei, Liang Lin |
| 2025 | Towards Understanding the Universality of Transformers for Next-Token Prediction. Michael Eli Sander, Gabriel Peyré |
| 2025 | Towards Unified Human Motion-Language Understanding via Sparse Interpretable Characterization. Guangtao Lyu, Chenghao Xu, Jiexi Yan, Muli Yang, Cheng Deng |
| 2025 | Towards Universality: Studying Mechanistic Similarity Across Language Model Architectures. Junxuan Wang, Xuyang Ge, Wentao Shu, Qiong Tang, Yunhua Zhou, Zhengfu He, Xipeng Qiu |
| 2025 | Towards a Complete Logical Framework for GNN Expressiveness. Tuo Xu |
| 2025 | Towards a General Time Series Anomaly Detector with Adaptive Bottlenecks and Dual Adversarial Decoders. Qichao Shentu, Beibu Li, Kai Zhao, Yang Shu, Zhongwen Rao, Lujia Pan, Bin Yang, Chenjuan Guo |
| 2025 | Towards a Theoretical Understanding of Synthetic Data in LLM Post-Training: A Reverse-Bottleneck Perspective. Zeyu Gan, Yong Liu |
| 2025 | Towards a Unified and Verified Understanding of Group-Operation Networks. Wilson Wu, Louis Jaburi, Jacob Drori, Jason Gross |
| 2025 | Towards a learning theory of representation alignment. Francesco Insulla, Shuo Huang, Lorenzo Rosasco |
| 2025 | Towards counterfactual fairness through auxiliary variables. Bowei Tian, Ziyao Wang, Shwai He, Wanghao Ye, Guoheng Sun, Yucong Dai, Yongkai Wu, Ang Li |
| 2025 | Towards hyperparameter-free optimization with differential privacy. Ruixuan Liu, Zhiqi Bu |
| 2025 | TraceVLA: Visual Trace Prompting Enhances Spatial-Temporal Awareness for Generalist Robotic Policies. Ruijie Zheng, Yongyuan Liang, Shuaiyi Huang, Jianfeng Gao, Hal Daumé III, Andrey Kolobov, Furong Huang, Jianwei Yang |
| 2025 | Tracing Representation Progression: Analyzing and Enhancing Layer-Wise Similarity. Jiachen Jiang, Jinxin Zhou, Zhihui Zhu |
| 2025 | Track-On: Transformer-based Online Point Tracking with Memory. Görkay Aydemir, Xiongyi Cai, Weidi Xie, Fatma Güney |
| 2025 | Tracking objects that change in appearance with phase synchrony. Sabine Muzellec, Drew Linsley, Alekh Karkada Ashok, Ennio Mingolla, Girik Malik, Rufin VanRullen, Thomas Serre |
| 2025 | Tracking the Copyright of Large Vision-Language Models through Parameter Learning Adversarial Images. Yubo Wang, Jianting Tang, Chaohu Liu, Linli Xu |
| 2025 | Tractable Multi-Agent Reinforcement Learning through Behavioral Economics. Eric Mazumdar, Kishan Panaganti, Laixi Shi |
| 2025 | Train Small, Infer Large: Memory-Efficient LoRA Training for Large Language Models. Jun Zhang, Jue Wang, Huan Li, Lidan Shou, Ke Chen, Yang You, Guiming Xie, Xuejian Gong, Kunlong Zhou |
| 2025 | Trained Transformer Classifiers Generalize and Exhibit Benign Overfitting In-Context. Spencer Frei, Gal Vardi |
| 2025 | Training Free Exponential Context Extension via Cascading KV Cache. Jeffrey Willette, Heejun Lee, Youngwan Lee, Myeongjae Jeon, Sung Ju Hwang |
| 2025 | Training Free Guided Flow-Matching with Optimal Control. Luran Wang, Chaoran Cheng, Yizhen Liao, Yanru Qu, Ge Liu |
| 2025 | Training Language Models on Synthetic Edit Sequences Improves Code Synthesis. Ulyana Piterbarg, Lerrel Pinto, Rob Fergus |
| 2025 | Training Language Models to Self-Correct via Reinforcement Learning. Aviral Kumar, Vincent Zhuang, Rishabh Agarwal, Yi Su, John D. Co-Reyes, Avi Singh, Kate Baumli, Shariq Iqbal, Colton Bishop, Rebecca Roelofs, Lei M. Zhang, Kay McKinney, Disha Shrivastava, Cosmin Paduraru, George Tucker, Doina Precup, Feryal M. P. Behbahani, Aleksandra Faust |
| 2025 | Training Large Language Models for Retrieval-Augmented Question Answering through Backtracking Correction. Huawen Feng, Zekun Yao, Junhao Zheng, Qianli Ma |
| 2025 | Training Neural Networks as Recognizers of Formal Languages. Alexandra Butoi, Ghazal Khalighinejad, Anej Svete, Josef Valvoda, Ryan Cotterell, Brian DuSell |
| 2025 | Training Nonlinear Transformers for Chain-of-Thought Inference: A Theoretical Generalization Analysis. Hongkang Li, Songtao Lu, Pin-Yu Chen, Xiaodong Cui, Meng Wang |
| 2025 | Training One-Dimensional Graph Neural Networks is NP-Hard. Robert Ganian, Mathis Rocton, Simon Wietheger |
| 2025 | Training Robust Ensembles Requires Rethinking Lipschitz Continuity. Ali Ebrahimpour Boroojeny, Hari Sundaram, Varun Chandrasekaran |
| 2025 | Training on the Test Task Confounds Evaluation and Emergence. Ricardo Dominguez-Olmedo, Florian E. Dorner, Moritz Hardt |
| 2025 | Training-Free Activation Sparsity in Large Language Models. James Liu, Pragaash Ponnusamy, Tianle Cai, Han Guo, Yoon Kim, Ben Athiwaratkun |
| 2025 | Training-Free Dataset Pruning for Instance Segmentation. Yalun Dai, Lingao Xiao, Ivor W. Tsang, Yang He |
| 2025 | Training-Free Diffusion Model Alignment with Sampling Demons. Po-Hung Yeh, Kuang-Huei Lee, Jun-Cheng Chen |
| 2025 | Training-Free Message Passing for Learning on Hypergraphs. Bohan Tang, Zexi Liu, Keyue Jiang, Siheng Chen, Xiaowen Dong |
| 2025 | Training-free Camera Control for Video Generation. Chen Hou, Zhibo Chen |
| 2025 | Training-free LLM-generated Text Detection by Mining Token Probability Sequences. Yihuai Xu, Yongwei Wang, Yifei Bi, Huangsen Cao, Zhouhan Lin, Yu Zhao, Fei Wu |
| 2025 | Trajectory attention for fine-grained video motion control. Zeqi Xiao, Wenqi Ouyang, Yifan Zhou, Shuai Yang, Lei Yang, Jianlou Si, Xingang Pan |
| 2025 | Trajectory-Class-Aware Multi-Agent Reinforcement Learning. Hyungho Na, Kwanghyeon Lee, Sumin Lee, Il-Chul Moon |
| 2025 | Trajectory-LLM: A Language-based Data Generator for Trajectory Prediction in Autonomous Driving. Kairui Yang, Zihao Guo, Gengjie Lin, Haotian Dong, Zhao Huang, Yipeng Wu, Die Zuo, Jibin Peng, Ziyuan Zhong, Xin Wang, Qing Guo, Xiaosong Jia, Junchi Yan, Di Lin |
| 2025 | Transformer Block Coupling and its Correlation with Generalization in LLMs. Murdock Aubry, Haoming Meng, Anton Sugolov, Vardan Papyan |
| 2025 | Transformer Encoder Satisfiability: Complexity and Impact on Formal Reasoning. Marco Sälzer, Eric Alsmann, Martin Lange |
| 2025 | Transformer Learns Optimal Variable Selection in Group-Sparse Classification. Chenyang Zhang, Xuran Meng, Yuan Cao |
| 2025 | Transformer Meets Twicing: Harnessing Unattended Residual Information. Laziz U. Abdullaev, Tan Minh Nguyen |
| 2025 | Transformer-Squared: Self-adaptive LLMs. Qi Sun, Edoardo Cetin, Yujin Tang |
| 2025 | Transformers Can Learn Temporal Difference Methods for In-Context Reinforcement Learning. Jiuqi Wang, Ethan Blaser, Hadi Daneshmand, Shangtong Zhang |
