ICLR A*

2261 papers

YearTitle / Authors
2024"What Data Benefits My Classifier?" Enhancing Model Performance and Interpretability through Influence-Based Data Selection.
Anshuman Chhabra, Peizhao Li, Prasant Mohapatra, Hongfu Liu
2024#InsTag: Instruction Tagging for Analyzing Supervised Fine-tuning of Large Language Models.
Keming Lu, Hongyi Yuan, Zheng Yuan, Runji Lin, Junyang Lin, Chuanqi Tan, Chang Zhou, Jingren Zhou
2024$t^3$-Variational Autoencoder: Learning Heavy-tailed Data with Student's t and Power Divergence.
Juno Kim, Jaehyuk Kwon, Mincheol Cho, Hyunjong Lee, Joong-Ho Won
20243D Feature Prediction for Masked-AutoEncoder-Based Point Cloud Pretraining.
Siming Yan, Yuqi Yang, Yu-Xiao Guo, Hao Pan, Peng-Shuai Wang, Xin Tong, Yang Liu, Qixing Huang
20243D Reconstruction with Generalizable Neural Fields using Scene Priors.
Yang Fu, Shalini De Mello, Xueting Li, Amey Kulkarni, Jan Kautz, Xiaolong Wang, Sifei Liu
20243D-Aware Hypothesis & Verification for Generalizable Relative Object Pose Estimation.
Chen Zhao, Tong Zhang, Mathieu Salzmann
2024A 2-Dimensional State Space Layer for Spatial Inductive Bias.
Ethan Baron, Itamar Zimerman, Lior Wolf
2024A Benchmark Study on Calibration.
Linwei Tao, Younan Zhu, Haolan Guo, Minjing Dong, Chang Xu
2024A Benchmark for Learning to Translate a New Language from One Grammar Book.
Garrett Tanzer, Mirac Suzgun, Eline Visser, Dan Jurafsky, Luke Melas-Kyriazi
2024A Black-box Approach for Non-stationary Multi-agent Reinforcement Learning.
Haozhe Jiang, Qiwen Cui, Zhihan Xiong, Maryam Fazel, Simon Shaolei Du
2024A Branching Decoder for Set Generation.
Zixian Huang, Gengyang Xiao, Yu Gu, Gong Cheng
2024A Characterization Theorem for Equivariant Networks with Point-wise Activations.
Marco Pacini, Xiaowen Dong, Bruno Lepri, Gabriele Santin
2024A Cognitive Model for Learning Abstract Relational Structures from Memory-based Decision-Making Tasks.
Haruo Hosoya
2024A Data-Driven Measure of Relative Uncertainty for Misclassification Detection.
Eduardo Dadalto Câmara Gomes, Marco Romanelli, Georg Pichler, Pablo Piantanida
2024A Differentially Private Clustering Algorithm for Well-Clustered Graphs.
Weiqiang He, Hendrik Fichtenberger, Pan Peng
2024A Discretization Framework for Robust Contextual Stochastic Optimization.
Rares Cristian, Georgia Perakis
2024A Dynamical View of the Question of Why.
Mehdi Fatemi, Sindhu C. M. Gowda
2024A Fast and Provable Algorithm for Sparse Phase Retrieval.
Jian-Feng Cai, Yu Long, Ruixue Wen, Jiaxi Ying
2024A Flexible Generative Model for Heterogeneous Tabular EHR with Missing Modality.
Huan He, William Hao, Yuanzhe Xi, Yong Chen, Bradley A. Malin, Joyce C. Ho
2024A Foundation Model for Error Correction Codes.
Yoni Choukroun, Lior Wolf
2024A Framework for Inference Inspired by Human Memory Mechanisms.
Xiangyu Zeng, Jie Lin, Piao Hu, Ruizheng Huang, Zhicheng Zhang
2024A General Framework for User-Guided Bayesian Optimization.
Carl Hvarfner, Frank Hutter, Luigi Nardi
2024A Good Learner can Teach Better: Teacher-Student Collaborative Knowledge Distillation.
Ayan Sengupta, Shantanu Dixit, Md. Shad Akhtar, Tanmoy Chakraborty
2024A Graph is Worth 1-bit Spikes: When Graph Contrastive Learning Meets Spiking Neural Networks.
Jintang Li, Huizhe Zhang, Ruofan Wu, Zulun Zhu, Baokun Wang, Changhua Meng, Zibin Zheng, Liang Chen
2024A Hard-to-Beat Baseline for Training-free CLIP-based Adaptation.
Zhengbo Wang, Jian Liang, Lijun Sheng, Ran He, Zilei Wang, Tieniu Tan
2024A Hierarchical Bayesian Model for Few-Shot Meta Learning.
Minyoung Kim, Timothy M. Hospedales
2024A Lie Group Approach to Riemannian Batch Normalization.
Ziheng Chen, Yue Song, Yunmei Liu, Nicu Sebe
2024A Lightweight Method for Tackling Unknown Participation Statistics in Federated Averaging.
Shiqiang Wang, Mingyue Ji
2024A Linear Algebraic Framework for Counterfactual Generation.
Jong-Hoon Ahn, Akshay Vashist
2024A Multi-Level Framework for Accelerating Training Transformer Models.
Longwei Zou, Han Zhang, Yangdong Deng
2024A Mutual Information Perspective on Federated Contrastive Learning.
Christos Louizos, Matthias Reisser, Denis Korzhenkov
2024A Neural Framework for Generalized Causal Sensitivity Analysis.
Dennis Frauen, Fergus Imrie, Alicia Curth, Valentyn Melnychuk, Stefan Feuerriegel, Mihaela van der Schaar
2024A Newborn Embodied Turing Test for Comparing Object Segmentation Across Animals and Machines.
Manju Garimella, Denizhan Pak, Justin N. Wood, Samantha Marie Waters Wood
2024A Paradigm Shift in Machine Translation: Boosting Translation Performance of Large Language Models.
Haoran Xu, Young Jin Kim, Amr Sharaf, Hany Hassan Awadalla
2024A Plug-and-Play Image Registration Network.
Junhao Hu, Weijie Gan, Zhixin Sun, Hongyu An, Ulugbek Kamilov
2024A Poincaré Inequality and Consistency Results for Signal Sampling on Large Graphs.
Thien Le, Luana Ruiz, Stefanie Jegelka
2024A Policy Gradient Method for Confounded POMDPs.
Mao Hong, Zhengling Qi, Yanxun Xu
2024A Precise Characterization of SGD Stability Using Loss Surface Geometry.
Gregory Dexter, Borja Ocejo, S. Sathiya Keerthi, Aman Gupta, Ayan Acharya, Rajiv Khanna
2024A Primal-Dual Approach to Solving Variational Inequalities with General Constraints.
Tatjana Chavdarova, Tong Yang, Matteo Pagliardini, Michael I. Jordan
2024A Probabilistic Framework for Modular Continual Learning.
Lazar Valkov, Akash Srivastava, Swarat Chaudhuri, Charles Sutton
2024A Progressive Training Framework for Spiking Neural Networks with Learnable Multi-hierarchical Model.
Zecheng Hao, Xinyu Shi, Zihan Huang, Tong Bu, Zhaofei Yu, Tiejun Huang
2024A Quadratic Synchronization Rule for Distributed Deep Learning.
Xinran Gu, Kaifeng Lyu, Sanjeev Arora, Jingzhao Zhang, Longbo Huang
2024A Real-World WebAgent with Planning, Long Context Understanding, and Program Synthesis.
Izzeddin Gur, Hiroki Furuta, Austin V. Huang, Mustafa Safdari, Yutaka Matsuo, Douglas Eck, Aleksandra Faust
2024A Recipe for Improved Certifiable Robustness.
Kai Hu, Klas Leino, Zifan Wang, Matt Fredrikson
2024A Restoration Network as an Implicit Prior.
Yuyang Hu, Mauricio Delbracio, Peyman Milanfar, Ulugbek Kamilov
2024A Semantic Invariant Robust Watermark for Large Language Models.
Aiwei Liu, Leyi Pan, Xuming Hu, Shiao Meng, Lijie Wen
2024A Simple Interpretable Transformer for Fine-Grained Image Classification and Analysis.
Dipanjyoti Paul, Arpita Chowdhury, Xinqi Xiong, Feng-Ju Chang, David Edward Carlyn, Samuel Stevens, Kaiya Provost, Anuj Karpatne, Bryan Carstens, Daniel I. Rubenstein, Charles V. Stewart, Tanya Y. Berger-Wolf, Yu Su, Wei-Lun Chao
2024A Simple Romance Between Multi-Exit Vision Transformer and Token Reduction.
Dongyang Liu, Meina Kan, Shiguang Shan, Xilin Chen
2024A Simple and Effective Pruning Approach for Large Language Models.
Mingjie Sun, Zhuang Liu, Anna Bair, J. Zico Kolter
2024A Simple and Scalable Representation for Graph Generation.
Yunhui Jang, Seul Lee, Sungsoo Ahn
2024A Stable, Fast, and Fully Automatic Learning Algorithm for Predictive Coding Networks.
Tommaso Salvatori, Yuhang Song, Yordan Yordanov, Beren Millidge, Lei Sha, Cornelius Emde, Zhenghua Xu, Rafal Bogacz, Thomas Lukasiewicz
2024A Statistical Analysis of Wasserstein Autoencoders for Intrinsically Low-dimensional Data.
Saptarshi Chakraborty, Peter L. Bartlett
2024A Study of Bayesian Neural Network Surrogates for Bayesian Optimization.
Yucen Lily Li, Tim G. J. Rudner, Andrew Gordon Wilson
2024A Sublinear Adversarial Training Algorithm.
Yeqi Gao, Lianke Qin, Zhao Song, Yitan Wang
2024A Symmetry-Aware Exploration of Bayesian Neural Network Posteriors.
Olivier Laurent, Emanuel Aldea, Gianni Franchi
2024A Topological Perspective on Demystifying GNN-Based Link Prediction Performance.
Yu Wang, Tong Zhao, Yuying Zhao, Yunchao Liu, Xueqi Cheng, Neil Shah, Tyler Derr
2024A Unified Framework for Bayesian Optimization under Contextual Uncertainty.
Sebastian Shenghong Tay, Chuan-Sheng Foo, Daisuke Urano, Richalynn Leong, Bryan Kian Hsiang Low
2024A Unified Sampling Framework for Solver Searching of Diffusion Probabilistic Models.
Enshu Liu, Xuefei Ning, Huazhong Yang, Yu Wang
2024A Unified and General Framework for Continual Learning.
Zhenyi Wang, Yan Li, Li Shen, Heng Huang
2024A Variational Framework for Estimating Continuous Treatment Effects with Measurement Error.
Erdun Gao, Howard D. Bondell, Wei Huang, Mingming Gong
2024A Variational Perspective on Solving Inverse Problems with Diffusion Models.
Morteza Mardani, Jiaming Song, Jan Kautz, Arash Vahdat
2024A Versatile Causal Discovery Framework to Allow Causally-Related Hidden Variables.
Xinshuai Dong, Biwei Huang, Ignavier Ng, Xiangchen Song, Yujia Zheng, Songyao Jin, Roberto Legaspi, Peter Spirtes, Kun Zhang
2024A differentiable brain simulator bridging brain simulation and brain-inspired computing.
Chaoming Wang, Tianqiu Zhang, Sichao He, Hongyaoxing Gu, Shangyang Li, Si Wu
2024A path-norm toolkit for modern networks: consequences, promises and challenges.
Antoine Gonon, Nicolas Brisebarre, Elisa Riccietti, Rémi Gribonval
2024A representation-learning game for classes of prediction tasks.
Neria Uzan, Nir Weinberger
2024A robust differential Neural ODE Optimizer.
Panagiotis Theodoropoulos, Guan-Horng Liu, Tianrong Chen, Augustinos D. Saravanos, Evangelos A. Theodorou
2024A unique M-pattern for micro-expression spotting in long videos.
Jinxuan Wang, Shiting Xu, Tong Zhang
2024ACRF: Compressing Explicit Neural Radiance Fields via Attribute Compression.
Guangchi Fang, Qingyong Hu, Longguang Wang, Yulan Guo
2024ADDP: Learning General Representations for Image Recognition and Generation with Alternating Denoising Diffusion Process.
Changyao Tian, Chenxin Tao, Jifeng Dai, Hao Li, Ziheng Li, Lewei Lu, Xiaogang Wang, Hongsheng Li, Gao Huang, Xizhou Zhu
2024ADOPD: A Large-Scale Document Page Decomposition Dataset.
Jiuxiang Gu, Xiangxi Shi, Jason Kuen, Lu Qi, Ruiyi Zhang, Anqi Liu, Ani Nenkova, Tong Sun
2024AGILE3D: Attention Guided Interactive Multi-object 3D Segmentation.
Yuanwen Yue, Sabarinath Mahadevan, Jonas Schult, Francis Engelmann, Bastian Leibe, Konrad Schindler, Theodora Kontogianni
2024ALAM: Averaged Low-Precision Activation for Memory-Efficient Training of Transformer Models.
Sunghyeon Woo, Sunwoo Lee, Dongsuk Jeon
2024AMAGO: Scalable In-Context Reinforcement Learning for Adaptive Agents.
Jake Grigsby, Linxi Fan, Yuke Zhu
2024ARGS: Alignment as Reward-Guided Search.
Maxim Khanov, Jirayu Burapacheep, Yixuan Li
2024ARM: Refining Multivariate Forecasting with Adaptive Temporal-Contextual Learning.
Jiecheng Lu, Xu Han, Shihao Yang
2024ASID: Active Exploration for System Identification in Robotic Manipulation.
Marius Memmel, Andrew Wagenmaker, Chuning Zhu, Dieter Fox, Abhishek Gupta
2024ASMR: Activation-Sharing Multi-Resolution Coordinate Networks for Efficient Inference.
Jason Chun Lok Li, Steven Tin Sui Luo, Le Xu, Ngai Wong
2024AUC-CL: A Batchsize-Robust Framework for Self-Supervised Contrastive Representation Learning.
Rohan Sharma, Kaiyi Ji, Zhiqiang Xu, Changyou Chen
2024AUGCAL: Improving Sim2Real Adaptation by Uncertainty Calibration on Augmented Synthetic Images.
Prithvijit Chattopadhyay, Bharat Goyal, Boglarka Ecsedi, Viraj Prabhu, Judy Hoffman
2024Abstractors and relational cross-attention: An inductive bias for explicit relational reasoning in Transformers.
Awni Altabaa, Taylor Whittington Webb, Jonathan D. Cohen, John Lafferty
2024Accelerated Convergence of Stochastic Heavy Ball Method under Anisotropic Gradient Noise.
Rui Pan, Yuxing Liu, Xiaoyu Wang, Tong Zhang
2024Accelerated Sampling with Stacked Restricted Boltzmann Machines.
Jorge Fernandez-de-Cossío-Diaz, Clément Roussel, Simona Cocco, Rémi Monasson
2024Accelerating Data Generation for Neural Operators via Krylov Subspace Recycling.
Hong Wang, Zhongkai Hao, Jie Wang, Zijie Geng, Zhen Wang, Bin Li, Feng Wu
2024Accelerating Distributed Stochastic Optimization via Self-Repellent Random Walks.
Jie Hu, Vishwaraj Doshi, Do Young Eun
2024Accelerating Sinkhorn algorithm with sparse Newton iterations.
Xun Tang, Michael Shavlovsky, Holakou Rahmanian, Elisa Tardini, Kiran Koshy Thekumparampil, Tesi Xiao, Lexing Ying
2024Accurate Forgetting for Heterogeneous Federated Continual Learning.
Abudukelimu Wuerkaixi, Sen Cui, Jingfeng Zhang, Kunda Yan, Bo Han, Gang Niu, Lei Fang, Changshui Zhang, Masashi Sugiyama
2024Accurate Retraining-free Pruning for Pretrained Encoder-based Language Models.
Seungcheol Park, Hojun Choi, U Kang
2024Accurate and Scalable Estimation of Epistemic Uncertainty for Graph Neural Networks.
Puja Trivedi, Mark Heimann, Rushil Anirudh, Danai Koutra, Jayaraman J. Thiagarajan
2024Achieving Fairness in Multi-Agent MDP Using Reinforcement Learning.
Peizhong Ju, Arnob Ghosh, Ness B. Shroff
2024Achieving Human Parity in Content-Grounded Datasets Generation.
Asaf Yehudai, Boaz Carmeli, Yosi Mass, Ofir Arviv, Nathaniel Mills, Eyal Shnarch, Leshem Choshen
2024Achieving Sample and Computational Efficient Reinforcement Learning by Action Space Reduction via Grouping.
Yining Li, Peizhong Ju, Ness B. Shroff
2024Active Retrosynthetic Planning Aware of Route Quality.
Luotian Yuan, Yemin Yu, Ying Wei, Yongwei Wang, Zhihua Wang, Fei Wu
2024Active Test-Time Adaptation: Theoretical Analyses and An Algorithm.
Shurui Gui, Xiner Li, Shuiwang Ji
2024AdaMerging: Adaptive Model Merging for Multi-Task Learning.
Enneng Yang, Zhenyi Wang, Li Shen, Shiwei Liu, Guibing Guo, Xingwei Wang, Dacheng Tao
2024Adapting Large Language Models via Reading Comprehension.
Daixuan Cheng, Shaohan Huang, Furu Wei
2024Adapting to Distribution Shift by Visual Domain Prompt Generation.
Zhixiang Chi, Li Gu, Tao Zhong, Huan Liu, Yuanhao Yu, Konstantinos N. Plataniotis, Yang Wang
2024Adaptive Chameleon or Stubborn Sloth: Revealing the Behavior of Large Language Models in Knowledge Conflicts.
Jian Xie, Kai Zhang, Jiangjie Chen, Renze Lou, Yu Su
2024Adaptive Federated Learning with Auto-Tuned Clients.
Junhyung Lyle Kim, Mohammad Taha Toghani, César A. Uribe, Anastasios Kyrillidis
2024Adaptive Instrument Design for Indirect Experiments.
Yash Chandak, Shiv Shankar, Vasilis Syrgkanis, Emma Brunskill
2024Adaptive Rational Activations to Boost Deep Reinforcement Learning.
Quentin Delfosse, Patrick Schramowski, Martin Mundt, Alejandro Molina, Kristian Kersting
2024Adaptive Regret for Bandits Made Possible: Two Queries Suffice.
Zhou Lu, Qiuyi Zhang, Xinyi Chen, Fred Zhang, David P. Woodruff, Elad Hazan
2024Adaptive Regularization of Representation Rank as an Implicit Constraint of Bellman Equation.
Qiang He, Tianyi Zhou, Meng Fang, Setareh Maghsudi
2024Adaptive Retrieval and Scalable Indexing for k-NN Search with Cross-Encoders.
Nishant Yadav, Nicholas Monath, Manzil Zaheer, Rob Fergus, Andrew McCallum
2024Adaptive Self-training Framework for Fine-grained Scene Graph Generation.
Kibum Kim, Kanghoon Yoon, Yeonjun In, Jinyoung Moon, Donghyun Kim, Chanyoung Park
2024Adaptive Sharpness-Aware Pruning for Robust Sparse Networks.
Anna Bair, Hongxu Yin, Maying Shen, Pavlo Molchanov, José M. Álvarez
2024Adaptive Stochastic Gradient Algorithm for Black-box Multi-Objective Learning.
Feiyang Ye, Yueming Lyu, Xuehao Wang, Yu Zhang, Ivor W. Tsang
2024Adaptive Window Pruning for Efficient Local Motion Deblurring.
Haoying Li, Jixin Zhao, Shangchen Zhou, Huajun Feng, Chongyi Li, Chen Change Loy
2024Adaptive deep spiking neural network with global-local learning via balanced excitatory and inhibitory mechanism.
Tingting Jiang, Qi Xu, Xuming Ran, Jiangrong Shen, Pan Lv, Qiang Zhang, Gang Pan
2024Addressing Loss of Plasticity and Catastrophic Forgetting in Continual Learning.
Mohamed Elsayed, A. Rupam Mahmood
2024Addressing Signal Delay in Deep Reinforcement Learning.
William Wei Wang, Dongqi Han, Xufang Luo, Dongsheng Li
2024AdjointDPM: Adjoint Sensitivity Method for Gradient Backpropagation of Diffusion Probabilistic Models.
Jiachun Pan, Jun Hao Liew, Vincent Y. F. Tan, Jiashi Feng, Hanshu Yan
2024Advancing Pose-Guided Image Synthesis with Progressive Conditional Diffusion Models.
Fei Shen, Hu Ye, Jun Zhang, Cong Wang, Xiao Han, Yang Wei
2024Advancing the Lower Bounds: an Accelerated, Stochastic, Second-order Method with Optimal Adaptation to Inexactness.
Artem Agafonov, Dmitry Kamzolov, Alexander V. Gasnikov, Ali Kavis, Kimon Antonakopoulos, Volkan Cevher, Martin Takác
2024Adversarial Adaptive Sampling: Unify PINN and Optimal Transport for the Approximation of PDEs.
Kejun Tang, Jiayu Zhai, Xiaoliang Wan, Chao Yang
2024Adversarial Attacks on Fairness of Graph Neural Networks.
Binchi Zhang, Yushun Dong, Chen Chen, Yada Zhu, Minnan Luo, Jundong Li
2024Adversarial AutoMixup.
Huafeng Qin, Xin Jin, Yun Jiang, Mounîm A. El-Yacoubi, Xinbo Gao
2024Adversarial Causal Bayesian Optimization.
Scott Sussex, Pier Giuseppe Sessa, Anastasia Makarova, Andreas Krause
2024Adversarial Feature Map Pruning for Backdoor.
Dong Huang, Qingwen Bu
2024Adversarial Imitation Learning via Boosting.
Jonathan D. Chang, Dhruv Sreenivas, Yingbing Huang, Kianté Brantley, Wen Sun
2024Adversarial Supervision Makes Layout-to-Image Diffusion Models Thrive.
Yumeng Li, Margret Keuper, Dan Zhang, Anna Khoreva
2024Adversarial Training Should Be Cast as a Non-Zero-Sum Game.
Alexander Robey, Fabian Latorre, George J. Pappas, Hamed Hassani, Volkan Cevher
2024Adversarial Training on Purification (AToP): Advancing Both Robustness and Generalization.
Guang Lin, Chao Li, Jianhai Zhang, Toshihisa Tanaka, Qibin Zhao
2024AffineQuant: Affine Transformation Quantization for Large Language Models.
Yuexiao Ma, Huixia Li, Xiawu Zheng, Feng Ling, Xuefeng Xiao, Rui Wang, Shilei Wen, Fei Chao, Rongrong Ji
2024AgentBench: Evaluating LLMs as Agents.
Xiao Liu, Hao Yu, Hanchen Zhang, Yifan Xu, Xuanyu Lei, Hanyu Lai, Yu Gu, Hangliang Ding, Kaiwen Men, Kejuan Yang, Shudan Zhang, Xiang Deng, Aohan Zeng, Zhengxiao Du, Chenhui Zhang, Sheng Shen, Tianjun Zhang, Yu Su, Huan Sun, Minlie Huang, Yuxiao Dong, Jie Tang
2024AgentVerse: Facilitating Multi-Agent Collaboration and Exploring Emergent Behaviors.
Weize Chen, Yusheng Su, Jingwei Zuo, Cheng Yang, Chenfei Yuan, Chi-Min Chan, Heyang Yu, Yaxi Lu, Yi-Hsin Hung, Chen Qian, Yujia Qin, Xin Cong, Ruobing Xie, Zhiyuan Liu, Maosong Sun, Jie Zhou
2024AirPhyNet: Harnessing Physics-Guided Neural Networks for Air Quality Prediction.
Kethmi Hirushini Hettige, Jiahao Ji, Shili Xiang, Cheng Long, Gao Cong, Jingyuan Wang
2024Algorithms for Caching and MTS with reduced number of predictions.
Karim Abdel Sadek, Marek Eliás
2024Alice Benchmarks: Connecting Real World Re-Identification with the Synthetic.
Xiaoxiao Sun, Yue Yao, Shengjin Wang, Hongdong Li, Liang Zheng
2024Align With Purpose: Optimize Desired Properties in CTC Models with a General Plug-and-Play Framework.
Eliya Segev, Maya Alroy, Ronen Katsir, Noam Wies, Ayana Shenhav, Yael Ben-Oren, David Zar, Oren Tadmor, Jacob Bitterman, Amnon Shashua, Tal Rosenwein
2024AlignDiff: Aligning Diverse Human Preferences via Behavior-Customisable Diffusion Model.
Zibin Dong, Yifu Yuan, Jianye Hao, Fei Ni, Yao Mu, Yan Zheng, Yujing Hu, Tangjie Lv, Changjie Fan, Zhipeng Hu
2024Aligning Relational Learning with Lipschitz Fairness.
Yaning Jia, Chunhui Zhang, Soroush Vosoughi
2024Alleviating Exposure Bias in Diffusion Models through Sampling with Shifted Time Steps.
Mingxiao Li, Tingyu Qu, Ruicong Yao, Wei Sun, Marie-Francine Moens
2024AlpaGasus: Training a Better Alpaca with Fewer Data.
Lichang Chen, Shiyang Li, Jun Yan, Hai Wang, Kalpa Gunaratna, Vikas Yadav, Zheng Tang, Vijay Srinivasan, Tianyi Zhou, Heng Huang, Hongxia Jin
2024Alt-Text with Context: Improving Accessibility for Images on Twitter.
Nikita Srivatsan, Sofía Samaniego, Omar Florez, Taylor Berg-Kirkpatrick
2024Amortized Network Intervention to Steer the Excitatory Point Processes.
Zitao Song, Wendi Ren, Shuang Li
2024AmortizedPeriod: Attention-based Amortized Inference for Periodicity Identification.
Hang Yu, Cong Liao, Ruolan Liu, Jianguo Li, Yun Hu, Xinzhe Wang
2024Amortizing intractable inference in large language models.
Edward J. Hu, Moksh Jain, Eric Elmoznino, Younesse Kaddar, Guillaume Lajoie, Yoshua Bengio, Nikolay Malkin
2024An Agnostic View on the Cost of Overfitting in (Kernel) Ridge Regression.
Lijia Zhou, James B. Simon, Gal Vardi, Nathan Srebro
2024An Analytical Solution to Gauss-Newton Loss for Direct Image Alignment.
Sergei Solonets, Daniil Sinitsyn, Lukas von Stumberg, Nikita Araslanov, Daniel Cremers
2024An Efficient Membership Inference Attack for the Diffusion Model by Proximal Initialization.
Fei Kong, Jinhao Duan, Ruipeng Ma, Heng Tao Shen, Xiaoshuang Shi, Xiaofeng Zhu, Kaidi Xu
2024An Efficient Tester-Learner for Halfspaces.
Aravind Gollakota, Adam R. Klivans, Konstantinos Stavropoulos, Arsen Vasilyan
2024An Emulator for Fine-tuning Large Language Models using Small Language Models.
Eric Mitchell, Rafael Rafailov, Archit Sharma, Chelsea Finn, Christopher D. Manning
2024An Extensible Framework for Open Heterogeneous Collaborative Perception.
Yifan Lu, Yue Hu, Yiqi Zhong, Dequan Wang, Yanfeng Wang, Siheng Chen
2024An Image Is Worth 1000 Lies: Transferability of Adversarial Images across Prompts on Vision-Language Models.
Haochen Luo, Jindong Gu, Fengyuan Liu, Philip Torr
2024An Intuitive Multi-Frequency Feature Representation for SO(3)-Equivariant Networks.
Dongwon Son, Jaehyung Kim, Sanghyeon Son, Beomjoon Kim
2024An Investigation of Representation and Allocation Harms in Contrastive Learning.
Subha Maity, Mayank Agarwal, Mikhail Yurochkin, Yuekai Sun
2024An LLM can Fool Itself: A Prompt-Based Adversarial Attack.
Xilie Xu, Keyi Kong, Ning Liu, Lizhen Cui, Di Wang, Jingfeng Zhang, Mohan S. Kankanhalli
2024An Unforgeable Publicly Verifiable Watermark for Large Language Models.
Aiwei Liu, Leyi Pan, Xuming Hu, Shuang Li, Lijie Wen, Irwin King, Philip S. Yu
2024An improved analysis of per-sample and per-update clipping in federated learning.
Bo Li, Xiaowen Jiang, Mikkel N. Schmidt, Tommy Sonne Alstrøm, Sebastian U. Stich
2024An interpretable error correction method for enhancing code-to-code translation.
Min Xue, Artur Andrzejak, Marla Leuther
2024An operator preconditioning perspective on training in physics-informed machine learning.
Tim De Ryck, Florent Bonnet, Siddhartha Mishra, Emmanuel de Bézenac
2024Analysis of Learning a Flow-based Generative Model from Limited Sample Complexity.
Hugo Cui, Florent Krzakala, Eric Vanden-Eijnden, Lenka Zdeborová
2024Analyzing Feed-Forward Blocks in Transformers through the Lens of Attention Maps.
Goro Kobayashi, Tatsuki Kuribayashi, Sho Yokoi, Kentaro Inui
2024Analyzing and Improving Optimal-Transport-based Adversarial Networks.
Jaemoo Choi, Jaewoong Choi, Myungjoo Kang
2024Analyzing and Mitigating Object Hallucination in Large Vision-Language Models.
Yiyang Zhou, Chenhang Cui, Jaehong Yoon, Linjun Zhang, Zhun Deng, Chelsea Finn, Mohit Bansal, Huaxiu Yao
2024AnimateDiff: Animate Your Personalized Text-to-Image Diffusion Models without Specific Tuning.
Yuwei Guo, Ceyuan Yang, Anyi Rao, Zhengyang Liang, Yaohui Wang, Yu Qiao, Maneesh Agrawala, Dahua Lin, Bo Dai
2024Annealing Self-Distillation Rectification Improves Adversarial Training.
Yu-Yu Wu, Hung-Jui Wang, Shang-Tse Chen
2024AnomalyCLIP: Object-agnostic Prompt Learning for Zero-shot Anomaly Detection.
Qihang Zhou, Guansong Pang, Yu Tian, Shibo He, Jiming Chen
2024AntGPT: Can Large Language Models Help Long-term Action Anticipation from Videos?
Qi Zhao, Shijie Wang, Ce Zhang, Changcheng Fu, Minh Quan Do, Nakul Agarwal, Kwonjoon Lee, Chen Sun
2024AnyText: Multilingual Visual Text Generation and Editing.
Yuxiang Tuo, Wangmeng Xiang, Jun-Yan He, Yifeng Geng, Xuansong Xie
2024Approximately Piecewise E(3) Equivariant Point Networks.
Matan Atzmon, Jiahui Huang, Francis Williams, Or Litany
2024Approximating Nash Equilibria in Normal-Form Games via Stochastic Optimization.
Ian Gemp, Luke Marris, Georgios Piliouras
2024ArchLock: Locking DNN Transferability at the Architecture Level with a Zero-Cost Binary Predictor.
Tong Zhou, Shaolei Ren, Xiaolin Xu
2024Are Bert Family Good Instruction Followers? A Study on Their Potential And Limitations.
Yisheng Xiao, Juntao Li, Zechen Sun, Zechang Li, Qingrong Xia, Xinyu Duan, Zhefeng Wang, Min Zhang
2024Are Human-generated Demonstrations Necessary for In-context Learning?
Rui Li, Guoyin Wang, Jiwei Li
2024Are Models Biased on Text without Gender-related Language?
Catarina G. Belém, Preethi Seshadri, Yasaman Razeghi, Sameer Singh
2024Are Transformers with One Layer Self-Attention Using Low-Rank Weight Matrices Universal Approximators?
Tokio Kajitsuka, Issei Sato
2024Assessing Uncertainty in Similarity Scoring: Performance & Fairness in Face Recognition.
Jean-Rémy Conti, Stéphan Clémençon
2024Asymptotically Free Sketched Ridge Ensembles: Risks, Cross-Validation, and Tuning.
Pratik Patil, Daniel LeJeune
2024At Which Training Stage Does Code Data Help LLMs Reasoning?
Yingwei Ma, Yue Liu, Yue Yu, Yuanliang Zhang, Yu Jiang, Changjian Wang, Shanshan Li
2024AttEXplore: Attribution for Explanation with model parameters eXploration.
Zhiyu Zhu, Huaming Chen, Jiayu Zhang, Xinyi Wang, Zhibo Jin, Jason Xue, Flora D. Salim
2024Attention Satisfies: A Constraint-Satisfaction Lens on Factual Errors of Language Models.
Mert Yüksekgönül, Varun Chandrasekaran, Erik Jones, Suriya Gunasekar, Ranjita Naik, Hamid Palangi, Ece Kamar, Besmira Nushi
2024Attention-Guided Contrastive Role Representations for Multi-agent Reinforcement Learning.
Zican Hu, Zongzhang Zhang, Huaxiong Li, Chunlin Chen, Hongyu Ding, Zhi Wang
2024Attention-based Iterative Decomposition for Tensor Product Representation.
Taewon Park, Inchul Choi, Minho Lee
2024AuG-KD: Anchor-Based Mixup Generation for Out-of-Domain Knowledge Distillation.
Zihao Tang, Zheqi Lv, Shengyu Zhang, Yifan Zhou, Xinyu Duan, Fei Wu, Kun Kuang
2024Augmented Bayesian Policy Search.
Mahdi Kallel, Debabrota Basu, Riad Akrour, Carlo D'Eramo
2024Augmenting Transformers with Recursively Composed Multi-grained Representations.
Xiang Hu, Qingyang Zhu, Kewei Tu, Wei Wu
2024AutoCast++: Enhancing World Event Prediction with Zero-shot Ranking-based Context Retrieval.
Qi Yan, Raihan Seraj, Jiawei He, Lili Meng, Tristan Sylvain
2024AutoChunk: Automated Activation Chunk for Memory-Efficient Deep Learning Inference.
Xuanlei Zhao, Shenggan Cheng, Guangyang Lu, Haotian Zhou, Bin Jia, Yang You
2024AutoDAN: Generating Stealthy Jailbreak Prompts on Aligned Large Language Models.
Xiaogeng Liu, Nan Xu, Muhao Chen, Chaowei Xiao
2024AutoLoRa: An Automated Robust Fine-Tuning Framework.
Xilie Xu, Jingfeng Zhang, Mohan S. Kankanhalli
2024AutoVP: An Automated Visual Prompting Framework and Benchmark.
Hsi-Ai Tsao, Lei Hsiung, Pin-Yu Chen, Si Liu, Tsung-Yi Ho
2024AutomaTikZ: Text-Guided Synthesis of Scientific Vector Graphics with TikZ.
Jonas Belouadi, Anne Lauscher, Steffen Eger
2024Automatic Functional Differentiation in JAX.
Min Lin
2024Aux-NAS: Exploiting Auxiliary Labels with Negligibly Extra Inference Cost.
Yuan Gao, Weizhong Zhang, Wenhan Luo, Lin Ma, Jin-Gang Yu, Gui-Song Xia, Jiayi Ma
2024B-Coder: Value-Based Deep Reinforcement Learning for Program Synthesis.
Zishun Yu, Yunzhe Tao, Liyu Chen, Tao Sun, Hongxia Yang
2024BECLR: Batch Enhanced Contrastive Few-Shot Learning.
Stylianos Poulakakis-Daktylidis, Hadi Jamali Rad
2024BEND: Benchmarking DNA Language Models on Biologically Meaningful Tasks.
Frederikke Isa Marin, Felix Teufel, Marc Horlacher, Dennis Madsen, Dennis Pultz, Ole Winther, Wouter Boomsma
2024BENO: Boundary-embedded Neural Operators for Elliptic PDEs.
Haixin Wang, Jiaxin Li, Anubhav Dwivedi, Kentaro Hara, Tailin Wu
2024BESA: Pruning Large Language Models with Blockwise Parameter-Efficient Sparsity Allocation.
Peng Xu, Wenqi Shao, Mengzhao Chen, Shitao Tang, Kaipeng Zhang, Peng Gao, Fengwei An, Yu Qiao, Ping Luo
2024BTR: Binary Token Representations for Efficient Retrieval Augmented Language Models.
Qingqing Cao, Sewon Min, Yizhong Wang, Hannaneh Hajishirzi
2024BaDExpert: Extracting Backdoor Functionality for Accurate Backdoor Input Detection.
Tinghao Xie, Xiangyu Qi, Ping He, Yiming Li, Jiachen T. Wang, Prateek Mittal
2024Backdoor Contrastive Learning via Bi-level Trigger Optimization.
Weiyu Sun, Xinyu Zhang, Hao Lu, Ying-Cong Chen, Ting Wang, Jinghui Chen, Lu Lin
2024Backdoor Federated Learning by Poisoning Backdoor-Critical Layers.
Haomin Zhuang, Mingxian Yu, Hao Wang, Yang Hua, Jian Li, Xu Yuan
2024Backdoor Secrets Unveiled: Identifying Backdoor Data with Optimized Scaled Prediction Consistency.
Soumyadeep Pal, Yuguang Yao, Ren Wang, Bingquan Shen, Sijia Liu
2024BadChain: Backdoor Chain-of-Thought Prompting for Large Language Models.
Zhen Xiang, Fengqing Jiang, Zidi Xiong, Bhaskar Ramasubramanian, Radha Poovendran, Bo Li
2024BadEdit: Backdooring Large Language Models by Model Editing.
Yanzhou Li, Tianlin Li, Kangjie Chen, Jian Zhang, Shangqing Liu, Wenhan Wang, Tianwei Zhang, Yang Liu
2024Balancing Act: Constraining Disparate Impact in Sparse Models.
Meraj Hashemizadeh, Juan Ramirez, Rohan Sukumaran, Golnoosh Farnadi, Simon Lacoste-Julien, Jose Gallego-Posada
2024Bandits Meet Mechanism Design to Combat Clickbait in Online Recommendation.
Thomas Kleine Buening, Aadirupa Saha, Christos Dimitrakakis, Haifeng Xu
2024Bandits with Replenishable Knapsacks: the Best of both Worlds.
Martino Bernasconi, Matteo Castiglioni, Andrea Celli, Federico Fusco
2024BarLeRIa: An Efficient Tuning Framework for Referring Image Segmentation.
Yaoming Wang, Jin Li, Xiaopeng Zhang, Bowen Shi, Chenglin Li, Wenrui Dai, Hongkai Xiong, Qi Tian
2024Batch Calibration: Rethinking Calibration for In-Context Learning and Prompt Engineering.
Han Zhou, Xingchen Wan, Lev Proleev, Diana Mincu, Jilin Chen, Katherine A. Heller, Subhrajit Roy
2024Batch normalization is sufficient for universal function approximation in CNNs.
Rebekka Burkholz
2024BatchPrompt: Accomplish more with less.
Jianzhe Lin, Maurice Diesendruck, Liang Du, Robin Abraham
2024Batched Low-Rank Adaptation of Foundation Models.
Yeming Wen, Swarat Chaudhuri
2024BatteryML: An Open-source Platform for Machine Learning on Battery Degradation.
Han Zhang, Xiaofan Gui, Shun Zheng, Ziheng Lu, Yuqi Li, Jiang Bian
2024Bayes Conditional Distribution Estimation for Knowledge Distillation Based on Conditional Mutual Information.
Linfeng Ye, Shayan Mohajer Hamidi, Renhao Tan, En-Hui Yang
2024BayesDiff: Estimating Pixel-wise Uncertainty in Diffusion via Bayesian Inference.
Siqi Kou, Lei Gan, Dequan Wang, Chongxuan Li, Zhijie Deng
2024BayesPrompt: Prompting Large-Scale Pre-Trained Language Models on Few-shot Inference via Debiased Domain Abstraction.
Jiangmeng Li, Fei Song, Yifan Jin, Wenwen Qiang, Changwen Zheng, Fuchun Sun, Hui Xiong
2024Bayesian Bi-clustering of Neural Spiking Activity with Latent Structures.
Ganchao Wei
2024Bayesian Coreset Optimization for Personalized Federated Learning.
Prateek Chanda, Shrey Modi, Ganesh Ramakrishnan
2024Bayesian Low-rank Adaptation for Large Language Models.
Adam X. Yang, Maxime Robeyns, Xi Wang, Laurence Aitchison
2024Bayesian Neural Controlled Differential Equations for Treatment Effect Estimation.
Konstantin Hess, Valentyn Melnychuk, Dennis Frauen, Stefan Feuerriegel
2024Bayesian Optimization through Gaussian Cox Process Models for Spatio-temporal Data.
Yongsheng Mei, Mahdi Imani, Tian Lan
2024Be Aware of the Neighborhood Effect: Modeling Selection Bias under Interference.
Haoxuan Li, Chunyuan Zheng, Sihao Ding, Peng Wu, Zhi Geng, Fuli Feng, Xiangnan He
2024Be Careful What You Smooth For: Label Smoothing Can Be a Privacy Shield but Also a Catalyst for Model Inversion Attacks.
Lukas Struppek, Dominik Hintersdorf, Kristian Kersting
2024Beam Enumeration: Probabilistic Explainability For Sample Efficient Self-conditioned Molecular Design.
Jeff Guo, Philippe Schwaller
2024Beating Price of Anarchy and Gradient Descent without Regret in Potential Games.
Iosif Sakos, Stefanos Leonardos, Stelios Andrew Stavroulakis, Will Overman, Ioannis Panageas, Georgios Piliouras
2024Behaviour Distillation.
Andrei Lupu, Chris Lu, Jarek Liesen, Robert Tjarko Lange, Jakob Nicolaus Foerster
2024Belief-Enriched Pessimistic Q-Learning against Adversarial State Perturbations.
Xiaolin Sun, Zizhan Zheng
2024Bellman Optimal Stepsize Straightening of Flow-Matching Models.
Bao Nguyen, Binh Nguyen, Viet Anh Nguyen
2024Benchmarking Algorithms for Federated Domain Generalization.
Ruqi Bai, Saurabh Bagchi, David I. Inouye
2024Benchmarking and Improving Generator-Validator Consistency of Language Models.
Xiang Lisa Li, Vaishnavi Shrivastava, Siyan Li, Tatsunori Hashimoto, Percy Liang
2024Benign Oscillation of Stochastic Gradient Descent with Large Learning Rate.
Miao Lu, Beining Wu, Xiaodong Yang, Difan Zou
2024Benign Overfitting and Grokking in ReLU Networks for XOR Cluster Data.
Zhiwei Xu, Yutong Wang, Spencer Frei, Gal Vardi, Wei Hu
2024Bespoke Solvers for Generative Flow Models.
Neta Shaul, Juan C. Pérez, Ricky T. Q. Chen, Ali K. Thabet, Albert Pumarola, Yaron Lipman
2024Better Neural PDE Solvers Through Data-Free Mesh Movers.
Peiyan Hu, Yue Wang, Zhi-Ming Ma
2024Beyond Accuracy: Evaluating Self-Consistency of Code Large Language Models with IdentityChain.
Marcus J. Min, Yangruibo Ding, Luca Buratti, Saurabh Pujar, Gail E. Kaiser, Suman Jana, Baishakhi Ray
2024Beyond IID weights: sparse and low-rank deep Neural Networks are also Gaussian Processes.
Thiziri Nait Saada, Alireza Naderi, Jared Tanner
2024Beyond Imitation: Leveraging Fine-grained Quality Signals for Alignment.
Geyang Guo, Ranchi Zhao, Tianyi Tang, Xin Zhao, Ji-Rong Wen
2024Beyond Memorization: Violating Privacy via Inference with Large Language Models.
Robin Staab, Mark Vero, Mislav Balunovic, Martin T. Vechev
2024Beyond Reverse KL: Generalizing Direct Preference Optimization with Diverse Divergence Constraints.
Chaoqi Wang, Yibo Jiang, Chenghao Yang, Han Liu, Yuxin Chen
2024Beyond Spatio-Temporal Representations: Evolving Fourier Transform for Temporal Graphs.
Anson Bastos, Kuldeep Singh, Abhishek Nadgeri, Manish Singh, Toyotaro Suzumura
2024Beyond Stationarity: Convergence Analysis of Stochastic Softmax Policy Gradient Methods.
Sara Klein, Simon Weissmann, Leif Döring
2024Beyond Vanilla Variational Autoencoders: Detecting Posterior Collapse in Conditional and Hierarchical Variational Autoencoders.
Hien Dang, Tho Tran Huu, Tan Minh Nguyen, Nhat Ho
2024Beyond Weisfeiler-Lehman: A Quantitative Framework for GNN Expressiveness.
Bohang Zhang, Jingchu Gai, Yiheng Du, Qiwei Ye, Di He, Liwei Wang
2024Beyond Worst-case Attacks: Robust RL with Adaptive Defense via Non-dominated Policies.
Xiangyu Liu, Chenghao Deng, Yanchao Sun, Yongyuan Liang, Furong Huang
2024Beyond task performance: evaluating and reducing the flaws of large multimodal models with in-context-learning.
Mustafa Shukor, Alexandre Ramé, Corentin Dancette, Matthieu Cord
2024Bias Runs Deep: Implicit Reasoning Biases in Persona-Assigned LLMs.
Shashank Gupta, Vaishnavi Shrivastava, Ameet Deshpande, Ashwin Kalyan, Peter Clark, Ashish Sabharwal, Tushar Khot
2024Biased Temporal Convolution Graph Network for Time Series Forecasting with Missing Values.
Xiaodan Chen, Xiucheng Li, Bo Liu, Zhijun Li
2024Bidirectional Temporal Diffusion Model for Temporally Consistent Human Animation.
Tserendorj Adiya, Jae Shin Yoon, Jungeun Lee, Sanghun Kim, Hwasup Lim
2024Bilevel Optimization under Unbounded Smoothness: A New Algorithm and Convergence Analysis.
Jie Hao, Xiaochuan Gong, Mingrui Liu
2024BioBridge: Bridging Biomedical Foundation Models via Knowledge Graphs.
Zifeng Wang, Zichen Wang, Balasubramaniam Srinivasan, Vassilis N. Ioannidis, Huzefa Rangwala, Rishita Anubhai
2024Blending Imitation and Reinforcement Learning for Robust Policy Improvement.
Xuefeng Liu, Takuma Yoneda, Rick Stevens, Matthew R. Walter, Yuxin Chen
2024Bongard-OpenWorld: Few-Shot Reasoning for Free-form Visual Concepts in the Real World.
Rujie Wu, Xiaojian Ma, Zhenliang Zhang, Wei Wang, Qing Li, Song-Chun Zhu, Yizhou Wang
2024BooookScore: A systematic exploration of book-length summarization in the era of LLMs.
Yapei Chang, Kyle Lo, Tanya Goyal, Mohit Iyyer
2024Boosting Graph Anomaly Detection with Adaptive Message Passing.
Jingyan Chen, Guanghui Zhu, Chunfeng Yuan, Yihua Huang
2024Boosting Vanilla Lightweight Vision Transformers via Re-parameterization.
Zhentao Tan, Xiaodan Li, Yue Wu, Qi Chu, Le Lu, Nenghai Yu, Jieping Ye
2024Boosting of Thoughts: Trial-and-Error Problem Solving with Large Language Models.
Sijia Chen, Baochun Li, Di Niu
2024Boosting the Adversarial Robustness of Graph Neural Networks: An OOD Perspective.
Kuan Li, Yiwen Chen, Yang Liu, Jin Wang, Qing He, Minhao Cheng, Xiang Ao
2024Bootstrapping Variational Information Pursuit with Large Language and Vision Models for Interpretable Image Classification.
Aditya Chattopadhyay, Kwan Ho Ryan Chan, René Vidal
2024Boundary Denoising for Video Activity Localization.
Mengmeng Xu, Mattia Soldan, Jialin Gao, Shuming Liu, Juan-Manuel Pérez-Rúa, Bernard Ghanem
2024Bounding Box Stability against Feature Dropout Reflects Detector Generalization across Environments.
Yang Yang, Wenhai Wang, Zhe Chen, Jifeng Dai, Liang Zheng
2024Bounding the Expected Robustness of Graph Neural Networks Subject to Node Feature Attacks.
Yassine Abbahaddou, Sofiane Ennadir, Johannes F. Lutzeyer, Michalis Vazirgiannis, Henrik Boström
2024Bounds on Representation-Induced Confounding Bias for Treatment Effect Estimation.
Valentyn Melnychuk, Dennis Frauen, Stefan Feuerriegel
2024Brain decoding: toward real-time reconstruction of visual perception.
Yohann Benchetrit, Hubert J. Banville, Jean-Remi King
2024BrainLM: A foundation model for brain activity recordings.
Josue Ortega Caro, Antonio Henrique de Oliveira Fonseca, Syed Asad Rizvi, Matteo Rosati, Christopher L. Averill, James L. Cross, Prateek Mittal, Emanuele Zappala, Rahul Madhav Dhodapkar, Chadi Abdallah, David van Dijk
2024BrainSCUBA: Fine-Grained Natural Language Captions of Visual Cortex Selectivity.
Andrew F. Luo, Margaret M. Henderson, Michael J. Tarr, Leila Wehbe
2024Branch-GAN: Improving Text Generation with (not so) Large Language Models.
Fredrik Carlsson, Johan Broberg, Erik Hillbom, Magnus Sahlgren, Joakim Nivre
2024Breaking Physical and Linguistic Borders: Multilingual Federated Prompt Tuning for Low-Resource Languages.
Wanru Zhao, Yihong Chen, Royson Lee, Xinchi Qiu, Yan Gao, Hongxiang Fan, Nicholas Donald Lane
2024Bridging Neural and Symbolic Representations with Transitional Dictionary Learning.
Junyan Cheng, Peter Chin
2024Bridging State and History Representations: Understanding Self-Predictive RL.
Tianwei Ni, Benjamin Eysenbach, Erfan Seyedsalehi, Michel Ma, Clement Gehring, Aditya Mahajan, Pierre-Luc Bacon
2024Bridging Vision and Language Spaces with Assignment Prediction.
Jungin Park, Jiyoung Lee, Kwanghoon Sohn
2024BroGNet: Momentum-Conserving Graph Neural Stochastic Differential Equation for Learning Brownian Dynamics.
Suresh Bishnoi, Jayadeva, Sayan Ranu, N. M. Anoop Krishnan
2024Brusleattack: a Query-Efficient Score- based Black-Box Sparse Adversarial Attack.
Viet Quoc Vo, Ehsan Abbasnejad, Damith Ranasinghe
2024Building Cooperative Embodied Agents Modularly with Large Language Models.
Hongxin Zhang, Weihua Du, Jiaming Shan, Qinhong Zhou, Yilun Du, Joshua B. Tenenbaum, Tianmin Shu, Chuang Gan
2024Butterfly Effects of SGD Noise: Error Amplification in Behavior Cloning and Autoregression.
Adam Block, Dylan J. Foster, Akshay Krishnamurthy, Max Simchowitz, Cyril Zhang
2024Byzantine Robust Cooperative Multi-Agent Reinforcement Learning as a Bayesian Game.
Simin Li, Jun Guo, Jingqiao Xiu, Ruixiao Xu, Xin Yu, Jiakai Wang, Aishan Liu, Yaodong Yang, Xianglong Liu
2024C-TPT: Calibrated Test-Time Prompt Tuning for Vision-Language Models via Text Feature Dispersion.
Hee Suk Yoon, Eunseop Yoon, Joshua Tian Jin Tee, Mark A. Hasegawa-Johnson, Yingzhen Li, Chang D. Yoo
2024CABINET: Content Relevance-based Noise Reduction for Table Question Answering.
Sohan Patnaik, Heril Changwal, Milan Aggarwal, Sumit Bhatia, Yaman Kumar, Balaji Krishnamurthy
2024CADS: Unleashing the Diversity of Diffusion Models through Condition-Annealed Sampling.
Seyedmorteza Sadat, Jakob Buhmann, Derek Bradley, Otmar Hilliges, Romann M. Weber
2024CALICO: Self-Supervised Camera-LiDAR Contrastive Pre-training for BEV Perception.
Jiachen Sun, Haizhong Zheng, Qingzhao Zhang, Atul Prakash, Zhuoqing Mao, Chaowei Xiao
2024CAMBranch: Contrastive Learning with Augmented MILPs for Branching.
Jiacheng Lin, Meng Xu, Zhihua Xiong, Huangang Wang
2024CAMIL: Context-Aware Multiple Instance Learning for Cancer Detection and Subtyping in Whole Slide Images.
Olga Fourkioti, Matt De Vries, Chris Bakal
2024CARD: Channel Aligned Robust Blend Transformer for Time Series Forecasting.
Xue Wang, Tian Zhou, Qingsong Wen, Jinyang Gao, Bolin Ding, Rong Jin
2024CAS: A Probability-Based Approach for Universal Condition Alignment Score.
Chunsan Hong, Byunghee Cha, Tae-Hyun Oh
2024CCIL: Continuity-Based Data Augmentation for Corrective Imitation Learning.
Liyiming Ke, Yunchu Zhang, Abhay Deshpande, Siddhartha S. Srinivasa, Abhishek Gupta
2024CIFAR-10-Warehouse: Broad and More Realistic Testbeds in Model Generalization Analysis.
Xiaoxiao Sun, Xingjian Leng, Zijian Wang, Yang Yang, Zi Huang, Liang Zheng
2024CLAP: Collaborative Adaptation for Patchwork Learning.
Sen Cui, Abudukelimu Wuerkaixi, Weishen Pan, Jian Liang, Lei Fang, Changshui Zhang, Fei Wang
2024CLEX: Continuous Length Extrapolation for Large Language Models.
Guanzheng Chen, Xin Li, Zaiqiao Meng, Shangsong Liang, Lidong Bing
2024CLIP the Bias: How Useful is Balancing Data in Multimodal Learning?
Ibrahim Alabdulmohsin, Xiao Wang, Andreas Peter Steiner, Priya Goyal, Alexander D'Amour, Xiaohua Zhai
2024CLIP-MUSED: CLIP-Guided Multi-Subject Visual Neural Information Semantic Decoding.
Qiongyi Zhou, Changde Du, Shengpei Wang, Huiguang He
2024CLIPSelf: Vision Transformer Distills Itself for Open-Vocabulary Dense Prediction.
Size Wu, Wenwei Zhang, Lumin Xu, Sheng Jin, Xiangtai Li, Wentao Liu, Chen Change Loy
2024CLaM-TTS: Improving Neural Codec Language Model for Zero-Shot Text-to-Speech.
Jaehyeon Kim, Keon Lee, Seungjun Chung, Jaewoong Cho
2024CNN Kernels Can Be the Best Shapelets.
Eric Qu, Yansen Wang, Xufang Luo, Wenqiang He, Kan Ren, Dongsheng Li
2024CO2: Efficient Distributed Training with Full Communication-Computation Overlap.
Weigao Sun, Zhen Qin, Weixuan Sun, Shidi Li, Dong Li, Xuyang Shen, Yu Qiao, Yiran Zhong
2024COCO-Periph: Bridging the Gap Between Human and Machine Perception in the Periphery.
Anne Harrington, Vasha DuTell, Mark Hamilton, Ayush Tewari, Simon Stent, William T. Freeman, Ruth Rosenholtz
2024COLEP: Certifiably Robust Learning-Reasoning Conformal Prediction via Probabilistic Circuits.
Mintong Kang, Nezihe Merve Gürel, Linyi Li, Bo Li
2024COLLIE: Systematic Construction of Constrained Text Generation Tasks.
Shunyu Yao, Howard Chen, Austin W. Hanjie, Runzhe Yang, Karthik R. Narasimhan
2024COPlanner: Plan to Roll Out Conservatively but to Explore Optimistically for Model-Based RL.
Xiyao Wang, Ruijie Zheng, Yanchao Sun, Ruonan Jia, Wichayaporn Wongkamjan, Huazhe Xu, Furong Huang
2024CORN: Contact-based Object Representation for Nonprehensile Manipulation of General Unseen Objects.
Yoonyoung Cho, Junhyek Han, Yoontae Cho, Beomjoon Kim
2024COSA: Concatenated Sample Pretrained Vision-Language Foundation Model.
Sihan Chen, Xingjian He, Handong Li, Xiaojie Jin, Jiashi Feng, Jing Liu
2024CPPO: Continual Learning for Reinforcement Learning with Human Feedback.
Han Zhang, Yu Lei, Lin Gui, Min Yang, Yulan He, Hui Wang, Ruifeng Xu
2024CRAFT: Customizing LLMs by Creating and Retrieving from Specialized Toolsets.
Lifan Yuan, Yangyi Chen, Xingyao Wang, Yi Fung, Hao Peng, Heng Ji
2024CRITIC: Large Language Models Can Self-Correct with Tool-Interactive Critiquing.
Zhibin Gou, Zhihong Shao, Yeyun Gong, Yelong Shen, Yujiu Yang, Nan Duan, Weizhu Chen
2024Cameras as Rays: Pose Estimation via Ray Diffusion.
Jason Y. Zhang, Amy Lin, Moneish Kumar, Tzu-Hsuan Yang, Deva Ramanan, Shubham Tulsiani
2024Can LLM-Generated Misinformation Be Detected?
Canyu Chen, Kai Shu
2024Can LLMs Express Their Uncertainty? An Empirical Evaluation of Confidence Elicitation in LLMs.
Miao Xiong, Zhiyuan Hu, Xinyang Lu, Yifei Li, Jie Fu, Junxian He, Bryan Hooi
2024Can LLMs Keep a Secret? Testing Privacy Implications of Language Models via Contextual Integrity Theory.
Niloofar Mireshghallah, Hyunwoo Kim, Xuhui Zhou, Yulia Tsvetkov, Maarten Sap, Reza Shokri, Yejin Choi
2024Can Large Language Models Infer Causation from Correlation?
Zhijing Jin, Jiarui Liu, Zhiheng Lyu, Spencer Poff, Mrinmaya Sachan, Rada Mihalcea, Mona T. Diab, Bernhard Schölkopf
2024Can Sensitive Information Be Deleted From LLMs? Objectives for Defending Against Extraction Attacks.
Vaidehi Patil, Peter Hase, Mohit Bansal
2024Can Transformers Capture Spatial Relations between Objects?
Chuan Wen, Dinesh Jayaraman, Yang Gao
2024Can We Evaluate Domain Adaptation Models Without Target-Domain Labels?
Jianfei Yang, Hanjie Qian, Yuecong Xu, Kai Wang, Lihua Xie
2024Can we get the best of both Binary Neural Networks and Spiking Neural Networks for Efficient Computer Vision?
Gourav Datta, Zeyu Liu, Peter Anthony Beerel
2024Candidate Label Set Pruning: A Data-centric Perspective for Deep Partial-label Learning.
Shuo He, Chaojie Wang, Guowu Yang, Lei Feng
2024Cascading Reinforcement Learning.
Yihan Du, R. Srikant, Wei Chen
2024Catastrophic Jailbreak of Open-source LLMs via Exploiting Generation.
Yangsibo Huang, Samyak Gupta, Mengzhou Xia, Kai Li, Danqi Chen
2024Cauchy-Schwarz Divergence Information Bottleneck for Regression.
Shujian Yu, Xi Yu, Sigurd Løkse, Robert Jenssen, José C. Príncipe
2024Causal Fairness under Unobserved Confounding: A Neural Sensitivity Framework.
Maresa Schröder, Dennis Frauen, Stefan Feuerriegel
2024Causal Inference with Conditional Front-Door Adjustment and Identifiable Variational Autoencoder.
Ziqi Xu, Debo Cheng, Jiuyong Li, Jixue Liu, Lin Liu, Kui Yu
2024Causal Modelling Agents: Causal Graph Discovery through Synergising Metadata- and Data-driven Reasoning.
Ahmed Abdulaal, Adamos Hadjivasiliou, Nina Montaña Brown, Tiantian He, Ayodeji Ijishakin, Ivana Drobnjak, Daniel C. Castro, Daniel C. Alexander
2024Causal Structure Recovery with Latent Variables under Milder Distributional and Graphical Assumptions.
Xiu-Chuan Li, Kun Zhang, Tongliang Liu
2024Causal-StoNet: Causal Inference for High-Dimensional Complex Data.
Yaxin Fang, Faming Liang
2024CausalLM is not optimal for in-context learning.
Nan Ding, Tomer Levinboim, Jialin Wu, Sebastian Goodman, Radu Soricut
2024CausalTime: Realistically Generated Time-series for Benchmarking of Causal Discovery.
Yuxiao Cheng, Ziqian Wang, Tingxiong Xiao, Qin Zhong, Jinli Suo, Kunlun He
2024Causality-Inspired Spatial-Temporal Explanations for Dynamic Graph Neural Networks.
Kesen Zhao, Liang Zhang
2024Causally Aligned Curriculum Learning.
Mingxuan Li, Junzhe Zhang, Elias Bareinboim
2024CellPLM: Pre-training of Cell Language Model Beyond Single Cells.
Hongzhi Wen, Wenzhuo Tang, Xinnan Dai, Jiayuan Ding, Wei Jin, Yuying Xie, Jiliang Tang
2024Certified Adversarial Robustness for Rate Encoded Spiking Neural Networks.
Bhaskar Mukhoty, Hilal AlQuabeh, Giulia De Masi, Huan Xiong, Bin Gu
2024Chain of Hindsight aligns Language Models with Feedback.
Hao Liu, Carmelo Sferrazza, Pieter Abbeel
2024Chain of Log-Concave Markov Chains.
Saeed Saremi, Ji Won Park, Francis R. Bach
2024Chain of Thought Empowers Transformers to Solve Inherently Serial Problems.
Zhiyuan Liu, Hong Liu, Denny Zhou, Tengyu Ma
2024Chain-of-Experts: When LLMs Meet Complex Operations Research Problems.
Ziyang Xiao, Dongxiang Zhang, Yangjun Wu, Lilin Xu, Yuan Jessica Wang, Xiongwei Han, Xiaojin Fu, Tao Zhong, Jia Zeng, Mingli Song, Gang Chen
2024Chain-of-Knowledge: Grounding Large Language Models via Dynamic Knowledge Adapting over Heterogeneous Sources.
Xingxuan Li, Ruochen Zhao, Yew Ken Chia, Bosheng Ding, Shafiq Joty, Soujanya Poria, Lidong Bing
2024Chain-of-Table: Evolving Tables in the Reasoning Chain for Table Understanding.
Zilong Wang, Hao Zhang, Chun-Liang Li, Julian Martin Eisenschlos, Vincent Perot, Zifeng Wang, Lesly Miculicich, Yasuhisa Fujii, Jingbo Shang, Chen-Yu Lee, Tomas Pfister
2024Chameleon: Increasing Label-Only Membership Leakage with Adaptive Poisoning.
Harsh Chaudhari, Giorgio Severi, Alina Oprea, Jonathan R. Ullman
2024Channel Vision Transformers: An Image Is Worth 1 x 16 x 16 Words.
Yujia Bao, Srinivasan Sivanandan, Theofanis Karaletsos
2024ChatEval: Towards Better LLM-based Evaluators through Multi-Agent Debate.
Chi-Min Chan, Weize Chen, Yusheng Su, Jianxuan Yu, Wei Xue, Shanghang Zhang, Jie Fu, Zhiyuan Liu
2024Circuit Component Reuse Across Tasks in Transformer Language Models.
Jack Merullo, Carsten Eickhoff, Ellie Pavlick
2024CircuitNet 2.0: An Advanced Dataset for Promoting Machine Learning Innovations in Realistic Chip Design Environment.
Xun Jiang, Zhuomin Chai, Yuxiang Zhao, Yibo Lin, Runsheng Wang, Ru Huang
2024Circumventing Concept Erasure Methods For Text-To-Image Generative Models.
Minh Pham, Kelly O. Marshall, Niv Cohen, Govind Mittal, Chinmay Hegde
2024CivRealm: A Learning and Reasoning Odyssey in Civilization for Decision-Making Agents.
Siyuan Qi, Shuo Chen, Yexin Li, Xiangyu Kong, Junqi Wang, Bangcheng Yang, Pring Wong, Yifan Zhong, Xiaoyuan Zhang, Zhaowei Zhang, Nian Liu, Yaodong Yang, Song-Chun Zhu
2024Class Incremental Learning via Likelihood Ratio Based Task Prediction.
Haowei Lin, Yijia Shao, Weinan Qian, Ningxin Pan, Yiduo Guo, Bing Liu
2024Class Probability Matching with Calibrated Networks for Label Shift Adaption.
Hongwei Wen, Annika Betken, Hanyuan Hang
2024Classification with Conceptual Safeguards.
Hailey Joren, Charles T. Marx, Berk Ustun
2024Cleanba: A Reproducible and Efficient Distributed Reinforcement Learning Platform.
Shengyi Huang, Jiayi Weng, Rujikorn Charakorn, Min Lin, Zhongwen Xu, Santiago Ontañón
2024Clifford Group Equivariant Simplicial Message Passing Networks.
Cong Liu, David Ruhe, Floor Eijkelboom, Patrick Forré
2024ClimODE: Climate and Weather Forecasting with Physics-informed Neural ODEs.
Yogesh Verma, Markus Heinonen, Vikas Garg
2024Closing the Curious Case of Neural Text Degeneration.
Matthew Finlayson, John Hewitt, Alexander Koller, Swabha Swayamdipta, Ashish Sabharwal
2024Closing the Gap between TD Learning and Supervised Learning - A Generalisation Point of View.
Raj Ghugare, Matthieu Geist, Glen Berseth, Benjamin Eysenbach
2024CoBIT: A Contrastive Bi-directional Image-Text Generation Model.
Haoxuan You, Mandy Guo, Zhecan Wang, Kai-Wei Chang, Jason M. Baldridge, Jiahui Yu
2024CoLiDE: Concomitant Linear DAG Estimation.
Seyed Saman Saboksayr, Gonzalo Mateos, Mariano Tepper
2024CoRe-GD: A Hierarchical Framework for Scalable Graph Visualization with GNNs.
Florian Grötschla, Joël Mathys, Robert Veres, Roger Wattenhofer
2024CoT3DRef: Chain-of-Thoughts Data-Efficient 3D Visual Grounding.
Eslam Mohamed Bakr, Mohamed Ayman, Mahmoud Ahmed, Habib Slim, Mohamed Elhoseiny
2024CoVLM: Composing Visual Entities and Relationships in Large Language Models Via Communicative Decoding.
Junyan Li, Delin Chen, Yining Hong, Zhenfang Chen, Peihao Chen, Yikang Shen, Chuang Gan
2024Code Representation Learning at Scale.
Dejiao Zhang, Wasi Uddin Ahmad, Ming Tan, Hantian Ding, Ramesh Nallapati, Dan Roth, Xiaofei Ma, Bing Xiang
2024CodeChain: Towards Modular Code Generation Through Chain of Self-revisions with Representative Sub-modules.
Hung Le, Hailin Chen, Amrita Saha, Akash Gokul, Doyen Sahoo, Shafiq Joty
2024Coeditor: Leveraging Repo-level Diffs for Code Auto-editing.
Jiayi Wei, Greg Durrett, Isil Dillig
2024Combinatorial Bandits for Maximum Value Reward Function under Value-Index Feedback.
Yiliu Wang, Wei Chen, Milan Vojnovic
2024Combining Axes Preconditioners through Kronecker Approximation for Deep Learning.
Sai Surya Duvvuri, Devvrit, Rohan Anil, Cho-Jui Hsieh, Inderjit S. Dhillon
2024Communication-Efficient Federated Non-Linear Bandit Optimization.
Chuanhao Li, Chong Liu, Yu-Xiang Wang
2024Communication-Efficient Gradient Descent-Accent Methods for Distributed Variational Inequalities: Unified Analysis and Local Updates.
Siqi Zhang, Sayantan Choudhury, Sebastian U. Stich, Nicolas Loizou
2024CompA: Addressing the Gap in Compositional Reasoning in Audio-Language Models.
Sreyan Ghosh, Ashish Seth, Sonal Kumar, Utkarsh Tyagi, Chandra Kiran Reddy Evuru, Ramaneswaran S., Sakshi Singh, Oriol Nieto, Ramani Duraiswami, Dinesh Manocha
2024Complete and Efficient Graph Transformers for Crystal Material Property Prediction.
Keqiang Yan, Cong Fu, Xiaofeng Qian, Xiaoning Qian, Shuiwang Ji
2024Complex priors and flexible inference in recurrent circuits with dendritic nonlinearities.
Benjamin Lyo, Cristina Savin
2024Compose and Conquer: Diffusion-Based 3D Depth Aware Composable Image Synthesis.
Jonghyun Lee, Hansam Cho, Young Joon Yoo, Seoung Bum Kim, Yonghyun Jeong
2024Composed Image Retrieval with Text Feedback via Multi-grained Uncertainty Regularization.
Yiyang Chen, Zhedong Zheng, Wei Ji, Leigang Qu, Tat-Seng Chua
2024Compositional Conservatism: A Transductive Approach in Offline Reinforcement Learning.
Yeda Song, Dongwook Lee, Gunhee Kim
2024Compositional Generative Inverse Design.
Tailin Wu, Takashi Maruyama, Long Wei, Tao Zhang, Yilun Du, Gianluca Iaccarino, Jure Leskovec
2024Compositional Preference Models for Aligning LMs.
Dongyoung Go, Tomasz Korbak, Germán Kruszewski, Jos Rozen, Marc Dymetman
2024Compressed Context Memory for Online Language Model Interaction.
Jang-Hyun Kim, Junyoung Yeom, Sangdoo Yun, Hyun Oh Song
2024Compressing LLMs: The Truth is Rarely Pure and Never Simple.
Ajay Kumar Jaiswal, Zhe Gan, Xianzhi Du, Bowen Zhang, Zhangyang Wang, Yinfei Yang
2024Compressing Latent Space via Least Volume.
Qiuyi Chen, Mark D. Fuge
2024ConR: Contrastive Regularizer for Deep Imbalanced Regression.
Mahsa Keramati, Lili Meng, R. David Evans
2024Concept Bottleneck Generative Models.
Aya Abdelsalam Ismail, Julius Adebayo, Héctor Corrada Bravo, Stephen Ra, Kyunghyun Cho
2024Conditional Information Bottleneck Approach for Time Series Imputation.
MinGyu Choi, Changhee Lee
2024Conditional Instrumental Variable Regression with Representation Learning for Causal Inference.
Debo Cheng, Ziqi Xu, Jiuyong Li, Lin Liu, Jixue Liu, Thuc Duy Le
2024Conditional Variational Diffusion Models.
Gabriel della Maggiora, Luis Alberto Croquevielle, Nikita Deshpande, Harry Horsley, Thomas Heinis, Artur Yakimovich
2024Confidence-aware Reward Optimization for Fine-tuning Text-to-Image Models.
Kyuyoung Kim, Jongheon Jeong, Minyong An, Mohammad Ghavamzadeh, Krishnamurthy Dj Dvijotham, Jinwoo Shin, Kimin Lee
2024Confidential-DPproof: Confidential Proof of Differentially Private Training.
Ali Shahin Shamsabadi, Gefei Tan, Tudor Cebere, Aurélien Bellet, Hamed Haddadi, Nicolas Papernot, Xiao Wang, Adrian Weller
2024Conformal Inductive Graph Neural Networks.
Soroush H. Zargarbashi, Aleksandar Bojchevski
2024Conformal Language Modeling.
Victor Quach, Adam Fisch, Tal Schuster, Adam Yala, Jae Ho Sohn, Tommi S. Jaakkola, Regina Barzilay
2024Conformal Prediction via Regression-as-Classification.
Etash Kumar Guha, Shlok Natarajan, Thomas Möllenhoff, Mohammad Emtiyaz Khan, Eugène Ndiaye
2024Conformal Risk Control.
Anastasios Nikolas Angelopoulos, Stephen Bates, Adam Fisch, Lihua Lei, Tal Schuster
2024Confronting Reward Model Overoptimization with Constrained RLHF.
Ted Moskovitz, Aaditya K. Singh, DJ Strouse, Tuomas Sandholm, Ruslan Salakhutdinov, Anca D. Dragan, Stephen Marcus McAleer
2024ConjNorm: Tractable Density Estimation for Out-of-Distribution Detection.
Bo Peng, Yadan Luo, Yonggang Zhang, Yixuan Li, Zhen Fang
2024Connect, Collapse, Corrupt: Learning Cross-Modal Tasks with Uni-Modal Data.
Yuhui Zhang, Elaine Sui, Serena Yeung
2024Connecting Large Language Models with Evolutionary Algorithms Yields Powerful Prompt Optimizers.
Qingyan Guo, Rui Wang, Junliang Guo, Bei Li, Kaitao Song, Xu Tan, Guoqing Liu, Jiang Bian, Yujiu Yang
2024Consciousness-Inspired Spatio-Temporal Abstractions for Better Generalization in Reinforcement Learning.
Harry Zhao, Safa Alver, Harm van Seijen, Romain Laroche, Doina Precup, Yoshua Bengio
2024Conserve-Update-Revise to Cure Generalization and Robustness Trade-off in Adversarial Training.
Shruthi Gowda, Bahram Zonooz, Elahe Arani
2024Consistency Models as a Rich and Efficient Policy Class for Reinforcement Learning.
Zihan Ding, Chi Jin
2024Consistency Training with Learnable Data Augmentation for Graph Anomaly Detection with Limited Supervision.
Nan Chen, Zemin Liu, Bryan Hooi, Bingsheng He, Rizal Fathony, Jun Hu, Jia Chen
2024Consistency Trajectory Models: Learning Probability Flow ODE Trajectory of Diffusion.
Dongjun Kim, Chieh-Hsin Lai, Wei-Hsiang Liao, Naoki Murata, Yuhta Takida, Toshimitsu Uesaka, Yutong He, Yuki Mitsufuji, Stefano Ermon
2024Consistency-guided Prompt Learning for Vision-Language Models.
Shuvendu Roy, Ali Etemad
2024Consistent Multi-Class Classification from Multiple Unlabeled Datasets.
Zixi Wei, Senlin Shu, Yuzhou Cao, Hongxin Wei, Bo An, Lei Feng
2024Consistent Video-to-Video Transfer Using Synthetic Dataset.
Jiaxin Cheng, Tianjun Xiao, Tong He
2024Consistent algorithms for multi-label classification with macro-at-k metrics.
Erik Schultheis, Wojciech Kotlowski, Marek Wydmuch, Rohit Babbar, Strom Borman, Krzysztof Dembczynski
2024Consistent4D: Consistent 360° Dynamic Object Generation from Monocular Video.
Yanqin Jiang, Li Zhang, Jin Gao, Weiming Hu, Yao Yao
2024Constrained Bi-Level Optimization: Proximal Lagrangian Value Function Approach and Hessian-free Algorithm.
Wei Yao, Chengming Yu, Shangzhi Zeng, Jin Zhang
2024Constrained Decoding for Cross-lingual Label Projection.
Duong Minh Le, Yang Chen, Alan Ritter, Wei Xu
2024Constraint-Free Structure Learning with Smooth Acyclic Orientations.