| 2025 | Transformers Handle Endogeneity in In-Context Linear Regression. Haodong Liang, Krishna Balasubramanian, Lifeng Lai |
| 2025 | Transformers Learn Low Sensitivity Functions: Investigations and Implications. Bhavya Vasudeva, Deqing Fu, Tianyi Zhou, Elliott Kau, Youqi Huang, Vatsal Sharan |
| 2025 | Transformers Learn to Implement Multi-step Gradient Descent with Chain of Thought. Jianhao Huang, Zixuan Wang, Jason D. Lee |
| 2025 | Transformers Provably Learn Two-Mixture of Linear Classification via Gradient Flow. Hongru Yang, Zhangyang Wang, Jason D. Lee, Yingbin Liang |
| 2025 | Transformers Provably Solve Parity Efficiently with Chain of Thought. Juno Kim, Taiji Suzuki |
| 2025 | Transformers Struggle to Learn to Search. Abulhair Saparov, Srushti Ajay Pawar, Shreyas Pimpalgaonkar, Nitish Joshi, Richard Yuanzhe Pang, Vishakh Padmakumar, Mehran Kazemi, Najoung Kim, He He |
| 2025 | Transformers are Universal In-context Learners. Takashi Furuya, Maarten V. de Hoop, Gabriel Peyré |
| 2025 | Transfusion: Predict the Next Token and Diffuse Images with One Multi-Modal Model. Chunting Zhou, Lili Yu, Arun Babu, Kushal Tirumala, Michihiro Yasunaga, Leonid Shamis, Jacob Kahn, Xuezhe Ma, Luke Zettlemoyer, Omer Levy |
| 2025 | Transition Path Sampling with Improved Off-Policy Training of Diffusion Path Samplers. Kiyoung Seong, Seonghyun Park, Seonghwan Kim, Woo Youn Kim, Sungsoo Ahn |
| 2025 | Tree of Attributes Prompt Learning for Vision-Language Models. Tong Ding, Wanhua Li, Zhongqi Miao, Hanspeter Pfister |
| 2025 | Tree-Wasserstein Distance for High Dimensional Data with a Latent Feature Hierarchy. Ya-Wei Eileen Lin, Ronald R. Coifman, Gal Mishne, Ronen Talmon |
| 2025 | Triples as the Key: Structuring Makes Decomposition and Verification Easier in LLM-based TableQA. Zhen Yang, Ziwei Du, Minghan Zhang, Wei Du, Jie Chen, Zhen Duan, Shu Zhao |
| 2025 | Trivialized Momentum Facilitates Diffusion Generative Modeling on Lie Groups. Yuchen Zhu, Tianrong Chen, Lingkai Kong, Evangelos A. Theodorou, Molei Tao |
| 2025 | Truncated Consistency Models. Sangyun Lee, Yilun Xu, Tomas Geffner, Giulia Fanti, Karsten Kreis, Arash Vahdat, Weili Nie |
| 2025 | Trust or Escalate: LLM Judges with Provable Guarantees for Human Agreement. Jaehun Jung, Faeze Brahman, Yejin Choi |
| 2025 | Trusted Multi-View Classification via Evolutionary Multi-View Fusion. Xinyan Liang, Pinhan Fu, Yuhua Qian, Qian Guo, Guoqing Liu |
| 2025 | Tuning Frequency Bias of State Space Models. Annan Yu, Dongwei Lyu, Soon Hoe Lim, Michael W. Mahoney, N. Benjamin Erichson |
| 2025 | Tuning Timestep-Distilled Diffusion Model Using Pairwise Sample Optimization. Zichen Miao, Zhengyuan Yang, Kevin Lin, Ze Wang, Zicheng Liu, Lijuan Wang, Qiang Qiu |
| 2025 | Tuning-Free Bilevel Optimization: New Algorithms and Convergence Analysis. Yifan Yang, Hao Ban, Minhui Huang, Shiqian Ma, Kaiyi Ji |
| 2025 | Turning Up the Heat: Min-p Sampling for Creative and Coherent LLM Outputs. Nguyen Nhat Minh, Andrew Baker, Clement Neo, Allen G. Roush, Andreas Kirsch, Ravid Shwartz-Ziv |
| 2025 | TweedieMix: Improving Multi-Concept Fusion for Diffusion-based Image/Video Generation. Gihyun Kwon, Jong Chul Ye |
| 2025 | Two Effects, One Trigger: On the Modality Gap, Object Bias, and Information Imbalance in Contrastive Vision-Language Models. Simon Schrodi, David T. Hoffmann, Max Argus, Volker Fischer, Thomas Brox |
| 2025 | Two Sparse Matrices are Better than One: Sparsifying Neural Networks with Double Sparse Factorization. Vladimír Boza, Vladimír Macko |
| 2025 | TypedThinker: Diversify Large Language Model Reasoning with Typed Thinking. Danqing Wang, Jianxin Ma, Fei Fang, Lei Li |
| 2025 | U-Nets as Belief Propagation: Efficient Classification, Denoising, and Diffusion in Generative Hierarchical Models. Song Mei |
| 2025 | U-shaped and Inverted-U Scaling behind Emergent Abilities of Large Language Models. Tung-Yu Wu, Melody Lo |
| 2025 | UGMathBench: A Diverse and Dynamic Benchmark for Undergraduate-Level Mathematical Reasoning with Large Language Models. Xin Xu, Jiaxin Zhang, Tianhao Chen, Zitong Chao, Jishan Hu, Can Yang |
| 2025 | UIFace: Unleashing Inherent Model Capabilities to Enhance Intra-Class Diversity in Synthetic Face Recognition. Xiao Lin, Yuge Huang, Jianqing Xu, Yuxi Mi, Shuigeng Zhou, Shouhong Ding |
| 2025 | UNIP: Rethinking Pre-trained Attention Patterns for Infrared Semantic Segmentation. Tao Zhang, Jinyong Wen, Zhen Chen, Kun Ding, Shiming Xiang, Chunhong Pan |
| 2025 | UNSURE: self-supervised learning with Unknown Noise level and Stein's Unbiased Risk Estimate. Julián Tachella, Mike E. Davies, Laurent Jacques |
| 2025 | URLOST: Unsupervised Representation Learning without Stationarity or Topology. Zeyu Yun, Juexiao Zhang, Yann LeCun, Yubei Chen |
| 2025 | UTILITY: Utilizing Explainable Reinforcement Learning to Improve Reinforcement Learning. Shicheng Liu, Minghui Zhu |
| 2025 | UV-Attack: Physical-World Adversarial Attacks on Person Detection via Dynamic-NeRF-based UV Mapping. Yanjie Li, Kaisheng Liang, Bin Xiao |
| 2025 | Ultra-Sparse Memory Network. Zihao Huang, Qiyang Min, Hongzhi Huang, Yutao Zeng, Defa Zhu, Ran Guo, Xun Zhou |
| 2025 | Unbounded: A Generative Infinite Game of Character Life Simulation. Jialu Li, Yuanzhen Li, Neal Wadhwa, Yael Pritch, David E. Jacobs, Michael Rubinstein, Mohit Bansal, Nataniel Ruiz |
| 2025 | Uncertainty Herding: One Active Learning Method for All Label Budgets. Wonho Bae, Danica J. Sutherland, Gabriel L. Oliveira |
| 2025 | Uncertainty Modeling in Graph Neural Networks via Stochastic Differential Equations. Richard Bergna, Sergio Calvo-Ordoñez, Felix L. Opolka, Pietro Lio, José Miguel Hernández-Lobato |
| 2025 | Uncertainty and Influence aware Reward Model Refinement for Reinforcement Learning from Human Feedback. Zexu Sun, Yiju Guo, Yankai Lin, Xu Chen, Qi Qi, Xing Tang, Xiuqiang He, Ji-Rong Wen |
| 2025 | Uncertainty modeling for fine-tuned implicit functions. Anna Susmelj, Mael Macuglia, Natasa Tagasovska, Reto Sutter, Sebastiano Caprara, Jean-Philippe Thiran, Ender Konukoglu |
| 2025 | Uncertainty-Aware Decoding with Minimum Bayes Risk. Nico Daheim, Clara Meister, Thomas Möllenhoff, Iryna Gurevych |
| 2025 | Uncovering Gaps in How Humans and LLMs Interpret Subjective Language. Erik Jones, Arjun Patrawala, Jacob Steinhardt |
| 2025 | Uncovering Latent Memories in Large Language Models. Sunny Duan, Mikail Khona, Abhiram Iyer, Rylan Schaeffer, Ila R. Fiete |