Riccardo Massidda, Francesco Landolfi, Martina Cinquini, Davide Bacciu
2024Constructing Adversarial Examples for Vertical Federated Learning: Optimal Client Corruption through Multi-Armed Bandit.
Duanyi Yao, Songze Li, Ye Xue, Jin Liu
2024Context is Environment.
Sharut Gupta, Stefanie Jegelka, David Lopez-Paz, Kartik Ahuja
2024Context-Aware Meta-Learning.
Christopher Fifty, Dennis Duan, Ronald G. Junkins, Ehsan Amid, Jure Leskovec, Christopher Ré, Sebastian Thrun
2024ContextRef: Evaluating Referenceless Metrics for Image Description Generation.
Elisa Kreiss, Eric Zelikman, Christopher Potts, Nick Haber
2024Contextual Bandits with Online Neural Regression.
Rohan Deb, Yikun Ban, Shiliang Zuo, Jingrui He, Arindam Banerjee
2024Continual Learning in the Presence of Spurious Correlations: Analyses and a Simple Baseline.
Donggyu Lee, Sangwon Jung, Taesup Moon
2024Continual Learning on a Diet: Learning from Sparsely Labeled Streams Under Constrained Computation.
Wenxuan Zhang, Youssef Mohamed, Bernard Ghanem, Philip Torr, Adel Bibi, Mohamed Elhoseiny
2024Continual Momentum Filtering on Parameter Space for Online Test-time Adaptation.
Jae-Hong Lee, Joon-Hyuk Chang
2024Continuous Field Reconstruction from Sparse Observations with Implicit Neural Networks.
Xihaier Luo, Wei Xu, Balu Nadiga, Yihui Ren, Shinjae Yoo
2024Continuous Invariance Learning.
Lin Yong, Fan Zhou, Lu Tan, Lintao Ma, Jianmeng Liu, Yansu He, Yuan Yuan, Yu Liu, James Y. Zhang, Yujiu Yang, Hao Wang
2024Continuous-Multiple Image Outpainting in One-Step via Positional Query and A Diffusion-based Approach.
Shaofeng Zhang, Jinfa Huang, Qiang Zhou, Zhibin Wang, Fan Wang, Jiebo Luo, Junchi Yan
2024Contrastive Difference Predictive Coding.
Chongyi Zheng, Ruslan Salakhutdinov, Benjamin Eysenbach
2024Contrastive Learning is Spectral Clustering on Similarity Graph.
Zhiquan Tan, Yifan Zhang, Jingqin Yang, Yang Yuan
2024Contrastive Preference Learning: Learning from Human Feedback without Reinforcement Learning.
Joey Hejna, Rafael Rafailov, Harshit Sikchi, Chelsea Finn, Scott Niekum, W. Bradley Knox, Dorsa Sadigh
2024ControlVideo: Training-free Controllable Text-to-video Generation.
Yabo Zhang, Yuxiang Wei, Dongsheng Jiang, Xiaopeng Zhang, Wangmeng Zuo, Qi Tian
2024Controlled Text Generation via Language Model Arithmetic.
Jasper Dekoninck, Marc Fischer, Luca Beurer-Kellner, Martin T. Vechev
2024Controlling Vision-Language Models for Multi-Task Image Restoration.
Ziwei Luo, Fredrik K. Gustafsson, Zheng Zhao, Jens Sjölund, Thomas B. Schön
2024Convergence of Bayesian Bilevel Optimization.
Shi Fu, Fengxiang He, Xinmei Tian, Dacheng Tao
2024Conversational Drug Editing Using Retrieval and Domain Feedback.
Shengchao Liu, Jiongxiao Wang, Yijin Yang, Chengpeng Wang, Ling Liu, Hongyu Guo, Chaowei Xiao
2024Convolution Meets LoRA: Parameter Efficient Finetuning for Segment Anything Model.
Zihan Zhong, ZhiQiang Tang, Tong He, Haoyang Fang, Chun Yuan
2024Convolutional Deep Kernel Machines.
Edward Milsom, Ben Anson, Laurence Aitchison
2024Coordinate-Aware Modulation for Neural Fields.
Joo Chan Lee, Daniel Rho, Seungtae Nam, Jong Hwan Ko, Eunbyung Park
2024Copilot4D: Learning Unsupervised World Models for Autonomous Driving via Discrete Diffusion.
Lunjun Zhang, Yuwen Xiong, Ze Yang, Sergio Casas, Rui Hu, Raquel Urtasun
2024Copula Conformal prediction for multi-step time series prediction.
Sophia Huiwen Sun, Rose Yu
2024Correlated Noise Provably Beats Independent Noise for Differentially Private Learning.
Christopher A. Choquette-Choo, Krishnamurthy Dj Dvijotham, Krishna Pillutla, Arun Ganesh, Thomas Steinke, Abhradeep Guha Thakurta
2024Counterfactual Density Estimation using Kernel Stein Discrepancies.
Diego Martinez-Taboada, Edward Kennedy
2024Counting Graph Substructures with Graph Neural Networks.
Charilaos I. Kanatsoulis, Alejandro Ribeiro
2024Course Correcting Koopman Representations.
Mahan Fathi, Clement Gehring, Jonathan Pilault, David Kanaa, Pierre-Luc Bacon, Ross Goroshin
2024CrIBo: Self-Supervised Learning via Cross-Image Object-Level Bootstrapping.
Tim Lebailly, Thomas Stegmüller, Behzad Bozorgtabar, Jean-Philippe Thiran, Tinne Tuytelaars
2024Critical Learning Periods Emerge Even in Deep Linear Networks.
Michael Kleinman, Alessandro Achille, Stefano Soatto
2024Cross-Modal Contextualized Diffusion Models for Text-Guided Visual Generation and Editing.
Ling Yang, Zhilong Zhang, Zhaochen Yu, Jingwei Liu, Minkai Xu, Stefano Ermon, Bin Cui
2024CrossLoco: Human Motion Driven Control of Legged Robots via Guided Unsupervised Reinforcement Learning.
Tianyu Li, Hyunyoung Jung, Matthew C. Gombolay, Yong Kwon Cho, Sehoon Ha
2024CrossQ: Batch Normalization in Deep Reinforcement Learning for Greater Sample Efficiency and Simplicity.
Aditya Bhatt, Daniel Palenicek, Boris Belousov, Max Argus, Artemij Amiranashvili, Thomas Brox, Jan Peters
2024Crystalformer: Infinitely Connected Attention for Periodic Structure Encoding.
Tatsunori Taniai, Ryo Igarashi, Yuta Suzuki, Naoya Chiba, Kotaro Saito, Yoshitaka Ushiku, Kanta Ono
2024Curiosity-driven Red-teaming for Large Language Models.
Zhang-Wei Hong, Idan Shenfeld, Tsun-Hsuan Wang, Yung-Sung Chuang, Aldo Pareja, James R. Glass, Akash Srivastava, Pulkit Agrawal
2024Curriculum reinforcement learning for quantum architecture search under hardware errors.
Yash J. Patel, Akash Kundu, Mateusz Ostaszewski, Xavier Bonet-Monroig, Vedran Dunjko, Onur Danaci
2024Customizable Combination of Parameter-Efficient Modules for Multi-Task Learning.
Haowen Wang, Tao Sun, Congyun Jin, Yingbo Wang, Yibo Fan, Yunqi Xu, Yuliang Du, Cong Fan
2024Cycle Consistency Driven Object Discovery.
Aniket Rajiv Didolkar, Anirudh Goyal, Yoshua Bengio
2024D2 Pruning: Message Passing for Balancing Diversity & Difficulty in Data Pruning.
Adyasha Maharana, Prateek Yadav, Mohit Bansal
2024DAFA: Distance-Aware Fair Adversarial Training.
Hyungyu Lee, Saehyung Lee, Hyemi Jang, Junsung Park, Ho Bae, Sungroh Yoon
2024DAM: Towards a Foundation Model for Forecasting.
Luke Nicholas Darlow, Qiwen Deng, Ahmed Hassan, Martin Asenov, Rajkarn Singh, Artjom Joosen, Adam Barker, Amos J. Storkey
2024DATS: Difficulty-Aware Task Sampler for Meta-Learning Physics-Informed Neural Networks.
Maryam Toloubidokhti, Yubo Ye, Ryan Missel, Xiajun Jiang, Nilesh Kumar, Ruby Shrestha, Linwei Wang
2024DDMI: Domain-agnostic Latent Diffusion Models for Synthesizing High-Quality Implicit Neural Representations.
Dogyun Park, Sihyeon Kim, Sojin Lee, Hyunwoo J. Kim
2024DFormer: Rethinking RGBD Representation Learning for Semantic Segmentation.
Bowen Yin, Xuying Zhang, Zhong-Yu Li, Li Liu, Ming-Ming Cheng, Qibin Hou
2024DIAGNOSIS: Detecting Unauthorized Data Usages in Text-to-image Diffusion Models.
Zhenting Wang, Chen Chen, Lingjuan Lyu, Dimitris N. Metaxas, Shiqing Ma
2024DIFFTACTILE: A Physics-based Differentiable Tactile Simulator for Contact-rich Robotic Manipulation.
Zilin Si, Gu Zhang, Qingwei Ben, Branden Romero, Zhou Xian, Chao Liu, Chuang Gan
2024DMBP: Diffusion model-based predictor for robust offline reinforcement learning against state observation perturbations.
Zhihe Yang, Yunjian Xu
2024DMV3D: Denoising Multi-view Diffusion Using 3D Large Reconstruction Model.
Yinghao Xu, Hao Tan, Fujun Luan, Sai Bi, Peng Wang, Jiahao Li, Zifan Shi, Kalyan Sunkavalli, Gordon Wetzstein, Zexiang Xu, Kai Zhang
2024DNA-GPT: Divergent N-Gram Analysis for Training-Free Detection of GPT-Generated Text.
Xianjun Yang, Wei Cheng, Yue Wu, Linda Ruth Petzold, William Yang Wang, Haifeng Chen
2024DNABERT-2: Efficient Foundation Model and Benchmark For Multi-Species Genomes.
Zhihan Zhou, Yanrong Ji, Weijian Li, Pratik Dutta, Ramana V. Davuluri, Han Liu
2024DORSal: Diffusion for Object-centric Representations of Scenes et al.
Allan Jabri, Sjoerd van Steenkiste, Emiel Hoogeboom, Mehdi S. M. Sajjadi, Thomas Kipf
2024DOS: Diverse Outlier Sampling for Out-of-Distribution Detection.
Wenyu Jiang, Hao Cheng, Mingcai Chen, Chongjun Wang, Hongxin Wei
2024DP-OPT: Make Large Language Model Your Privacy-Preserving Prompt Engineer.
Junyuan Hong, Jiachen T. Wang, Chenhui Zhang, Zhangheng Li, Bo Li, Zhangyang Wang
2024DP-SGD Without Clipping: The Lipschitz Neural Network Way.
Louis Béthune, Thomas Massena, Thibaut Boissin, Aurélien Bellet, Franck Mamalet, Yannick Prudent, Corentin Friedrich, Mathieu Serrurier, David Vigouroux
2024DQ-LoRe: Dual Queries with Low Rank Approximation Re-ranking for In-Context Learning.
Jing Xiong, Zixuan Li, Chuanyang Zheng, Zhijiang Guo, Yichun Yin, Enze Xie, Zhicheng Yang, Qingxing Cao, Haiming Wang, Xiongwei Han, Jing Tang, Chengming Li, Xiaodan Liang
2024DREAM: Dual Structured Exploration with Mixup for Open-set Graph Domain Adaption.
Nan Yin, Mengzhu Wang, Zhenghan Chen, Li Shen, Huan Xiong, Bin Gu, Xiao Luo
2024DRSM: De-Randomized Smoothing on Malware Classifier Providing Certified Robustness.
Shoumik Saha, Wenxiao Wang, Yigitcan Kaya, Soheil Feizi, Tudor Dumitras
2024DSPy: Compiling Declarative Language Model Calls into State-of-the-Art Pipelines.
Omar Khattab, Arnav Singhvi, Paridhi Maheshwari, Zhiyuan Zhang, Keshav Santhanam, Sri Vardhamanan, Saiful Haq, Ashutosh Sharma, Thomas T. Joshi, Hanna Moazam, Heather Miller, Matei Zaharia, Christopher Potts
2024DV-3DLane: End-to-end Multi-modal 3D Lane Detection with Dual-view Representation.
Yueru Luo, Shuguang Cui, Zhen Li
2024Data Debugging with Shapley Importance over Machine Learning Pipelines.
Bojan Karlas, David Dao, Matteo Interlandi, Sebastian Schelter, Wentao Wu, Ce Zhang
2024Data Distillation Can Be Like Vodka: Distilling More Times For Better Quality.
Xuxi Chen, Yu Yang, Zhangyang Wang, Baharan Mirzasoleiman
2024Data Filtering Networks.
Alex Fang, Albin Madappally Jose, Amit Jain, Ludwig Schmidt, Alexander T. Toshev, Vaishaal Shankar
2024Data-independent Module-aware Pruning for Hierarchical Vision Transformers.
Yang He, Joey Tianyi Zhou
2024DataInf: Efficiently Estimating Data Influence in LoRA-tuned LLMs and Diffusion Models.
Yongchan Kwon, Eric Wu, Kevin Wu, James Zou
2024Davidsonian Scene Graph: Improving Reliability in Fine-grained Evaluation for Text-to-Image Generation.
Jaemin Cho, Yushi Hu, Jason M. Baldridge, Roopal Garg, Peter Anderson, Ranjay Krishna, Mohit Bansal, Jordi Pont-Tuset, Su Wang
2024De novo Protein Design Using Geometric Vector Field Networks.
Weian Mao, Muzhi Zhu, Zheng Sun, Shuaike Shen, Lin Yuanbo Wu, Hao Chen, Chunhua Shen
2024DePT: Decomposed Prompt Tuning for Parameter-Efficient Fine-tuning.
Zhengxiang Shi, Aldo Lipani
2024Debiased Collaborative Filtering with Kernel-Based Causal Balancing.
Haoxuan Li, Chunyuan Zheng, Yanghao Xiao, Peng Wu, Zhi Geng, Xu Chen, Peng Cui
2024Debiasing Algorithm through Model Adaptation.
Tomasz Limisiewicz, David Marecek, Tomás Musil
2024Debiasing Attention Mechanism in Transformer without Demographics.
Shenyu Lu, Yipei Wang, Xiaoqian Wang
2024Decentralized Riemannian Conjugate Gradient Method on the Stiefel Manifold.
Jun Chen, Haishan Ye, Mengmeng Wang, Tianxin Huang, Guang Dai, Ivor W. Tsang, Yong Liu
2024Deceptive Fairness Attacks on Graphs via Meta Learning.
Jian Kang, Yinglong Xia, Ross Maciejewski, Jiebo Luo, Hanghang Tong
2024Decision ConvFormer: Local Filtering in MetaFormer is Sufficient for Decision Making.
Jeonghye Kim, Suyoung Lee, Woojun Kim, Youngchul Sung
2024Decodable and Sample Invariant Continuous Object Encoder.
Dehao Yuan, Furong Huang, Cornelia Fermüller, Yiannis Aloimonos
2024Decoding Natural Images from EEG for Object Recognition.
Yonghao Song, Bingchuan Liu, Xiang Li, Nanlin Shi, Yijun Wang, Xiaorong Gao
2024DecompOpt: Controllable and Decomposed Diffusion Models for Structure-based Molecular Optimization.
Xiangxin Zhou, Xiwei Cheng, Yuwei Yang, Yu Bao, Liang Wang, Quanquan Gu
2024Decomposed Diffusion Sampler for Accelerating Large-Scale Inverse Problems.
Hyungjin Chung, Suhyeon Lee, Jong Chul Ye
2024Decongestion by Representation: Learning to Improve Economic Welfare in Marketplaces.
Omer Nahum, Gali Noti, David C. Parkes, Nir Rosenfeld
2024Decoupled Marked Temporal Point Process using Neural Ordinary Differential Equations.
Yujee Song, Donghyun Lee, Rui Meng, Won Hwa Kim
2024Decoupling Weighing and Selecting for Integrating Multiple Graph Pre-training Tasks.
Tianyu Fan, Lirong Wu, Yufei Huang, Haitao Lin, Cheng Tan, Zhangyang Gao, Stan Z. Li
2024Decoupling regularization from the action space.
Sobhan Mohammadpour, Emma Frejinger, Pierre-Luc Bacon
2024Deep Confident Steps to New Pockets: Strategies for Docking Generalization.
Gabriele Corso, Arthur Deng, Nicholas Polizzi, Regina Barzilay, Tommi S. Jaakkola
2024Deep Generative Clustering with Multimodal Diffusion Variational Autoencoders.
Emanuele Palumbo, Laura Manduchi, Sonia Laguna, Daphné Chopard, Julia E. Vogt
2024Deep Geodesic Canonical Correlation Analysis for Covariance-Based Neuroimaging Data.
Ce Ju, Reinmar J. Kobler, Liyao Tang, Cuntai Guan, Motoaki Kawanabe
2024Deep Neural Network Initialization with Sparsity Inducing activations.
Ilan Price, Nicholas Daultry Ball, Adam C. Jones, Samuel C. H. Lam, Jared Tanner
2024Deep Neural Networks Tend To Extrapolate Predictably.
Katie Kang, Amrith Setlur, Claire J. Tomlin, Sergey Levine
2024Deep Orthogonal Hypersphere Compression for Anomaly Detection.
Yunhe Zhang, Yan Sun, Jinyu Cai, Jicong Fan
2024Deep Reinforcement Learning Guided Improvement Heuristic for Job Shop Scheduling.
Cong Zhang, Zhiguang Cao, Wen Song, Yaoxin Wu, Jie Zhang
2024Deep Reinforcement Learning for Modelling Protein Complexes.
Ziqi Gao, Tao Feng, Jiaxuan You, Chenyi Zi, Yan Zhou, Chen Zhang, Jia Li
2024Deep SE(3)-Equivariant Geometric Reasoning for Precise Placement Tasks.
Ben Eisner, Yi Yang, Todor Davchev, Mel Vecerík, Jonathan Scholz, David Held
2024Deep Temporal Graph Clustering.
Meng Liu, Yue Liu, Ke Liang, Wenxuan Tu, Siwei Wang, Sihang Zhou, Xinwang Liu
2024DeepSPF: Spherical SO(3)-Equivariant Patches for Scan-to-CAD Estimation.
Driton Salihu, Adam Misik, Yuankai Wu, Constantin Patsch, Fabián Seguel, Eckehard G. Steinbach
2024DeepZero: Scaling Up Zeroth-Order Optimization for Deep Model Training.
Aochuan Chen, Yimeng Zhang, Jinghan Jia, James Diffenderfer, Konstantinos Parasyris, Jiancheng Liu, Yihua Zhang, Zheng Zhang, Bhavya Kailkhura, Sijia Liu
2024Defining Expertise: Applications to Treatment Effect Estimation.
Alihan Hüyük, Qiyao Wei, Alicia Curth, Mihaela van der Schaar
2024Defining and extracting generalizable interaction primitives from DNNs.
Lu Chen, Siyu Lou, Benhao Huang, Quanshi Zhang
2024Delphic Offline Reinforcement Learning under Nonidentifiable Hidden Confounding.
Alizée Pace, Hugo Yèche, Bernhard Schölkopf, Gunnar Rätsch, Guy Tennenholtz
2024Delta-AI: Local objectives for amortized inference in sparse graphical models.
Jean-Pierre R. Falet, Hae Beom Lee, Nikolay Malkin, Chen Sun, Dragos Secrieru, Dinghuai Zhang, Guillaume Lajoie, Yoshua Bengio
2024Democratizing Fine-grained Visual Recognition with Large Language Models.
Mingxuan Liu, Subhankar Roy, Wenjing Li, Zhun Zhong, Nicu Sebe, Elisa Ricci
2024Demonstration-Regularized RL.
Daniil Tiapkin, Denis Belomestny, Daniele Calandriello, Eric Moulines, Alexey Naumov, Pierre Perrault, Michal Valko, Pierre Ménard
2024Demystifying CLIP Data.
Hu Xu, Saining Xie, Xiaoqing Ellen Tan, Po-Yao Huang, Russell Howes, Vasu Sharma, Shang-wen Li, Gargi Ghosh, Luke Zettlemoyer, Christoph Feichtenhofer
2024Demystifying Embedding Spaces using Large Language Models.
Guy Tennenholtz, Yinlam Chow, Chih-Wei Hsu, Jihwan Jeong, Lior Shani, Azamat Tulepbergenov, Deepak Ramachandran, Martin Mladenov, Craig Boutilier
2024Demystifying Linear MDPs and Novel Dynamics Aggregation Framework.
Joongkyu Lee, Min-hwan Oh
2024Demystifying Local & Global Fairness Trade-offs in Federated Learning Using Partial Information Decomposition.
Faisal Hamman, Sanghamitra Dutta
2024Demystifying Poisoning Backdoor Attacks from a Statistical Perspective.
Ganghua Wang, Xun Xian, Ashish Kundu, Jayanth Srinivasa, Xuan Bi, Mingyi Hong, Jie Ding
2024Denevil: towards Deciphering and Navigating the Ethical Values of Large Language Models via Instruction Learning.
Shitong Duan, Xiaoyuan Yi, Peng Zhang, Tun Lu, Xing Xie, Ning Gu
2024Denoising Diffusion Bridge Models.
Linqi Zhou, Aaron Lou, Samar Khanna, Stefano Ermon
2024Denoising Diffusion Step-aware Models.
Shuai Yang, Yukang Chen, Luozhou Wang, Shu Liu, Ying-Cong Chen
2024Denoising Diffusion via Image-Based Rendering.
Titas Anciukevicius, Fabian Manhardt, Federico Tombari, Paul Henderson
2024Denoising Task Routing for Diffusion Models.
Byeongjun Park, Sangmin Woo, Hyojun Go, Jin-Young Kim, Changick Kim
2024Depthwise Hyperparameter Transfer in Residual Networks: Dynamics and Scaling Limit.
Blake Bordelon, Lorenzo Noci, Mufan Bill Li, Boris Hanin, Cengiz Pehlevan
2024Designing Skill-Compatible AI: Methodologies and Frameworks in Chess.
Karim Hamade, Reid McIlroy-Young, Siddhartha Sen, Jon M. Kleinberg, Ashton Anderson
2024Det-CGD: Compressed Gradient Descent with Matrix Stepsizes for Non-Convex Optimization.
Hanmin Li, Avetik G. Karagulyan, Peter Richtárik
2024Detecting Machine-Generated Texts by Multi-Population Aware Optimization for Maximum Mean Discrepancy.
Shuhai Zhang, Yiliao Song, Jiahao Yang, Yuanqing Li, Bo Han, Mingkui Tan
2024Detecting Pretraining Data from Large Language Models.
Weijia Shi, Anirudh Ajith, Mengzhou Xia, Yangsibo Huang, Daogao Liu, Terra Blevins, Danqi Chen, Luke Zettlemoyer
2024Detecting, Explaining, and Mitigating Memorization in Diffusion Models.
Yuxin Wen, Yuchen Liu, Chen Chen, Lingjuan Lyu
2024DiLu: A Knowledge-Driven Approach to Autonomous Driving with Large Language Models.
Licheng Wen, Daocheng Fu, Xin Li, Xinyu Cai, Tao Ma, Pinlong Cai, Min Dou, Botian Shi, Liang He, Yu Qiao
2024Diagnosing Transformers: Illuminating Feature Spaces for Clinical Decision-Making.
Aliyah R. Hsu, Yeshwanth Cherapanamjeri, Briton Park, Tristan Naumann, Anobel Y. Odisho, Bin Yu
2024Dichotomy of Early and Late Phase Implicit Biases Can Provably Induce Grokking.
Kaifeng Lyu, Jikai Jin, Zhiyuan Li, Simon Shaolei Du, Jason D. Lee, Wei Hu
2024Dictionary Contrastive Learning for Efficient Local Supervision without Auxiliary Networks.
Suhwan Choi, Myeongho Jeon, Yeonjung Hwang, Jeonglyul Oh, Sungjun Lim, Joonseok Lee, Myungjoo Kang
2024DiffAR: Denoising Diffusion Autoregressive Model for Raw Speech Waveform Generation.
Roi Benita, Michael Elad, Joseph Keshet
2024DiffEnc: Variational Diffusion with a Learned Encoder.
Beatrix Miranda Ginn Nielsen, Anders Christensen, Andrea Dittadi, Ole Winther
2024Diffeomorphic Mesh Deformation via Efficient Optimal Transport for Cortical Surface Reconstruction.
Thanh-Tung Le, Khai Nguyen, Shanlin Sun, Kun Han, Nhat Ho, Xiaohui Xie
2024Differentiable Euler Characteristic Transforms for Shape Classification.
Ernst Röell, Bastian Rieck
2024Differentiable Learning of Generalized Structured Matrices for Efficient Deep Neural Networks.
Changwoo Lee, Hun-Seok Kim
2024Differentially Private SGD Without Clipping Bias: An Error-Feedback Approach.
Xinwei Zhang, Zhiqi Bu, Steven Wu, Mingyi Hong
2024Differentially Private Synthetic Data via Foundation Model APIs 1: Images.
Zinan Lin, Sivakanth Gopi, Janardhan Kulkarni, Harsha Nori, Sergey Yekhanin
2024Diffusion Generative Flow Samplers: Improving learning signals through partial trajectory optimization.
Dinghuai Zhang, Ricky T. Q. Chen, Cheng-Hao Liu, Aaron C. Courville, Yoshua Bengio
2024Diffusion Model for Dense Matching.
Jisu Nam, Gyuseong Lee, Sunwoo Kim, Hyeonsu Kim, Hyoungwon Cho, Seyeon Kim, Seungryong Kim
2024Diffusion Models for Multi-Task Generative Modeling.
Changyou Chen, Han Ding, Bunyamin Sisman, Yi Xu, Ouye Xie, Benjamin Z. Yao, Son Dinh Tran, Belinda Zeng
2024Diffusion Posterior Sampling for Linear Inverse Problem Solving: A Filtering Perspective.
Zehao Dou, Yang Song
2024Diffusion Sampling with Momentum for Mitigating Divergence Artifacts.
Suttisak Wizadwongsa, Worameth Chinchuthakun, Pramook Khungurn, Amit Raj, Supasorn Suwajanakorn
2024Diffusion in Diffusion: Cyclic One-Way Diffusion for Text-Vision-Conditioned Generation.
Ruoyu Wang, Yongqi Yang, Zhihao Qian, Ye Zhu, Yu Wu
2024Diffusion-TS: Interpretable Diffusion for General Time Series Generation.
Xinyu Yuan, Yan Qiao
2024DiffusionNAG: Predictor-guided Neural Architecture Generation with Diffusion Models.
Sohyun An, Hayeon Lee, Jaehyeong Jo, Seanie Lee, Sung Ju Hwang
2024DiffusionSat: A Generative Foundation Model for Satellite Imagery.
Samar Khanna, Patrick Liu, Linqi Zhou, Chenlin Meng, Robin Rombach, Marshall Burke, David B. Lobell, Stefano Ermon
2024Directly Fine-Tuning Diffusion Models on Differentiable Rewards.
Kevin Clark, Paul Vicol, Kevin Swersky, David J. Fleet
2024Dirichlet-based Per-Sample Weighting by Transition Matrix for Noisy Label Learning.
HeeSun Bae, Seungjae Shin, Byeonghu Na, Il-Chul Moon
2024Discovering Failure Modes of Text-guided Diffusion Models via Adversarial Search.
Qihao Liu, Adam Kortylewski, Yutong Bai, Song Bai, Alan L. Yuille
2024Discovering Temporally-Aware Reinforcement Learning Algorithms.
Matthew Thomas Jackson, Chris Lu, Louis Kirsch, Robert Tjarko Lange, Shimon Whiteson, Jakob Nicolaus Foerster
2024Discovering modular solutions that generalize compositionally.
Simon Schug, Seijin Kobayashi, Yassir Akram, Maciej Wolczyk, Alexandra Maria Proca, Johannes von Oswald, Razvan Pascanu, João Sacramento, Angelika Steger
2024DisenBooth: Identity-Preserving Disentangled Tuning for Subject-Driven Text-to-Image Generation.
Hong Chen, Yipeng Zhang, Simin Wu, Xin Wang, Xuguang Duan, Yuwei Zhou, Wenwu Zhu
2024Disentangling Time Series Representations via Contrastive Independence-of-Support on l-Variational Inference.
Khalid Oublal, Saïd Ladjal, David Benhaiem, Emmanuel Le-borgne, François Roueff
2024Dissecting Sample Hardness: A Fine-Grained Analysis of Hardness Characterization Methods for Data-Centric AI.
Nabeel Seedat, Fergus Imrie, Mihaela van der Schaar
2024Dissecting learning and forgetting in language model finetuning.
Xiao Zhang, Ji Wu
2024DistillSpec: Improving Speculative Decoding via Knowledge Distillation.
Yongchao Zhou, Kaifeng Lyu, Ankit Singh Rawat, Aditya Krishna Menon, Afshin Rostamizadeh, Sanjiv Kumar, Jean-François Kagy, Rishabh Agarwal
2024Distinguished In Uniform: Self-Attention Vs. Virtual Nodes.
Eran Rosenbluth, Jan Tönshoff, Martin Ritzert, Berke Kisin, Martin Grohe
2024Distributional Preference Learning: Understanding and Accounting for Hidden Context in RLHF.
Anand Siththaranjan, Cassidy Laidlaw, Dylan Hadfield-Menell
2024Distributionally Robust Optimization with Bias and Variance Reduction.
Ronak Mehta, Vincent Roulet, Krishna Pillutla, Zaïd Harchaoui
2024DittoGym: Learning to Control Soft Shape-Shifting Robots.
Suning Huang, Boyuan Chen, Huazhe Xu, Vincent Sitzmann
2024Diverse Projection Ensembles for Distributional Reinforcement Learning.
Moritz Akiya Zanger, Wendelin Boehmer, Matthijs T. J. Spaan
2024Divide and not forget: Ensemble of selectively trained experts in Continual Learning.
Grzegorz Rypesc, Sebastian Cygert, Valeriya Khan, Tomasz Trzcinski, Bartosz Zielinski, Bartlomiej Twardowski
2024Diving Segmentation Model into Pixels.
Chen Gan, Zihao Yin, Kelei He, Yang Gao, Junfeng Zhang
2024Do Generated Data Always Help Contrastive Learning?
Yifei Wang, Jizhe Zhang, Yisen Wang
2024DoLa: Decoding by Contrasting Layers Improves Factuality in Large Language Models.
Yung-Sung Chuang, Yujia Xie, Hongyin Luo, Yoon Kim, James R. Glass, Pengcheng He
2024Does CLIP's generalization performance mainly stem from high train-test similarity?
Prasanna Mayilvahanan, Thaddäus Wiedemer, Evgenia Rusak, Matthias Bethge, Wieland Brendel
2024Does Progress On Object Recognition Benchmarks Improve Generalization on Crowdsourced, Global Data?
Megan Richards, Polina Kirichenko, Diane Bouchacourt, Mark Ibrahim
2024Does Writing with Language Models Reduce Content Diversity?
Vishakh Padmakumar, He He
2024Domain Randomization via Entropy Maximization.
Gabriele Tiboni, Pascal Klink, Jan Peters, Tatiana Tommasi, Carlo D'Eramo, Georgia Chalvatzaki
2024Domain constraints improve risk prediction when outcome data is missing.
Sidhika Balachandar, Nikhil Garg, Emma Pierson
2024Domain-Agnostic Molecular Generation with Chemical Feedback.
Yin Fang, Ningyu Zhang, Zhuo Chen, Lingbing Guo, Xiaohui Fan, Huajun Chen
2024Domain-Inspired Sharpness-Aware Minimization Under Domain Shifts.
Ruipeng Zhang, Ziqing Fan, Jiangchao Yao, Ya Zhang, Yanfeng Wang
2024Don't Judge by the Look: Towards Motion Coherent Video Representation.
Yitian Zhang, Yue Bai, Huan Wang, Yizhou Wang, Yun Fu
2024Don't Play Favorites: Minority Guidance for Diffusion Models.
Soobin Um, Suhyeon Lee, Jong Chul Ye
2024Don't Trust: Verify - Grounding LLM Quantitative Reasoning with Autoformalization.
Jin Peng Zhou, Charles Staats, Wenda Li, Christian Szegedy, Kilian Q. Weinberger, Yuhuai Wu
2024Doubly Robust Instance-Reweighted Adversarial Training.
Daouda Sow, Sen Lin, Zhangyang Wang, Yingbin Liang
2024Doubly Robust Proximal Causal Learning for Continuous Treatments.
Yong Wu, Yanwei Fu, Shouyan Wang, Xinwei Sun
2024DrM: Mastering Visual Reinforcement Learning through Dormant Ratio Minimization.
Guowei Xu, Ruijie Zheng, Yongyuan Liang, Xiyao Wang, Zhecheng Yuan, Tianying Ji, Yu Luo, Xiaoyu Liu, Jiaxin Yuan, Pu Hua, Shuzhen Li, Yanjie Ze, Hal Daumé III, Furong Huang, Huazhe Xu
2024DrS: Learning Reusable Dense Rewards for Multi-Stage Tasks.
Tongzhou Mu, Minghua Liu, Hao Su
2024DragonDiffusion: Enabling Drag-style Manipulation on Diffusion Models.
Chong Mou, Xintao Wang, Jiechong Song, Ying Shan, Jian Zhang
2024DreamClean: Restoring Clean Image Using Deep Diffusion Prior.
Jie Xiao, Ruili Feng, Han Zhang, Zhiheng Liu, Zhantao Yang, Yurui Zhu, Xueyang Fu, Kai Zhu, Yu Liu, Zheng-Jun Zha
2024DreamCraft3D: Hierarchical 3D Generation with Bootstrapped Diffusion Prior.
Jingxiang Sun, Bo Zhang, Ruizhi Shao, Lizhen Wang, Wen Liu, Zhenda Xie, Yebin Liu
2024DreamFlow: High-quality text-to-3D generation by Approximating Probability Flow.
Kyungmin Lee, Kihyuk Sohn, Jinwoo Shin
2024DreamGaussian: Generative Gaussian Splatting for Efficient 3D Content Creation.
Jiaxiang Tang, Jiawei Ren, Hang Zhou, Ziwei Liu, Gang Zeng
2024DreamLLM: Synergistic Multimodal Comprehension and Creation.
Runpei Dong, Chunrui Han, Yuang Peng, Zekun Qi, Zheng Ge, Jinrong Yang, Liang Zhao, Jianjian Sun, Hongyu Zhou, Haoran Wei, Xiangwen Kong, Xiangyu Zhang, Kaisheng Ma, Li Yi
2024DreamSmooth: Improving Model-based Reinforcement Learning via Reward Smoothing.
Vint Lee, Pieter Abbeel, Youngwoon Lee
2024DreamTime: An Improved Optimization Strategy for Diffusion-Guided 3D Generation.
Yukun Huang, Jianan Wang, Yukai Shi, Boshi Tang, Xianbiao Qi, Lei Zhang
2024Dropout Enhanced Bilevel Training.
Peiran Yu, Junyi Li, Heng Huang
2024Dropout-Based Rashomon Set Exploration for Efficient Predictive Multiplicity Estimation.
Hsiang Hsu, Guihong Li, Shaohan Hu, Chun-Fu Chen
2024Dual Associated Encoder for Face Restoration.
Yu-Ju Tsai, Yu-Lun Liu, Lu Qi, Kelvin C. K. Chan, Ming-Hsuan Yang
2024Dual RL: Unification and New Methods for Reinforcement and Imitation Learning.
Harshit Sikchi, Qinqing Zheng, Amy Zhang, Scott Niekum
2024Dual-Encoders for Extreme Multi-label Classification.
Nilesh Gupta, Devvrit, Ankit Singh Rawat, Srinadh Bhojanapalli, Prateek Jain, Inderjit S. Dhillon
2024Duolando: Follower GPT with Off-Policy Reinforcement Learning for Dance Accompaniment.
Li Siyao, Tianpei Gu, Zhitao Yang, Zhengyu Lin, Ziwei Liu, Henghui Ding, Lei Yang, Chen Change Loy
2024DyST: Towards Dynamic Neural Scene Representations on Real-World Videos.
Maximilian Seitzer, Sjoerd van Steenkiste, Thomas Kipf, Klaus Greff, Mehdi S. M. Sajjadi
2024DyVal: Dynamic Evaluation of Large Language Models for Reasoning Tasks.
Kaijie Zhu, Jiaao Chen, Jindong Wang, Neil Zhenqiang Gong, Diyi Yang, Xing Xie
2024DynaVol: Unsupervised Learning for Dynamic Scenes through Object-Centric Voxelization.
Yanpeng Zhao, Siyu Gao, Yunbo Wang, Xiaokang Yang
2024Dynamic Discounted Counterfactual Regret Minimization.
Hang Xu, Kai Li, Haobo Fu, Qiang Fu, Junliang Xing, Jian Cheng
2024Dynamic Layer Tying for Parameter-Efficient Transformers.
Tamir David Hay, Lior Wolf
2024Dynamic Neighborhood Construction for Structured Large Discrete Action Spaces.
Fabian Akkerman, Julius Luy, Wouter van Heeswijk, Maximilian Schiffer
2024Dynamic Neural Response Tuning.
Tian Qiu, Wenxiang Xu, Lin Chen, Linyun Zhou, Zunlei Feng, Mingli Song
2024Dynamic Sparse No Training: Training-Free Fine-tuning for Sparse LLMs.