| 2025 | Uncovering Overfitting in Large Language Model Editing. Mengqi Zhang, Xiaotian Ye, Qiang Liu, Shu Wu, Pengjie Ren, Zhumin Chen |
| 2025 | Underdamped Diffusion Bridges with Applications to Sampling. Denis Blessing, Julius Berner, Lorenz Richter, Gerhard Neumann |
| 2025 | Understanding Constraint Inference in Safety-Critical Inverse Reinforcement Learning. Bo Yue, Shufan Wang, Ashish Gaurav, Jian Li, Pascal Poupart, Guiliang Liu |
| 2025 | Understanding Factual Recall in Transformers via Associative Memories. Eshaan Nichani, Jason D. Lee, Alberto Bietti |
| 2025 | Understanding Long Videos with Multimodal Language Models. Kanchana Ranasinghe, Xiang Li, Kumara Kahatapitiya, Michael S. Ryoo |
| 2025 | Understanding Matrix Function Normalizations in Covariance Pooling through the Lens of Riemannian Geometry. Ziheng Chen, Yue Song, Xiaojun Wu, Gaowen Liu, Nicu Sebe |
| 2025 | Understanding Optimization in Deep Learning with Central Flows. Jeremy Cohen, Alex Damian, Ameet Talwalkar, J. Zico Kolter, Jason D. Lee |
| 2025 | Understanding Virtual Nodes: Oversquashing and Node Heterogeneity. Joshua Southern, Francesco Di Giovanni, Michael M. Bronstein, Johannes F. Lutzeyer |
| 2025 | Understanding Warmup-Stable-Decay Learning Rates: A River Valley Loss Landscape View. Kaiyue Wen, Zhiyuan Li, Jason S. Wang, David Leo Wright Hall, Percy Liang, Tengyu Ma |
| 2025 | Understanding and Enhancing Safety Mechanisms of LLMs via Safety-Specific Neuron. Yiran Zhao, Wenxuan Zhang, Yuxi Xie, Anirudh Goyal, Kenji Kawaguchi, Michael Shieh |
| 2025 | Understanding and Enhancing the Transferability of Jailbreaking Attacks. Runqi Lin, Bo Han, Fengwang Li, Tongliang Liu |
| 2025 | Understanding and Mitigating Bottlenecks of State Space Models through the Lens of Recency and Over-smoothing. Peihao Wang, Ruisi Cai, Yuehao Wang, Jiajun Zhu, Pragya Srivastava, Zhangyang Wang, Pan Li |
| 2025 | Understanding and Mitigating Hallucination in Large Vision-Language Models via Modular Attribution and Intervention. Tianyun Yang, Ziniu Li, Juan Cao, Chang Xu |
| 2025 | Understanding the Generalization of In-Context Learning in Transformers: An Empirical Study. Xingxuan Zhang, Haoran Wang, Jiansheng Li, Yuan Xue, Shikai Guan, Renzhe Xu, Hao Zou, Han Yu, Peng Cui |
| 2025 | Understanding the Stability-based Generalization of Personalized Federated Learning. Yingqi Liu, Qinglun Li, Jie Tang, Yifan Shi, Li Shen, Xiaochun Cao |
| 2025 | Unearthing Skill-level Insights for Understanding Trade-offs of Foundation Models. Mazda Moayeri, Vidhisha Balachandran, Varun Chandrasekaran, Safoora Yousefi, Thomas Fel, Soheil Feizi, Besmira Nushi, Neel Joshi, Vibhav Vineet |
| 2025 | Unhackable Temporal Reward for Scalable Video MLLMs. En Yu, Kangheng Lin, Liang Zhao, Yana Wei, Zining Zhu, Haoran Wei, Jianjian Sun, Zheng Ge, Xiangyu Zhang, Jingyu Wang, Wenbing Tao |
| 2025 | Uni-Sign: Toward Unified Sign Language Understanding at Scale. Zecheng Li, Wengang Zhou, Weichao Zhao, Kepeng Wu, Hezhen Hu, Houqiang Li |
| 2025 | Uni2Det: Unified and Universal Framework for Prompt-Guided Multi-dataset 3D Detection. Yubin Wang, Zhikang Zou, Xiaoqing Ye, Xiao Tan, Errui Ding, Cairong Zhao |
| 2025 | UniCBE: An Uniformity-driven Comparing Based Evaluation Framework with Unified Multi-Objective Optimization. Peiwen Yuan, Shaoxiong Feng, Yiwei Li, Xinglin Wang, Yueqi Zhang, Jiayi Shi, Chuyi Tan, Boyuan Pan, Yao Hu, Kan Li |
| 2025 | UniCO: On Unified Combinatorial Optimization via Problem Reduction to Matrix-Encoded General TSP. Wenzheng Pan, Hao Xiong, Jiale Ma, Wentao Zhao, Yang Li, Junchi Yan |
| 2025 | UniCoTT: A Unified Framework for Structural Chain-of-Thought Distillation. Xianwei Zhuang, Zhihong Zhu, Zhichang Wang, Xuxin Cheng, Yuexian Zou |
| 2025 | UniCon: Unidirectional Information Flow for Effective Control of Large-Scale Diffusion Models. Fanghua Yu, Jinjin Gu, Jinfan Hu, Zheyuan Li, Chao Dong |
| 2025 | UniDetox: Universal Detoxification of Large Language Models via Dataset Distillation. Huimin Lu, Masaru Isonuma, Junichiro Mori, Ichiro Sakata |
| 2025 | UniDrive: Towards Universal Driving Perception Across Camera Configurations. Ye Li, Wenzhao Zheng, Xiaonan Huang, Kurt Keutzer |
| 2025 | UniGEM: A Unified Approach to Generation and Property Prediction for Molecules. Shikun Feng, Yuyan Ni, Yan Lu, Zhi-Ming Ma, Wei-Ying Ma, Yanyan Lan |
| 2025 | UniGS: Unified Language-Image-3D Pretraining with Gaussian Splatting. Haoyuan Li, Yanpeng Zhou, Tao Tang, Jifei Song, Yihan Zeng, Michael Kampffmeyer, Hang Xu, Xiaodan Liang |
| 2025 | UniMatch: Universal Matching from Atom to Task for Few-Shot Drug Discovery. Ruifeng Li, Mingqian Li, Wei Liu, Yuhua Zhou, Xiangxin Zhou, Yuan Yao, Qiang Zhang, Hongyang Chen |
| 2025 | UniRestore3D: A Scalable Framework For General Shape Restoration. Yuang Wang, Yujian Zhang, Sida Peng, Xingyi He, Haoyu Guo, Yujun Shen, Hujun Bao, Xiaowei Zhou |
| 2025 | UniWav: Towards Unified Pre-training for Speech Representation Learning and Generation. Alexander H. Liu, Sang-gil Lee, Chao-Han Huck Yang, Yuan Gong, Yu-Chiang Frank Wang, James R. Glass, Rafael Valle, Bryan Catanzaro |
| 2025 | Unified Convergence Analysis for Score-Based Diffusion Models with Deterministic Samplers. Runjia Li, Qiwei Di, Quanquan Gu |
| 2025 | Unified Parameter-Efficient Unlearning for LLMs. Chenlu Ding, Jiancan Wu, Yancheng Yuan, Jinda Lu, Kai Zhang, Alex Su, Xiang Wang, Xiangnan He |
| 2025 | Unify ML4TSP: Drawing Methodological Principles for TSP and Beyond from Streamlined Design Space of Learning and Search. Yang Li, Jiale Ma, Wenzheng Pan, Runzhong Wang, Haoyu Geng, Nianzu Yang, Junchi Yan |
| 2025 | Unifying Causal Representation Learning with the Invariance Principle. Dingling Yao, Dario Rancati, Riccardo Cadei, Marco Fumero, Francesco Locatello |
| 2025 | Unifying Unsupervised Graph-Level Anomaly Detection and Out-of-Distribution Detection: A Benchmark. Yili Wang, Yixin Liu, Xu Shen, Chenyu Li, Rui Miao, Kaize Ding, Ying Wang, Shirui Pan, Xin Wang |
| 2025 | Unintentional Unalignment: Likelihood Displacement in Direct Preference Optimization. Noam Razin, Sadhika Malladi, Adithya Bhaskar, Danqi Chen, Sanjeev Arora, Boris Hanin |
| 2025 | Union-over-Intersections: Object Detection beyond Winner-Takes-All. Aritra Bhowmik, Pascal Mettes, Martin R. Oswald, Cees G. M. Snoek |
| 2025 | Universal Image Restoration Pre-training via Degradation Classification. Jiakui Hu, Lujia Jin, Zhengjian Yao, Yanye Lu |