Yuxin Zhang, Lirui Zhao, Mingbao Lin, Yunyun Sun, Yiwu Yao, Xingjia Han, Jared Tanner, Shiwei Liu, Rongrong Ji
2024Dynamic Sparse Training with Structured Sparsity.
Mike Lasby, Anna Golubeva, Utku Evci, Mihai Nica, Yani Ioannou
2024Dynamics-Informed Protein Design with Structure Conditioning.
Urszula Julia Komorowska, Simon V. Mathis, Kieran Didi, Francisco Vargas, Pietro Lio, Mateja Jamnik
2024EBMDock: Neural Probabilistic Protein-Protein Docking via a Differentiable Energy Model.
Huaijin Wu, Wei Liu, Yatao Bian, Jiaxiang Wu, Nianzu Yang, Junchi Yan
2024ECoFLaP: Efficient Coarse-to-Fine Layer-Wise Pruning for Vision-Language Models.
Yi-Lin Sung, Jaehong Yoon, Mohit Bansal
2024EControl: Fast Distributed Optimization with Compression and Error Control.
Yuan Gao, Rustem Islamov, Sebastian U. Stich
2024ED-NeRF: Efficient Text-Guided Editing of 3D Scene With Latent Space NeRF.
Jangho Park, Gihyun Kwon, Jong Chul Ye
2024EQA-MX: Embodied Question Answering using Multimodal Expression.
Md Mofijul Islam, Alexi Gladstone, Riashat Islam, Tariq Iqbal
2024EX-Graph: A Pioneering Dataset Bridging Ethereum and X.
Qian Wang, Zhen Zhang, Zemin Liu, Shengliang Lu, Bingqiao Luo, Bingsheng He
2024Early Neuron Alignment in Two-layer ReLU Networks with Small Initialization.
Hancheng Min, Enrique Mallada, René Vidal
2024Early Stopping Against Label Noise Without Validation Data.
Suqin Yuan, Lei Feng, Tongliang Liu
2024EasyTPP: Towards Open Benchmarking Temporal Point Processes.
Siqiao Xue, Xiaoming Shi, Zhixuan Chu, Yan Wang, Hongyan Hao, Fan Zhou, Caigao Jiang, Chen Pan, James Y. Zhang, Qingsong Wen, Jun Zhou, Hongyuan Mei
2024Effective Data Augmentation With Diffusion Models.
Brandon Trabucco, Kyle Doherty, Max Gurinas, Ruslan Salakhutdinov
2024Effective Structural Encodings via Local Curvature Profiles.
Lukas Fesser, Melanie Weber
2024Effective and Efficient Federated Tree Learning on Hybrid Data.
Qinbin Li, Chulin Xie, Xiaojun Xu, Xiaoyuan Liu, Ce Zhang, Bo Li, Bingsheng He, Dawn Song
2024Effective pruning of web-scale datasets based on complexity of concept clusters.
Amro Abbas, Evgenia Rusak, Kushal Tirumala, Wieland Brendel, Kamalika Chaudhuri, Ari S. Morcos
2024Efficient Backdoor Attacks for Deep Neural Networks in Real-world Scenarios.
Ziqiang Li, Hong Sun, Pengfei Xia, Heng Li, Beihao Xia, Yi Wu, Bin Li
2024Efficient Backpropagation with Variance Controlled Adaptive Sampling.
Ziteng Wang, Jianfei Chen, Jun Zhu
2024Efficient Continual Finite-Sum Minimization.
Ioannis Mavrothalassitis, Stratis Skoulakis, Leello Tadesse Dadi, Volkan Cevher
2024Efficient ConvBN Blocks for Transfer Learning and Beyond.
Kaichao You, Guo Qin, Anchang Bao, Meng Cao, Ping Huang, Jiulong Shan, Mingsheng Long
2024Efficient Dynamics Modeling in Interactive Environments with Koopman Theory.
Arnab Kumar Mondal, Siba Smarak Panigrahi, Sai Rajeswar, Kaleem Siddiqi, Siamak Ravanbakhsh
2024Efficient Episodic Memory Utilization of Cooperative Multi-Agent Reinforcement Learning.
Hyungho Na, Yunkyeong Seo, Il-Chul Moon
2024Efficient Heterogeneous Meta-Learning via Channel Shuffling Modulation.
Minh Hoang, Carl Kingsford
2024Efficient Integrators for Diffusion Generative Models.
Kushagra Pandey, Maja Rudolph, Stephan Mandt
2024Efficient Inverse Multiagent Learning.
Denizalp Goktas, Amy Greenwald, Sadie Zhao, Alec Koppel, Sumitra Ganesh
2024Efficient Modulation for Vision Networks.
Xu Ma, Xiyang Dai, Jianwei Yang, Bin Xiao, Yinpeng Chen, Yun Fu, Lu Yuan
2024Efficient Multi-agent Reinforcement Learning by Planning.
Qihan Liu, Jianing Ye, Xiaoteng Ma, Jun Yang, Bin Liang, Chongjie Zhang
2024Efficient Planning with Latent Diffusion.
Wenhao Li
2024Efficient Score Matching with Deep Equilibrium Layers.
Yuhao Huang, Qingsong Wang, Akwum Onwunta, Bao Wang
2024Efficient Sharpness-Aware Minimization for Molecular Graph Transformer Models.
Yili Wang, Kaixiong Zhou, Ninghao Liu, Ying Wang, Xin Wang
2024Efficient Streaming Language Models with Attention Sinks.
Guangxuan Xiao, Yuandong Tian, Beidi Chen, Song Han, Mike Lewis
2024Efficient Subgraph GNNs by Learning Effective Selection Policies.
Beatrice Bevilacqua, Moshe Eliasof, Eli A. Meirom, Bruno Ribeiro, Haggai Maron
2024Efficient Video Diffusion Models via Content-Frame Motion-Latent Decomposition.
Sihyun Yu, Weili Nie, De-An Huang, Boyi Li, Jinwoo Shin, Anima Anandkumar
2024Efficient and Scalable Graph Generation through Iterative Local Expansion.
Andreas Bergmeister, Karolis Martinkus, Nathanaël Perraudin, Roger Wattenhofer
2024Efficient local linearity regularization to overcome catastrophic overfitting.
Elías Abad-Rocamora, Fanghui Liu, Grigorios Chrysos, Pablo M. Olmos, Volkan Cevher
2024Efficient-3Dim: Learning a Generalizable Single-image Novel-view Synthesizer in One Day.
Yifan Jiang, Hao Tang, Jen-Hao Rick Chang, Liangchen Song, Zhangyang Wang, Liangliang Cao
2024EfficientDM: Efficient Quantization-Aware Fine-Tuning of Low-Bit Diffusion Models.
Yefei He, Jing Liu, Weijia Wu, Hong Zhou, Bohan Zhuang
2024Efficiently Computing Similarities to Private Datasets.
Arturs Backurs, Zinan Lin, Sepideh Mahabadi, Sandeep Silwal, Jakub Tarnawski
2024Elastic Feature Consolidation For Cold Start Exemplar-Free Incremental Learning.
Simone Magistri, Tomaso Trinci, Albin Soutif-Cormerais, Joost van de Weijer, Andrew D. Bagdanov
2024Elucidating the Exposure Bias in Diffusion Models.
Mang Ning, Mingxiao Li, Jianlin Su, Albert Ali Salah, Itir Önal Ertugrul
2024Elucidating the design space of classifier-guided diffusion generation.
Jiajun Ma, Tianyang Hu, Wenjia Wang, Jiacheng Sun
2024Embarrassingly Simple Dataset Distillation.
Yunzhen Feng, Shanmukha Ramakrishna Vedantam, Julia Kempe
2024Embodied Active Defense: Leveraging Recurrent Feedback to Counter Adversarial Patches.
Lingxuan Wu, Xiao Yang, Yinpeng Dong, Liuwei Xie, Hang Su, Jun Zhu
2024EmerDiff: Emerging Pixel-level Semantic Knowledge in Diffusion Models.
Koichi Namekata, Amirmojtaba Sabour, Sanja Fidler, Seung Wook Kim
2024EmerNeRF: Emergent Spatial-Temporal Scene Decomposition via Self-Supervision.
Jiawei Yang, Boris Ivanovic, Or Litany, Xinshuo Weng, Seung Wook Kim, Boyi Li, Tong Che, Danfei Xu, Sanja Fidler, Marco Pavone, Yue Wang
2024Emergent Communication with Conversational Repair.
Mitja Nikolaus
2024Emergent mechanisms for long timescales depend on training curriculum and affect performance in memory tasks.
Sina Khajehabdollahi, Roxana Zeraati, Emmanouil Giannakakis, Tim Jakob Schäfer, Georg Martius, Anna Levina
2024Emo: Earth Mover Distance Optimization for Auto-Regressive Language Modeling.
Siyu Ren, Zhiyong Wu, Kenny Q. Zhu
2024Empirical Analysis of Model Selection for Heterogeneous Causal Effect Estimation.
Divyat Mahajan, Ioannis Mitliagkas, Brady Neal, Vasilis Syrgkanis
2024Empirical Likelihood for Fair Classification.
Pangpang Liu, Yichuan Zhao
2024Emu: Generative Pretraining in Multimodality.
Quan Sun, Qiying Yu, Yufeng Cui, Fan Zhang, Xiaosong Zhang, Yueze Wang, Hongcheng Gao, Jingjing Liu, Tiejun Huang, Xinlong Wang
2024Enabling Efficient Equivariant Operations in the Fourier Basis via Gaunt Tensor Products.
Shengjie Luo, Tianlang Chen, Aditi S. Krishnapriyan
2024Enabling Lanuguage Models to Implicitly Learn Self-Improvement.
Ziqi Wang, Le Hou, Tianjian Lu, Yuexin Wu, Yunxuan Li, Hongkun Yu, Heng Ji
2024Encoding Unitig-level Assembly Graphs with Heterophilous Constraints for Metagenomic Contigs Binning.
Hansheng Xue, Vijini Mallawaarachchi, Lexing Xie, Vaibhav Rajan
2024End-to-End (Instance)-Image Goal Navigation through Correspondence as an Emergent Phenomenon.
Guillaume Bono, Leonid Antsfeld, Boris Chidlovskii, Philippe Weinzaepfel, Christian Wolf
2024Energy-Based Concept Bottleneck Models: Unifying Prediction, Concept Intervention, and Probabilistic Interpretations.
Xinyue Xu, Yi Qin, Lu Mi, Hao Wang, Xiaomeng Li
2024Energy-based Automated Model Evaluation.
Ru Peng, Heming Zou, Haobo Wang, Yawen Zeng, Zenan Huang, Junbo Zhao
2024Energy-conserving equivariant GNN for elasticity of lattice architected metamaterials.
Ivan Grega, Ilyes Batatia, Gábor Csányi, Sri Karlapati, Vikram S. Deshpande
2024Energy-guided Entropic Neural Optimal Transport.
Petr Mokrov, Alexander Korotin, Alexander Kolesov, Nikita Gushchin, Evgeny Burnaev
2024Enhanced Face Recognition using Intra-class Incoherence Constraint.
Yuanqing Huang, Yinggui Wang, Le Yang, Lei Wang
2024Enhancing Contrastive Learning for Ordinal Regression via Ordinal Content Preserved Data Augmentation.
Jiyang Zheng, Yu Yao, Bo Han, Dadong Wang, Tongliang Liu
2024Enhancing Group Fairness in Online Settings Using Oblique Decision Forests.
Somnath Basu Roy Chowdhury, Nicholas Monath, Ahmad Beirami, Rahul Kidambi, Kumar Avinava Dubey, Amr Ahmed, Snigdha Chaturvedi
2024Enhancing High-Resolution 3D Generation through Pixel-wise Gradient Clipping.
Zijie Pan, Jiachen Lu, Xiatian Zhu, Li Zhang
2024Enhancing Human Experience in Human-Agent Collaboration: A Human-Centered Modeling Approach Based on Positive Human Gain.
Yiming Gao, Feiyu Liu, Liang Wang, Dehua Zheng, Zhenjie Lian, Weixuan Wang, Wenjin Yang, Siqin Li, Xianliang Wang, Wenhui Chen, Jing Dai, Qiang Fu, Wei Yang, Lanxiao Huang, Wei Liu
2024Enhancing Human-AI Collaboration Through Logic-Guided Reasoning.
Chengzhi Cao, Yinghao Fu, Sheng Xu, Ruimao Zhang, Shuang Li
2024Enhancing Instance-Level Image Classification with Set-Level Labels.
Renyu Zhang, Aly A. Khan, Yuxin Chen, Robert L. Grossman
2024Enhancing Neural Subset Selection: Integrating Background Information into Set Representations.
Binghui Xie, Yatao Bian, Kaiwen Zhou, Yongqiang Chen, Peilin Zhao, Bo Han, Wei Meng, James Cheng
2024Enhancing Neural Training via a Correlated Dynamics Model.
Jonathan Brokman, Roy Betser, Rotem Turjeman, Tom Berkov, Ido Cohen, Guy Gilboa
2024Enhancing One-Shot Federated Learning Through Data and Ensemble Co-Boosting.
Rong Dai, Yonggang Zhang, Ang Li, Tongliang Liu, Xun Yang, Bo Han
2024Enhancing Small Medical Learners with Privacy-preserving Contextual Prompting.
Xinlu Zhang, Shiyang Li, Xianjun Yang, Chenxin Tian, Yao Qin, Linda Ruth Petzold
2024Enhancing Tail Performance in Extreme Classifiers by Label Variance Reduction.
Anirudh Buvanesh, Rahul Chand, Jatin Prakash, Bhawna Paliwal, Mudit Dhawan, Neelabh Madan, Deepesh Hada, Vidit Jain, Sonu Mehta, Yashoteja Prabhu, Manish Gupta, Ramachandran Ramjee, Manik Varma
2024Enhancing Transfer Learning with Flexible Nonparametric Posterior Sampling.
Hyungi Lee, Giung Nam, Edwin Fong, Juho Lee
2024Enhancing Transferable Adversarial Attacks on Vision Transformers through Gradient Normalization Scaling and High-Frequency Adaptation.
Zhiyu Zhu, Xinyi Wang, Zhibo Jin, Jiayu Zhang, Huaming Chen
2024Ensemble Distillation for Unsupervised Constituency Parsing.
Behzad Shayegh, Yanshuai Cao, Xiaodan Zhu, Jackie C. K. Cheung, Lili Mou
2024Entity-Centric Reinforcement Learning for Object Manipulation from Pixels.
Dan Haramati, Tal Daniel, Aviv Tamar
2024Entropy Coding of Unordered Data Structures.
Julius Kunze, Daniel Severo, Giulio Zani, Jan-Willem van de Meent, James Townsend
2024Entropy is not Enough for Test-Time Adaptation: From the Perspective of Disentangled Factors.
Jonghyun Lee, Dahuin Jung, Saehyung Lee, Junsung Park, Juhyeon Shin, Uiwon Hwang, Sungroh Yoon
2024Entropy-MCMC: Sampling from Flat Basins with Ease.
Bolian Li, Ruqi Zhang
2024Epitopological learning and Cannistraci-Hebb network shape intelligence brain-inspired theory for ultra-sparse advantage in deep learning.
Yingtao Zhang, Jialin Zhao, Wenjing Wu, Alessandro Muscoloni, Carlo Vittorio Cannistraci
2024EquiformerV2: Improved Equivariant Transformer for Scaling to Higher-Degree Representations.
Yi-Lun Liao, Brandon M. Wood, Abhishek Das, Tess E. Smidt
2024Equivariant Matrix Function Neural Networks.
Ilyes Batatia, Lars L. Schaaf, Gábor Csányi, Christoph Ortner, Felix A. Faber
2024Equivariant Scalar Fields for Molecular Docking with Fast Fourier Transforms.
Bowen Jing, Tommi S. Jaakkola, Bonnie Berger
2024Error Feedback Reloaded: From Quadratic to Arithmetic Mean of Smoothness Constants.
Peter Richtárik, Elnur Gasanov, Konstantin Burlachenko
2024Error Norm Truncation: Robust Training in the Presence of Data Noise for Text Generation Models.
Tianjian Li, Haoran Xu, Philipp Koehn, Daniel Khashabi, Kenton Murray
2024Escape Sky-high Cost: Early-stopping Self-Consistency for Multi-step Reasoning.
Yiwei Li, Peiwen Yuan, Shaoxiong Feng, Boyuan Pan, Xinglin Wang, Bin Sun, Heda Wang, Kan Li
2024Estimating Conditional Mutual Information for Dynamic Feature Selection.
Soham Gadgil, Ian Connick Covert, Su-In Lee
2024Estimating Shape Distances on Neural Representations with Limited Samples.
Dean A. Pospisil, Brett W. Larsen, Sarah E. Harvey, Alex H. Williams
2024Eureka: Human-Level Reward Design via Coding Large Language Models.
Yecheng Jason Ma, William Liang, Guanzhi Wang, De-An Huang, Osbert Bastani, Dinesh Jayaraman, Yuke Zhu, Linxi Fan, Anima Anandkumar
2024Evaluating Language Model Agency Through Negotiations.
Tim R. Davidson, Veniamin Veselovsky, Michal Kosinski, Robert West
2024Evaluating Large Language Models at Evaluating Instruction Following.
Zhiyuan Zeng, Jiatong Yu, Tianyu Gao, Yu Meng, Tanya Goyal, Danqi Chen
2024Evaluating Representation Learning on the Protein Structure Universe.
Arian Rokkum Jamasb, Alex Morehead, Chaitanya K. Joshi, Zuobai Zhang, Kieran Didi, Simon V. Mathis, Charles Harris, Jian Tang, Jianlin Cheng, Pietro Lio, Tom L. Blundell
2024Evaluating the Zero-shot Robustness of Instruction-tuned Language Models.
Jiuding Sun, Chantal Shaib, Byron C. Wallace
2024EventRPG: Event Data Augmentation with Relevance Propagation Guidance.
Mingyuan Sun, Donghao Zhang, Zongyuan Ge, Jiaxu Wang, Jia Li, Zheng Fang, Renjing Xu
2024Evoke: Evoking Critical Thinking Abilities in LLMs via Reviewer-Author Prompt Editing.
Xinyu Hu, Pengfei Tang, Simiao Zuo, Zihan Wang, Bowen Song, Qiang Lou, Jian Jiao, Denis Charles
2024ExeDec: Execution Decomposition for Compositional Generalization in Neural Program Synthesis.
Kensen Shi, Joey Hong, Yinlin Deng, Pengcheng Yin, Manzil Zaheer, Charles Sutton
2024Expected flow networks in stochastic environments and two-player zero-sum games.
Marco Jiralerspong, Bilun Sun, Danilo Vucetic, Tianyu Zhang, Yoshua Bengio, Gauthier Gidel, Nikolay Malkin
2024Experimental Design for Multi-Channel Imaging via Task-Driven Feature Selection.
Stefano B. Blumberg, Paddy J. Slator, Daniel C. Alexander
2024Explaining Kernel Clustering via Decision Trees.
Maximilian Fleissner, Leena Chennuru Vankadara, Debarghya Ghoshdastidar
2024Explaining Time Series via Contrastive and Locally Sparse Perturbations.
Zichuan Liu, Yingying Zhang, Tianchun Wang, Zefan Wang, Dongsheng Luo, Mengnan Du, Min Wu, Yi Wang, Chunlin Chen, Lunting Fan, Qingsong Wen
2024Exploiting Causal Graph Priors with Posterior Sampling for Reinforcement Learning.
Mirco Mutti, Riccardo De Santi, Marcello Restelli, Alexander Marx, Giorgia Ramponi
2024Exploring Diffusion Time-steps for Unsupervised Representation Learning.
Zhongqi Yue, Jiankun Wang, Qianru Sun, Lei Ji, Eric I-Chao Chang, Hanwang Zhang
2024Exploring Effective Stimulus Encoding via Vision System Modeling for Visual Prostheses.
Chuanqing Wang, Di Wu, Chaoming Fang, Jie Yang, Mohamad Sawan
2024Exploring Target Representations for Masked Autoencoders.
Xingbin Liu, Jinghao Zhou, Tao Kong, Xianming Lin, Rongrong Ji
2024Exploring Weight Balancing on Long-Tailed Recognition Problem.
Naoya Hasegawa, Issei Sato
2024Exploring the Common Appearance-Boundary Adaptation for Nighttime Optical Flow.
Hanyu Zhou, Yi Chang, Haoyue Liu, Wending Yan, Yuxing Duan, Zhiwei Shi, Luxin Yan
2024Exploring the Promise and Limits of Real-Time Recurrent Learning.
Kazuki Irie, Anand Gopalakrishnan, Jürgen Schmidhuber
2024Exploring the cloud of feature interaction scores in a Rashomon set.
Sichao Li, Rong Wang, Quanling Deng, Amanda S. Barnard
2024Exposing Text-Image Inconsistency Using Diffusion Models.
Mingzhen Huang, Shan Jia, Zhou Zhou, Yan Ju, Jialing Cai, Siwei Lyu
2024Expressive Losses for Verified Robustness via Convex Combinations.
Alessandro De Palma, Rudy Bunel, Krishnamurthy (Dj) Dvijotham, M. Pawan Kumar, Robert Stanforth, Alessio Lomuscio
2024Expressivity of ReLU-Networks under Convex Relaxations.
Maximilian Baader, Mark Niklas Müller, Yuhao Mao, Martin T. Vechev
2024Extending Power of Nature from Binary to Real-Valued Graph Learning in Real World.
Chunshu Wu, Ruibing Song, Chuan Liu, Yunan Yang, Ang Li, Michael C. Huang, Tong Geng
2024FFB: A Fair Fairness Benchmark for In-Processing Group Fairness Methods.
Xiaotian Han, Jianfeng Chi, Yu Chen, Qifan Wang, Han Zhao, Na Zou, Xia Hu
2024FITS: Modeling Time Series with 10k Parameters.
Zhijian Xu, Ailing Zeng, Qiang Xu
2024FLASK: Fine-grained Language Model Evaluation based on Alignment Skill Sets.
Seonghyeon Ye, Doyoung Kim, Sungdong Kim, Hyeonbin Hwang, Seungone Kim, Yongrae Jo, James Thorne, Juho Kim, Minjoon Seo
2024FLATTEN: optical FLow-guided ATTENtion for consistent text-to-video editing.
Yuren Cong, Mengmeng Xu, Christian Simon, Shoufa Chen, Jiawei Ren, Yanping Xie, Juan-Manuel Pérez-Rúa, Bodo Rosenhahn, Tao Xiang, Sen He
2024FLD: Fourier Latent Dynamics for Structured Motion Representation and Learning.
Chenhao Li, Elijah Stanger-Jones, Steve Heim, Sangbae Kim
2024FOSI: Hybrid First and Second Order Optimization.
Hadar Sivan, Moshe Gabel, Assaf Schuster
2024FROSTER: Frozen CLIP is A Strong Teacher for Open-Vocabulary Action Recognition.
Xiaohu Huang, Hao Zhou, Kun Yao, Kai Han
2024Facing the Elephant in the Room: Visual Prompt Tuning or Full finetuning?
Cheng Han, Qifan Wang, Yiming Cui, Wenguan Wang, Lifu Huang, Siyuan Qi, Dongfang Liu
2024Fair Classifiers that Abstain without Harm.
Tongxin Yin, Jean-Francois Ton, Ruocheng Guo, Yuanshun Yao, Mingyan Liu, Yang Liu
2024Fair and Efficient Contribution Valuation for Vertical Federated Learning.
Zhenan Fan, Huang Fang, Xinglu Wang, Zirui Zhou, Jian Pei, Michael P. Friedlander, Yong Zhang
2024FairSeg: A Large-Scale Medical Image Segmentation Dataset for Fairness Learning Using Segment Anything Model with Fair Error-Bound Scaling.
Yu Tian, Min Shi, Yan Luo, Ava Kouhana, Tobias Elze, Mengyu Wang
2024FairTune: Optimizing Parameter Efficient Fine Tuning for Fairness in Medical Image Analysis.
Raman Dutt, Ondrej Bohdal, Sotirios A. Tsaftaris, Timothy M. Hospedales
2024FairerCLIP: Debiasing CLIP's Zero-Shot Predictions using Functions in RKHSs.
Sepehr Dehdashtian, Lan Wang, Vishnu Boddeti
2024Faithful Explanations of Black-box NLP Models Using LLM-generated Counterfactuals.
Yair Ori Gat, Nitay Calderon, Amir Feder, Alexander Chapanin, Amit Sharma, Roi Reichart
2024Faithful Rule Extraction for Differentiable Rule Learning Models.
Xiaxia Wang, David Jaime Tena Cucala, Bernardo Cuenca Grau, Ian Horrocks
2024Faithful Vision-Language Interpretation via Concept Bottleneck Models.
Songning Lai, Lijie Hu, Junxiao Wang, Laure Berti-Équille, Di Wang
2024Faithful and Efficient Explanations for Neural Networks via Neural Tangent Kernel Surrogate Models.
Andrew Engel, Zhichao Wang, Natalie Frank, Ioana Dumitriu, Sutanay Choudhury, Anand D. Sarwate, Tony Chiang
2024Fake It Till Make It: Federated Learning with Consensus-Oriented Generation.
Rui Ye, Yaxin Du, Zhenyang Ni, Yanfeng Wang, Siheng Chen
2024Fantastic Gains and Where to Find Them: On the Existence and Prospect of General Knowledge Transfer between Any Pretrained Model.
Karsten Roth, Lukas Thede, A. Sophia Koepke, Oriol Vinyals, Olivier J. Hénaff, Zeynep Akata
2024Fantastic Generalization Measures are Nowhere to be Found.
Michael Gastpar, Ido Nachum, Jonathan Shafer, Thomas Weinberger
2024Fast Ensembling with Diffusion Schrödinger Bridge.
Hyunsu Kim, Jongmin Yoon, Juho Lee
2024Fast Equilibrium of SGD in Generic Situations.
Zhiyuan Liu, Yi Wang, Zhiren Wang
2024Fast Hyperboloid Decision Tree Algorithms.
Philippe Chlenski, Ethan Turok, Antonio Khalil Moretti, Itsik Pe'er
2024Fast Imitation via Behavior Foundation Models.
Matteo Pirotta, Andrea Tirinzoni, Ahmed Touati, Alessandro Lazaric, Yann Ollivier
2024Fast Updating Truncated SVD for Representation Learning with Sparse Matrices.
Haoran Deng, Yang Yang, Jiahe Li, Cheng Chen, Weihao Jiang, Shiliang Pu
2024Fast Value Tracking for Deep Reinforcement Learning.
Frank Shih, Faming Liang
2024Fast and unified path gradient estimators for normalizing flows.
Lorenz Vaitl, Ludwig Winkler, Lorenz Richter, Pan Kessel
2024Fast, Expressive SE(n) Equivariant Networks through Weight-Sharing in Position-Orientation Space.
Erik J. Bekkers, Sharvaree P. Vadgama, Rob Hesselink, Putri A. van der Linden, David W. Romero
2024Fast-DetectGPT: Efficient Zero-Shot Detection of Machine-Generated Text via Conditional Probability Curvature.
Guangsheng Bao, Yanbin Zhao, Zhiyang Teng, Linyi Yang, Yue Zhang
2024Fast-ELECTRA for Efficient Pre-training.
Chengyu Dong, Liyuan Liu, Hao Cheng, Jingbo Shang, Jianfeng Gao, Xiaodong Liu
2024Faster Approximation of Probabilistic and Distributional Values via Least Squares.
Weida Li, Yaoliang Yu
2024Faster Sampling from Log-Concave Densities over Polytopes via Efficient Linear Solvers.
Oren Mangoubi, Nisheeth K. Vishnoi
2024FasterViT: Fast Vision Transformers with Hierarchical Attention.
Ali Hatamizadeh, Greg Heinrich, Hongxu Yin, Andrew Tao, José M. Álvarez, Jan Kautz, Pavlo Molchanov
2024FeatUp: A Model-Agnostic Framework for Features at Any Resolution.
Stephanie Fu, Mark Hamilton, Laura E. Brandt, Axel Feldmann, Zhoutong Zhang, William T. Freeman
2024Feature Collapse.
Thomas Laurent, James von Brecht, Xavier Bresson
2024Feature emergence via margin maximization: case studies in algebraic tasks.
Depen Morwani, Benjamin L. Edelman, Costin-Andrei Oncescu, Rosie Zhao, Sham M. Kakade
2024Feature-aligned N-BEATS with Sinkhorn divergence.
Joonhun Lee, Myeongho Jeon, Myungjoo Kang, Kyunghyun Park
2024FedCDA: Federated Learning with Cross-rounds Divergence-aware Aggregation.
Haozhao Wang, Haoran Xu, Yichen Li, Yuan Xu, Ruixuan Li, Tianwei Zhang
2024FedCompass: Efficient Cross-Silo Federated Learning on Heterogeneous Client Devices Using a Computing Power-Aware Scheduler.
Zilinghan Li, Pranshu Chaturvedi, Shilan He, Han Chen, Gagandeep Singh, Volodymyr V. Kindratenko, Eliu A. Huerta, Kibaek Kim, Ravi K. Madduri
2024FedDA: Faster Adaptive Gradient Methods for Federated Constrained Optimization.
Junyi Li, Feihu Huang, Heng Huang
2024FedHyper: A Universal and Robust Learning Rate Scheduler for Federated Learning with Hypergradient Descent.
Ziyao Wang, Jianyu Wang, Ang Li
2024FedImpro: Measuring and Improving Client Update in Federated Learning.
Zhenheng Tang, Yonggang Zhang, Shaohuai Shi, Xinmei Tian, Tongliang Liu, Bo Han, Xiaowen Chu
2024FedInverse: Evaluating Privacy Leakage in Federated Learning.
Di Wu, Jun Bai, Yiliao Song, Junjun Chen, Wei Zhou, Yong Xiang, Atul Sajjanhar
2024FedLoGe: Joint Local and Generic Federated Learning under Long-tailed Data.
Zikai Xiao, Zihan Chen, Liyinglan Liu, Yang Feng, Joey Tianyi Zhou, Jian Wu, Wanlu Liu, Howard Hao Yang, Zuozhu Liu
2024FedP3: Federated Personalized and Privacy-friendly Network Pruning under Model Heterogeneity.
Kai Yi, Nidham Gazagnadou, Peter Richtárik, Lingjuan Lyu
2024FedTrans: Client-Transparent Utility Estimation for Robust Federated Learning.
Mingkun Yang, Ran Zhu, Qing Wang, Jie Yang
2024FedWon: Triumphing Multi-domain Federated Learning Without Normalization.
Weiming Zhuang, Lingjuan Lyu
2024Federated Causal Discovery from Heterogeneous Data.
Loka Li, Ignavier Ng, Gongxu Luo, Biwei Huang, Guangyi Chen, Tongliang Liu, Bin Gu, Kun Zhang
2024Federated Orthogonal Training: Mitigating Global Catastrophic Forgetting in Continual Federated Learning.
Yavuz Faruk Bakman, Duygu Nur Yaldiz, Yahya H. Ezzeldin, Salman Avestimehr
2024Federated Q-Learning: Linear Regret Speedup with Low Communication Cost.
Zhong Zheng, Fengyu Gao, Lingzhou Xue, Jing Yang
2024Federated Recommendation with Additive Personalization.
Zhiwei Li, Guodong Long, Tianyi Zhou
2024Federated Text-driven Prompt Generation for Vision-Language Models.
Chen Qiu, Xingyu Li, Chaithanya Kumar Mummadi, Madan Ravi Ganesh, Zhenzhen Li, Lu Peng, Wan-Yi Lin
2024Federated Wasserstein Distance.
Alain Rakotomamonjy, Kimia Nadjahi, Liva Ralaivola
2024Ferret: Refer and Ground Anything Anywhere at Any Granularity.
Haoxuan You, Haotian Zhang, Zhe Gan, Xianzhi Du, Bowen Zhang, Zirui Wang, Liangliang Cao, Shih-Fu Chang, Yinfei Yang
2024Few-Shot Detection of Machine-Generated Text using Style Representations.
Rafael A. Rivera Soto, Kailin Koch, Aleem Khan, Barry Y. Chen, Marcus Bishop, Nicholas Andrews
2024Few-shot Hybrid Domain Adaptation of Image Generator.
Hengjia Li, Yang Liu, Linxuan Xia, Yuqi Lin, Wenxiao Wang, Tu Zheng, Zheng Yang, Xiaohui Zhong, Xiaobo Ren, Xiaofei He
2024Fiber Monte Carlo.
Nick Richardson, Deniz Oktay, Yaniv Ovadia, James C. Bowden, Ryan P. Adams
2024Fine-Tuned Language Models Generate Stable Inorganic Materials as Text.
Nate Gruver, Anuroop Sriram, Andrea Madotto, Andrew Gordon Wilson, C. Lawrence Zitnick, Zachary W. Ulissi
2024Fine-Tuning Enhances Existing Mechanisms: A Case Study on Entity Tracking.
Nikhil Prakash, Tamar Rott Shaham, Tal Haklay, Yonatan Belinkov, David Bau
2024Fine-Tuning Language Models for Factuality.
Katherine Tian, Eric Mitchell, Huaxiu Yao, Christopher D. Manning, Chelsea Finn
2024Fine-tuning Aligned Language Models Compromises Safety, Even When Users Do Not Intend To!
Xiangyu Qi, Yi Zeng, Tinghao Xie, Pin-Yu Chen, Ruoxi Jia, Prateek Mittal, Peter Henderson
2024Fine-tuning Multimodal LLMs to Follow Zero-shot Demonstrative Instructions.
Juncheng Li, Kaihang Pan, Zhiqi Ge, Minghe Gao, Wei Ji, Wenqiao Zhang, Tat-Seng Chua, Siliang Tang, Hanwang Zhang, Yueting Zhuang
2024Finetuning Text-to-Image Diffusion Models for Fairness.
Xudong Shen, Chao Du, Tianyu Pang, Min Lin, Yongkang Wong, Mohan S. Kankanhalli
2024Finite Scalar Quantization: VQ-VAE Made Simple.
Fabian Mentzer, David Minnen, Eirikur Agustsson, Michael Tschannen
2024Finite-State Autoregressive Entropy Coding for Efficient Learned Lossless Compression.
Yufeng Zhang, Hang Yu, Jianguo Li, Weiyao Lin
2024Finite-Time Analysis of On-Policy Heterogeneous Federated Reinforcement Learning.
Chenyu Zhang, Han Wang, Aritra Mitra, James Anderson
2024First-order ANIL provably learns representations despite overparametrisation.
Oguz Kaan Yüksel, Etienne Boursier, Nicolas Flammarion
2024Fixed Non-negative Orthogonal Classifier: Inducing Zero-mean Neural Collapse with Feature Dimension Separation.
Hoyong Kim, Kangil Kim
2024Fixed-Budget Differentially Private Best Arm Identification.
Zhirui Chen, P. N. Karthik, Yeow Meng Chee, Vincent Y. F. Tan
2024Flag Aggregator: Scalable Distributed Training under Failures and Augmented Losses using Convex Optimization.
Hamidreza Almasi, Harsh Mishra, Balajee Vamanan, Sathya N. Ravi
2024FlashAttention-2: Faster Attention with Better Parallelism and Work Partitioning.
Tri Dao
2024FlashFFTConv: Efficient Convolutions for Long Sequences with Tensor Cores.
Daniel Y. Fu, Hermann Kumbong, Eric Nguyen, Christopher Ré
2024Flat Minima in Linear Estimation and an Extended Gauss Markov Theorem.
Simon N. Segert
2024Flow Matching on General Geometries.
Ricky T. Q. Chen, Yaron Lipman
2024Flow to Better: Offline Preference-based Reinforcement Learning via Preferred Trajectory Generation.
Zhilong Zhang, Yihao Sun, Junyin Ye, Tian-Shuo Liu, Jiaji Zhang, Yang Yu
2024Follow-Up Differential Descriptions: Language Models Resolve Ambiguities for Image Classification.
Reza Esfandiarpoor, Stephen H. Bach
2024Forward Learning of Graph Neural Networks.
Namyong Park, Xing Wang, Antoine Simoulin, Shuai Yang, Grey Yang, Ryan A. Rossi, Puja Trivedi, Nesreen K. Ahmed
2024Forward Learning with Top-Down Feedback: Empirical and Analytical Characterization.
Ravi Francesco Srinivasan, Francesca Mignacco, Martino Sorbaro, Maria Refinetti, Avi Cooper, Gabriel Kreiman, Giorgia Dellaferrera
2024Forward χ2 Divergence Based Variational Importance Sampling.
Chengrui Li, Yule Wang, Weihan Li, Anqi Wu
2024Foundation Model-oriented Robustness: Robust Image Model Evaluation with Pretrained Models.
Peiyan Zhang, Haoyang Liu, Chaozhuo Li, Xing Xie, Sunghun Kim, Haohan Wang
2024Fourier Transporter: Bi-Equivariant Robotic Manipulation in 3D.
Haojie Huang, Owen Howell, Dian Wang, Xupeng Zhu, Robert Platt, Robin Walters
2024Free from Bellman Completeness: Trajectory Stitching via Model-based Return-conditioned Supervised Learning.
Zhaoyi Zhou, Chuning Zhu, Runlong Zhou, Qiwen Cui, Abhishek Gupta, Simon Shaolei Du
2024FreeDyG: Frequency Enhanced Continuous-Time Dynamic Graph Model for Link Prediction.
Yuxing Tian, Yiyan Qi, Fan Guo
2024FreeNoise: Tuning-Free Longer Video Diffusion via Noise Rescheduling.
Haonan Qiu, Menghan Xia, Yong Zhang, Yingqing He, Xintao Wang, Ying Shan, Ziwei Liu
2024FreeReg: Image-to-Point Cloud Registration Leveraging Pretrained Diffusion Models and Monocular Depth Estimators.
Haiping Wang, Yuan Liu, Bing Wang, Yujing Sun, Zhen Dong, Wenping Wang, Bisheng Yang
2024Frequency-Aware Transformer for Learned Image Compression.
Han Li, Shaohui Li, Wenrui Dai, Chenglin Li, Junni Zou, Hongkai Xiong
2024From Bricks to Bridges: Product of Invariances to Enhance Latent Space Communication.
Irene Cannistraci, Luca Moschella, Marco Fumero, Valentino Maiorca, Emanuele Rodolà
2024From Graphs to Hypergraphs: Hypergraph Projection and its Reconstruction.
Yanbang Wang, Jon M. Kleinberg
2024From Latent Graph to Latent Topology Inference: Differentiable Cell Complex Module.
Claudio Battiloro, Indro Spinelli, Lev Telyatnikov, Michael M. Bronstein, Simone Scardapane, Paolo Di Lorenzo
2024From Molecules to Materials: Pre-training Large Generalizable Models for Atomic Property Prediction.
Nima Shoghi, Adeesh Kolluru, John R. Kitchin, Zachary W. Ulissi, C. Lawrence Zitnick, Brandon M. Wood
2024From Posterior Sampling to Meaningful Diversity in Image Restoration.
Noa Cohen, Hila Manor, Yuval Bahat, Tomer Michaeli
2024From Sparse to Soft Mixtures of Experts.
Joan Puigcerver, Carlos Riquelme Ruiz, Basil Mustafa, Neil Houlsby
2024From Zero to Turbulence: Generative Modeling for 3D Flow Simulation.
Marten Lienen, David Lüdke, Jan Hansen-Palmus, Stephan Günnemann
2024Frozen Transformers in Language Models Are Effective Visual Encoder Layers.
Ziqi Pang, Ziyang Xie, Yunze Man, Yu-Xiong Wang
2024Fully Hyperbolic Convolutional Neural Networks for Computer Vision.
Ahmad Bdeir, Kristian Schwethelm, Niels Landwehr
2024Function Vectors in Large Language Models.
Eric Todd, Millicent L. Li, Arnab Sen Sharma, Aaron Mueller, Byron C. Wallace, David Bau
2024Function-space Parameterization of Neural Networks for Sequential Learning.
Aidan Scannell, Riccardo Mereu, Paul Edmund Chang, Ella Tamir, Joni Pajarinen, Arno Solin
2024Functional Bayesian Tucker Decomposition for Continuous-indexed Tensor Data.
Shikai Fang, Xin Yu, Zheng Wang, Shibo Li, Mike Kirby, Shandian Zhe
2024Functional Interpolation for Relative Positions improves Long Context Transformers.
Shanda Li, Chong You, Guru Guruganesh, Joshua Ainslie, Santiago Ontañón, Manzil Zaheer, Sumit Sanghai, Yiming Yang, Sanjiv Kumar, Srinadh Bhojanapalli
2024Fusing Models with Complementary Expertise.
Hongyi Wang, Felipe Maia Polo, Yuekai Sun, Souvik Kundu, Eric P. Xing, Mikhail Yurochkin
2024Fusion Is Not Enough: Single Modal Attacks on Fusion Models for 3D Object Detection.
Zhiyuan Cheng, Hongjun Choi, Shiwei Feng, James Chenhao Liang, Guanhong Tao, Dongfang Liu, Michael Zuzak, Xiangyu Zhang
2024Future Language Modeling from Temporal Document History.
Changmao Li, Jeffrey Flanigan
2024G2N2 : Weisfeiler and Lehman go grammatical.
Jason Piquenot, Aldo Moscatelli, Maxime Berar, Pierre Héroux, Romain Raveaux, Jean-Yves Ramel, Sébastien Adam
2024GAFormer: Enhancing Timeseries Transformers Through Group-Aware Embeddings.
Jingyun Xiao, Ran Liu, Eva L. Dyer
2024GAIA: Zero-shot Talking Avatar Generation.
Tianyu He, Junliang Guo, Runyi Yu, Yuchi Wang, Jialiang Zhu, Kaikai An, Leyi Li, Xu Tan, Chunyu Wang, Han Hu, HsiangTao Wu, Sheng Zhao, Jiang Bian
2024GAIA: a benchmark for General AI Assistants.
Grégoire Mialon, Clémentine Fourrier, Thomas Wolf, Yann LeCun, Thomas Scialom
2024GENOME: Generative Neuro-Symbolic Visual Reasoning by Growing and Reusing Modules.
Zhenfang Chen, Rui Sun, Wenjun Liu, Yining Hong, Chuang Gan
2024GIM: Learning Generalizable Image Matcher From Internet Videos.
Xuelun Shen, Zhipeng Cai, Wei Yin, Matthias Müller, Zijun Li, Kaixuan Wang, Xiaozhi Chen, Cheng Wang
2024GIO: Gradient Information Optimization for Training Dataset Selection.
Dante Everaert, Christopher Potts
2024GNNBoundary: Towards Explaining Graph Neural Networks through the Lens of Decision Boundaries.
Xiaoqi Wang, Han-Wei Shen
2024GNNCert: Deterministic Certification of Graph Neural Networks against Adversarial Perturbations.
Zaishuo Xia, Han Yang, Binghui Wang, Jinyuan Jia
2024GNNX-BENCH: Unravelling the Utility of Perturbation-based GNN Explainers through In-depth Benchmarking.
Mert Kosan, Samidha Verma, Burouj Armgaan, Khushbu Pahwa, Ambuj K. Singh, Sourav Medya, Sayan Ranu
2024GNeRP: Gaussian-guided Neural Reconstruction of Reflective Objects with Noisy Polarization Priors.
Li Yang, Ruizheng Wu, Jiyong Li, Ying-Cong Chen
2024GOAt: Explaining Graph Neural Networks via Graph Output Attribution.
Shengyao Lu, Keith G. Mills, Jiao He, Bang Liu, Di Niu
2024GPAvatar: Generalizable and Precise Head Avatar from Image(s).
Xuangeng Chu, Yu Li, Ailing Zeng, Tianyu Yang, Lijian Lin, Yunfei Liu, Tatsuya Harada
2024GPT-4 Is Too Smart To Be Safe: Stealthy Chat with LLMs via Cipher.
Youliang Yuan, Wenxiang Jiao, Wenxuan Wang, Jen-tse Huang, Pinjia He, Shuming Shi, Zhaopeng Tu
2024GRANDE: Gradient-Based Decision Tree Ensembles for Tabular Data.
Sascha Marton, Stefan Lüdtke, Christian Bartelt, Heiner Stuckenschmidt
2024GROOT: Learning to Follow Instructions by Watching Gameplay Videos.
Shaofei Cai, Bowei Zhang, Zihao Wang, Xiaojian Ma, Anji Liu, Yitao Liang
2024GTA: A Geometry-Aware Attention Mechanism for Multi-View Transformers.
Takeru Miyato, Bernhard Jaeger, Max Welling, Andreas Geiger
2024GTMGC: Using Graph Transformer to Predict Molecule's Ground-State Conformation.
Guikun Xu, Yongquan Jiang, PengChuan Lei, Yan Yang, Jim Chen
2024Gaining Wisdom from Setbacks: Aligning Large Language Models via Mistake Analysis.
Kai Chen, Chunwei Wang, Kuo Yang, Jianhua Han, Lanqing Hong, Fei Mi, Hang Xu, Zhengying Liu, Wenyong Huang, Zhenguo Li, Dit-Yan Yeung, Lifeng Shang, Xin Jiang, Qun Liu
2024Game-Theoretic Robust Reinforcement Learning Handles Temporally-Coupled Perturbations.
Yongyuan Liang, Yanchao Sun, Ruijie Zheng, Xiangyu Liu, Benjamin Eysenbach, Tuomas Sandholm, Furong Huang, Stephen Marcus McAleer
2024Gen-Z: Generative Zero-Shot Text Classification with Contextualized Label Descriptions.
Sachin Kumar, Chan Young Park, Yulia Tsvetkov
2024GenCorres: Consistent Shape Matching via Coupled Implicit-Explicit Shape Generative Models.
Haitao Yang, Xiangru Huang, Bo Sun, Chandrajit L. Bajaj, Qixing Huang
2024GenSim: Generating Robotic Simulation Tasks via Large Language Models.
Lirui Wang, Yiyang Ling, Zhecheng Yuan, Mohit Shridhar, Chen Bao, Yuzhe Qin, Bailin Wang, Huazhe Xu, Xiaolong Wang
2024Gene Regulatory Network Inference in the Presence of Dropouts: a Causal View.
Haoyue Dai, Ignavier Ng, Gongxu Luo, Peter Spirtes, Petar Stojanov, Kun Zhang
2024GeneOH Diffusion: Towards Generalizable Hand-Object Interaction Denoising via Denoising Diffusion.
Xueyi Liu, Li Yi
2024General Graph Random Features.
Isaac Reid, Krzysztof Marcin Choromanski, Eli Berger, Adrian Weller
2024General Stability Analysis for Zeroth-Order Optimization Algorithms.
Xinyue Liu, Hualin Zhang, Bin Gu, Hong Chen
2024Generalization error of spectral algorithms.
Maksim Velikanov, Maxim Panov, Dmitry Yarotsky
2024Generalization in diffusion models arises from geometry-adaptive harmonic representations.
Zahra Kadkhodaie, Florentin Guth, Eero P. Simoncelli, Stéphane Mallat
2024Generalization of Scaled Deep ResNets in the Mean-Field Regime.
Yihang Chen, Fanghui Liu, Yiping Lu, Grigorios Chrysos, Volkan Cevher
2024Generalized Neural Sorting Networks with Error-Free Differentiable Swap Functions.
Jungtaek Kim, Jeongbeen Yoon, Minsu Cho
2024Generalized Policy Iteration using Tensor Approximation for Hybrid Control.
Suhan Shetty, Teng Xue, Sylvain Calinon
2024Generalized Schrödinger Bridge Matching.
Guan-Horng Liu, Yaron Lipman, Maximilian Nickel, Brian Karrer, Evangelos A. Theodorou, Ricky T. Q. Chen
2024Generating Images with 3D Annotations Using Diffusion Models.
Wufei Ma, Qihao Liu, Jiahao Wang, Angtian Wang, Xiaoding Yuan, Yi Zhang, Zihao Xiao, Guofeng Zhang, Beijia Lu, Ruxiao Duan, Yongrui Qi, Adam Kortylewski, Yaoyao Liu, Alan L. Yuille
2024Generating Pragmatic Examples to Train Neural Program Synthesizers.
Saujas Vaduguru, Daniel Fried, Yewen Pu
2024Generative Adversarial Equilibrium Solvers.
Denizalp Goktas, David C. Parkes, Ian Gemp, Luke Marris, Georgios Piliouras, Romuald Elie, Guy Lever, Andrea Tacchetti
2024Generative Human Motion Stylization in Latent Space.
Chuan Guo, Yuxuan Mu, Xinxin Zuo, Peng Dai, Youliang Yan, Juwei Lu, Li Cheng
2024Generative Judge for Evaluating Alignment.
Junlong Li, Shichao Sun, Weizhe Yuan, Run-Ze Fan, Hai Zhao, Pengfei Liu
2024Generative Learning for Financial Time Series with Irregular and Scale-Invariant Patterns.
Hongbin Huang, Minghua Chen, Xiao Qiao
2024Generative Learning for Solving Non-Convex Problem with Multi-Valued Input-Solution Mapping.
Enming Liang, Minghua Chen
2024Generative Modeling of Regular and Irregular Time Series Data via Koopman VAEs.
Ilan Naiman, N. Benjamin Erichson, Pu Ren, Michael W. Mahoney, Omri Azencot
2024Generative Modeling with Phase Stochastic Bridge.
Tianrong Chen, Jiatao Gu, Laurent Dinh, Evangelos A. Theodorou, Joshua M. Susskind, Shuangfei Zhai
2024Generative Pre-training for Speech with Flow Matching.
Alexander H. Liu, Matthew Le, Apoorv Vyas, Bowen Shi, Andros Tjandra, Wei-Ning Hsu
2024Generative Sliced MMD Flows with Riesz Kernels.
Johannes Hertrich, Christian Wald, Fabian Altekrüger, Paul Hagemann
2024GeoDiffusion: Text-Prompted Geometric Control for Object Detection Data Generation.
Kai Chen, Enze Xie, Zhe Chen, Yibo Wang, Lanqing Hong, Zhenguo Li, Dit-Yan Yeung
2024GeoLLM: Extracting Geospatial Knowledge from Large Language Models.
Rohin Manvi, Samar Khanna, Gengchen Mai, Marshall Burke, David B. Lobell, Stefano Ermon
2024Geographic Location Encoding with Spherical Harmonics and Sinusoidal Representation Networks.
Marc Rußwurm, Konstantin Klemmer, Esther Rolf, Robin Zbinden, Devis Tuia
2024Geometrically Aligned Transfer Encoder for Inductive Transfer in Regression Tasks.
Sung Moon Ko, Sumin Lee, Dae-Woong Jeong, Woohyung Lim, Sehui Han
2024Geometry-Aware Projective Mapping for Unbounded Neural Radiance Fields.
Junoh Lee, HyunJun Jung, Jin-Hwi Park, Inhwan Bae, Hae-Gon Jeon
2024Get What You Want, Not What You Don't: Image Content Suppression for Text-to-Image Diffusion Models.
Senmao Li, Joost van de Weijer, Taihang Hu, Fahad Shahbaz Khan, Qibin Hou, Yaxing Wang, Jian Yang
2024Get more for less: Principled Data Selection for Warming Up Fine-Tuning in LLMs.
Feiyang Kang, Hoang Anh Just, Yifan Sun, Himanshu Jahagirdar, Yuanzhi Zhang, Rongxing Du, Anit Kumar Sahu, Ruoxi Jia
2024Ghost on the Shell: An Expressive Representation of General 3D Shapes.
Zhen Liu, Yao Feng, Yuliang Xiu, Weiyang Liu, Liam Paull, Michael J. Black, Bernhard Schölkopf
2024Global Optimality for Non-linear Constrained Restoration Problems via Invexity.
Samuel Pinilla, Jeyan Thiyagalingam
2024GlucoBench: Curated List of Continuous Glucose Monitoring Datasets with Prediction Benchmarks.
Renat Sergazinov, Elizabeth Chun, Valeriya Rogovchenko, Nathaniel J. Fernandes, Nicholas Kasman, Irina Gaynanova
2024GoLLIE: Annotation Guidelines improve Zero-Shot Information-Extraction.
Oscar Sainz, Iker García-Ferrero, Rodrigo Agerri, Oier Lopez de Lacalle, German Rigau, Eneko Agirre
2024Going Beyond Neural Network Feature Similarity: The Network Feature Complexity and Its Interpretation Using Category Theory.
Yiting Chen, Zhanpeng Zhou, Junchi Yan
2024Goodhart's Law in Reinforcement Learning.
Jacek Karwowski, Oliver Hayman, Xingjian Bai, Klaus Kiendlhofer, Charlie Griffin, Joar Max Viktor Skalse
2024Gradual Domain Adaptation via Gradient Flow.
Zhan Zhuang, Yu Zhang, Ying Wei
2024Gradual Optimization Learning for Conformational Energy Minimization.
Artem Tsypin, Leonid Ugadiarov, Kuzma Khrabrov, Alexander Telepov, Egor Rumiantsev, Alexey Skrynnik, Aleksandr Panov, Dmitry P. Vetrov, Elena Tutubalina, Artur Kadurin
2024Graph Generation with K2-trees.
Yunhui Jang, Dongwoo Kim, Sungsoo Ahn
2024Graph Lottery Ticket Automated.
Guibin Zhang, Kun Wang, Wei Huang, Yanwei Yue, Yang Wang, Roger Zimmermann, Aojun Zhou, Dawei Cheng, Jin Zeng, Yuxuan Liang
2024Graph Metanetworks for Processing Diverse Neural Architectures.
Derek Lim, Haggai Maron, Marc T. Law, Jonathan Lorraine, James Lucas
2024Graph Neural Networks for Learning Equivariant Representations of Neural Networks.
Miltiadis Kofinas, Boris Knyazev, Yan Zhang, Yunlu Chen, Gertjan J. Burghouts, Efstratios Gavves, Cees G. M. Snoek, David W. Zhang
2024Graph Parsing Networks.
Yunchong Song, Siyuan Huang, Xinbing Wang, Chenghu Zhou, Zhouhan Lin
2024Graph Transformers on EHRs: Better Representation Improves Downstream Performance.
Raphael Poulain, Rahmatollah Beheshti
2024Graph-based Virtual Sensing from Sparse and Partial Multivariate Observations.
Giovanni de Felice, Andrea Cini, Daniele Zambon, Vladimir V. Gusev, Cesare Alippi
2024Graph-constrained diffusion for End-to-End Path Planning.
Dingyuan Shi, Yongxin Tong, Zimu Zhou, Ke Xu, Zheng Wang, Jieping Ye
2024GraphCare: Enhancing Healthcare Predictions with Personalized Knowledge Graphs.
Pengcheng Jiang, Cao Xiao, Adam Cross, Jimeng Sun
2024GraphChef: Decision-Tree Recipes to Explain Graph Neural Networks.
Peter Müller, Lukas Faber, Karolis Martinkus, Roger Wattenhofer
2024GraphPulse: Topological representations for temporal graph property prediction.
Kiarash Shamsi, Farimah Poursafaei, Shenyang Huang, Tran Gia Bao Ngo, Baris Coskunuzer, Cuneyt Gurcan Akcora
2024Graphical Multioutput Gaussian Process with Attention.
Yijue Dai, Wenzhong Yan, Feng Yin
2024Grokking as a First Order Phase Transition in Two Layer Networks.
Noa Rubin, Inbar Seroussi, Zohar Ringel
2024Grokking as the transition from lazy to rich training dynamics.
Tanishq Kumar, Blake Bordelon, Samuel J. Gershman, Cengiz Pehlevan
2024Grokking in Linear Estimators - A Solvable Model that Groks without Understanding.
Noam Itzhak Levi, Alon Beck, Yohai Bar-Sinai
2024Ground-A-Video: Zero-shot Grounded Video Editing using Text-to-image Diffusion Models.
Hyeonho Jeong, Jong Chul Ye
2024Grounded Object-Centric Learning.
Avinash Kori, Francesco Locatello, Fabio De Sousa Ribeiro, Francesca Toni, Ben Glocker
2024Grounding Language Plans in Demonstrations Through Counterfactual Perturbations.
Yanwei Wang, Tsun-Hsuan Wang, Jiayuan Mao, Michael Hagenow, Julie Shah
2024Grounding Multimodal Large Language Models to the World.
Zhiliang Peng, Wenhui Wang, Li Dong, Yaru Hao, Shaohan Huang, Shuming Ma, Qixiang Ye, Furu Wei
2024Group Preference Optimization: Few-Shot Alignment of Large Language Models.
Siyan Zhao, John Dang, Aditya Grover
2024Guaranteed Approximation Bounds for Mixed-Precision Neural Operators.
Renbo Tu, Colin White, Jean Kossaifi, Boris Bonev, Gennady Pekhimenko, Kamyar Azizzadenesheli, Anima Anandkumar
2024Guess & Sketch: Language Model Guided Transpilation.
Celine Lee, Abdulrahman Mahmoud, Michal Kurek, Simone Campanoni, David Brooks, Stephen Chong, Gu-Yeon Wei, Alexander M. Rush
2024Guiding Instruction-based Image Editing via Multimodal Large Language Models.
Tsu-Jui Fu, Wenze Hu, Xianzhi Du, William Yang Wang, Yinfei Yang, Zhe Gan
2024Guiding Masked Representation Learning to Capture Spatio-Temporal Relationship of Electrocardiogram.
Yeongyeon Na, Minje Park, Yunwon Tae, Sunghoon Joo
2024H-GAP: Humanoid Control with a Generalist Planner.
Zhengyao Jiang, Yingchen Xu, Nolan Wagener, Yicheng Luo, Michael Janner, Edward Grefenstette, Tim Rocktäschel, Yuandong Tian
2024H2O-SDF: Two-phase Learning for 3D Indoor Reconstruction using Object Surface Fields.
Minyoung Park, Mirae Do, YeonJae Shin, Jaeseok Yoo, Jongkwang Hong, Joongrock Kim, Chul Lee
2024HAZARD Challenge: Embodied Decision Making in Dynamically Changing Environments.
Qinhong Zhou, Sunli Chen, Yisong Wang, Haozhe Xu, Weihua Du, Hongxin Zhang, Yilun Du, Joshua B. Tenenbaum, Chuang Gan
2024HIFA: High-fidelity Text-to-3D Generation with Advanced Diffusion Guidance.
Junzhe Zhu, Peiye Zhuang, Sanmi Koyejo
2024HYPO: Hyperspherical Out-Of-Distribution Generalization.
Haoyue Bai, Yifei Ming, Julian Katz-Samuels, Yixuan Li
2024Habitat 3.0: A Co-Habitat for Humans, Avatars, and Robots.
Xavier Puig, Eric Undersander, Andrew Szot, Mikael Dallaire Cote, Tsung-Yen Yang, Ruslan Partsey, Ruta Desai, Alexander Clegg, Michal Hlavac, So Yeon Min, Vladimir Vondrus, Théophile Gervet, Vincent-Pierre Berges, John M. Turner, Oleksandr Maksymets, Zsolt Kira, Mrinal Kalakrishnan, Jitendra Malik, Devendra Singh Chaplot, Unnat Jain, Dhruv Batra, Akshara Rai, Roozbeh Mottaghi
2024Harnessing Density Ratios for Online Reinforcement Learning.
Philip Amortila, Dylan J. Foster, Nan Jiang, Ayush Sekhari, Tengyang Xie
2024Harnessing Explanations: LLM-to-LM Interpreter for Enhanced Text-Attributed Graph Representation Learning.
Xiaoxin He, Xavier Bresson, Thomas Laurent, Adam Perold, Yann LeCun, Bryan Hooi
2024Harnessing Joint Rain-/Detail-aware Representations to Eliminate Intricate Rains.
Wu Ran, Peirong Ma, Zhiquan He, Hao Ren, Hong Lu
2024Headless Language Models: Learning without Predicting with Contrastive Weight Tying.
Nathan Godey, Éric Villemonte de la Clergerie, Benoît Sagot
2024Hebbian Learning based Orthogonal Projection for Continual Learning of Spiking Neural Networks.
Mingqing Xiao, Qingyan Meng, Zongpeng Zhang, Di He, Zhouchen Lin
2024Heterogeneous Personalized Federated Learning by Local-Global Updates Mixing via Convergence Rate.
Meirui Jiang, Anjie Le, Xiaoxiao Li, Qi Dou
2024HiGen: Hierarchical Graph Generative Networks.
Mahdi Karami
2024Hiding in Plain Sight: Disguising Data Stealing Attacks in Federated Learning.
Kostadin Garov, Dimitar Iliev Dimitrov, Nikola Jovanovic, Martin T. Vechev
2024Hierarchical Context Merging: Better Long Context Understanding for Pre-trained LLMs.
Woomin Song, Seunghyuk Oh, Sangwoo Mo, Jaehyung Kim, Sukmin Yun, Jung-Woo Ha, Jinwoo Shin
2024High-dimensional SGD aligns with emerging outlier eigenspaces.
Gérard Ben Arous, Reza Gheissari, Jiaoyang Huang, Aukosh Jagannath
2024Hindsight PRIORs for Reward Learning from Human Preferences.
Mudit Verma, Katherine Metcalf
2024HoloNets: Spectral Convolutions do extend to Directed Graphs.
Christian Koke, Daniel Cremers
2024Horizon-Free Regret for Linear Markov Decision Processes.
Zihan Zhang, Jason D. Lee, Yuxin Chen, Simon Shaolei Du
2024Horizon-free Reinforcement Learning in Adversarial Linear Mixture MDPs.
Kaixuan Ji, Qingyue Zhao, Jiafan He, Weitong Zhang, Quanquan Gu
2024How Do Transformers Learn In-Context Beyond Simple Functions? A Case Study on Learning with Representations.
Tianyu Guo, Wei Hu, Song Mei, Huan Wang, Caiming Xiong, Silvio Savarese, Yu Bai
2024How Does Unlabeled Data Provably Help Out-of-Distribution Detection?
Xuefeng Du, Zhen Fang, Ilias Diakonikolas, Yixuan Li
2024How I Warped Your Noise: a Temporally-Correlated Noise Prior for Diffusion Models.
Pascal Chang, Jingwei Tang, Markus Gross, Vinicius C. Azevedo
2024How Many Pretraining Tasks Are Needed for In-Context Learning of Linear Regression?
Jingfeng Wu, Difan Zou, Zixiang Chen, Vladimir Braverman, Quanquan Gu, Peter L. Bartlett
2024How Over-Parameterization Slows Down Gradient Descent in Matrix Sensing: The Curses of Symmetry and Initialization.
Nuoya Xiong, Lijun Ding, Simon Shaolei Du
2024How Realistic Is Your Synthetic Data? Constraining Deep Generative Models for Tabular Data.
Mihaela C. Stoian, Salijona Dyrmishi, Maxime Cordy, Thomas Lukasiewicz, Eleonora Giunchiglia
2024How Well Do Supervised 3D Models Transfer to Medical Imaging Tasks?
Wenxuan Li, Alan L. Yuille, Zongwei Zhou
2024How connectivity structure shapes rich and lazy learning in neural circuits.
Yuhan Helena Liu, Aristide Baratin, Jonathan Cornford, Stefan Mihalas, Eric Shea-Brown, Guillaume Lajoie
2024How do Language Models Bind Entities in Context?
Jiahai Feng, Jacob Steinhardt
2024How to Capture Higher-order Correlations? Generalizing Matrix Softmax Attention to Kronecker Computation.
Josh Alman, Zhao Song
2024How to Catch an AI Liar: Lie Detection in Black-Box LLMs by Asking Unrelated Questions.
Lorenzo Pacchiardi, Alex James Chan, Sören Mindermann, Ilan Moscovitz, Alexa Y. Pan, Yarin Gal, Owain Evans, Jan Markus Brauner
2024How to Fine-Tune Vision Models with SGD.
Ananya Kumar, Ruoqi Shen, Sébastien Bubeck, Suriya Gunasekar
2024Human Feedback is not Gold Standard.
Tom Hosking, Phil Blunsom, Max Bartolo
2024Human Motion Diffusion as a Generative Prior.
Yoni Shafir, Guy Tevet, Roy Kapon, Amit Haim Bermano
2024Hybrid Directional Graph Neural Network for Molecules.
Junyi An, Chao Qu, Zhipeng Zhou, Fenglei Cao, Yinghui Xu, Yuan Qi, Furao Shen
2024Hybrid Distillation: Connecting Masked Autoencoders with Contrastive Learners.
Bowen Shi, Xiaopeng Zhang, Yaoming Wang, Jin Li, Wenrui Dai, Junni Zou, Hongkai Xiong, Qi Tian
2024Hybrid Internal Model: Learning Agile Legged Locomotion with Simulated Robot Response.
Junfeng Long, Zirui Wang, Quanyi Li, Liu Cao, Jiawei Gao, Jiangmiao Pang
2024Hybrid LLM: Cost-Efficient and Quality-Aware Query Routing.
Dujian Ding, Ankur Mallick, Chi Wang, Robert Sim, Subhabrata Mukherjee, Victor Rühle, Laks V. S. Lakshmanan, Ahmed Hassan Awadallah
2024Hybrid Sharing for Multi-Label Image Classification.
Zihao Yin, Chen Gan, Kelei He, Yang Gao, Junfeng Zhang
2024HypeBoy: Generative Self-Supervised Representation Learning on Hypergraphs.
Sunwoo Kim, Shinhwan Kang, Fanchen Bu, Soo Yong Lee, Jaemin Yoo, Kijung Shin
2024Hyper Evidential Deep Learning to Quantify Composite Classification Uncertainty.
Changbin Li, Kangshuo Li, Yuzhe Ou, Lance M. Kaplan, Audun Jøsang, Jin-Hee Cho, Dong Hyun Jeong, Feng Chen
2024HyperAttention: Long-context Attention in Near-Linear Time.
Insu Han, Rajesh Jayaram, Amin Karbasi, Vahab Mirrokni, David P. Woodruff, Amir Zandieh
2024HyperHuman: Hyper-Realistic Human Generation with Latent Structural Diffusion.
Xian Liu, Jian Ren, Aliaksandr Siarohin, Ivan Skorokhodov, Yanyu Li, Dahua Lin, Xihui Liu, Ziwei Liu, Sergey Tulyakov
2024Hypergraph Dynamic System.
Jielong Yan, Yifan Feng, Shihui Ying, Yue Gao
2024Hypothesis Search: Inductive Reasoning with Language Models.
Ruocheng Wang, Eric Zelikman, Gabriel Poesia, Yewen Pu, Nick Haber, Noah D. Goodman
2024I-PHYRE: Interactive Physical Reasoning.
Shiqian Li, Kewen Wu, Chi Zhang, Yixin Zhu
2024IDEAL: Influence-Driven Selective Annotations Empower In-Context Learners in Large Language Models.
Shaokun Zhang, Xiaobo Xia, Zhaoqing Wang, Ling-Hao Chen, Jiale Liu, Qingyun Wu, Tongliang Liu
2024IMPUS: Image Morphing with Perceptually-Uniform Sampling Using Diffusion Models.
Zhaoyuan Yang, Zhengyang Yu, Zhiwei Xu, Jaskirat Singh, Jing Zhang, Dylan Campbell, Peter H. Tu, Richard Hartley
2024INSIDE: LLMs' Internal States Retain the Power of Hallucination Detection.
Chao Chen, Kai Liu, Ze Chen, Yi Gu, Yue Wu, Mingyuan Tao, Zhihang Fu, Jieping Ye
2024INViTE: INterpret and Control Vision-Language Models with Text Explanations.
Haozhe Chen, Junfeng Yang, Carl Vondrick, Chengzhi Mao
2024IRAD: Implicit Representation-driven Image Resampling against Adversarial Attacks.
Yue Cao, Tianlin Li, Xiaofeng Cao, Ivor W. Tsang, Yang Liu, Qing Guo
2024IceFormer: Accelerated Inference with Long-Sequence Transformers on CPUs.
Yuzhen Mao, Martin Ester, Ke Li
2024Idempotence and Perceptual Image Compression.
Tongda Xu, Ziran Zhu, Dailan He, Yanghao Li, Lina Guo, Yuanyuan Wang, Zhe Wang, Hongwei Qin, Yan Wang, Jingjing Liu, Ya-Qin Zhang
2024Idempotent Generative Network.
Assaf Shocher, Amil Dravid, Yossi Gandelsman, Inbar Mosseri, Michael Rubinstein, Alexei A. Efros
2024Identifiable Latent Polynomial Causal Models through the Lens of Change.
Yuhang Liu, Zhen Zhang, Dong Gong, Mingming Gong, Biwei Huang, Anton van den Hengel, Kun Zhang, Javen Qinfeng Shi
2024Identifying Policy Gradient Subspaces.
Jan Schneider, Pierre Schumacher, Simon Guist, Le Chen, Daniel F. B. Haeufle, Bernhard Schölkopf, Dieter Büchler
2024Identifying Representations for Intervention Extrapolation.
Sorawit Saengkyongam, Elan Rosenfeld, Pradeep Kumar Ravikumar, Niklas Pfister, Jonas Peters
2024Identifying the Risks of LM Agents with an LM-Emulated Sandbox.
Yangjun Ruan, Honghua Dong, Andrew Wang, Silviu Pitis, Yongchao Zhou, Jimmy Ba, Yann Dubois, Chris J. Maddison, Tatsunori Hashimoto
2024Illusory Attacks: Information-theoretic detectability matters in adversarial attacks.
Tim Franzmeyer, Stephen Marcus McAleer, João F. Henriques, Jakob Nicolaus Foerster, Philip Torr, Adel Bibi, Christian Schröder de Witt
2024Image Background Serves as Good Proxy for Out-of-distribution Data.
Sen Pei
2024Image Clustering Conditioned on Text Criteria.
Sehyun Kwon, Jaeseung Park, Minkyu Kim, Jaewoong Cho, Ernest K. Ryu, Kangwook Lee
2024Image Clustering via the Principle of Rate Reduction in the Age of Pretrained Models.
Tianzhe Chu, Shengbang Tong, Tianjiao Ding, Xili Dai, Benjamin David Haeffele, René Vidal, Yi Ma
2024Image Inpainting via Iteratively Decoupled Probabilistic Modeling.
Wenbo Li, Xin Yu, Kun Zhou, Yibing Song, Zhe Lin
2024Image Inpainting via Tractable Steering of Diffusion Models.
Anji Liu, Mathias Niepert, Guy Van den Broeck
2024Image Translation as Diffusion Visual Programmers.
Cheng Han, James Chenhao Liang, Qifan Wang, Majid Rabbani, Sohail A. Dianat, Raghuveer Rao, Ying Nian Wu, Dongfang Liu
2024Image2Sentence based Asymmetrical Zero-shot Composed Image Retrieval.
Yongchao Du, Min Wang, Wengang Zhou, Shuping Hui, Houqiang Li
2024ImageNet-OOD: Deciphering Modern Out-of-Distribution Detection Algorithms.
William Yang, Byron Zhang, Olga Russakovsky
2024ImagenHub: Standardizing the evaluation of conditional image generation models.
Max Ku, Tianle Li, Kai Zhang, Yujie Lu, Xingyu Fu, Wenwen Zhuang, Wenhu Chen
2024Imitation Learning from Observation with Automatic Discount Scheduling.
Yuyang Liu, Weijun Dong, Yingdong Hu, Chuan Wen, Zhao-Heng Yin, Chongjie Zhang, Yang Gao
2024Impact of Computation in Integral Reinforcement Learning for Continuous-Time Control.
Wenhan Cao, Wei Pan
2024Implicit Gaussian process representation of vector fields over arbitrary latent manifolds.
Robert L. Peach, Matteo Vinao-Carl, Nir Grossman, Michael David, Emma Mallas, David J. Sharp, Paresh A. Malhotra, Pierre Vandergheynst, Adam Gosztolai
2024Implicit Maximum a Posteriori Filtering via Adaptive Optimization.
Gianluca M. Bencomo, Jake Snell, Thomas L. Griffiths
2024Implicit Neural Representation Inference for Low-Dimensional Bayesian Deep Learning.
Panagiotis Dimitrakopoulos, Giorgos Sfikas, Christophoros Nikou
2024Implicit Neural Representations and the Algebra of Complex Wavelets.
T. Mitchell Roddenberry, Vishwanath Saragadam, Maarten V. de Hoop, Richard G. Baraniuk
2024Implicit bias of SGD in L2-regularized linear DNNs: One-way jumps from high to low rank.
Zihan Wang, Arthur Jacot
2024Implicit regularization of deep residual networks towards neural ODEs.
Pierre Marion, Yu-Han Wu, Michael Eli Sander, Gérard Biau
2024ImplicitSLIM and How it Improves Embedding-based Collaborative Filtering.
Ilya Shenbin, Sergey I. Nikolenko
2024Improved Active Learning via Dependent Leverage Score Sampling.
Atsushi Shimizu, Xiaoou Cheng, Christopher Musco, Jonathan Weare
2024Improved Analysis of Sparse Linear Regression in Local Differential Privacy Model.
Liyang Zhu, Meng Ding, Vaneet Aggarwal, Jinhui Xu, Di Wang
2024Improved Efficiency Based on Learned Saccade and Continuous Scene Reconstruction From Foveated Visual Sampling.
Jiayang Liu, Yiming Bu, Daniel Tso, Qinru Qiu
2024Improved Probabilistic Image-Text Representations.
Sanghyuk Chun
2024Improved Regret Bounds for Non-Convex Online-Within-Online Meta Learning.
Jiechao Guan, Hui Xiong
2024Improved Techniques for Training Consistency Models.
Yang Song, Prafulla Dhariwal
2024Improved algorithm and bounds for successive projection.
Jiashun Jin, Zheng Tracy Ke, Gabriel Moryoussef, Jiajun Tang, Jingming Wang
2024Improved sampling via learned diffusions.
Lorenz Richter, Julius Berner
2024Improved statistical and computational complexity of the mean-field Langevin dynamics under structured data.
Atsushi Nitanda, Kazusato Oko, Taiji Suzuki, Denny Wu
2024Improving Convergence and Generalization Using Parameter Symmetries.
Bo Zhao, Robert M. Gower, Robin Walters, Rose Yu
2024Improving Domain Generalization with Domain Relations.
Huaxiu Yao, Xinyu Yang, Xinyi Pan, Shengchao Liu, Pang Wei Koh, Chelsea Finn
2024Improving Generalization of Alignment with Human Preferences through Group Invariant Learning.
Rui Zheng, Wei Shen, Yuan Hua, Wenbin Lai, Shihan Dou, Yuhao Zhou, Zhiheng Xi, Xiao Wang, Haoran Huang, Tao Gui, Qi Zhang, Xuanjing Huang
2024Improving Intrinsic Exploration by Creating Stationary Objectives.
Roger Creus Castanyer, Joshua Romoff, Glen Berseth
2024Improving LoRA in Privacy-preserving Federated Learning.