| 2025 | Universal Sharpness Dynamics in Neural Network Training: Fixed Point Analysis, Edge of Stability, and Route to Chaos. Dayal Singh Kalra, Tianyu He, Maissam Barkeshli |
| 2025 | Universal generalization guarantees for Wasserstein distributionally robust models. Tam Le, Jérôme Malick |
| 2025 | Unlearn and Burn: Adversarial Machine Unlearning Requests Destroy Model Accuracy. Yangsibo Huang, Daogao Liu, Lynn Chua, Badih Ghazi, Pritish Kamath, Ravi Kumar, Pasin Manurangsi, Milad Nasr, Amer Sinha, Chiyuan Zhang |
| 2025 | Unlearning or Obfuscating? Jogging the Memory of Unlearned LLMs via Benign Relearning. Shengyuan Hu, Yiwei Fu, Steven Z. Wu, Virginia Smith |
| 2025 | Unlearning-based Neural Interpretations. Ching Lam Choi, Alexandre Duplessis, Serge J. Belongie |
| 2025 | Unleashing the Potential of Vision-Language Pre-Training for 3D Zero-Shot Lesion Segmentation via Mask-Attribute Alignment. Yankai Jiang, Wenhui Lei, Xiaofan Zhang, Shaoting Zhang |
| 2025 | Unleashing the Power of Task-Specific Directions in Parameter Efficient Fine-tuning. Chongjie Si, Zhiyi Shi, Shifan Zhang, Xiaokang Yang, Hanspeter Pfister, Wei Shen |
| 2025 | Unlocking Efficient, Scalable, and Continual Knowledge Editing with Basis-Level Representation Fine-Tuning. Tianci Liu, Ruirui Li, Yunzhe Qi, Hui Liu, Xianfeng Tang, Tianqi Zheng, Qingyu Yin, Monica Xiao Cheng, Jun Huan, Haoyu Wang, Jing Gao |
| 2025 | Unlocking Global Optimality in Bilevel Optimization: A Pilot Study. Quan Xiao, Tianyi Chen |
| 2025 | Unlocking Guidance for Discrete State-Space Diffusion and Flow Models. Hunter Nisonoff, Junhao Xiong, Stephan Allenspach, Jennifer Listgarten |
| 2025 | Unlocking Point Processes through Point Set Diffusion. David Lüdke, Enric Rabasseda Raventós, Marcel Kollovieh, Stephan Günnemann |
| 2025 | Unlocking State-Tracking in Linear RNNs Through Negative Eigenvalues. Riccardo Grazzi, Julien Siems, Arber Zela, Jörg K. H. Franke, Frank Hutter, Massimiliano Pontil |
| 2025 | Unlocking the Potential of Model Calibration in Federated Learning. Yun-Wei Chu, Dong-Jun Han, Seyyedali Hosseinalipour, Christopher Brinton |
| 2025 | Unlocking the Power of Function Vectors for Characterizing and Mitigating Catastrophic Forgetting in Continual Instruction Tuning. Gangwei Jiang, Caigao Jiang, Zhaoyi Li, Siqiao Xue, Jun Zhou, Linqi Song, Defu Lian, Ying Wei |
| 2025 | Unposed Sparse Views Room Layout Reconstruction in the Age of Pretrain Model. Yaxuan Huang, Xili Dai, Jianan Wang, Xianbiao Qi, Yixing Yuan, Xiangyu Yue |
| 2025 | Unsupervised Disentanglement of Content and Style via Variance-Invariance Constraints. Yuxuan Wu, Ziyu Wang, Bhiksha Raj, Gus Xia |
| 2025 | Unsupervised Meta-Learning via In-Context Learning. Anna Vettoruzzo, Lorenzo Braccaioli, Joaquin Vanschoren, Marlena Nowaczyk |
| 2025 | Unsupervised Model Tree Heritage Recovery. Eliahu Horwitz, Asaf Shul, Yedid Hoshen |
| 2025 | Unsupervised Multiple Kernel Learning for Graphs via Ordinality Preservation. Yan Sun, Stanley Kok |
| 2025 | Unsupervised Zero-Shot Reinforcement Learning via Dual-Value Forward-Backward Representation. Jingbo Sun, Songjun Tu, Qichao Zhang, Haoran Li, Xin Liu, Yaran Chen, Ke Chen, Dongbin Zhao |
| 2025 | Unveiling the Magic of Code Reasoning through Hypothesis Decomposition and Amendment. Yuze Zhao, Tianyun Ji, Wenjun Feng, Zhenya Huang, Qi Liu, Zhiding Liu, Yixiao Ma, Kai Zhang, Enhong Chen |
| 2025 | Unveiling the Secret Recipe: A Guide For Supervised Fine-Tuning Small LLMs. Aldo Pareja, Nikhil Shivakumar Nayak, Hao Wang, Krishnateja Killamsetty, Shivchander Sudalairaj, Wenlong Zhao, Seungwook Han, Abhishek Bhandwaldar, Guangxuan Xu, Kai Xu, Ligong Han, Luke Inglis, Akash Srivastava |
| 2025 | Utilitarian Algorithm Configuration for Infinite Parameter Spaces. Devon R. Graham, Kevin Leyton-Brown |
| 2025 | Utility-Directed Conformal Prediction: A Decision-Aware Framework for Actionable Uncertainty Quantification. Santiago Cortes-Gomez, Carlos Miguel Patiño, Yewon Byun, Steven Wu, Eric Horvitz, Bryan Wilder |
| 2025 | VAE-Var: Variational Autoencoder-Enhanced Variational Methods for Data Assimilation in Meteorology. Yi Xiao, Qilong Jia, Kun Chen, Lei Bai, Wei Xue |
| 2025 | VCR: A Task for Pixel-Level Complex Reasoning in Vision Language Models via Restoring Occluded Text. Tianyu Zhang, Suyuchen Wang, Lu Li, Ge Zhang, Perouz Taslakian, Sai Rajeswar, Jie Fu, Bang Liu, Yoshua Bengio |
| 2025 | VD3D: Taming Large Video Diffusion Transformers for 3D Camera Control. Sherwin Bahmani, Ivan Skorokhodov, Aliaksandr Siarohin, Willi Menapace, Guocheng Qian, Michael Vasilkovsky, Hsin-Ying Lee, Chaoyang Wang, Jiaxu Zou, Andrea Tagliasacchi, David B. Lindell, Sergey Tulyakov |
| 2025 | VEDIT: Latent Prediction Architecture For Procedural Video Representation Learning. Han Lin, Tushar Nagarajan, Nicolas Ballas, Mido Assran, Mojtaba Komeili, Mohit Bansal, Koustuv Sinha |
| 2025 | VICtoR: Learning Hierarchical Vision-Instruction Correlation Rewards for Long-horizon Manipulation. Kuo-Han Hung, Pang-Chi Lo, Jia-Fong Yeh, Han-Yuan Hsu, Yi-Ting Chen, Winston H. Hsu |
| 2025 | VILA-U: a Unified Foundation Model Integrating Visual Understanding and Generation. Yecheng Wu, Zhuoyang Zhang, Junyu Chen, Haotian Tang, Dacheng Li, Yunhao Fang, Ligeng Zhu, Enze Xie, Hongxu Yin, Li Yi, Song Han, Yao Lu |
| 2025 | VL-Cache: Sparsity and Modality-Aware KV Cache Compression for Vision-Language Model Inference Acceleration. Dezhan Tu, Danylo Vashchilenko, Yuzhe Lu, Panpan Xu |
| 2025 | VL-ICL Bench: The Devil in the Details of Multimodal In-Context Learning. Yongshuo Zong, Ondrej Bohdal, Timothy M. Hospedales |
| 2025 | VLAS: Vision-Language-Action Model with Speech Instructions for Customized Robot Manipulation. Wei Zhao, Pengxiang Ding, Min Zhang, Zhefei Gong, Shuanghao Bai, Han Zhao, Donglin Wang |
| 2025 | VLM2Vec: Training Vision-Language Models for Massive Multimodal Embedding Tasks. Ziyan Jiang, Rui Meng, Xinyi Yang, Semih Yavuz, Yingbo Zhou, Wenhu Chen |
| 2025 | VLMaterial: Procedural Material Generation with Large Vision-Language Models. Beichen Li, Rundi Wu, Armando Solar-Lezama, Changxi Zheng, Liang Shi, Bernd Bickel, Wojciech Matusik |
| 2025 | VOILA: Evaluation of MLLMs For Perceptual Understanding and Analogical Reasoning. Nilay Yilmaz, Maitreya Patel, Yiran Lawrence Luo, Tejas Gokhale, Chitta Baral, Suren Jayasuriya, Yezhou Yang |
| 2025 | VSTAR: Generative Temporal Nursing for Longer Dynamic Video Synthesis. Yumeng Li, William H. Beluch, Margret Keuper, Dan Zhang, Anna Khoreva |
| 2025 | VTDexManip: A Dataset and Benchmark for Visual-tactile Pretraining and Dexterous Manipulation with Reinforcement Learning. Qingtao Liu, Yu Cui, Zhengnan Sun, Gaofeng Li, Jiming Chen, Qi Ye |
| 2025 | VVC-Gym: A Fixed-Wing UAV Reinforcement Learning Environment for Multi-Goal Long-Horizon Problems. Xudong Gong, Dawei Feng, Kele Xu, Weijia Wang, Zhangjun Sun, Xing Zhou, Si Zheng, Bo Ding, Huaimin Wang |
| 2025 | Valid Conformal Prediction for Dynamic GNNs. Ed Davis, Ian Gallagher, Daniel John Lawson, Patrick Rubin-Delanchy |
| 2025 | Value-Incentivized Preference Optimization: A Unified Approach to Online and Offline RLHF. Shicong Cen, Jincheng Mei, Katayoon Goshvadi, Hanjun Dai, Tong Yang, Sherry Yang, Dale Schuurmans, Yuejie Chi, Bo Dai |
| 2025 | Value-aligned Behavior Cloning for Offline Reinforcement Learning via Bi-level Optimization. Xingyu Jiang, Ning Gao, Xiuhui Zhang, Hongkun Dou, Yue Deng |
| 2025 | Variance-Reducing Couplings for Random Features. Isaac Reid, Stratis Markou, Krzysztof Marcin Choromanski, Richard E. Turner, Adrian Weller |
| 2025 | Variational Bayesian Pseudo-Coreset. Hyungi Lee, Seungyoo Lee, Juho Lee |
| 2025 | Variational Best-of-N Alignment. Afra Amini, Tim Vieira, Elliott Ash, Ryan Cotterell |
| 2025 | Variational Diffusion Posterior Sampling with Midpoint Guidance. Badr Moufad, Yazid Janati, Lisa Bedin, Alain Oliviero Durmus, Randal Douc, Eric Moulines, Jimmy Olsson |
| 2025 | Variational Search Distributions. Daniel M. Steinberg, Rafael Oliveira, Cheng Soon Ong, Edwin V. Bonilla |
| 2025 | Varying Shades of Wrong: Aligning LLMs with Wrong Answers Only. Jihan Yao, Wenxuan Ding, Shangbin Feng, Lucy Lu Wang, Yulia Tsvetkov |
| 2025 | Vec2Face: Scaling Face Dataset Generation with Loosely Constrained Vectors. Haiyu Wu, Jaskirat Singh, Sicong Tian, Liang Zheng, Kevin W. Bowyer |
| 2025 | Vector-ICL: In-context Learning with Continuous Vector Representations. Yufan Zhuang, Chandan Singh, Liyuan Liu, Jingbo Shang, Jianfeng Gao |
| 2025 | Verifying Properties of Binary Neural Networks Using Sparse Polynomial Optimization. Jianting Yang, Srecko Ðurasinovic, Jean B. Lasserre, Victor Magron, Jun Zhao |
| 2025 | Vertical Federated Learning with Missing Features During Training and Inference. Pedro Valdeira, Shiqiang Wang, Yuejie Chi |
| 2025 | Vevo: Controllable Zero-Shot Voice Imitation with Self-Supervised Disentanglement. Xueyao Zhang, Xiaohui Zhang, Kainan Peng, Zhenyu Tang, Vimal Manohar, Yingru Liu, Jeff Hwang, Dangna Li, Yuhao Wang, Julian Chan, Yuan Huang, Zhizheng Wu, Mingbo Ma |
| 2025 | ViBiDSampler: Enhancing Video Interpolation Using Bidirectional Diffusion Sampler. Serin Yang, Taesung Kwon, Jong Chul Ye |
| 2025 | ViDiT-Q: Efficient and Accurate Quantization of Diffusion Transformers for Image and Video Generation. Tianchen Zhao, Tongcheng Fang, Haofeng Huang, Rui Wan, Widyadewi Soedarmadji, Enshu Liu, Shiyao Li, Zinan Lin, Guohao Dai, Shengen Yan, Huazhong Yang, Xuefei Ning, Yu Wang |
| 2025 | ViSAGe: Video-to-Spatial Audio Generation. Jaeyeon Kim, Heeseung Yun, Gunhee Kim |
| 2025 | VibeCheck: Discover and Quantify Qualitative Differences in Large Language Models. Lisa Dunlap, Krishna Mandal, Trevor Darrell, Jacob Steinhardt, Joseph E. Gonzalez |
| 2025 | Video Action Differencing. James Burgess, Xiaohan Wang, Yuhui Zhang, Anita Rau, Alejandro Lozano, Lisa Dunlap, Trevor Darrell, Serena Yeung-Levy |
| 2025 | Video In-context Learning: Autoregressive Transformers are Zero-Shot Video Imitators. Wentao Zhang, Junliang Guo, Tianyu He, Li Zhao, Linli Xu, Jiang Bian |
| 2025 | Video-STaR: Self-Training Enables Video Instruction Tuning with Any Supervision. Orr Zohar, Xiaohan Wang, Yonatan Bitton, Idan Szpektor, Serena Yeung-Levy |
| 2025 | VideoGrain: Modulating Space-Time Attention for Multi-Grained Video Editing. Xiangpeng Yang, Linchao Zhu, Hehe Fan, Yi Yang |
| 2025 | VideoPhy: Evaluating Physical Commonsense for Video Generation. Hritik Bansal, Zongyu Lin, Tianyi Xie, Zeshun Zong, Michal Yarom, Yonatan Bitton, Chenfanfu Jiang, Yizhou Sun, Kai-Wei Chang, Aditya Grover |
| 2025 | VideoShield: Regulating Diffusion-based Video Generation Models via Watermarking. Runyi Hu, Jie Zhang, Yiming Li, Jiwei Li, Qing Guo, Han Qiu, Tianwei Zhang |
| 2025 | VideoWebArena: Evaluating Long Context Multimodal Agents with Video Understanding Web Tasks. Lawrence Keunho Jang, Yinheng Li, Dan Zhao, Charles Ding, Justin Lin, Paul Pu Liang, Rogerio Bonatti, Kazuhito Koishida |
| 2025 | VisRAG: Vision-based Retrieval-augmented Generation on Multi-modality Documents. Shi Yu, Chaoyue Tang, Bokai Xu, Junbo Cui, Junhao Ran, Yukun Yan, Zhenghao Liu, Shuo Wang, Xu Han, Zhiyuan Liu, Maosong Sun |
| 2025 | Vision CNNs trained to estimate spatial latents learned similar ventral-stream-aligned representations. Yudi Xie, Weichen Huang, Esther Alter, Jeremy Schwartz, Joshua B. Tenenbaum, James J. DiCarlo |
| 2025 | Vision Language Models are In-Context Value Learners. Yecheng Jason Ma, Joey Hejna, Chuyuan Fu, Dhruv Shah, Jacky Liang, Zhuo Xu, Sean Kirmani, Peng Xu, Danny Driess, Ted Xiao, Osbert Bastani, Dinesh Jayaraman, Wenhao Yu, Tingnan Zhang, Dorsa Sadigh, Fei Xia |
| 2025 | Vision and Language Synergy for Rehearsal Free Continual Learning. Muhammad Anwar Ma'sum, Mahardhika Pratama, Savitha Ramasamy, Lin Liu, Habibullah, Ryszard Kowalczyk |
| 2025 | Vision-LSTM: xLSTM as Generic Vision Backbone. Benedikt Alkin, Maximilian Beck, Korbinian Pöppel, Sepp Hochreiter, Johannes Brandstetter |
| 2025 | Vision-RWKV: Efficient and Scalable Visual Perception with RWKV-Like Architectures. Yuchen Duan, Weiyun Wang, Zhe Chen, Xizhou Zhu, Lewei Lu, Tong Lu, Yu Qiao, Hongsheng Li, Jifeng Dai, Wenhai Wang |
| 2025 | Visual Agents as Fast and Slow Thinkers. Guangyan Sun, Mingyu Jin, Zhenting Wang, Cheng-Long Wang, Siqi Ma, Qifan Wang, Tong Geng, Ying Nian Wu, Yongfeng Zhang, Dongfang Liu |
| 2025 | Visual Description Grounding Reduces Hallucinations and Boosts Reasoning in LVLMs. Sreyan Ghosh, Chandra Kiran Reddy Evuru, Sonal Kumar, Utkarsh Tyagi, Oriol Nieto, Zeyu Jin, Dinesh Manocha |
| 2025 | Visual Haystacks: A Vision-Centric Needle-In-A-Haystack Benchmark. Tsung-Han Wu, Giscard Biamby, Jerome Quenum, Ritwik Gupta, Joseph E. Gonzalez, Trevor Darrell, David M. Chan |
| 2025 | Visual-O1: Understanding Ambiguous Instructions via Multi-modal Multi-turn Chain-of-thoughts Reasoning. Minheng Ni, Yutao Fan, Lei Zhang, Wangmeng Zuo |