Youbang Sun, Zitao Li, Yaliang Li, Bolin Ding
2024Improving Non-Transferable Representation Learning by Harnessing Content and Style.
Ziming Hong, Zhenyi Wang, Li Shen, Yu Yao, Zhuo Huang, Shiming Chen, Chuanwu Yang, Mingming Gong, Tongliang Liu
2024Improving Offline RL by Blending Heuristics.
Sinong Geng, Aldo Pacchiano, Andrey Kolobov, Ching-An Cheng
2024Improving equilibrium propagation without weight symmetry through Jacobian homeostasis.
Axel Laborieux, Friedemann Zenke
2024Improving protein optimization with smoothed fitness landscapes.
Andrew Kirjner, Jason Yim, Raman Samusevich, Shahar Bracha, Tommi S. Jaakkola, Regina Barzilay, Ila R. Fiete
2024Improving the Convergence of Dynamic NeRFs via Optimal Transport.
Sameera Ramasinghe, Violetta Shevchenko, Gil Avraham, Hisham Husain, Anton van den Hengel
2024In defense of parameter sharing for model-compression.
Aditya Desai, Anshumali Shrivastava
2024In-Context Learning Dynamics with Random Binary Sequences.
Eric J. Bigelow, Ekdeep Singh Lubana, Robert P. Dick, Hidenori Tanaka, Tomer D. Ullman
2024In-Context Learning Learns Label Relationships but Is Not Conventional Learning.
Jannik Kossen, Yarin Gal, Tom Rainforth
2024In-Context Learning through the Bayesian Prism.
Madhur Panwar, Kabir Ahuja, Navin Goyal
2024In-Context Pretraining: Language Modeling Beyond Document Boundaries.
Weijia Shi, Sewon Min, Maria Lomeli, Chunting Zhou, Margaret Li, Xi Victoria Lin, Noah A. Smith, Luke Zettlemoyer, Wen-tau Yih, Mike Lewis
2024In-context Autoencoder for Context Compression in a Large Language Model.
Tao Ge, Jing Hu, Lei Wang, Xun Wang, Si-Qing Chen, Furu Wei
2024In-context Exploration-Exploitation for Reinforcement Learning.
Zhenwen Dai, Federico Tomasi, Sina Ghiassian
2024Incentive-Aware Federated Learning with Training-Time Model Rewards.
Zhaoxuan Wu, Mohammad Mohammadi Amiri, Ramesh Raskar, Bryan Kian Hsiang Low
2024Incentivized Truthful Communication for Federated Bandits.
Zhepei Wei, Chuanhao Li, Tianze Ren, Haifeng Xu, Hongning Wang
2024Increasing Model Capacity for Free: A Simple Strategy for Parameter Efficient Fine-tuning.
Haobo Song, Hao Zhao, Soumajit Majumder, Tao Lin
2024Incremental Randomized Smoothing Certification.
Shubham Ugare, Tarun Suresh, Debangshu Banerjee, Gagandeep Singh, Sasa Misailovic
2024Independent-Set Design of Experiments for Estimating Treatment and Spillover Effects under Network Interference.
Chencheng Cai, Xu Zhang, Edoardo M. Airoldi
2024Inducing High Energy-Latency of Large Vision-Language Models with Verbose Images.
Kuofeng Gao, Yang Bai, Jindong Gu, Shu-Tao Xia, Philip Torr, Zhifeng Li, Wei Liu
2024Influencer Backdoor Attack on Semantic Segmentation.
Haoheng Lan, Jindong Gu, Philip Torr, Hengshuang Zhao
2024InfoBatch: Lossless Training Speed Up by Unbiased Dynamic Data Pruning.
Ziheng Qin, Kai Wang, Zangwei Zheng, Jianyang Gu, Xiangyu Peng, Zhaopan Xu, Daquan Zhou, Lei Shang, Baigui Sun, Xuansong Xie, Yang You
2024InfoCon: Concept Discovery with Generative and Discriminative Informativeness.
Ruizhe Liu, Qian Luo, Yanchao Yang
2024Information Bottleneck Analysis of Deep Neural Networks via Lossy Compression.
Ivan Butakov, Aleksander Tolmachev, Sofia Malanchuk, Anna Neopryatnaya, Alexey A. Frolov, Kirill Andreev
2024Information Retention via Learning Supplemental Features.
Zhipeng Xie, Yahe Li
2024Inherently Interpretable Time Series Classification via Multiple Instance Learning.
Joseph Early, Gavin K. C. Cheung, Kurt Cutajar, Hanting Xie, Jas Kandola, Niall Twomey
2024Initializing Models with Larger Ones.
Zhiqiu Xu, Yanjie Chen, Kirill Vishniakov, Yida Yin, Zhiqiang Shen, Trevor Darrell, Lingjie Liu, Zhuang Liu
2024Inner Classifier-Free Guidance and Its Taylor Expansion for Diffusion Models.
Shikun Sun, Longhui Wei, Zhicai Wang, Zixuan Wang, Junliang Xing, Jia Jia, Qi Tian
2024Input-gradient space particle inference for neural network ensembles.
Trung Q. Trinh, Markus Heinonen, Luigi Acerbi, Samuel Kaski
2024Ins-DetCLIP: Aligning Detection Model to Follow Human-Language Instruction.
Renjie Pi, Lewei Yao, Jianhua Han, Xiaodan Liang, Wei Zhang, Hang Xu
2024InsertNeRF: Instilling Generalizability into NeRF with HyperNet Modules.
Yanqi Bao, Tianyu Ding, Jing Huo, Wenbin Li, Yuxin Li, Yang Gao
2024InstaFlow: One Step is Enough for High-Quality Diffusion-Based Text-to-Image Generation.
Xingchao Liu, Xiwen Zhang, Jianzhu Ma, Jian Peng, Qiang Liu
2024Instant3D: Fast Text-to-3D with Sparse-view Generation and Large Reconstruction Model.
Jiahao Li, Hao Tan, Kai Zhang, Zexiang Xu, Fujun Luan, Yinghao Xu, Yicong Hong, Kalyan Sunkavalli, Greg Shakhnarovich, Sai Bi
2024InstructCV: Instruction-Tuned Text-to-Image Diffusion Models as Vision Generalists.
Yulu Gan, Sungwoo Park, Alexander Schubert, Anthony Philippakis, Ahmed M. Alaa
2024InstructDET: Diversifying Referring Object Detection with Generalized Instructions.
Ronghao Dang, Jiangyan Feng, Haodong Zhang, Chongjian Ge, Lin Song, Lijun Gong, Chengju Liu, Qijun Chen, Feng Zhu, Rui Zhao, Yibing Song
2024InstructPix2NeRF: Instructed 3D Portrait Editing from a Single Image.
Jianhui Li, Shilong Liu, Zidong Liu, Yikai Wang, Kaiwen Zheng, Jinghui Xu, Jianmin Li, Jun Zhu
2024InstructScene: Instruction-Driven 3D Indoor Scene Synthesis with Semantic Graph Prior.
Chenguo Lin, Yadong Mu
2024Instructive Decoding: Instruction-Tuned Large Language Models are Self-Refiner from Noisy Instructions.
Taehyeon Kim, Joonkee Kim, Gihun Lee, Se-Young Yun
2024Integrating Planning and Deep Reinforcement Learning via Automatic Induction of Task Substructures.
Jung-Chun Liu, Chi-Hsien Chang, Shao-Hua Sun, Tian-Li Yu
2024Intelligent Switching for Reset-Free RL.
Darshan Patil, Janarthanan Rajendran, Glen Berseth, Sarath Chandar
2024InternVid: A Large-scale Video-Text Dataset for Multimodal Understanding and Generation.
Yi Wang, Yinan He, Yizhuo Li, Kunchang Li, Jiashuo Yu, Xin Ma, Xinhao Li, Guo Chen, Xinyuan Chen, Yaohui Wang, Ping Luo, Ziwei Liu, Yali Wang, Limin Wang, Yu Qiao
2024Internal Cross-layer Gradients for Extending Homogeneity to Heterogeneity in Federated Learning.
Yun-Hin Chan, Rui Zhou, Running Zhao, Zhihan Jiang, Edith C. H. Ngai
2024InterpGNN: Understand and Improve Generalization Ability of Transdutive GNNs through the Lens of Interplay between Train and Test Nodes.
Jiawei Sun, Kailai Li, Ruoxin Chen, Jie Li, Chentao Wu, Yue Ding, Junchi Yan
2024Interpretable Diffusion via Information Decomposition.
Xianghao Kong, Ollie Liu, Han Li, Dani Yogatama, Greg Ver Steeg
2024Interpretable Meta-Learning of Physical Systems.
Matthieu Blanke, Marc Lelarge
2024Interpretable Sparse System Identification: Beyond Recent Deep Learning Techniques on Time-Series Prediction.
Xiaoyi Liu, Duxin Chen, Wenjia Wei, Xia Zhu, Wenwu Yu
2024Interpreting CLIP's Image Representation via Text-Based Decomposition.
Yossi Gandelsman, Alexei A. Efros, Jacob Steinhardt
2024Interpreting Robustness Proofs of Deep Neural Networks.
Debangshu Banerjee, Avaljot Singh, Gagandeep Singh
2024Interventional Fairness on Partially Known Causal Graphs: A Constrained Optimization Approach.
Aoqi Zuo, Yiqing Li, Susan Wei, Mingming Gong
2024Intriguing Properties of Data Attribution on Diffusion Models.
Xiaosen Zheng, Tianyu Pang, Chao Du, Jing Jiang, Min Lin
2024Intriguing Properties of Generative Classifiers.
Priyank Jaini, Kevin Clark, Robert Geirhos
2024Invariance-based Learning of Latent Dynamics.
Kai Lagemann, Christian Lagemann, Sach Mukherjee
2024Inverse Approximation Theory for Nonlinear Recurrent Neural Networks.
Shida Wang, Zhong Li, Qianxiao Li
2024Investigating the Benefits of Projection Head for Representation Learning.
Yihao Xue, Eric Gan, Jiayi Ni, Siddharth Joshi, Baharan Mirzasoleiman
2024Is ImageNet worth 1 video? Learning strong image encoders from 1 long unlabelled video.
Shashanka Venkataramanan, Mamshad Nayeem Rizve, João Carreira, Yuki M. Asano, Yannis Avrithis
2024Is Self-Repair a Silver Bullet for Code Generation?
Theo X. Olausson, Jeevana Priya Inala, Chenglong Wang, Jianfeng Gao, Armando Solar-Lezama
2024Is This the Subspace You Are Looking for? An Interpretability Illusion for Subspace Activation Patching.
Aleksandar Makelov, Georg Lange, Atticus Geiger, Neel Nanda
2024Is attention required for ICL? Exploring the Relationship Between Model Architecture and In-Context Learning Ability.
Ivan Lee, Nan Jiang, Taylor Berg-Kirkpatrick
2024It's Never Too Late: Fusing Acoustic Information into Large Language Models for Automatic Speech Recognition.
Chen Chen, Ruizhe Li, Yuchen Hu, Sabato Marco Siniscalchi, Pin-Yu Chen, Engsiong Chng, Chao-Han Huck Yang
2024Ito Diffusion Approximation of Universal Ito Chains for Sampling, Optimization and Boosting.
Aleksei Ustimenko, Aleksandr Beznosikov
2024Jailbreak in pieces: Compositional Adversarial Attacks on Multi-Modal Language Models.
Erfan Shayegani, Yue Dong, Nael B. Abu-Ghazaleh
2024JoMA: Demystifying Multilayer Transformers via Joint Dynamics of MLP and Attention.
Yuandong Tian, Yiping Wang, Zhenyu Zhang, Beidi Chen, Simon Shaolei Du
2024JointNet: Extending Text-to-Image Diffusion for Dense Distribution Modeling.
Jingyang Zhang, Shiwei Li, Yuanxun Lu, Tian Fang, David McKinnon, Yanghai Tsin, Long Quan, Yao Yao
2024Jointly Training Large Autoregressive Multimodal Models.
Emanuele Aiello, Lili Yu, Yixin Nie, Armen Aghajanyan, Barlas Oguz
2024Jointly-Learned Exit and Inference for a Dynamic Neural Network.
Florence Regol, Joud Chataoui, Mark Coates
2024Jumanji: a Diverse Suite of Scalable Reinforcement Learning Environments in JAX.
Clément Bonnet, Daniel Luo, Donal Byrne, Shikha Surana, Sasha Abramowitz, Paul Duckworth, Vincent Coyette, Laurence Illing Midgley, Elshadai Tegegn, Tristan Kalloniatis, Omayma Mahjoub, Matthew Macfarlane, Andries P. Smit, Nathan Grinsztajn, Raphaël Boige, Cemlyn N. Waters, Mohamed A. Mimouni, Ulrich A. Mbou Sob, Ruan de Kock, Siddarth Singh, Daniel Furelos-Blanco, Victor Le, Arnu Pretorius, Alexandre Laterre
2024KITAB: Evaluating LLMs on Constraint Satisfaction for Information Retrieval.
Marah I Abdin, Suriya Gunasekar, Varun Chandrasekaran, Jerry Li, Mert Yüksekgönül, Rahee Ghosh Peshawaria, Ranjita Naik, Besmira Nushi
2024KW-Design: Pushing the Limit of Protein Design via Knowledge Refinement.
Zhangyang Gao, Cheng Tan, Xingran Chen, Yijie Zhang, Jun Xia, Siyuan Li, Stan Z. Li
2024Kalman Filter for Online Classification of Non-Stationary Data.
Michalis K. Titsias, Alexandre Galashov, Amal Rannen-Triki, Razvan Pascanu, Yee Whye Teh, Jörg Bornschein
2024Kernel Metric Learning for In-Sample Off-Policy Evaluation of Deterministic RL Policies.
Haanvid Lee, Tri Wahyu Guntara, Jongmin Lee, Yung-Kyun Noh, Kee-Eung Kim
2024Kernelised Normalising Flows.
Eshant English, Matthias Kirchler, Christoph Lippert
2024Kill Two Birds with One Stone: Rethinking Data Augmentation for Deep Long-tailed Learning.
Binwu Wang, Pengkun Wang, Wei Xu, Xu Wang, Yudong Zhang, Kun Wang, Yang Wang
2024Knowledge Card: Filling LLMs' Knowledge Gaps with Plug-in Specialized Language Models.
Shangbin Feng, Weijia Shi, Yuyang Bai, Vidhisha Balachandran, Tianxing He, Yulia Tsvetkov
2024Knowledge Distillation Based on Transformed Teacher Matching.
Kaixiang Zheng, En-Hui Yang
2024Knowledge Fusion of Large Language Models.
Fanqi Wan, Xinting Huang, Deng Cai, Xiaojun Quan, Wei Bi, Shuming Shi
2024KoLA: Carefully Benchmarking World Knowledge of Large Language Models.
Jifan Yu, Xiaozhi Wang, Shangqing Tu, Shulin Cao, Daniel Zhang-Li, Xin Lv, Hao Peng, Zijun Yao, Xiaohan Zhang, Hanming Li, Chunyang Li, Zheyuan Zhang, Yushi Bai, Yantao Liu, Amy Xin, Kaifeng Yun, Linlu Gong, Nianyi Lin, Jianhui Chen, Zhili Wu, Yunjia Qi, Weikai Li, Yong Guan, Kaisheng Zeng, Ji Qi, Hailong Jin, Jinxin Liu, Yu Gu, Yuan Yao, Ning Ding, Lei Hou, Zhiyuan Liu, Bin Xu, Jie Tang, Juanzi Li
2024Koopman-based generalization bound: New aspect for full-rank weights.
Yuka Hashimoto, Sho Sonoda, Isao Ishikawa, Atsushi Nitanda, Taiji Suzuki
2024Kosmos-G: Generating Images in Context with Multimodal Large Language Models.
Xichen Pan, Li Dong, Shaohan Huang, Zhiliang Peng, Wenhu Chen, Furu Wei
2024L2MAC: Large Language Model Automatic Computer for Extensive Code Generation.
Samuel Holt, Max Ruiz Luyten, Mihaela van der Schaar
2024L2P-MIP: Learning to Presolve for Mixed Integer Programming.
Chang Liu, Zhichen Dong, Haobo Ma, Weilin Luo, Xijun Li, Bowen Pang, Jia Zeng, Junchi Yan
2024LCOT: Linear Circular Optimal Transport.
Rocio Diaz Martin, Ivan Vladimir Medri, Yikun Bai, Xinran Liu, Kangbai Yan, Gustavo K. Rohde, Soheil Kolouri
2024LDReg: Local Dimensionality Regularized Self-Supervised Learning.
Hanxun Huang, Ricardo J. G. B. Campello, Sarah Monazam Erfani, Xingjun Ma, Michael E. Houle, James Bailey
2024LEAP: Liberate Sparse-View 3D Modeling from Camera Poses.
Hanwen Jiang, Zhenyu Jiang, Yue Zhao, Qixing Huang
2024LEGO-Prover: Neural Theorem Proving with Growing Libraries.
Haiming Wang, Huajian Xin, Chuanyang Zheng, Zhengying Liu, Qingxing Cao, Yinya Huang, Jing Xiong, Han Shi, Enze Xie, Jian Yin, Zhenguo Li, Xiaodan Liang
2024LEMON: Lossless model expansion.
Yite Wang, Jiahao Su, Hanlin Lu, Cong Xie, Tianyi Liu, Jianbo Yuan, Haibin Lin, Ruoyu Sun, Hongxia Yang
2024LILO: Learning Interpretable Libraries by Compressing and Documenting Code.
Gabriel Grand, Lionel Wong, Matthew Bowers, Theo X. Olausson, Muxin Liu, Joshua B. Tenenbaum, Jacob Andreas
2024LLCP: Learning Latent Causal Processes for Reasoning-based Video Question Answer.
Guangyi Chen, Yuke Li, Xiao Liu, Zijian Li, Eman Al Suradi, Donglai Wei, Kun Zhang
2024LLM Augmented LLMs: Expanding Capabilities through Composition.
Rachit Bansal, Bidisha Samanta, Siddharth Dalmia, Nitish Gupta, Sriram Ganapathy, Abhishek Bapna, Prateek Jain, Partha Talukdar
2024LLM Blueprint: Enabling Text-to-Image Generation with Complex and Detailed Prompts.
Hanan Gani, Shariq Farooq Bhat, Muzammal Naseer, Salman Khan, Peter Wonka
2024LLM-Assisted Code Cleaning For Training Accurate Code Generators.
Naman Jain, Tianjun Zhang, Wei-Lin Chiang, Joseph E. Gonzalez, Koushik Sen, Ion Stoica
2024LLM-CXR: Instruction-Finetuned LLM for CXR Image Understanding and Generation.
Suhyeon Lee, Won Jun Kim, Jinho Chang, Jong Chul Ye
2024LLM-grounded Video Diffusion Models.
Long Lian, Baifeng Shi, Adam Yala, Trevor Darrell, Boyi Li
2024LLMCarbon: Modeling the End-to-End Carbon Footprint of Large Language Models.
Ahmad Faiz, Sotaro Kaneda, Ruhan Wang, Rita Chukwunyere Osi, Prateek Sharma, Fan Chen, Lei Jiang
2024LLMs Meet VLMs: Boost Open Vocabulary Object Detection with Fine-grained Descriptors.
Sheng Jin, Xueying Jiang, Jiaxing Huang, Lewei Lu, Shijian Lu
2024LLaMA-Adapter: Efficient Fine-tuning of Large Language Models with Zero-initialized Attention.
Renrui Zhang, Jiaming Han, Chris Liu, Aojun Zhou, Pan Lu, Yu Qiao, Hongsheng Li, Peng Gao
2024LMSYS-Chat-1M: A Large-Scale Real-World LLM Conversation Dataset.
Lianmin Zheng, Wei-Lin Chiang, Ying Sheng, Tianle Li, Siyuan Zhuang, Zhanghao Wu, Yonghao Zhuang, Zhuohan Li, Zi Lin, Eric P. Xing, Joseph E. Gonzalez, Ion Stoica, Hao Zhang
2024LMUFormer: Low Complexity Yet Powerful Spiking Model With Legendre Memory Units.
Zeyu Liu, Gourav Datta, Anni Li, Peter Anthony Beerel
2024LOQA: Learning with Opponent Q-Learning Awareness.
Milad Aghajohari, Juan Agustin Duque, Tim Cooijmans, Aaron C. Courville
2024LQ-LoRA: Low-rank plus Quantized Matrix Decomposition for Efficient Language Model Finetuning.
Han Guo, Philip Greengard, Eric P. Xing, Yoon Kim
2024LRM: Large Reconstruction Model for Single Image to 3D.
Yicong Hong, Kai Zhang, Jiuxiang Gu, Sai Bi, Yang Zhou, Difan Liu, Feng Liu, Kalyan Sunkavalli, Trung Bui, Hao Tan
2024LRR: Language-Driven Resamplable Continuous Representation against Adversarial Tracking Attacks.
Jianlang Chen, Xuhong Ren, Qing Guo, Felix Juefei-Xu, Di Lin, Wei Feng, Lei Ma, Jianjun Zhao
2024LUM-ViT: Learnable Under-sampling Mask Vision Transformer for Bandwidth Limited Optical Signal Acquisition.
Lingfeng Liu, Dong Ni, Hangjie Yuan
2024LUT-GEMM: Quantized Matrix Multiplication based on LUTs for Efficient Inference in Large-Scale Generative Language Models.
Gunho Park, Baeseong Park, Minsub Kim, Sungjae Lee, Jeonghoon Kim, Beomseok Kwon, Se Jung Kwon, Byeongwook Kim, Youngjoo Lee, Dongsoo Lee
2024Label-Agnostic Forgetting: A Supervision-Free Unlearning in Deep Models.
Shaofei Shen, Chenhao Zhang, Yawen Zhao, Alina Bialkowski, Weitong Chen, Miao Xu
2024Label-Focused Inductive Bias over Latent Object Features in Visual Classification.
Ilmin Kang, HyounYoung Bae, Kangil Kim
2024Label-Noise Robust Diffusion Models.
Byeonghu Na, Yeongmin Kim, HeeSun Bae, Jung Hyun Lee, Se Jung Kwon, Wanmo Kang, Il-Chul Moon
2024Label-free Node Classification on Graphs with Large Language Models (LLMs).
Zhikai Chen, Haitao Mao, Hongzhi Wen, Haoyu Han, Wei Jin, Haiyang Zhang, Hui Liu, Jiliang Tang
2024LabelDP-Pro: Learning with Label Differential Privacy via Projections.
Badih Ghazi, Yangsibo Huang, Pritish Kamath, Ravi Kumar, Pasin Manurangsi, Chiyuan Zhang
2024Lagrangian Flow Networks for Conservation Laws.
Fabricio Arend Torres, Marcello Massimo Negri, Marco Inversi, Jonathan Aellen, Volker Roth
2024LaneSegNet: Map Learning with Lane Segment Perception for Autonomous Driving.
Tianyu Li, Peijin Jia, Bangjun Wang, Li Chen, Kun Jiang, Junchi Yan, Hongyang Li
2024Langevin Monte Carlo for strongly log-concave distributions: Randomized midpoint revisited.
Lu Yu, Avetik G. Karagulyan, Arnak S. Dalalyan
2024Language Control Diffusion: Efficiently Scaling through Space, Time, and Tasks.
Edwin Zhang, Yujie Lu, Shinda Huang, William Yang Wang, Amy Zhang
2024Language Model Beats Diffusion - Tokenizer is key to visual generation.
Lijun Yu, José Lezama, Nitesh Bharadwaj Gundavarapu, Luca Versari, Kihyuk Sohn, David Minnen, Yong Cheng, Agrim Gupta, Xiuye Gu, Alexander G. Hauptmann, Boqing Gong, Ming-Hsuan Yang, Irfan Essa, David A. Ross, Lu Jiang
2024Language Model Cascades: Token-Level Uncertainty And Beyond.
Neha Gupta, Harikrishna Narasimhan, Wittawat Jitkrittum, Ankit Singh Rawat, Aditya Krishna Menon, Sanjiv Kumar
2024Language Model Decoding as Direct Metrics Optimization.
Haozhe Ji, Pei Ke, Hongning Wang, Minlie Huang
2024Language Model Detectors Are Easily Optimized Against.
Charlotte Nicks, Eric Mitchell, Rafael Rafailov, Archit Sharma, Christopher D. Manning, Chelsea Finn, Stefano Ermon
2024Language Model Inversion.
John X. Morris, Wenting Zhao, Justin T. Chiu, Vitaly Shmatikov, Alexander M. Rush
2024Language Model Self-improvement by Reinforcement Learning Contemplation.
Jing-Cheng Pang, Pengyuan Wang, Kaiyuan Li, Xiong-Hui Chen, Jiacheng Xu, Zongzhang Zhang, Yang Yu
2024Language Modeling Is Compression.
Grégoire Delétang, Anian Ruoss, Paul-Ambroise Duquenne, Elliot Catt, Tim Genewein, Christopher Mattern, Jordi Grau-Moya, Li Kevin Wenliang, Matthew Aitchison, Laurent Orseau, Marcus Hutter, Joel Veness
2024Language Models Represent Space and Time.
Wes Gurnee, Max Tegmark
2024Language-Informed Visual Concept Learning.
Sharon Lee, Yunzhi Zhang, Shangzhe Wu, Jiajun Wu
2024Language-Interfaced Tabular Oversampling via Progressive Imputation and Self-Authentication.
June Yong Yang, Geondo Park, Joowon Kim, Hyeongwon Jang, Eunho Yang
2024LanguageBind: Extending Video-Language Pretraining to N-modality by Language-based Semantic Alignment.
Bin Zhu, Bin Lin, Munan Ning, Yang Yan, Jiaxi Cui, Hongfa Wang, Yatian Pang, Wenhao Jiang, Junwu Zhang, Zongwei Li, Caiwan Zhang, Zhifeng Li, Wei Liu, Li Yuan
2024Large Brain Model for Learning Generic Representations with Tremendous EEG Data in BCI.
Wei-Bang Jiang, Li-Ming Zhao, Bao-Liang Lu
2024Large Content And Behavior Models To Understand, Simulate, And Optimize Content And Behavior.
Ashmit Khandelwal, Aditya Agrawal, Aanisha Bhattacharyya, Yaman Kumar, Somesh Singh, Uttaran Bhattacharya, Ishita Dasgupta, Stefano Petrangeli, Rajiv Ratn Shah, Changyou Chen, Balaji Krishnamurthy
2024Large Language Model Cascades with Mixture of Thought Representations for Cost-Efficient Reasoning.
Murong Yue, Jie Zhao, Min Zhang, Liang Du, Ziyu Yao
2024Large Language Models Are Not Robust Multiple Choice Selectors.
Chujie Zheng, Hao Zhou, Fandong Meng, Jie Zhou, Minlie Huang
2024Large Language Models Cannot Self-Correct Reasoning Yet.
Jie Huang, Xinyun Chen, Swaroop Mishra, Huaixiu Steven Zheng, Adams Wei Yu, Xinying Song, Denny Zhou
2024Large Language Models are Efficient Learners of Noise-Robust Speech Recognition.
Yuchen Hu, Chen Chen, Chao-Han Huck Yang, Ruizhe Li, Chao Zhang, Pin-Yu Chen, Engsiong Chng
2024Large Language Models as Analogical Reasoners.
Michihiro Yasunaga, Xinyun Chen, Yujia Li, Panupong Pasupat, Jure Leskovec, Percy Liang, Ed H. Chi, Denny Zhou
2024Large Language Models as Automated Aligners for benchmarking Vision-Language Models.
Yuanfeng Ji, Chongjian Ge, Weikai Kong, Enze Xie, Zhengying Liu, Zhenguo Li, Ping Luo
2024Large Language Models as Generalizable Policies for Embodied Tasks.
Andrew Szot, Max Schwarzer, Harsh Agrawal, Bogdan Mazoure, Rin Metcalf, Walter Talbott, Natalie Mackraz, R. Devon Hjelm, Alexander T. Toshev
2024Large Language Models as Optimizers.
Chengrun Yang, Xuezhi Wang, Yifeng Lu, Hanxiao Liu, Quoc V. Le, Denny Zhou, Xinyun Chen
2024Large Language Models as Tool Makers.
Tianle Cai, Xuezhi Wang, Tengyu Ma, Xinyun Chen, Denny Zhou
2024Large Language Models to Enhance Bayesian Optimization.
Tennison Liu, Nicolás Astorga, Nabeel Seedat, Mihaela van der Schaar
2024Large Multilingual Models Pivot Zero-Shot Multimodal Learning across Languages.
Jinyi Hu, Yuan Yao, Chongyi Wang, Shan Wang, Yinxu Pan, Qianyu Chen, Tianyu Yu, Hanghao Wu, Yue Zhao, Haoye Zhang, Xu Han, Yankai Lin, Jiao Xue, Dahai Li, Zhiyuan Liu, Maosong Sun
2024Large-Vocabulary 3D Diffusion Model with Transformer.
Ziang Cao, Fangzhou Hong, Tong Wu, Liang Pan, Ziwei Liu
2024Large-scale Training of Foundation Models for Wearable Biosignals.
Salar Abbaspourazad, Oussama Elachqar, Andrew C. Miller, Saba Emrani, Udhyakumar Nallasamy, Ian Shapiro
2024Latent 3D Graph Diffusion.
Yuning You, Ruida Zhou, Jiwoong Park, Haotian Xu, Chao Tian, Zhangyang Wang, Yang Shen
2024Latent Intuitive Physics: Learning to Transfer Hidden Physics from A 3D Video.
Xiangming Zhu, Huayu Deng, Haochen Yuan, Yunbo Wang, Xiaokang Yang
2024Latent Representation and Simulation of Markov Processes via Time-Lagged Information Bottleneck.
Marco Federici, Patrick Forré, Ryota Tomioka, Bastiaan S. Veeling
2024Latent Trajectory Learning for Limited Timestamps under Distribution Shift over Time.
Qiuhao Zeng, Changjian Shui, Long-Kai Huang, Peng Liu, Xi Chen, Charles Ling, Boyu Wang
2024Layer-wise linear mode connectivity.
Linara Adilova, Maksym Andriushchenko, Michael Kamp, Asja Fischer, Martin Jaggi
2024LayoutNUWA: Revealing the Hidden Layout Expertise of Large Language Models.
Zecheng Tang, Chenfei Wu, Juntao Li, Nan Duan
2024Learning 3D Particle-based Simulators from RGB-D Videos.
William F. Whitney, Tatiana Lopez-Guevara, Tobias Pfaff, Yulia Rubanova, Thomas Kipf, Kim Stachenfeld, Kelsey R. Allen
2024Learning Adaptive Multiresolution Transforms via Meta-Framelet-based Graph Convolutional Network.
Tianze Luo, Zhanfeng Mo, Sinno Jialin Pan
2024Learning Conditional Invariances through Non-Commutativity.
Abhra Chaudhuri, Serban Georgescu, Anjan Dutta
2024Learning Decentralized Partially Observable Mean Field Control for Artificial Collective Behavior.
Kai Cui, Sascha Hauck, Christian Fabian, Heinz Koeppl
2024Learning Delays in Spiking Neural Networks using Dilated Convolutions with Learnable Spacings.
Ilyass Hammouamri, Ismail Khalfaoui Hassani, Timothée Masquelier
2024Learning Energy Decompositions for Partial Inference in GFlowNets.
Hyosoon Jang, Minsu Kim, Sungsoo Ahn
2024Learning Energy-Based Models by Cooperative Diffusion Recovery Likelihood.
Yaxuan Zhu, Jianwen Xie, Ying Nian Wu, Ruiqi Gao
2024Learning Flexible Body Collision Dynamics with Hierarchical Contact Mesh Transformer.
Youn-Yeol Yu, Jeongwhan Choi, Woojin Cho, Kookjin Lee, Nayong Kim, Kiseok Chang, ChangSeung Woo, Ilho Kim, SeokWoo Lee, Joon-Young Yang, Sooyoung Yoon, Noseong Park
2024Learning From Simplicial Data Based on Random Walks and 1D Convolutions.
Florian Frantzen, Michael T. Schaub
2024Learning Grounded Action Abstractions from Language.
Lionel Wong, Jiayuan Mao, Pratyusha Sharma, Zachary S. Siegel, Jiahai Feng, Noa Korneev, Joshua B. Tenenbaum, Jacob Andreas
2024Learning Hierarchical Image Segmentation For Recognition and By Recognition.
Tsung-Wei Ke, Sangwoo Mo, Stella X. Yu
2024Learning Hierarchical Polynomials with Three-Layer Neural Networks.
Zihao Wang, Eshaan Nichani, Jason D. Lee
2024Learning Hierarchical World Models with Adaptive Temporal Abstractions from Discrete Latent Dynamics.
Christian Gumbsch, Noor Sajid, Georg Martius, Martin V. Butz
2024Learning Implicit Representation for Reconstructing Articulated Objects.
Hao Zhang, Fang Li, Samyak Rawlekar, Narendra Ahuja
2024Learning Interactive Real-World Simulators.
Sherry Yang, Yilun Du, Seyed Kamyar Seyed Ghasemipour, Jonathan Tompson, Leslie Pack Kaelbling, Dale Schuurmans, Pieter Abbeel
2024Learning Large DAGs is Harder than you Think: Many Losses are Minimal for the Wrong DAG.
Jonas Seng, Matej Zecevic, Devendra Singh Dhami, Kristian Kersting
2024Learning Mean Field Games on Sparse Graphs: A Hybrid Graphex Approach.
Christian Fabian, Kai Cui, Heinz Koeppl
2024Learning Multi-Agent Communication from Graph Modeling Perspective.
Shengchao Hu, Li Shen, Ya Zhang, Dacheng Tao
2024Learning Multi-Agent Communication with Contrastive Learning.
Yat Long Lo, Biswa Sengupta, Jakob Nicolaus Foerster, Michael Noukhovitch
2024Learning Multi-Faceted Prototypical User Interests.
Nhu-Thuat Tran, Hady W. Lauw
2024Learning Nash Equilibria in Rank-1 Games.
Nikolas Patris, Ioannis Panageas
2024Learning No-Regret Sparse Generalized Linear Models with Varying Observation(s).
Diyang Li, Charles Ling, Zhiqiang Xu, Huan Xiong, Bin Gu
2024Learning Optimal Contracts: How to Exploit Small Action Spaces.
Francesco Bacchiocchi, Matteo Castiglioni, Alberto Marchesi, Nicola Gatti
2024Learning Over Molecular Conformer Ensembles: Datasets and Benchmarks.
Yanqiao Zhu, Jeehyun Hwang, Keir Adams, Zhen Liu, Bozhao Nan, Brock Stenfors, Yuanqi Du, Jatin Chauhan, Olaf Wiest, Olexandr Isayev, Connor W. Coley, Yizhou Sun, Wei Wang
2024Learning Performance-Improving Code Edits.
Alexander Shypula, Aman Madaan, Yimeng Zeng, Uri Alon, Jacob R. Gardner, Yiming Yang, Milad Hashemi, Graham Neubig, Parthasarathy Ranganathan, Osbert Bastani, Amir Yazdanbakhsh
2024Learning Personalized Causally Invariant Representations for Heterogeneous Federated Clients.
Xueyang Tang, Song Guo, Jie Zhang, Jingcai Guo
2024Learning Planning Abstractions from Language.
Weiyu Liu, Geng Chen, Joy Hsu, Jiayuan Mao, Jiajun Wu
2024Learning Polynomial Problems with SL(2, R)-Equivariance.
Hannah Lawrence, Mitchell Tong Harris
2024Learning Robust Generalizable Radiance Field with Visibility and Feature Augmented Point Representation.
Jiaxu Wang, Ziyi Zhang, Renjing Xu
2024Learning Semantic Proxies from Visual Prompts for Parameter-Efficient Fine-Tuning in Deep Metric Learning.
Li Ren, Chen Chen, Liqiang Wang, Kien A. Hua
2024Learning Stackable and Skippable LEGO Bricks for Efficient, Reconfigurable, and Variable-Resolution Diffusion Modeling.
Huangjie Zheng, Zhendong Wang, Jianbo Yuan, Guanghan Ning, Pengcheng He, Quanzeng You, Hongxia Yang, Mingyuan Zhou
2024Learning Thresholds with Latent Values and Censored Feedback.
Jiahao Zhang, Tao Lin, Weiqiang Zheng, Zhe Feng, Yifeng Teng, Xiaotie Deng
2024Learning dynamic representations of the functional connectome in neurobiological networks.
Luciano Dyballa, Samuel Lang, Alexandra Haslund-Gourley, Eviatar Yemini, Steven W. Zucker
2024Learning from Aggregate responses: Instance Level versus Bag Level Loss Functions.
Adel Javanmard, Lin Chen, Vahab Mirrokni, Ashwinkumar Badanidiyuru, Gang Fu
2024Learning from Label Proportions: Bootstrapping Supervised Learners via Belief Propagation.
Shreyas Havaldar, Navodita Sharma, Shubhi Sareen, Karthikeyan Shanmugam, Aravindan Raghuveer
2024Learning from Sparse Offline Datasets via Conservative Density Estimation.
Zhepeng Cen, Zuxin Liu, Zitong Wang, Yihang Yao, Henry Lam, Ding Zhao
2024Learning in reverse causal strategic environments with ramifications on two sided markets.
Seamus Somerstep, Yuekai Sun, Yaacov Ritov
2024Learning interpretable control inputs and dynamics underlying animal locomotion.
Thomas Soares Mullen, Marine Schimel, Guillaume Hennequin, Christian K. Machens, Michael B. Orger, Adrien Jouary
2024Learning invariant representations of time-homogeneous stochastic dynamical systems.