| 2025 | VisualAgentBench: Towards Large Multimodal Models as Visual Foundation Agents. Xiao Liu, Tianjie Zhang, Yu Gu, Iat Long Iong, Xixuan Song, Yifan Xu, Shudan Zhang, Hanyu Lai, Jiadai Sun, Xinyue Yang, Yu Yang, Zehan Qi, Shuntian Yao, Xueqiao Sun, Siyi Cheng, Qinkai Zheng, Hao Yu, Hanchen Zhang, Wenyi Hong, Ming Ding, Lihang Pan, Xiaotao Gu, Aohan Zeng, Zhengxiao Du, Chan Hee Song, Yu Su, Yuxiao Dong, Jie Tang |
| 2025 | VisualPredicator: Learning Abstract World Models with Neuro-Symbolic Predicates for Robot Planning. Yichao Liang, Nishanth Kumar, Hao Tang, Adrian Weller, Joshua B. Tenenbaum, Tom Silver, João F. Henriques, Kevin Ellis |
| 2025 | Visually Consistent Hierarchical Image Classification. Seulki Park, Youren Zhang, Stella X. Yu, Sara Beery, Jonathan Huang |
| 2025 | Visually Guided Decoding: Gradient-Free Hard Prompt Inversion with Language Models. Donghoon Kim, Minji Bae, Kyuhong Shim, Byonghyo Shim |
| 2025 | VoxDialogue: Can Spoken Dialogue Systems Understand Information Beyond Words? Xize Cheng, Ruofan Hu, Xiaoda Yang, Jingyu Lu, Dongjie Fu, Zehan Wang, Shengpeng Ji, Rongjie Huang, Boyang Zhang, Tao Jin, Zhou Zhao |
| 2025 | W-PCA Based Gradient-Free Proxy for Efficient Search of Lightweight Language Models. Shang Wang |
| 2025 | Walk the Talk? Measuring the Faithfulness of Large Language Model Explanations. Katie Matton, Robert Osazuwa Ness, John V. Guttag, Emre Kiciman |
| 2025 | Ward: Provable RAG Dataset Inference via LLM Watermarks. Nikola Jovanovic, Robin Staab, Maximilian Baader, Martin T. Vechev |
| 2025 | WardropNet: Traffic Flow Predictions via Equilibrium-Augmented Learning. Kai Jungel, Dario Paccagnan, Axel Parmentier, Maximilian Schiffer |
| 2025 | Warm Diffusion: Recipe for Blur-Noise Mixture Diffusion Models. Hao-Chien Hsueh, Wen-Hsiao Peng, Ching-Chun Huang |
| 2025 | Wasserstein Distances, Neuronal Entanglement, and Sparsity. Shashata Sawmya, Linghao Kong, Ilia Markov, Dan Alistarh, Nir Shavit |
| 2025 | Wasserstein-Regularized Conformal Prediction under General Distribution Shift. Rui Xu, Chao Chen, Yue Sun, Parvathinathan Venkitasubramaniam, Sihong Xie |
| 2025 | Watch Less, Do More: Implicit Skill Discovery for Video-Conditioned Policy. Jiangxing Wang, Zongqing Lu |
| 2025 | Watermark Anything With Localized Messages. Tom Sander, Pierre Fernandez, Alain Oliviero Durmus, Teddy Furon, Matthijs Douze |
| 2025 | WavTokenizer: an Efficient Acoustic Discrete Codec Tokenizer for Audio Language Modeling. Shengpeng Ji, Ziyue Jiang, Wen Wang, Yifu Chen, Minghui Fang, Jialong Zuo, Qian Yang, Xize Cheng, Zehan Wang, Ruiqi Li, Ziang Zhang, Xiaoda Yang, Rongjie Huang, Yidi Jiang, Qian Chen, Siqi Zheng, Zhou Zhao |
| 2025 | Wavelet Diffusion Neural Operator. Peiyan Hu, Rui Wang, Xiang Zheng, Tao Zhang, Haodong Feng, Ruiqi Feng, Long Wei, Yue Wang, Zhi-Ming Ma, Tailin Wu |
| 2025 | Wavelet-based Positional Representation for Long Context. Yui Oka, Taku Hasegawa, Kyosuke Nishida, Kuniko Saito |
| 2025 | Wayward Concepts In Multimodal Models. Brandon Trabucco, Max Gurinas, Kyle Doherty, Russ Salakhutdinov |
| 2025 | Weak to Strong Generalization for Large Language Models with Multi-capabilities. Yucheng Zhou, Jianbing Shen, Yu Cheng |
| 2025 | Weak-to-Strong Generalization Through the Data-Centric Lens. Changho Shin, John Cooper, Frederic Sala |
| 2025 | Weak-to-Strong Preference Optimization: Stealing Reward from Weak Aligned Model. Wenhong Zhu, Zhiwei He, Xiaofeng Wang, Pengfei Liu, Rui Wang |
| 2025 | Weakly Supervised Video Scene Graph Generation via Natural Language Supervision. Kibum Kim, Kanghoon Yoon, Yeonjun In, Jaehyeong Jeon, Jinyoung Moon, Donghyun Kim, Chanyoung Park |
| 2025 | Weakly-Supervised Affordance Grounding Guided by Part-Level Semantic Priors. Peiran Xu, Yadong Mu |
| 2025 | WeatherGFM: Learning a Weather Generalist Foundation Model via In-context Learning. Xiangyu Zhao, Zhiwang Zhou, Wenlong Zhang, Yihao Liu, Xiangyu Chen, Junchao Gong, Hao Chen, Ben Fei, Shiqi Chen, Wanli Ouyang, Xiao-Ming Wu, Lei Bai |
| 2025 | Web Agents with World Models: Learning and Leveraging Environment Dynamics in Web Navigation. Hyungjoo Chae, Namyoung Kim, Kai Tzu-iunn Ong, Minju Gwak, Gwanwoo Song, Jihoon Kim, Sunghwan Kim, Dongha Lee, Jinyoung Yeo |
| 2025 | WebRL: Training LLM Web Agents via Self-Evolving Online Curriculum Reinforcement Learning. Zehan Qi, Xiao Liu, Iat Long Iong, Hanyu Lai, Xueqiao Sun, Jiadai Sun, Xinyue Yang, Yu Yang, Shuntian Yao, Wei Xu, Jie Tang, Yuxiao Dong |
| 2025 | Weighted Multi-Prompt Learning with Description-free Large Language Model Distillation. Sua Lee, Kyubum Shin, Jung Ho Park |
| 2025 | Weighted Point Set Embedding for Multimodal Contrastive Learning Toward Optimal Similarity Metric. Toshimitsu Uesaka, Taiji Suzuki, Yuhta Takida, Chieh-Hsin Lai, Naoki Murata, Yuki Mitsufuji |
| 2025 | Weighted-Reward Preference Optimization for Implicit Model Fusion. Ziyi Yang, Fanqi Wan, Longguang Zhong, Tianyuan Shi, Xiaojun Quan |
| 2025 | What Are Good Positional Encodings for Directed Graphs? Yinan Huang, Haoyu Peter Wang, Pan Li |
| 2025 | What Do You See in Common? Learning Hierarchical Prototypes over Tree-of-Life to Discover Evolutionary Traits. Harish Babu Manogaran, M. Maruf, Arka Daw, Kazi Sajeed Mehrab, Caleb Patrick Charpentier, Josef C. Uyeda, Wasila M. Dahdul, Matthew J. Thompson, Elizabeth G. Campolongo, Kaiya L. Provost, Wei-Lun Chao, Tanya Y. Berger-Wolf, Paula M. Mabee, Hilmar Lapp, Anuj Karpatne |
| 2025 | What Does It Mean to Be a Transformer? Insights from a Theoretical Hessian Analysis. Weronika Ormaniec, Felix Dangel, Sidak Pal Singh |
| 2025 | What Makes Large Language Models Reason in (Multi-Turn) Code Generation? Kunhao Zheng, Juliette Decugis, Jonas Gehring, Taco Cohen, Benjamin NéXuanjinggrevergne, Gabriel Synnaeve |
| 2025 | What Makes a Good Diffusion Planner for Decision Making? Haofei Lu, Dongqi Han, Yifei Shen, Dongsheng Li |
| 2025 | What Makes a Maze Look Like a Maze? Joy Hsu, Jiayuan Mao, Joshua B. Tenenbaum, Noah D. Goodman, Jiajun Wu |
| 2025 | What Matters When Repurposing Diffusion Models for General Dense Perception Tasks? Guangkai Xu, Yongtao Ge, Mingyu Liu, Chengxiang Fan, Kangyang Xie, Zhiyue Zhao, Hao Chen, Chunhua Shen |
| 2025 | What Matters in Learning from Large-Scale Datasets for Robot Manipulation. Vaibhav Saxena, Matthew Bronars, Nadun Ranawaka Arachchige, Kuancheng Wang, Woo-Chul Shin, Soroush Nasiriany, Ajay Mandlekar, Danfei Xu |
| 2025 | What Secrets Do Your Manifolds Hold? Understanding the Local Geometry of Generative Models. Ahmed Imtiaz Humayun, Ibtihel Amara, Cristina Nader Vasconcelos, Deepak Ramachandran, Candice Schumann, Junfeng He, Katherine A. Heller, Golnoosh Farnadi, Negar Rostamzadeh, Mohammad Havaei |
| 2025 | What is Wrong with Perplexity for Long-context Language Modeling? Lizhe Fang, Yifei Wang, Zhaoyang Liu, Chenheng Zhang, Stefanie Jegelka, Jinyang Gao, Bolin Ding, Yisen Wang |
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| 2025 | What to align in multimodal contrastive learning? Benoit Dufumier, Javiera Castillo Navarro, Devis Tuia, Jean-Philippe Thiran |
| 2025 | What's New in My Data? Novelty Exploration via Contrastive Generation. Masaru Isonuma, Ivan Titov |
| 2025 | What's the Move? Hybrid Imitation Learning via Salient Points. Priya Sundaresan, Hengyuan Hu, Quan Vuong, Jeannette Bohg, Dorsa Sadigh |
| 2025 | When Attention Sink Emerges in Language Models: An Empirical View. Xiangming Gu, Tianyu Pang, Chao Du, Qian Liu, Fengzhuo Zhang, Cunxiao Du, Ye Wang, Min Lin |
| 2025 | When GNNs meet symmetry in ILPs: an orbit-based feature augmentation approach. Qian Chen, Lei Li, Qian Li, Jianghua Wu, Akang Wang, Ruoyu Sun, Xiaodong Luo, Tsung-Hui Chang, Qingjiang Shi |
| 2025 | When Graph Neural Networks Meet Dynamic Mode Decomposition. Dai Shi, Lequan Lin, Andi Han, Zhiyong Wang, Yi Guo, Junbin Gao |
| 2025 | When LLMs Play the Telephone Game: Cultural Attractors as Conceptual Tools to Evaluate LLMs in Multi-turn Settings. Jérémy Perez, Grgur Kovac, Corentin Léger, Cédric Colas, Gaia Molinaro, Maxime Derex, Pierre-Yves Oudeyer, Clément Moulin-Frier |
| 2025 | When Prompt Engineering Meets Software Engineering: CNL-P as Natural and Robust "APIs" for Human-AI Interaction. Zhenchang Xing, Yang Liu, Zhuo Cheng, Qing Huang, Dehai Zhao, Daniel Sun, Chenhua Liu |
| 2025 | When Selection Meets Intervention: Additional Complexities in Causal Discovery. Haoyue Dai, Ignavier Ng, Jianle Sun, Zeyu Tang, Gongxu Luo, Xinshuai Dong, Peter Spirtes, Kun Zhang |
| 2025 | When do GFlowNets learn the right distribution? Tiago da Silva, Rodrigo Barreto Alves, Eliezer de Souza da Silva, Amauri H. Souza, Vikas Garg, Samuel Kaski, Diego Mesquita |
| 2025 | When does compositional structure yield compositional generalization? A kernel theory. Samuel Lippl, Kim Stachenfeld |
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| 2025 | When narrower is better: the narrow width limit of Bayesian parallel branching neural networks. Zechen Zhang, Haim Sompolinsky |
| 2025 | Where Am I and What Will I See: An Auto-Regressive Model for Spatial Localization and View Prediction. Junyi Chen, Di Huang, Weicai Ye, Wanli Ouyang, Tong He |
| 2025 | Which Tasks Should Be Compressed Together? A Causal Discovery Approach for Efficient Multi-Task Representation Compression. Sha Guo, Jing Chen, Zixuan Hu, Zhuo Chen, Wenhan Yang, Yu Lin, Xing Jiang, Lingyu Duan |
| 2025 | Why Does the Effective Context Length of LLMs Fall Short? Chenxin An, Jun Zhang, Ming Zhong, Lei Li, Shansan Gong, Yao Luo, Jingjing Xu, Lingpeng Kong |
| 2025 | Why In-Context Learning Models are Good Few-Shot Learners? Shiguang Wu, Yaqing Wang, Quanming Yao |
| 2025 | Wicked Oddities: Selectively Poisoning for Effective Clean-Label Backdoor Attacks. Nguyen Hung-Quang, Ngoc-Hieu Nguyen, The-Anh Ta, Thanh Nguyen-Tang, Kok-Seng Wong, Hoang Thanh-Tung, Khoa D. Doan |
| 2025 | Wide Neural Networks Trained with Weight Decay Provably Exhibit Neural Collapse. Arthur Jacot, Peter Súkeník, Zihan Wang, Marco Mondelli |
| 2025 | WildBench: Benchmarking LLMs with Challenging Tasks from Real Users in the Wild. Bill Yuchen Lin, Yuntian Deng, Khyathi Raghavi Chandu, Abhilasha Ravichander, Valentina Pyatkin, Nouha Dziri, Ronan Le Bras, Yejin Choi |
| 2025 | WizardMath: Empowering Mathematical Reasoning for Large Language Models via Reinforced Evol-Instruct. Haipeng Luo, Qingfeng Sun, Can Xu, Pu Zhao, Jian-Guang Lou, Chongyang Tao, Xiubo Geng, Qingwei Lin, Shifeng Chen, Yansong Tang, Dongmei Zhang |
| 2025 | Words in Motion: Extracting Interpretable Control Vectors for Motion Transformers. Ömer Sahin Tas, Royden Wagner |
| 2025 | WorkflowLLM: Enhancing Workflow Orchestration Capability of Large Language Models. Shengda Fan, Xin Cong, Yuepeng Fu, Zhong Zhang, Shuyan Zhang, Yuanwei Liu, Yesai Wu, Yankai Lin, Zhiyuan Liu, Maosong Sun |
| 2025 | World Model on Million-Length Video And Language With Blockwise RingAttention. Hao Liu, Wilson Yan, Matei Zaharia, Pieter Abbeel |
| 2025 | X-ALMA: Plug & Play Modules and Adaptive Rejection for Quality Translation at Scale. Haoran Xu, Kenton Murray, Philipp Koehn, Hieu Hoang, Akiko Eriguchi, Huda Khayrallah |
| 2025 | X-Drive: Cross-modality Consistent Multi-Sensor Data Synthesis for Driving Scenarios. Yichen Xie, Chenfeng Xu, Chensheng Peng, Shuqi Zhao, Nhat Ho, Alexander T. Pham, Mingyu Ding, Masayoshi Tomizuka, Wei Zhan |
| 2025 | X-Fi: A Modality-Invariant Foundation Model for Multimodal Human Sensing. Xinyan Chen, Jianfei Yang |
| 2025 | X-NeMo: Expressive Neural Motion Reenactment via Disentangled Latent Attention. Xiaochen Zhao, Hongyi Xu, Guoxian Song, You Xie, Chenxu Zhang, Xiu Li, Linjie Luo, Jinli Suo, Yebin Liu |
| 2025 | X-Sample Contrastive Loss: Improving Contrastive Learning with Sample Similarity Graphs. Vlad Sobal, Mark Ibrahim, Randall Balestriero, Vivien Cabannes, Diane Bouchacourt, Pietro Astolfi, Kyunghyun Cho, Yann LeCun |
| 2025 | XAIguiFormer: explainable artificial intelligence guided transformer for brain disorder identification. Hanning Guo, Farah Abdellatif, Yu Fu, N. Jon Shah, Abigail Morrison, Jürgen Dammers |
| 2025 | XLand-100B: A Large-Scale Multi-Task Dataset for In-Context Reinforcement Learning. Alexander Nikulin, Ilya Zisman, Alexey Zemtsov, Vladislav Kurenkov |
| 2025 | YOLO-RD: Introducing Relevant and Compact Explicit Knowledge to YOLO by Retriever-Dictionary. Hao-Tang Tsui, Chien-Yao Wang, Hong-Yuan Mark Liao |
| 2025 | You Only Prune Once: Designing Calibration-Free Model Compression With Policy Learning. Ayan Sengupta, Siddhant Chaudhary, Tanmoy Chakraborty |
| 2025 | You Only Sample Once: Taming One-Step Text-to-Image Synthesis by Self-Cooperative Diffusion GANs. Yihong Luo, Xiaolong Chen, Xinghua Qu, Tianyang Hu, Jing Tang |
| 2025 | YouTube-SL-25: A Large-Scale, Open-Domain Multilingual Sign Language Parallel Corpus. Garrett Tanzer, Biao Zhang |