Vladimir R. Kostic, Pietro Novelli, Riccardo Grazzi, Karim Lounici, Massimiliano Pontil
2024Learning model uncertainty as variance-minimizing instance weights.
Nishant Jain, Karthikeyan Shanmugam, Pradeep Shenoy
2024Learning semilinear neural operators: A unified recursive framework for prediction and data assimilation.
Ashutosh Singh, Ricardo Augusto Borsoi, Deniz Erdogmus, Tales Imbiriba
2024Learning the greatest common divisor: explaining transformer predictions.
François Charton
2024Learning to Act from Actionless Videos through Dense Correspondences.
Po-Chen Ko, Jiayuan Mao, Yilun Du, Shao-Hua Sun, Joshua B. Tenenbaum
2024Learning to Act without Actions.
Dominik Schmidt, Minqi Jiang
2024Learning to Compose: Improving Object Centric Learning by Injecting Compositionality.
Whie Jung, Jaehoon Yoo, Sungjin Ahn, Seunghoon Hong
2024Learning to Embed Time Series Patches Independently.
Seunghan Lee, Taeyoung Park, Kibok Lee
2024Learning to Jointly Understand Visual and Tactile Signals.
Yichen Li, Yilun Du, Chao Liu, Chao Liu, Francis Williams, Michael Foshey, Benjamin Eckart, Jan Kautz, Joshua B. Tenenbaum, Antonio Torralba, Wojciech Matusik
2024Learning to Make Adherence-aware Advice.
Guanting Chen, Xiaocheng Li, Chunlin Sun, Hanzhao Wang
2024Learning to Reject Meets Long-tail Learning.
Harikrishna Narasimhan, Aditya Krishna Menon, Wittawat Jitkrittum, Neha Gupta, Sanjiv Kumar
2024Learning to Reject with a Fixed Predictor: Application to Decontextualization.
Christopher Mohri, Daniel Andor, Eunsol Choi, Michael Collins, Anqi Mao, Yutao Zhong
2024Learning to Relax: Setting Solver Parameters Across a Sequence of Linear System Instances.
Mikhail Khodak, Edmond Chow, Maria-Florina Balcan, Ameet Talwalkar
2024Learning to Solve Bilevel Programs with Binary Tender.
Bo Zhou, Ruiwei Jiang, Siqian Shen
2024Learning to design protein-protein interactions with enhanced generalization.
Anton Bushuiev, Roman Bushuiev, Petr Kouba, Anatolii Filkin, Marketa Gabrielova, Michal Gabriel, Jirí Sedlár, Tomás Pluskal, Jirí Damborský, Stanislav Mazurenko, Josef Sivic
2024Learning to solve Class-Constrained Bin Packing Problems via Encoder-Decoder Model.
Hanni Cheng, Ya Cong, Weihao Jiang, Shiliang Pu
2024Learning with Language-Guided State Abstractions.
Andi Peng, Ilia Sucholutsky, Belinda Z. Li, Theodore R. Sumers, Thomas L. Griffiths, Jacob Andreas, Julie Shah
2024Learning with Mixture of Prototypes for Out-of-Distribution Detection.
Haodong Lu, Dong Gong, Shuo Wang, Jason Xue, Lina Yao, Kristen Moore
2024Learning with a Mole: Transferable latent spatial representations for navigation without reconstruction.
Guillaume Bono, Leonid Antsfeld, Assem Sadek, Gianluca Monaci, Christian Wolf
2024Leave-one-out Distinguishability in Machine Learning.
Jiayuan Ye, Anastasia Borovykh, Soufiane Hayou, Reza Shokri
2024Leftover Lunch: Advantage-based Offline Reinforcement Learning for Language Models.
Ashutosh Baheti, Ximing Lu, Faeze Brahman, Ronan Le Bras, Maarten Sap, Mark O. Riedl
2024Lemur: Harmonizing Natural Language and Code for Language Agents.
Yiheng Xu, Hongjin Su, Chen Xing, Boyu Mi, Qian Liu, Weijia Shi, Binyuan Hui, Fan Zhou, Yitao Liu, Tianbao Xie, Zhoujun Cheng, Siheng Zhao, Lingpeng Kong, Bailin Wang, Caiming Xiong, Tao Yu
2024Lemur: Integrating Large Language Models in Automated Program Verification.
Haoze Wu, Clark W. Barrett, Nina Narodytska
2024Less is More: Fewer Interpretable Region via Submodular Subset Selection.
Ruoyu Chen, Hua Zhang, Siyuan Liang, Jingzhi Li, Xiaochun Cao
2024Less is More: One-shot Subgraph Reasoning on Large-scale Knowledge Graphs.
Zhanke Zhou, Yongqi Zhang, Jiangchao Yao, Quanming Yao, Bo Han
2024Less or More From Teacher: Exploiting Trilateral Geometry For Knowledge Distillation.
Chengming Hu, Haolun Wu, Xuan Li, Chen Ma, Xi Chen, Boyu Wang, Jun Yan, Xue Liu
2024Let 2D Diffusion Model Know 3D-Consistency for Robust Text-to-3D Generation.
Junyoung Seo, Wooseok Jang, Minseop Kwak, Inès Hyeonsu Kim, Jaehoon Ko, Junho Kim, Jin-Hwa Kim, Jiyoung Lee, Seungryong Kim
2024Let Models Speak Ciphers: Multiagent Debate through Embeddings.
Chau Pham, Boyi Liu, Yingxiang Yang, Zhengyu Chen, Tianyi Liu, Jianbo Yuan, Bryan A. Plummer, Zhaoran Wang, Hongxia Yang
2024Let's Verify Step by Step.
Hunter Lightman, Vineet Kosaraju, Yuri Burda, Harrison Edwards, Bowen Baker, Teddy Lee, Jan Leike, John Schulman, Ilya Sutskever, Karl Cobbe
2024Let's do the time-warp-attend: Learning topological invariants of dynamical systems.
Noa Moriel, Matthew Ricci, Mor Nitzan
2024Leveraging Generative Models for Unsupervised Alignment of Neural Time Series Data.
Ayesha Vermani, Il Memming Park, Josue Nassar
2024Leveraging Hyperbolic Embeddings for Coarse-to-Fine Robot Design.
Heng Dong, Junyu Zhang, Chongjie Zhang
2024Leveraging Low-Rank and Sparse Recurrent Connectivity for Robust Closed-Loop Control.
Neehal Tumma, Mathias Lechner, Noel Loo, Ramin M. Hasani, Daniela Rus
2024Leveraging Optimization for Adaptive Attacks on Image Watermarks.
Nils Lukas, Abdulrahman Diaa, Lucas Fenaux, Florian Kerschbaum
2024Leveraging Uncertainty Estimates To Improve Classifier Performance.
Gundeep Arora, Srujana Merugu, Anoop Saladi, Rajeev Rastogi
2024Leveraging Unpaired Data for Vision-Language Generative Models via Cycle Consistency.
Tianhong Li, Sangnie Bhardwaj, Yonglong Tian, Han Zhang, Jarred Barber, Dina Katabi, Guillaume Lajoie, Huiwen Chang, Dilip Krishnan
2024Leveraging augmented-Lagrangian techniques for differentiating over infeasible quadratic programs in machine learning.
Antoine Bambade, Fabian Schramm, Adrien B. Taylor, Justin Carpentier
2024Lewis's Signaling Game as beta-VAE For Natural Word Lengths and Segments.
Ryo Ueda, Tadahiro Taniguchi
2024LiDAR-PTQ: Post-Training Quantization for Point Cloud 3D Object Detection.
Sifan Zhou, Liang Li, Xinyu Zhang, Bo Zhang, Shipeng Bai, Miao Sun, Ziyu Zhao, Xiaobo Lu, Xiangxiang Chu
2024LiDAR: Sensing Linear Probing Performance in Joint Embedding SSL Architectures.
Vimal Thilak, Chen Huang, Omid Saremi, Laurent Dinh, Hanlin Goh, Preetum Nakkiran, Joshua M. Susskind, Etai Littwin
2024Lie Group Decompositions for Equivariant Neural Networks.
Mircea Mironenco, Patrick Forré
2024Lifting Architectural Constraints of Injective Flows.
Peter Sorrenson, Felix Draxler, Armand Rousselot, Sander Hummerich, Lea Zimmermann, Ullrich Köthe
2024Light Schrödinger Bridge.
Alexander Korotin, Nikita Gushchin, Evgeny Burnaev
2024Light-MILPopt: Solving Large-scale Mixed Integer Linear Programs with Lightweight Optimizer and Small-scale Training Dataset.
Huigen Ye, Hua Xu, Hongyan Wang
2024LightHGNN: Distilling Hypergraph Neural Networks into MLPs for 100x Faster Inference.
Yifan Feng, Yihe Luo, Shihui Ying, Yue Gao
2024Like Oil and Water: Group Robustness Methods and Poisoning Defenses May Be at Odds.
Michael-Andrei Panaitescu-Liess, Yigitcan Kaya, Sicheng Zhu, Furong Huang, Tudor Dumitras
2024Likelihood Training of Cascaded Diffusion Models via Hierarchical Volume-preserving Maps.
Henry Li, Ronen Basri, Yuval Kluger
2024Linear Log-Normal Attention with Unbiased Concentration.
Yury Nahshan, Joseph Kampeas, Emir Haleva
2024Linear attention is (maybe) all you need (to understand Transformer optimization).
Kwangjun Ahn, Xiang Cheng, Minhak Song, Chulhee Yun, Ali Jadbabaie, Suvrit Sra
2024Linearity of Relation Decoding in Transformer Language Models.
Evan Hernandez, Arnab Sen Sharma, Tal Haklay, Kevin Meng, Martin Wattenberg, Jacob Andreas, Yonatan Belinkov, David Bau
2024Lion Secretly Solves a Constrained Optimization: As Lyapunov Predicts.
Lizhang Chen, Bo Liu, Kaizhao Liang, Qiang Liu
2024LipSim: A Provably Robust Perceptual Similarity Metric.
Sara Ghazanfari, Alexandre Araujo, Prashanth Krishnamurthy, Farshad Khorrami, Siddharth Garg
2024LipVoicer: Generating Speech from Silent Videos Guided by Lip Reading.
Yochai Yemini, Aviv Shamsian, Lior Bracha, Sharon Gannot, Ethan Fetaya
2024Lipschitz Singularities in Diffusion Models.
Zhantao Yang, Ruili Feng, Han Zhang, Yujun Shen, Kai Zhu, Lianghua Huang, Yifei Zhang, Yu Liu, Deli Zhao, Jingren Zhou, Fan Cheng
2024Lipsum-FT: Robust Fine-Tuning of Zero-Shot Models Using Random Text Guidance.
Giung Nam, Byeongho Heo, Juho Lee
2024Listen, Think, and Understand.
Yuan Gong, Hongyin Luo, Alexander H. Liu, Leonid Karlinsky, James R. Glass
2024LitCab: Lightweight Language Model Calibration over Short- and Long-form Responses.
Xin Liu, Muhammad Khalifa, Lu Wang
2024Llemma: An Open Language Model for Mathematics.
Zhangir Azerbayev, Hailey Schoelkopf, Keiran Paster, Marco Dos Santos, Stephen Marcus McAleer, Albert Q. Jiang, Jia Deng, Stella Biderman, Sean Welleck
2024LoTa-Bench: Benchmarking Language-oriented Task Planners for Embodied Agents.
Jae-Woo Choi, Youngwoo Yoon, Hyobin Ong, Jaehong Kim, Minsu Jang
2024Local Composite Saddle Point Optimization.
Site Bai, Brian Bullins
2024Local Graph Clustering with Noisy Labels.
Artur Back de Luca, Kimon Fountoulakis, Shenghao Yang
2024Local Search GFlowNets.
Minsu Kim, Taeyoung Yun, Emmanuel Bengio, Dinghuai Zhang, Yoshua Bengio, Sungsoo Ahn, Jinkyoo Park
2024Locality Sensitive Sparse Encoding for Learning World Models Online.
Zichen Liu, Chao Du, Wee Sun Lee, Min Lin
2024Locality-Aware Graph Rewiring in GNNs.
Federico Barbero, Ameya Velingker, Amin Saberi, Michael M. Bronstein, Francesco Di Giovanni
2024Localizing and Editing Knowledge In Text-to-Image Generative Models.
Samyadeep Basu, Nanxuan Zhao, Vlad I. Morariu, Soheil Feizi, Varun Manjunatha
2024LoftQ: LoRA-Fine-Tuning-aware Quantization for Large Language Models.
Yixiao Li, Yifan Yu, Chen Liang, Nikos Karampatziakis, Pengcheng He, Weizhu Chen, Tuo Zhao
2024LogicMP: A Neuro-symbolic Approach for Encoding First-order Logic Constraints.
Weidi Xu, Jingwei Wang, Lele Xie, Jianshan He, Hongting Zhou, Taifeng Wang, Xiaopei Wan, Jingdong Chen, Chao Qu, Wei Chu
2024Logical Languages Accepted by Transformer Encoders with Hard Attention.
Pablo Barceló, Alexander Kozachinskiy, Anthony Widjaja Lin, Vladimir V. Podolskii
2024Long-Short-Range Message-Passing: A Physics-Informed Framework to Capture Non-Local Interaction for Scalable Molecular Dynamics Simulation.
Yunyang Li, Yusong Wang, Lin Huang, Han Yang, Xinran Wei, Jia Zhang, Tong Wang, Zun Wang, Bin Shao, Tie-Yan Liu
2024Long-Term Typhoon Trajectory Prediction: A Physics-Conditioned Approach Without Reanalysis Data.
Young-Jae Park, Minseok Seo, Doyi Kim, Hyeri Kim, Sanghoon Choi, Beomkyu Choi, Jeongwon Ryu, Sohee Son, Hae-Gon Jeon, Yeji Choi
2024Long-tailed Diffusion Models with Oriented Calibration.
Tianjiao Zhang, Huangjie Zheng, Jiangchao Yao, Xiangfeng Wang, Mingyuan Zhou, Ya Zhang, Yanfeng Wang
2024LongLoRA: Efficient Fine-tuning of Long-Context Large Language Models.
Yukang Chen, Shengju Qian, Haotian Tang, Xin Lai, Zhijian Liu, Song Han, Jiaya Jia
2024Look, Remember and Reason: Grounded Reasoning in Videos with Language Models.
Apratim Bhattacharyya, Sunny Panchal, Reza Pourreza, Mingu Lee, Pulkit Madan, Roland Memisevic
2024Looped Transformers are Better at Learning Learning Algorithms.
Liu Yang, Kangwook Lee, Robert D. Nowak, Dimitris Papailiopoulos
2024Low Rank Matrix Completion via Robust Alternating Minimization in Nearly Linear Time.
Yuzhou Gu, Zhao Song, Junze Yin, Lichen Zhang
2024M3C: A Framework towards Convergent, Flexible, and Unsupervised Learning of Mixture Graph Matching and Clustering.
Jiaxin Lu, Zetian Jiang, Tianzhe Wang, Junchi Yan
2024MAMBA: an Effective World Model Approach for Meta-Reinforcement Learning.
Zohar Rimon, Tom Jurgenson, Orr Krupnik, Gilad Adler, Aviv Tamar
2024MAP IT to Visualize Representations.
Robert Jenssen
2024MAPE-PPI: Towards Effective and Efficient Protein-Protein Interaction Prediction via Microenvironment-Aware Protein Embedding.
Lirong Wu, Yijun Tian, Yufei Huang, Siyuan Li, Haitao Lin, Nitesh V. Chawla, Stan Z. Li
2024MAmmoTH: Building Math Generalist Models through Hybrid Instruction Tuning.
Xiang Yue, Xingwei Qu, Ge Zhang, Yao Fu, Wenhao Huang, Huan Sun, Yu Su, Wenhu Chen
2024MBR and QE Finetuning: Training-time Distillation of the Best and Most Expensive Decoding Methods.
Mara Finkelstein, Markus Freitag
2024MCM: Masked Cell Modeling for Anomaly Detection in Tabular Data.
Jiaxin Yin, Yuanyuan Qiao, Zitang Zhou, Xiangchao Wang, Jie Yang
2024MEND: Meta Demonstration Distillation for Efficient and Effective In-Context Learning.
Yichuan Li, Xiyao Ma, Sixing Lu, Kyumin Lee, Xiaohu Liu, Chenlei Guo
2024MERT: Acoustic Music Understanding Model with Large-Scale Self-supervised Training.
Yizhi Li, Ruibin Yuan, Ge Zhang, Yinghao Ma, Xingran Chen, Hanzhi Yin, Chenghao Xiao, Chenghua Lin, Anton Ragni, Emmanouil Benetos, Norbert Gyenge, Roger B. Dannenberg, Ruibo Liu, Wenhu Chen, Gus Xia, Yemin Shi, Wenhao Huang, Zili Wang, Yike Guo, Jie Fu
2024METRA: Scalable Unsupervised RL with Metric-Aware Abstraction.
Seohong Park, Oleh Rybkin, Sergey Levine
2024MG-TSD: Multi-Granularity Time Series Diffusion Models with Guided Learning Process.
Xinyao Fan, Yueying Wu, Chang Xu, Yuhao Huang, Weiqing Liu, Jiang Bian
2024MINDE: Mutual Information Neural Diffusion Estimation.
Giulio Franzese, Mustapha Bounoua, Pietro Michiardi
2024MINT: Evaluating LLMs in Multi-turn Interaction with Tools and Language Feedback.
Xingyao Wang, Zihan Wang, Jiateng Liu, Yangyi Chen, Lifan Yuan, Hao Peng, Heng Ji
2024MIntRec2.0: A Large-scale Benchmark Dataset for Multimodal Intent Recognition and Out-of-scope Detection in Conversations.
Hanlei Zhang, Xin Wang, Hua Xu, Qianrui Zhou, Kai Gao, Jianhua Su, Jinyue Zhao, Wenrui Li, Yanting Chen
2024MMD Graph Kernel: Effective Metric Learning for Graphs via Maximum Mean Discrepancy.
Yan Sun, Jicong Fan
2024MMICL: Empowering Vision-language Model with Multi-Modal In-Context Learning.
Haozhe Zhao, Zefan Cai, Shuzheng Si, Xiaojian Ma, Kaikai An, Liang Chen, Zixuan Liu, Sheng Wang, Wenjuan Han, Baobao Chang
2024MOFDiff: Coarse-grained Diffusion for Metal-Organic Framework Design.
Xiang Fu, Tian Xie, Andrew S. Rosen, Tommi S. Jaakkola, Jake Smith
2024MOFI: Learning Image Representations from Noisy Entity Annotated Images.
Wentao Wu, Aleksei Timofeev, Chen Chen, Bowen Zhang, Kun Duan, Shuangning Liu, Yantao Zheng, Jonathon Shlens, Xianzhi Du, Yinfei Yang
2024MOTOR: A Time-to-Event Foundation Model For Structured Medical Records.
Ethan Steinberg, Jason Alan Fries, Yizhe Xu, Nigam Shah
2024MT-Ranker: Reference-free machine translation evaluation by inter-system ranking.
Ibraheem Muhammad Moosa, Rui Zhang, Wenpeng Yin
2024MUFFIN: Curating Multi-Faceted Instructions for Improving Instruction Following.
Renze Lou, Kai Zhang, Jian Xie, Yuxuan Sun, Janice Ahn, Hanzi Xu, Yu Su, Wenpeng Yin
2024MUSTARD: Mastering Uniform Synthesis of Theorem and Proof Data.
Yinya Huang, Xiaohan Lin, Zhengying Liu, Qingxing Cao, Huajian Xin, Haiming Wang, Zhenguo Li, Linqi Song, Xiaodan Liang
2024MVDream: Multi-view Diffusion for 3D Generation.
Yichun Shi, Peng Wang, Jianglong Ye, Long Mai, Kejie Li, Xiao Yang
2024MVSFormer++: Revealing the Devil in Transformer's Details for Multi-View Stereo.
Chenjie Cao, Xinlin Ren, Yanwei Fu
2024MaGIC: Multi-modality Guided Image Completion.
Hao Wang, Yongsheng Yu, Tiejian Luo, Heng Fan, Libo Zhang
2024Machine Unlearning for Image-to-Image Generative Models.
Guihong Li, Hsiang Hsu, Chun-Fu Chen, Radu Marculescu
2024Magic123: One Image to High-Quality 3D Object Generation Using Both 2D and 3D Diffusion Priors.
Guocheng Qian, Jinjie Mai, Abdullah Hamdi, Jian Ren, Aliaksandr Siarohin, Bing Li, Hsin-Ying Lee, Ivan Skorokhodov, Peter Wonka, Sergey Tulyakov, Bernard Ghanem
2024MagicDrive: Street View Generation with Diverse 3D Geometry Control.
Ruiyuan Gao, Kai Chen, Enze Xie, Lanqing Hong, Zhenguo Li, Dit-Yan Yeung, Qiang Xu
2024Magnitude Invariant Parametrizations Improve Hypernetwork Learning.
Jose Javier Gonzalez Ortiz, John V. Guttag, Adrian V. Dalca
2024Magnushammer: A Transformer-Based Approach to Premise Selection.
Maciej Mikula, Szymon Tworkowski, Szymon Antoniak, Bartosz Piotrowski, Albert Q. Jiang, Jin Peng Zhou, Christian Szegedy, Lukasz Kucinski, Piotr Milos, Yuhuai Wu
2024Making LLaMA SEE and Draw with SEED Tokenizer.
Yuying Ge, Sijie Zhao, Ziyun Zeng, Yixiao Ge, Chen Li, Xintao Wang, Ying Shan
2024Making Pre-trained Language Models Great on Tabular Prediction.
Jiahuan Yan, Bo Zheng, Hongxia Xu, Yiheng Zhu, Danny Z. Chen, Jimeng Sun, Jian Wu, Jintai Chen
2024Making RL with Preference-based Feedback Efficient via Randomization.
Runzhe Wu, Wen Sun
2024Making Retrieval-Augmented Language Models Robust to Irrelevant Context.
Ori Yoran, Tomer Wolfson, Ori Ram, Jonathan Berant
2024Manifold Diffusion Fields.
Ahmed A. A. Elhag, Yuyang Wang, Joshua M. Susskind, Miguel Ángel Bautista
2024Manifold Preserving Guided Diffusion.
Yutong He, Naoki Murata, Chieh-Hsin Lai, Yuhta Takida, Toshimitsu Uesaka, Dongjun Kim, Wei-Hsiang Liao, Yuki Mitsufuji, J. Zico Kolter, Ruslan Salakhutdinov, Stefano Ermon
2024Manipulating dropout reveals an optimal balance of efficiency and robustness in biological and machine visual systems.
Jacob S. Prince, Gabriel Fajardo, George A. Alvarez, Talia Konkle
2024Mask-Based Modeling for Neural Radiance Fields.
Ganlin Yang, Guoqiang Wei, Zhizheng Zhang, Yan Lu, Dong Liu
2024Masked Audio Generation using a Single Non-Autoregressive Transformer.
Alon Ziv, Itai Gat, Gaël Le Lan, Tal Remez, Felix Kreuk, Jade Copet, Alexandre Défossez, Gabriel Synnaeve, Yossi Adi
2024Masked Autoencoders with Multi-Window Local-Global Attention Are Better Audio Learners.
Sarthak Yadav, Sergios Theodoridis, Lars Kai Hansen, Zheng-Hua Tan
2024Masked Completion via Structured Diffusion with White-Box Transformers.
Druv Pai, Sam Buchanan, Ziyang Wu, Yaodong Yu, Yi Ma
2024Masked Distillation Advances Self-Supervised Transformer Architecture Search.
Caixia Yan, Xiaojun Chang, Zhihui Li, Lina Yao, Minnan Luo, Qinghua Zheng
2024Masked Structural Growth for 2x Faster Language Model Pre-training.
Yiqun Yao, Zheng Zhang, Jing Li, Yequan Wang
2024Masks, Signs, And Learning Rate Rewinding.
Advait Harshal Gadhikar, Rebekka Burkholz
2024Massive Editing for Large Language Models via Meta Learning.
Chenmien Tan, Ge Zhang, Jie Fu
2024Massively Scalable Inverse Reinforcement Learning in Google Maps.
Matt Barnes, Matthew Abueg, Oliver F. Lange, Matt Deeds, Jason Trader, Denali Molitor, Markus Wulfmeier, Shawn O'Banion
2024Mastering Memory Tasks with World Models.
Mohammad Reza Samsami, Artem Zholus, Janarthanan Rajendran, Sarath Chandar
2024Mastering Symbolic Operations: Augmenting Language Models with Compiled Neural Networks.
Yixuan Weng, Minjun Zhu, Fei Xia, Bin Li, Shizhu He, Kang Liu, Jun Zhao
2024Matcher: Segment Anything with One Shot Using All-Purpose Feature Matching.
Yang Liu, Muzhi Zhu, Hengtao Li, Hao Chen, Xinlong Wang, Chunhua Shen
2024MathCoder: Seamless Code Integration in LLMs for Enhanced Mathematical Reasoning.
Ke Wang, Houxing Ren, Aojun Zhou, Zimu Lu, Sichun Luo, Weikang Shi, Renrui Zhang, Linqi Song, Mingjie Zhan, Hongsheng Li
2024MathVista: Evaluating Mathematical Reasoning of Foundation Models in Visual Contexts.
Pan Lu, Hritik Bansal, Tony Xia, Jiacheng Liu, Chunyuan Li, Hannaneh Hajishirzi, Hao Cheng, Kai-Wei Chang, Michel Galley, Jianfeng Gao
2024Mathematical Justification of Hard Negative Mining via Isometric Approximation Theorem.
Albert Xu, Jhih-Yi Hsieh, Bhaskar Vundurthy, Nithya Kemp, Eliana Cohen, Lu Li, Howie Choset
2024Matrix Manifold Neural Networks++.
Xuan Son Nguyen, Shuo Yang, Aymeric Histace
2024Matryoshka Diffusion Models.
Jiatao Gu, Shuangfei Zhai, Yizhe Zhang, Joshua M. Susskind, Navdeep Jaitly
2024Maximum Entropy Heterogeneous-Agent Reinforcement Learning.
Jiarong Liu, Yifan Zhong, Siyi Hu, Haobo Fu, Qiang Fu, Xiaojun Chang, Yaodong Yang
2024Maximum Entropy Model Correction in Reinforcement Learning.
Amin Rakhsha, Mete Kemertas, Mohammad Ghavamzadeh, Amir-massoud Farahmand
2024Maximum Likelihood Estimation is All You Need for Well-Specified Covariate Shift.
Jiawei Ge, Shange Tang, Jianqing Fan, Cong Ma, Chi Jin
2024Mayfly: a Neural Data Structure for Graph Stream Summarization.
Yuan Feng, Yukun Cao, Hairu Wang, Xike Xie, S. Kevin Zhou
2024Mean Field Theory in Deep Metric Learning.
Takuya Furusawa
2024Meaning Representations from Trajectories in Autoregressive Models.
Tian Yu Liu, Matthew Trager, Alessandro Achille, Pramuditha Perera, Luca Zancato, Stefano Soatto
2024Measuring Vision-Language STEM Skills of Neural Models.
Jianhao Shen, Ye Yuan, Srbuhi Mirzoyan, Ming Zhang, Chenguang Wang
2024Mechanistically analyzing the effects of fine-tuning on procedurally defined tasks.
Samyak Jain, Robert Kirk, Ekdeep Singh Lubana, Robert P. Dick, Hidenori Tanaka, Tim Rocktäschel, Edward Grefenstette, David Scott Krueger
2024Mediator Interpretation and Faster Learning Algorithms for Linear Correlated Equilibria in General Sequential Games.
Brian Hu Zhang, Gabriele Farina, Tuomas Sandholm
2024Mega-TTS 2: Boosting Prompting Mechanisms for Zero-Shot Speech Synthesis.
Ziyue Jiang, Jinglin Liu, Yi Ren, Jinzheng He, Zhenhui Ye, Shengpeng Ji, Qian Yang, Chen Zhang, Pengfei Wei, Chunfeng Wang, Xiang Yin, Zejun Ma, Zhou Zhao
2024Memorization Capacity of Multi-Head Attention in Transformers.
Sadegh Mahdavi, Renjie Liao, Christos Thrampoulidis
2024Memorization in Self-Supervised Learning Improves Downstream Generalization.
Wenhao Wang, Muhammad Ahmad Kaleem, Adam Dziedzic, Michael Backes, Nicolas Papernot, Franziska Boenisch
2024Memory-Assisted Sub-Prototype Mining for Universal Domain Adaptation.
Yuxiang Lai, Yi Zhou, Xinghong Liu, Tao Zhou
2024Memory-Consistent Neural Networks for Imitation Learning.
Kaustubh Sridhar, Souradeep Dutta, Dinesh Jayaraman, James Weimer, Insup Lee
2024Merge, Then Compress: Demystify Efficient SMoE with Hints from Its Routing Policy.
Pingzhi Li, Zhenyu Zhang, Prateek Yadav, Yi-Lin Sung, Yu Cheng, Mohit Bansal, Tianlong Chen
2024Meta Continual Learning Revisited: Implicitly Enhancing Online Hessian Approximation via Variance Reduction.
Yichen Wu, Long-Kai Huang, Renzhen Wang, Deyu Meng, Ying Wei
2024Meta Inverse Constrained Reinforcement Learning: Convergence Guarantee and Generalization Analysis.
Shicheng Liu, Minghui Zhu
2024Meta-Evolve: Continuous Robot Evolution for One-to-many Policy Transfer.
Xingyu Liu, Deepak Pathak, Ding Zhao
2024Meta-Learning Priors Using Unrolled Proximal Networks.
Yilang Zhang, Georgios B. Giannakis
2024Meta-VBO: Utilizing Prior Tasks in Optimizing Risk Measures with Gaussian Processes.
Quoc Phong Nguyen, Bryan Kian Hsiang Low, Patrick Jaillet
2024MetaCoCo: A New Few-Shot Classification Benchmark with Spurious Correlation.
Min Zhang, Haoxuan Li, Fei Wu, Kun Kuang
2024MetaGPT: Meta Programming for A Multi-Agent Collaborative Framework.
Sirui Hong, Mingchen Zhuge, Jonathan Chen, Xiawu Zheng, Yuheng Cheng, Jinlin Wang, Ceyao Zhang, Zili Wang, Steven Ka Shing Yau, Zijuan Lin, Liyang Zhou, Chenyu Ran, Lingfeng Xiao, Chenglin Wu, Jürgen Schmidhuber
2024MetaMath: Bootstrap Your Own Mathematical Questions for Large Language Models.
Longhui Yu, Weisen Jiang, Han Shi, Jincheng Yu, Zhengying Liu, Yu Zhang, James T. Kwok, Zhenguo Li, Adrian Weller, Weiyang Liu
2024MetaPhysiCa: Improving OOD Robustness in Physics-informed Machine Learning.
S. Chandra Mouli, Muhammad Ashraful Alam, Bruno Ribeiro
2024MetaTool Benchmark for Large Language Models: Deciding Whether to Use Tools and Which to Use.
Yue Huang, Jiawen Shi, Yuan Li, Chenrui Fan, Siyuan Wu, Qihui Zhang, Yixin Liu, Pan Zhou, Yao Wan, Neil Zhenqiang Gong, Lichao Sun
2024MgNO: Efficient Parameterization of Linear Operators via Multigrid.
Juncai He, Xinliang Liu, Jinchao Xu
2024Mind Your Augmentation: The Key to Decoupling Dense Self-Supervised Learning.
Congpei Qiu, Tong Zhang, Yanhao Wu, Wei Ke, Mathieu Salzmann, Sabine Süsstrunk
2024MiniGPT-4: Enhancing Vision-Language Understanding with Advanced Large Language Models.
Deyao Zhu, Jun Chen, Xiaoqian Shen, Xiang Li, Mohamed Elhoseiny
2024MiniLLM: Knowledge Distillation of Large Language Models.
Yuxian Gu, Li Dong, Furu Wei, Minlie Huang
2024Minimax optimality of convolutional neural networks for infinite dimensional input-output problems and separation from kernel methods.
Yuto Nishimura, Taiji Suzuki
2024Minimum width for universal approximation using ReLU networks on compact domain.
Namjun Kim, Chanho Min, Sejun Park
2024Mirage: Model-agnostic Graph Distillation for Graph Classification.
Mridul Gupta, Sahil Manchanda, Hariprasad Kodamana, Sayan Ranu
2024Mitigating Emergent Robustness Degradation while Scaling Graph Learning.
Xiangchi Yuan, Chunhui Zhang, Yijun Tian, Yanfang Ye, Chuxu Zhang
2024Mitigating Hallucination in Large Multi-Modal Models via Robust Instruction Tuning.
Fuxiao Liu, Kevin Lin, Linjie Li, Jianfeng Wang, Yaser Yacoob, Lijuan Wang
2024Mitigating the Curse of Dimensionality for Certified Robustness via Dual Randomized Smoothing.
Song Xia, Yi Yu, Xudong Jiang, Henghui Ding
2024MixSATGEN: Learning Graph Mixing for SAT Instance Generation.
Xinyan Chen, Yang Li, Runzhong Wang, Junchi Yan
2024MixSup: Mixed-grained Supervision for Label-efficient LiDAR-based 3D Object Detection.
Yuxue Yang, Lue Fan, Zhaoxiang Zhang
2024Mixed-Type Tabular Data Synthesis with Score-based Diffusion in Latent Space.
Hengrui Zhang, Jiani Zhang, Zhengyuan Shen, Balasubramaniam Srinivasan, Xiao Qin, Christos Faloutsos, Huzefa Rangwala, George Karypis
2024Mixture of LoRA Experts.
Xun Wu, Shaohan Huang, Furu Wei
2024Mixture of Weak and Strong Experts on Graphs.
Hanqing Zeng, Hanjia Lyu, Diyi Hu, Yinglong Xia, Jiebo Luo
2024Mixture-of-Experts Meets Instruction Tuning: A Winning Combination for Large Language Models.
Sheng Shen, Le Hou, Yanqi Zhou, Nan Du, Shayne Longpre, Jason Wei, Hyung Won Chung, Barret Zoph, William Fedus, Xinyun Chen, Tu Vu, Yuexin Wu, Wuyang Chen, Albert Webson, Yunxuan Li, Vincent Y. Zhao, Hongkun Yu, Kurt Keutzer, Trevor Darrell, Denny Zhou
2024Model Merging by Uncertainty-Based Gradient Matching.
Nico Daheim, Thomas Möllenhoff, Edoardo M. Ponti, Iryna Gurevych, Mohammad Emtiyaz Khan
2024Model Tells You What to Discard: Adaptive KV Cache Compression for LLMs.
Suyu Ge, Yunan Zhang, Liyuan Liu, Minjia Zhang, Jiawei Han, Jianfeng Gao
2024Modeling Boundedly Rational Agents with Latent Inference Budgets.
Athul Paul Jacob, Abhishek Gupta, Jacob Andreas
2024Modeling state-dependent communication between brain regions with switching nonlinear dynamical systems.
Orren Karniol-Tambour, David M. Zoltowski, E. Mika Diamanti, Lucas Pinto, Carlos D. Brody, David W. Tank, Jonathan W. Pillow
2024Modelling complex vector drawings with stroke-clouds.
Alexander Ashcroft, Ayan Das, Yulia Gryaditskaya, Zhiyu Qu, Yi-Zhe Song
2024ModernTCN: A Modern Pure Convolution Structure for General Time Series Analysis.
Donghao Luo, Xue Wang
2024Modulate Your Spectrum in Self-Supervised Learning.
Xi Weng, Yunhao Ni, Tengwei Song, Jie Luo, Rao Muhammad Anwer, Salman Khan, Fahad Khan, Lei Huang
2024Modulated Phase Diffusor: Content-Oriented Feature Synthesis for Detecting Unknown Objects.
Aming Wu, Cheng Deng
2024MogaNet: Multi-order Gated Aggregation Network.
Siyuan Li, Zedong Wang, Zicheng Liu, Cheng Tan, Haitao Lin, Di Wu, Zhiyuan Chen, Jiangbin Zheng, Stan Z. Li
2024Mol-Instructions: A Large-Scale Biomolecular Instruction Dataset for Large Language Models.
Yin Fang, Xiaozhuan Liang, Ningyu Zhang, Kangwei Liu, Rui Huang, Zhuo Chen, Xiaohui Fan, Huajun Chen
2024Momentum Benefits Non-iid Federated Learning Simply and Provably.
Ziheng Cheng, Xinmeng Huang, Pengfei Wu, Kun Yuan
2024Monte Carlo guided Denoising Diffusion models for Bayesian linear inverse problems.
Gabriel Cardoso, Yazid Janati El Idrissi, Sylvain Le Corff, Eric Moulines
2024More is Better: when Infinite Overparameterization is Optimal and Overfitting is Obligatory.
James B. Simon, Dhruva Karkada, Nikhil Ghosh, Mikhail Belkin
2024Most discriminative stimuli for functional cell type clustering.
Max F. Burg, Thomas Zenkel, Michaela Vystrcilová, Jonathan Oesterle, Larissa Höfling, Konstantin F. Willeke, Jan Lause, Sarah Müller, Paul G. Fahey, Zhiwei Ding, Kelli Restivo, Shashwat Sridhar, Tim Gollisch, Philipp Berens, Andreas S. Tolias, Thomas Euler, Matthias Bethge, Alexander S. Ecker
2024Motif: Intrinsic Motivation from Artificial Intelligence Feedback.