| 2025 | Youku Dense Caption: A Large-scale Chinese Video Dense Caption Dataset and Benchmarks. Zixuan Xiong, Guangwei Xu, Wenkai Zhang, Yuan Miao, Xuan Wu, LinHai, Ruijie Guo, Hai-Tao Zheng |
| 2025 | Your Absorbing Discrete Diffusion Secretly Models the Conditional Distributions of Clean Data. Jingyang Ou, Shen Nie, Kaiwen Xue, Fengqi Zhu, Jiacheng Sun, Zhenguo Li, Chongxuan Li |
| 2025 | Your Mixture-of-Experts LLM Is Secretly an Embedding Model for Free. Ziyue Li, Tianyi Zhou |
| 2025 | Your Weak LLM is Secretly a Strong Teacher for Alignment. Leitian Tao, Yixuan Li |
| 2025 | ZAPBench: A Benchmark for Whole-Brain Activity Prediction in Zebrafish. Jan-Matthis Lueckmann, Alexander Immer, Alex Bo-Yuan Chen, Peter H. Li, Mariela D. Petkova, Nirmala A. Iyer, Luuk Willem Hesselink, Aparna Dev, Gudrun Ihrke, Woohyun Park, Alyson Petruncio, Aubrey Weigel, Wyatt Korff, Florian Engert, Jeff Lichtman, Misha B. Ahrens, Michal Januszewski, Viren Jain |
| 2025 | ZETA: Leveraging Z-order Curves for Efficient Top-k Attention. Qiuhao Zeng, Jerry Huang, Peng Lu, Gezheng Xu, Boxing Chen, Charles Ling, Boyu Wang |
| 2025 | ZIP: An Efficient Zeroth-order Prompt Tuning for Black-box Vision-Language Models. Seonghwan Park, Jaehyeon Jeong, Yongjun Kim, Jaeho Lee, Namhoon Lee |
| 2025 | Zero-Shot Natural Language Explanations. Fawaz Sammani, Nikos Deligiannis |
| 2025 | Zero-Shot Whole-Body Humanoid Control via Behavioral Foundation Models. Andrea Tirinzoni, Ahmed Touati, Jesse Farebrother, Mateusz Guzek, Anssi Kanervisto, Yingchen Xu, Alessandro Lazaric, Matteo Pirotta |
| 2025 | Zero-cost Proxy for Adversarial Robustness Evaluation. Yuqi Feng, Yuwei Ou, Jiahao Fan, Yanan Sun |
| 2025 | Zero-shot Imputation with Foundation Inference Models for Dynamical Systems. Patrick Seifner, Kostadin Cvejoski, Antonia Körner, Ramsés J. Sánchez |
| 2025 | Zero-shot Model-based Reinforcement Learning using Large Language Models. Abdelhakim Benechehab, Youssef Attia El Hili, Ambroise Odonnat, Oussama Zekri, Albert Thomas, Giuseppe Paolo, Maurizio Filippone, Ievgen Redko, Balázs Kégl |
| 2025 | Zero-shot forecasting of chaotic systems. Yuanzhao Zhang, William Gilpin |
| 2025 | ZeroDiff: Solidified Visual-semantic Correlation in Zero-Shot Learning. Zihan Ye, Shreyank N. Gowda, Shiming Chen, Xiaowei Huang, Haotian Xu, Fahad Shahbaz Khan, Yaochu Jin, Kaizhu Huang, Xiaobo Jin |
| 2025 | Zeroth-Order Fine-Tuning of LLMs with Transferable Static Sparsity. Wentao Guo, Jikai Long, Yimeng Zeng, Zirui Liu, Xinyu Yang, Yide Ran, Jacob R. Gardner, Osbert Bastani, Christopher De Sa, Xiaodong Yu, Beidi Chen, Zhaozhuo Xu |
| 2025 | Zeroth-Order Policy Gradient for Reinforcement Learning from Human Feedback without Reward Inference. Qining Zhang, Lei Ying |
| 2025 | Zigzag Diffusion Sampling: Diffusion Models Can Self-Improve via Self-Reflection. Lichen Bai, Shitong Shao, Zikai Zhou, Zipeng Qi, Zhiqiang Xu, Haoyi Xiong, Zeke Xie |
| 2025 | ZooProbe: A Data Engine for Evaluating, Exploring, and Evolving Large-scale Training Data for Multimodal LLMs. Yi-Kai Zhang, Shiyin Lu, Qing-Guo Chen, De-Chuan Zhan, Han-Jia Ye |
| 2025 | cryoSPHERE: Single-Particle HEterogeneous REconstruction from cryo EM. Gabriel Ducrocq, Lukas Grunewald, Sebastian Westenhoff, Fredrik Lindsten |
| 2025 | dEBORA: Efficient Bilevel Optimization-based low-Rank Adaptation. Emanuele Zangrando, Sara Venturini, Francesco Rinaldi, Francesco Tudisco |
| 2025 | eQMARL: Entangled Quantum Multi-Agent Reinforcement Learning for Distributed Cooperation over Quantum Channels. Alexander C. DeRieux, Walid Saad |
| 2025 | econSG: Efficient and Multi-view Consistent Open-Vocabulary 3D Semantic Gaussians. Can Zhang, Gim Hee Lee |
| 2025 | gRNAde: Geometric Deep Learning for 3D RNA inverse design. Chaitanya K. Joshi, Arian Rokkum Jamasb, Ramón Viñas Torné, Charles Harris, Simon V. Mathis, Alex Morehead, Rishabh Anand, Pietro Lio |
| 2025 | h4rm3l: A Language for Composable Jailbreak Attack Synthesis. Moussa Koulako Bala Doumbouya, Ananjan Nandi, Gabriel Poesia, Davide Ghilardi, Anna Goldie, Federico Bianchi, Dan Jurafsky, Christopher D. Manning |
| 2025 | kNN Attention Demystified: A Theoretical Exploration for Scalable Transformers. Themistoklis Haris |
| 2025 | mPLUG-Owl3: Towards Long Image-Sequence Understanding in Multi-Modal Large Language Models. Jiabo Ye, Haiyang Xu, Haowei Liu, Anwen Hu, Ming Yan, Qi Qian, Ji Zhang, Fei Huang, Jingren Zhou |
| 2025 | metabench - A Sparse Benchmark of Reasoning and Knowledge in Large Language Models. Alexander Kipnis, Konstantinos Voudouris, Luca M. Schulze Buschoff, Eric Schulz |
| 2025 | miniCTX: Neural Theorem Proving with (Long-)Contexts. Jiewen Hu, Thomas Zhu, Sean Welleck |
| 2025 | nGPT: Normalized Transformer with Representation Learning on the Hypersphere. Ilya Loshchilov, Cheng-Ping Hsieh, Simeng Sun, Boris Ginsburg |
| 2025 | pMoE: Prompting Diverse Experts Together Wins More in Visual Adaptation. Shentong Mo, Xufang Luo, Dongsheng Li |
| 2025 | q-exponential family for policy optimization. Lingwei Zhu, Haseeb Shah, Han Wang, Yukie Nagai, Martha White |
| 2025 | qNBO: quasi-Newton Meets Bilevel Optimization. Sheng Fang, Yongjin Liu, Wei Yao, Chengming Yu, Jin Zhang |
| 2025 | u-μP: The Unit-Scaled Maximal Update Parametrization. Charlie Blake, Constantin Eichenberg, Josef Dean, Lukas Balles, Luke Yuri Prince, Björn Deiseroth, Andrés Felipe Cruz-Salinas, Carlo Luschi, Samuel Weinbach, Douglas Orr |
| 2025 | uniINF: Best-of-Both-Worlds Algorithm for Parameter-Free Heavy-Tailed MABs. Yu Chen, Jiatai Huang, Yan Dai, Longbo Huang |
| 2025 | xFinder: Large Language Models as Automated Evaluators for Reliable Evaluation. Qingchen Yu, Zifan Zheng, Shichao Song, Zhiyu Li, Feiyu Xiong, Bo Tang, Ding Chen |
| 2025 | {τ}-bench: A Benchmark for \underline{T}ool-\underline{A}gent-\underline{U}ser Interaction in Real-World Domains. Shunyu Yao, Noah Shinn, Pedram Razavi, Karthik R. Narasimhan |
| 2025 | γ-MoD: Exploring Mixture-of-Depth Adaptation for Multimodal Large Language Models. Yaxin Luo, Gen Luo, Jiayi Ji, Yiyi Zhou, Xiaoshuai Sun, Zhiqiang Shen, Rongrong Ji |
| 2025 | σ-zero: Gradient-based Optimization of ℓ0-norm Adversarial Examples. Antonio Emanuele Cinà, Francesco Villani, Maura Pintor, Lea Schönherr, Battista Biggio, Marcello Pelillo |
| 2025 | ϕ-Update: A Class of Policy Update Methods with Policy Convergence Guarantee. Wenye Li, Jiacai Liu, Ke Wei |