Martin Klissarov, Pierluca D'Oro, Shagun Sodhani, Roberta Raileanu, Pierre-Luc Bacon, Pascal Vincent, Amy Zhang, Mikael Henaff
2024Motion Guidance: Diffusion-Based Image Editing with Differentiable Motion Estimators.
Daniel Geng, Andrew Owens
2024MovingParts: Motion-based 3D Part Discovery in Dynamic Radiance Field.
Kaizhi Yang, Xiaoshuai Zhang, Zhiao Huang, Xuejin Chen, Zexiang Xu, Hao Su
2024MuSR: Testing the Limits of Chain-of-thought with Multistep Soft Reasoning.
Zayne Sprague, Xi Ye, Kaj Bostrom, Swarat Chaudhuri, Greg Durrett
2024MuSc: Zero-Shot Industrial Anomaly Classification and Segmentation with Mutual Scoring of the Unlabeled Images.
Xurui Li, Ziming Huang, Feng Xue, Yu Zhou
2024Multi-Resolution Diffusion Models for Time Series Forecasting.
Lifeng Shen, Weiyu Chen, James T. Kwok
2024Multi-Scale Representations by Varying Window Attention for Semantic Segmentation.
Haotian Yan, Ming Wu, Chuang Zhang
2024Multi-Source Diffusion Models for Simultaneous Music Generation and Separation.
Giorgio Mariani, Irene Tallini, Emilian Postolache, Michele Mancusi, Luca Cosmo, Emanuele Rodolà
2024Multi-Task Reinforcement Learning with Mixture of Orthogonal Experts.
Ahmed Hendawy, Jan Peters, Carlo D'Eramo
2024Multi-View Causal Representation Learning with Partial Observability.
Dingling Yao, Danru Xu, Sébastien Lachapelle, Sara Magliacane, Perouz Taslakian, Georg Martius, Julius von Kügelgen, Francesco Locatello
2024Multi-View Representation is What You Need for Point-Cloud Pre-Training.
Siming Yan, Chen Song, Youkang Kong, Qixing Huang
2024Multi-granularity Correspondence Learning from Long-term Noisy Videos.
Yijie Lin, Jie Zhang, Zhenyu Huang, Jia Liu, Zujie Wen, Xi Peng
2024Multi-modal Gaussian Process Variational Autoencoders for Neural and Behavioral Data.
Rabia Gondur, Usama Bin Sikandar, Evan Schaffer, Mikio Christian Aoi, Stephen L. Keeley
2024Multi-resolution HuBERT: Multi-resolution Speech Self-Supervised Learning with Masked Unit Prediction.
Jiatong Shi, Hirofumi Inaguma, Xutai Ma, Ilia Kulikov, Anna Y. Sun
2024Multi-task Learning with 3D-Aware Regularization.
Wei-Hong Li, Steven McDonagh, Ales Leonardis, Hakan Bilen
2024Multilinear Operator Networks.
Yixin Cheng, Grigorios Chrysos, Markos Georgopoulos, Volkan Cevher
2024Multilingual Jailbreak Challenges in Large Language Models.
Yue Deng, Wenxuan Zhang, Sinno Jialin Pan, Lidong Bing
2024Multimarginal Generative Modeling with Stochastic Interpolants.
Michael S. Albergo, Nicholas Matthew Boffi, Michael Lindsey, Eric Vanden-Eijnden
2024Multimodal Learning Without Labeled Multimodal Data: Guarantees and Applications.
Paul Pu Liang, Chun Kai Ling, Yun Cheng, Alexander Obolenskiy, Yudong Liu, Rohan Pandey, Alex Wilf, Louis-Philippe Morency, Russ Salakhutdinov
2024Multimodal Molecular Pretraining via Modality Blending.
Qiying Yu, Yudi Zhang, Yuyan Ni, Shikun Feng, Yanyan Lan, Hao Zhou, Jingjing Liu
2024Multimodal Patient Representation Learning with Missing Modalities and Labels.
Zhenbang Wu, Anant Dadu, Nicholas J. Tustison, Brian B. Avants, Mike A. Nalls, Jimeng Sun, Faraz Faghri
2024Multimodal Web Navigation with Instruction-Finetuned Foundation Models.
Hiroki Furuta, Kuang-Huei Lee, Ofir Nachum, Yutaka Matsuo, Aleksandra Faust, Shixiang Shane Gu, Izzeddin Gur
2024Multiscale Positive-Unlabeled Detection of AI-Generated Texts.
Yuchuan Tian, Hanting Chen, Xutao Wang, Zheyuan Bai, Qinghua Zhang, Ruifeng Li, Chao Xu, Yunhe Wang
2024Multisize Dataset Condensation.
Yang He, Lingao Xiao, Joey Tianyi Zhou, Ivor W. Tsang
2024NAISR: A 3D Neural Additive Model for Interpretable Shape Representation.
Yining Jiao, Carlton J. Zdanski, Julia S. Kimbell, Andrew Prince, Cameron Worden, Samuel Kirse, Christopher Rutter, Benjamin Shields, William Dunn, Jisan Mahmud, Marc Niethammer
2024NECO: NEural Collapse Based Out-of-distribution detection.
Mouïn Ben Ammar, Nacim Belkhir, Sebastian Popescu, Antoine Manzanera, Gianni Franchi
2024NEFTune: Noisy Embeddings Improve Instruction Finetuning.
Neel Jain, Ping-Yeh Chiang, Yuxin Wen, John Kirchenbauer, Hong-Min Chu, Gowthami Somepalli, Brian R. Bartoldson, Bhavya Kailkhura, Avi Schwarzschild, Aniruddha Saha, Micah Goldblum, Jonas Geiping, Tom Goldstein
2024NOLA: Compressing LoRA using Linear Combination of Random Basis.
Soroush Abbasi Koohpayegani, Navaneet K. L., Parsa Nooralinejad, Soheil Kolouri, Hamed Pirsiavash
2024NaturalSpeech 2: Latent Diffusion Models are Natural and Zero-Shot Speech and Singing Synthesizers.
Kai Shen, Zeqian Ju, Xu Tan, Eric Liu, Yichong Leng, Lei He, Tao Qin, Sheng Zhao, Jiang Bian
2024Navigating Dataset Documentations in AI: A Large-Scale Analysis of Dataset Cards on HuggingFace.
Xinyu Yang, Weixin Liang, James Zou
2024Navigating Text-To-Image Customization: From LyCORIS Fine-Tuning to Model Evaluation.
Shih-Ying Yeh, Yu-Guan Hsieh, Zhidong Gao, Bernard B. W. Yang, Giyeong Oh, Yanmin Gong
2024Navigating the Design Space of Equivariant Diffusion-Based Generative Models for De Novo 3D Molecule Generation.
Tuan Le, Julian Cremer, Frank Noé, Djork-Arné Clevert, Kristof T. Schütt
2024NeRM: Learning Neural Representations for High-Framerate Human Motion Synthesis.
Dong Wei, Huaijiang Sun, Bin Li, Xiaoning Sun, Shengxiang Hu, Weiqing Li, Jianfeng Lu
2024Near-Optimal Quantum Algorithm for Minimizing the Maximal Loss.
Hao Wang, Chenyi Zhang, Tongyang Li
2024Near-Optimal Solutions of Constrained Learning Problems.
Juan Elenter, Luiz F. O. Chamon, Alejandro Ribeiro
2024Nearly d-Linear Convergence Bounds for Diffusion Models via Stochastic Localization.
Joe Benton, Valentin De Bortoli, Arnaud Doucet, George Deligiannidis
2024Negative Label Guided OOD Detection with Pretrained Vision-Language Models.
Xue Jiang, Feng Liu, Zhen Fang, Hong Chen, Tongliang Liu, Feng Zheng, Bo Han
2024Negatively Correlated Ensemble Reinforcement Learning for Online Diverse Game Level Generation.
Ziqi Wang, Chengpeng Hu, Jialin Liu, Xin Yao
2024Nemesis: Normalizing the Soft-prompt Vectors of Vision-Language Models.
Shuai Fu, Xiequn Wang, Qiushi Huang, Yu Zhang
2024NetInfoF Framework: Measuring and Exploiting Network Usable Information.
Meng-Chieh Lee, Haiyang Yu, Jian Zhang, Vassilis N. Ioannidis, Xiang Song, Soji Adeshina, Da Zheng, Christos Faloutsos
2024Network Memory Footprint Compression Through Jointly Learnable Codebooks and Mappings.
Edouard Yvinec, Arnaud Dapogny, Kevin Bailly
2024Neur2RO: Neural Two-Stage Robust Optimization.
Justin Dumouchelle, Esther Julien, Jannis Kurtz, Elias Boutros Khalil
2024NeurRev: Train Better Sparse Neural Network Practically via Neuron Revitalization.
Gen Li, Lu Yin, Jie Ji, Wei Niu, Minghai Qin, Bin Ren, Linke Guo, Shiwei Liu, Xiaolong Ma
2024Neural Active Learning Beyond Bandits.
Yikun Ban, Ishika Agarwal, Ziwei Wu, Yada Zhu, Kommy Weldemariam, Hanghang Tong, Jingrui He
2024Neural Architecture Retrieval.
Xiaohuan Pei, Yanxi Li, Minjing Dong, Chang Xu
2024Neural Atoms: Propagating Long-range Interaction in Molecular Graphs through Efficient Communication Channel.
Xuan Li, Zhanke Zhou, Jiangchao Yao, Yu Rong, Lu Zhang, Bo Han
2024Neural Auto-designer for Enhanced Quantum Kernels.
Cong Lei, Yuxuan Du, Peng Mi, Jun Yu, Tongliang Liu
2024Neural Common Neighbor with Completion for Link Prediction.
Xiyuan Wang, Haotong Yang, Muhan Zhang
2024Neural Contractive Dynamical Systems.
Hadi Beik-Mohammadi, Søren Hauberg, Georgios Arvanitidis, Nadia Figueroa, Gerhard Neumann, Leonel Rozo
2024Neural Field Classifiers via Target Encoding and Classification Loss.
Xindi Yang, Zeke Xie, Xiong Zhou, Boyu Liu, Buhua Liu, Yi Liu, Haoran Wang, Yunfeng Cai, Mingming Sun
2024Neural Fine-Tuning Search for Few-Shot Learning.
Panagiotis Eustratiadis, Lukasz Dudziak, Da Li, Timothy M. Hospedales
2024Neural Fourier Transform: A General Approach to Equivariant Representation Learning.
Masanori Koyama, Kenji Fukumizu, Kohei Hayashi, Takeru Miyato
2024Neural Language of Thought Models.
Yi-Fu Wu, Minseung Lee, Sungjin Ahn
2024Neural Neighborhood Search for Multi-agent Path Finding.
Zhongxia Yan, Cathy Wu
2024Neural Network-Based Score Estimation in Diffusion Models: Optimization and Generalization.
Yinbin Han, Meisam Razaviyayn, Renyuan Xu
2024Neural Optimal Transport with General Cost Functionals.
Arip Asadulaev, Alexander Korotin, Vage Egiazarian, Petr Mokrov, Evgeny Burnaev
2024Neural Polynomial Gabor Fields for Macro Motion Analysis.
Chen Geng, Hong-Xing Yu, Sida Peng, Xiaowei Zhou, Jiajun Wu
2024Neural Processing of Tri-Plane Hybrid Neural Fields.
Adriano Cardace, Pierluigi Zama Ramirez, Francesco Ballerini, Allan Zhou, Samuele Salti, Luigi Di Stefano
2024Neural Rate Control for Learned Video Compression.
Yiwei Zhang, Guo Lu, Yunuo Chen, Shen Wang, Yibo Shi, Jing Wang, Li Song
2024Neural SDF Flow for 3D Reconstruction of Dynamic Scenes.
Wei Mao, Richard Hartley, Mathieu Salzmann, Miaomiao Liu
2024Neural Snowflakes: Universal Latent Graph Inference via Trainable Latent Geometries.
Haitz Sáez de Ocáriz Borde, Anastasis Kratsios
2024Neural Spectral Methods: Self-supervised learning in the spectral domain.
Yiheng Du, Nithin Chalapathi, Aditi S. Krishnapriyan
2024Neural structure learning with stochastic differential equations.
Benjie Wang, Joel Jennings, Wenbo Gong
2024Neural-Symbolic Recursive Machine for Systematic Generalization.
Qing Li, Yixin Zhu, Yitao Liang, Ying Nian Wu, Song-Chun Zhu, Siyuan Huang
2024Neuro-Inspired Information-Theoretic Hierarchical Perception for Multimodal Learning.
Xiongye Xiao, Gengshuo Liu, Gaurav Gupta, Defu Cao, Shixuan Li, Yaxing Li, Tianqing Fang, Mingxi Cheng, Paul Bogdan
2024NeuroBack: Improving CDCL SAT Solving using Graph Neural Networks.
Wenxi Wang, Yang Hu, Mohit Tiwari, Sarfraz Khurshid, Kenneth L. McMillan, Risto Miikkulainen
2024Neuroformer: Multimodal and Multitask Generative Pretraining for Brain Data.
Antonis Antoniades, Yiyi Yu, Joseph Canzano, William Yang Wang, Spencer L. Smith
2024Neuron Activation Coverage: Rethinking Out-of-distribution Detection and Generalization.
Yibing Liu, Chris Xing Tian, Haoliang Li, Lei Ma, Shiqi Wang
2024Neuron-Enhanced AutoEncoder Matrix Completion and Collaborative Filtering: Theory and Practice.
Jicong Fan, Rui Chen, Zhao Zhang, Chris Ding
2024Neurosymbolic Grounding for Compositional World Models.
Atharva Sehgal, Arya Grayeli, Jennifer J. Sun, Swarat Chaudhuri
2024Never Train from Scratch: Fair Comparison of Long-Sequence Models Requires Data-Driven Priors.
Ido Amos, Jonathan Berant, Ankit Gupta
2024New Insight of Variance reduce in Zero-Order Hard-Thresholding: Mitigating Gradient Error and Expansivity Contradictions.
Xinzhe Yuan, William de Vazelhes, Bin Gu, Huan Xiong
2024NfgTransformer: Equivariant Representation Learning for Normal-form Games.
Siqi Liu, Luke Marris, Georgios Piliouras, Ian Gemp, Nicolas Heess
2024Node2ket: Efficient High-Dimensional Network Embedding in Quantum Hilbert Space.
Hao Xiong, Yehui Tang, Yunlin He, Wei Tan, Junchi Yan
2024Noise Map Guidance: Inversion with Spatial Context for Real Image Editing.
Hansam Cho, Jonghyun Lee, Seoung Bum Kim, Tae-Hyun Oh, Yonghyun Jeong
2024Noise-free Score Distillation.
Oren Katzir, Or Patashnik, Daniel Cohen-Or, Dani Lischinski
2024NoiseDiffusion: Correcting Noise for Image Interpolation with Diffusion Models beyond Spherical Linear Interpolation.
Pengfei Zheng, Yonggang Zhang, Zhen Fang, Tongliang Liu, Defu Lian, Bo Han
2024Noisy Interpolation Learning with Shallow Univariate ReLU Networks.
Nirmit Joshi, Gal Vardi, Nathan Srebro
2024Non-Exchangeable Conformal Risk Control.
António Farinhas, Chrysoula Zerva, Dennis Ulmer, André F. T. Martins
2024Non-negative Contrastive Learning.
Yifei Wang, Qi Zhang, Yaoyu Guo, Yisen Wang
2024Nougat: Neural Optical Understanding for Academic Documents.
Lukas Blecher, Guillem Cucurull, Thomas Scialom, Robert Stojnic
2024Novel Quadratic Constraints for Extending LipSDP beyond Slope-Restricted Activations.
Patricia Pauli, Aaron J. Havens, Alexandre Araujo, Siddharth Garg, Farshad Khorrami, Frank Allgöwer, Bin Hu
2024NuwaDynamics: Discovering and Updating in Causal Spatio-Temporal Modeling.
Kun Wang, Hao Wu, Yifan Duan, Guibin Zhang, Kai Wang, Xiaojiang Peng, Yu Zheng, Yuxuan Liang, Yang Wang
2024ODE Discovery for Longitudinal Heterogeneous Treatment Effects Inference.
Krzysztof Kacprzyk, Samuel Holt, Jeroen Berrevoets, Zhaozhi Qian, Mihaela van der Schaar
2024ODEFormer: Symbolic Regression of Dynamical Systems with Transformers.
Stéphane d'Ascoli, Sören Becker, Philippe Schwaller, Alexander Mathis, Niki Kilbertus
2024ODICE: Revealing the Mystery of Distribution Correction Estimation via Orthogonal-gradient Update.
Liyuan Mao, Haoran Xu, Weinan Zhang, Xianyuan Zhan
2024OMNI: Open-endedness via Models of human Notions of Interestingness.
Jenny Zhang, Joel Lehman, Kenneth O. Stanley, Jeff Clune
2024OVOR: OnePrompt with Virtual Outlier Regularization for Rehearsal-Free Class-Incremental Learning.
Wei-Cheng Huang, Chun-Fu Richard Chen, Hsiang Hsu
2024OWL: A Large Language Model for IT Operations.
Hongcheng Guo, Jian Yang, Jiaheng Liu, Liqun Yang, Linzheng Chai, Jiaqi Bai, Junran Peng, Xiaorong Hu, Chao Chen, Dongfeng Zhang, Xu Shi, Tieqiao Zheng, Liangfan Zheng, Bo Zhang, Ke Xu, Zhoujun Li
2024Object centric architectures enable efficient causal representation learning.
Amin Mansouri, Jason S. Hartford, Yan Zhang, Yoshua Bengio
2024Object-Aware Inversion and Reassembly for Image Editing.
Zhen Yang, Ganggui Ding, Wen Wang, Hao Chen, Bohan Zhuang, Chunhua Shen
2024Object-Centric Learning with Slot Mixture Module.
Daniil E. Kirilenko, Vitaliy Vorobyov, Alexey K. Kovalev, Aleksandr Panov
2024Octavius: Mitigating Task Interference in MLLMs via LoRA-MoE.
Zeren Chen, Ziqin Wang, Zhen Wang, Huayang Liu, Zhenfei Yin, Si Liu, Lu Sheng, Wanli Ouyang, Jing Shao
2024OctoPack: Instruction Tuning Code Large Language Models.
Niklas Muennighoff, Qian Liu, Armel Randy Zebaze, Qinkai Zheng, Binyuan Hui, Terry Yue Zhuo, Swayam Singh, Xiangru Tang, Leandro von Werra, Shayne Longpre
2024Off-Policy Primal-Dual Safe Reinforcement Learning.
Zifan Wu, Bo Tang, Qian Lin, Chao Yu, Shangqin Mao, Qianlong Xie, Xingxing Wang, Dong Wang
2024Offline Data Enhanced On-Policy Policy Gradient with Provable Guarantees.
Yifei Zhou, Ayush Sekhari, Yuda Song, Wen Sun
2024Offline RL with Observation Histories: Analyzing and Improving Sample Complexity.
Joey Hong, Anca D. Dragan, Sergey Levine
2024OmniControl: Control Any Joint at Any Time for Human Motion Generation.
Yiming Xie, Varun Jampani, Lei Zhong, Deqing Sun, Huaizu Jiang
2024OmniQuant: Omnidirectionally Calibrated Quantization for Large Language Models.
Wenqi Shao, Mengzhao Chen, Zhaoyang Zhang, Peng Xu, Lirui Zhao, Zhiqian Li, Kaipeng Zhang, Peng Gao, Yu Qiao, Ping Luo
2024On Accelerating Diffusion-Based Sampling Processes via Improved Integration Approximation.
Guoqiang Zhang, Kenta Niwa, W. Bastiaan Kleijn
2024On Adversarial Training without Perturbing all Examples.
Max Maria Losch, Mohamed Omran, David Stutz, Mario Fritz, Bernt Schiele
2024On Bias-Variance Alignment in Deep Models.
Lin Chen, Michal Lukasik, Wittawat Jitkrittum, Chong You, Sanjiv Kumar
2024On Differentially Private Federated Linear Contextual Bandits.
Xingyu Zhou, Sayak Ray Chowdhury
2024On Diffusion Modeling for Anomaly Detection.
Victor Livernoche, Vineet Jain, Yashar Hezaveh, Siamak Ravanbakhsh
2024On Double Descent in Reinforcement Learning with LSTD and Random Features.
David Brellmann, Eloïse Berthier, David Filliat, Goran Frehse
2024On Error Propagation of Diffusion Models.
Yangming Li, Mihaela van der Schaar
2024On Harmonizing Implicit Subpopulations.
Feng Hong, Jiangchao Yao, Yueming Lyu, Zhihan Zhou, Ivor W. Tsang, Ya Zhang, Yanfeng Wang
2024On Penalty Methods for Nonconvex Bilevel Optimization and First-Order Stochastic Approximation.
Jeongyeol Kwon, Dohyun Kwon, Stephen Wright, Robert D. Nowak
2024On Representation Complexity of Model-based and Model-free Reinforcement Learning.
Hanlin Zhu, Baihe Huang, Stuart Russell
2024On Stationary Point Convergence of PPO-Clip.
Ruinan Jin, Shuai Li, Baoxiang Wang
2024On Trajectory Augmentations for Off-Policy Evaluation.
Ge Gao, Qitong Gao, Xi Yang, Song Ju, Miroslav Pajic, Min Chi
2024On gauge freedom, conservativity and intrinsic dimensionality estimation in diffusion models.
Christian Horvat, Jean-Pascal Pfister
2024On the Analysis of GAN-based Image-to-Image Translation with Gaussian Noise Injection.
Chaohua Shi, Kexin Huang, Lu Gan, Hongqing Liu, Mingrui Zhu, Nannan Wang, Xinbo Gao
2024On the Effect of Batch Size in Byzantine-Robust Distributed Learning.
Yi-Rui Yang, Chang-Wei Shi, Wu-Jun Li
2024On the Expressivity of Objective-Specification Formalisms in Reinforcement Learning.
Rohan Subramani, Marcus Williams, Max Heitmann, Halfdan Holm, Charlie Griffin, Joar Max Viktor Skalse
2024On the Fairness ROAD: Robust Optimization for Adversarial Debiasing.
Vincent Grari, Thibault Laugel, Tatsunori Hashimoto, Sylvain Lamprier, Marcin Detyniecki
2024On the Foundations of Shortcut Learning.
Katherine L. Hermann, Hossein Mobahi, Thomas Fel, Michael Curtis Mozer
2024On the Generalization and Approximation Capacities of Neural Controlled Differential Equations.
Linus Bleistein, Agathe Guilloux
2024On the Hardness of Constrained Cooperative Multi-Agent Reinforcement Learning.
Ziyi Chen, Yi Zhou, Heng Huang
2024On the Hardness of Online Nonconvex Optimization with Single Oracle Feedback.
Ziwei Guan, Yi Zhou, Yingbin Liang
2024On the Humanity of Conversational AI: Evaluating the Psychological Portrayal of LLMs.
Jen-tse Huang, Wenxuan Wang, Eric John Li, Man Ho Lam, Shujie Ren, Youliang Yuan, Wenxiang Jiao, Zhaopeng Tu, Michael R. Lyu
2024On the Joint Interaction of Models, Data, and Features.
Yiding Jiang, Christina Baek, J. Zico Kolter
2024On the Learnability of Watermarks for Language Models.
Chenchen Gu, Xiang Lisa Li, Percy Liang, Tatsunori Hashimoto
2024On the Limitations of Temperature Scaling for Distributions with Overlaps.
Muthu Chidambaram, Rong Ge
2024On the Markov Property of Neural Algorithmic Reasoning: Analyses and Methods.
Montgomery Bohde, Meng Liu, Alexandra Saxton, Shuiwang Ji
2024On the Over-Memorization During Natural, Robust and Catastrophic Overfitting.
Runqi Lin, Chaojian Yu, Bo Han, Tongliang Liu
2024On the Parameterization of Second-Order Optimization Effective towards the Infinite Width.
Satoki Ishikawa, Ryo Karakida
2024On the Posterior Distribution in Denoising: Application to Uncertainty Quantification.
Hila Manor, Tomer Michaeli
2024On the Power of the Weisfeiler-Leman Test for Graph Motif Parameters.
Matthias Lanzinger, Pablo Barceló
2024On the Provable Advantage of Unsupervised Pretraining.
Jiawei Ge, Shange Tang, Jianqing Fan, Chi Jin
2024On the Reliability of Watermarks for Large Language Models.
John Kirchenbauer, Jonas Geiping, Yuxin Wen, Manli Shu, Khalid Saifullah, Kezhi Kong, Kasun Fernando, Aniruddha Saha, Micah Goldblum, Tom Goldstein
2024On the Role of Discrete Tokenization in Visual Representation Learning.
Tianqi Du, Yifei Wang, Yisen Wang
2024On the Role of General Function Approximation in Offline Reinforcement Learning.
Chenjie Mao, Qiaosheng Zhang, Zhen Wang, Xuelong Li
2024On the Scalability and Memory Efficiency of Semidefinite Programs for Lipschitz Constant Estimation of Neural Networks.
Zi Wang, Bin Hu, Aaron J. Havens, Alexandre Araujo, Yang Zheng, Yudong Chen, Somesh Jha
2024On the Stability of Expressive Positional Encodings for Graphs.
Yinan Huang, William Lu, Joshua Robinson, Yu Yang, Muhan Zhang, Stefanie Jegelka, Pan Li
2024On the Stability of Iterative Retraining of Generative Models on their own Data.
Quentin Bertrand, Avishek Joey Bose, Alexandre Duplessis, Marco Jiralerspong, Gauthier Gidel
2024On the Variance of Neural Network Training with respect to Test Sets and Distributions.
Keller Jordan
2024On the Vulnerability of Adversarially Trained Models Against Two-faced Attacks.
Shengjie Zhou, Lue Tao, Yuzhou Cao, Tao Xiang, Bo An, Lei Feng
2024On the generalization capacity of neural networks during generic multimodal reasoning.
Takuya Ito, Soham Dan, Mattia Rigotti, James R. Kozloski, Murray Campbell
2024On the hardness of learning under symmetries.
Bobak T. Kiani, Thien Le, Hannah Lawrence, Stefanie Jegelka, Melanie Weber
2024On-Policy Distillation of Language Models: Learning from Self-Generated Mistakes.
Rishabh Agarwal, Nino Vieillard, Yongchao Zhou, Piotr Stanczyk, Sabela Ramos Garea, Matthieu Geist, Olivier Bachem
2024One For All: Towards Training One Graph Model For All Classification Tasks.
Hao Liu, Jiarui Feng, Lecheng Kong, Ningyue Liang, Dacheng Tao, Yixin Chen, Muhan Zhang
2024One Forward is Enough for Neural Network Training via Likelihood Ratio Method.
Jinyang Jiang, Zeliang Zhang, Chenliang Xu, Zhaofei Yu, Yijie Peng
2024One Step of Gradient Descent is Provably the Optimal In-Context Learner with One Layer of Linear Self-Attention.
Arvind V. Mahankali, Tatsunori Hashimoto, Tengyu Ma
2024One-hot Generalized Linear Model for Switching Brain State Discovery.
Chengrui Li, Soon Ho Kim, Chris Rodgers, Hannah Choi, Anqi Wu
2024One-shot Active Learning Based on Lewis Weight Sampling for Multiple Deep Models.
Sheng-Jun Huang, Yi Li, Yiming Sun, Ying-Peng Tang
2024One-shot Empirical Privacy Estimation for Federated Learning.
Galen Andrew, Peter Kairouz, Sewoong Oh, Alina Oprea, Hugh Brendan McMahan, Vinith Menon Suriyakumar
2024Online Continual Learning for Interactive Instruction Following Agents.
Byeonghwi Kim, Minhyuk Seo, Jonghyun Choi
2024Online GNN Evaluation Under Test-time Graph Distribution Shifts.
Xin Zheng, Dongjin Song, Qingsong Wen, Bo Du, Shirui Pan
2024Online Information Acquisition: Hiring Multiple Agents.
Federico Cacciamani, Matteo Castiglioni, Nicola Gatti
2024Online Stabilization of Spiking Neural Networks.
Yaoyu Zhu, Jianhao Ding, Tiejun Huang, Xiaodong Xie, Zhaofei Yu
2024Only Pay for What Is Uncertain: Variance-Adaptive Thompson Sampling.
Aadirupa Saha, Branislav Kveton
2024Open the Black Box: Step-based Policy Updates for Temporally-Correlated Episodic Reinforcement Learning.
Ge Li, Hongyi Zhou, Dominik Roth, Serge Thilges, Fabian Otto, Rudolf Lioutikov, Gerhard Neumann
2024Open-ended VQA benchmarking of Vision-Language models by exploiting Classification datasets and their semantic hierarchy.
Simon Ging, María Alejandra Bravo, Thomas Brox
2024OpenChat: Advancing Open-source Language Models with Mixed-Quality Data.
Guan Wang, Sijie Cheng, Xianyuan Zhan, Xiangang Li, Sen Song, Yang Liu
2024OpenNeRF: Open Set 3D Neural Scene Segmentation with Pixel-Wise Features and Rendered Novel Views.
Francis Engelmann, Fabian Manhardt, Michael Niemeyer, Keisuke Tateno, Federico Tombari
2024OpenTab: Advancing Large Language Models as Open-domain Table Reasoners.
Kezhi Kong, Jiani Zhang, Zhengyuan Shen, Balasubramaniam Srinivasan, Chuan Lei, Christos Faloutsos, Huzefa Rangwala, George Karypis
2024OpenWebMath: An Open Dataset of High-Quality Mathematical Web Text.
Keiran Paster, Marco Dos Santos, Zhangir Azerbayev, Jimmy Ba
2024Optimal Sample Complexity for Average Reward Markov Decision Processes.
Shengbo Wang, José H. Blanchet, Peter W. Glynn
2024Optimal Sample Complexity of Contrastive Learning.
Noga Alon, Dmitrii Avdiukhin, Dor Elboim, Orr Fischer, Grigory Yaroslavtsev
2024Optimal Sketching for Residual Error Estimation for Matrix and Vector Norms.
Yi Li, Honghao Lin, David P. Woodruff
2024Optimal criterion for feature learning of two-layer linear neural network in high dimensional interpolation regime.
Keita Suzuki, Taiji Suzuki
2024Optimal robust Memorization with ReLU Neural Networks.
Lijia Yu, Xiao-Shan Gao, Lijun Zhang
2024Optimal transport based adversarial patch to leverage large scale attack transferability.
Pol Labarbarie, Adrien Chan-Hon-Tong, Stéphane Herbin, Milad Leyli-Abadi
2024Optimistic Bayesian Optimization with Unknown Constraints.
Quoc Phong Nguyen, Wan Theng Ruth Chew, Le Song, Bryan Kian Hsiang Low, Patrick Jaillet
2024Oracle Efficient Algorithms for Groupwise Regret.
Krishna Acharya, Eshwar Ram Arunachaleswaran, Sampath Kannan, Aaron Roth, Juba Ziani
2024Orbit-Equivariant Graph Neural Networks.
Matthew Morris, Bernardo Cuenca Grau, Ian Horrocks
2024Order-Preserving GFlowNets.
Yihang Chen, Lukas Mauch
2024Out-Of-Domain Unlabeled Data Improves Generalization.
Seyed Amir Hossein Saberi, Amir Najafi, Alireza Heidari, Mohammad Hosein Movasaghinia, Abolfazl S. Motahari, Babak H. Khalaj
2024Out-of-Distribution Detection by Leveraging Between-Layer Transformation Smoothness.
Fran Jelenic, Josip Jukic, Martin Tutek, Mate Puljiz, Jan Snajder
2024Out-of-Distribution Detection with Negative Prompts.
Jun Nie, Yonggang Zhang, Zhen Fang, Tongliang Liu, Bo Han, Xinmei Tian
2024Out-of-Variable Generalisation for Discriminative Models.
Siyuan Guo, Jonas Bernhard Wildberger, Bernhard Schölkopf
2024Outliers with Opposing Signals Have an Outsized Effect on Neural Network Optimization.
Elan Rosenfeld, Andrej Risteski
2024Overcoming the Pitfalls of Vision-Language Model Finetuning for OOD Generalization.
Yuhang Zang, Hanlin Goh, Joshua M. Susskind, Chen Huang
2024Overthinking the Truth: Understanding how Language Models Process False Demonstrations.
Danny Halawi, Jean-Stanislas Denain, Jacob Steinhardt
2024P2OT: Progressive Partial Optimal Transport for Deep Imbalanced Clustering.
Chuyu Zhang, Hui Ren, Xuming He
2024P2Seg: Pointly-supervised Segmentation via Mutual Distillation.
Zipeng Wang, Xuehui Yu, Xumeng Han, Wenwen Yu, Zhixun Huang, Jianbin Jiao, Zhenjun Han
2024PAC Prediction Sets Under Label Shift.
Wenwen Si, Sangdon Park, Insup Lee, Edgar Dobriban, Osbert Bastani
2024PAC-FNO: Parallel-Structured All-Component Fourier Neural Operators for Recognizing Low-Quality Images.
Jinsung Jeon, Hyundong Jin, Jonghyun Choi, Sanghyun Hong, Dongeun Lee, Kookjin Lee, Noseong Park
2024PAE: Reinforcement Learning from External Knowledge for Efficient Exploration.
Zhe Wu, Haofei Lu, Junliang Xing, You Wu, Renye Yan, Yaozhong Gan, Yuanchun Shi
2024PARL: A Unified Framework for Policy Alignment in Reinforcement Learning from Human Feedback.
Souradip Chakraborty, Amrit Singh Bedi, Alec Koppel, Huazheng Wang, Dinesh Manocha, Mengdi Wang, Furong Huang
2024PB-LLM: Partially Binarized Large Language Models.
Zhihang Yuan, Yuzhang Shang, Zhen Dong
2024PBADet: A One-Stage Anchor-Free Approach for Part-Body Association.
Zhongpai Gao, Huayi Zhou, Abhishek Sharma, Meng Zheng, Benjamin Planche, Terrence Chen, Ziyan Wu
2024PF-LRM: Pose-Free Large Reconstruction Model for Joint Pose and Shape Prediction.
Peng Wang, Hao Tan, Sai Bi, Yinghao Xu, Fujun Luan, Kalyan Sunkavalli, Wenping Wang, Zexiang Xu, Kai Zhang
2024PILOT: An $\mathcal{O}(1/K)$-Convergent Approach for Policy Evaluation with Nonlinear Function Approximation.
Zhuqing Liu, Xin Zhang, Jia Liu, Zhengyuan Zhu, Songtao Lu
2024PINNACLE: PINN Adaptive ColLocation and Experimental points selection.
Gregory Kang Ruey Lau, Apivich Hemachandra, See-Kiong Ng, Bryan Kian Hsiang Low
2024PINNsFormer: A Transformer-Based Framework For Physics-Informed Neural Networks.
Leo Zhiyuan Zhao, Xueying Ding, B. Aditya Prakash
2024PRES: Toward Scalable Memory-Based Dynamic Graph Neural Networks.
Junwei Su, Difan Zou, Chuan Wu
2024PRIME: Prioritizing Interpretability in Failure Mode Extraction.
Keivan Rezaei, Mehrdad Saberi, Mazda Moayeri, Soheil Feizi
2024PROGRAM: PROtotype GRAph Model based Pseudo-Label Learning for Test-Time Adaptation.
Haopeng Sun, Lumin Xu, Sheng Jin, Ping Luo, Chen Qian, Wentao Liu
2024PTaRL: Prototype-based Tabular Representation Learning via Space Calibration.
Hangting Ye, Wei Fan, Xiaozhuang Song, Shun Zheng, He Zhao, Dandan Guo, Yi Chang
2024PandaLM: An Automatic Evaluation Benchmark for LLM Instruction Tuning Optimization.
Yidong Wang, Zhuohao Yu, Wenjin Yao, Zhengran Zeng, Linyi Yang, Cunxiang Wang, Hao Chen, Chaoya Jiang, Rui Xie, Jindong Wang, Xing Xie, Wei Ye, Shikun Zhang, Yue Zhang
2024PanoDiffusion: 360-degree Panorama Outpainting via Diffusion.
Tianhao Wu, Chuanxia Zheng, Tat-Jen Cham
2024Parallelizing non-linear sequential models over the sequence length.
Yi Heng Lim, Qi Zhu, Joshua Selfridge, Muhammad Firmansyah Kasim
2024Parameter-Efficient Multi-Task Model Fusion with Partial Linearization.
Anke Tang, Li Shen, Yong Luo, Yibing Zhan, Han Hu, Bo Du, Yixin Chen, Dacheng Tao
2024Parameter-Efficient Orthogonal Finetuning via Butterfly Factorization.
Weiyang Liu, Zeju Qiu, Yao Feng, Yuliang Xiu, Yuxuan Xue, Longhui Yu, Haiwen Feng, Zhen Liu, Juyeon Heo, Songyou Peng, Yandong Wen, Michael J. Black, Adrian Weller, Bernhard Schölkopf
2024Parametric Augmentation for Time Series Contrastive Learning.
Xu Zheng, Tianchun Wang, Wei Cheng, Aitian Ma, Haifeng Chen, Mo Sha, Dongsheng Luo
2024Pareto Deep Long-Tailed Recognition: A Conflict-Averse Solution.
Zhipeng Zhou, Liu Liu, Peilin Zhao, Wei Gong
2024Parsing neural dynamics with infinite recurrent switching linear dynamical systems.
Victor Geadah, International Brain Laboratory, Jonathan W. Pillow
2024Particle Guidance: non-I.I.D. Diverse Sampling with Diffusion Models.
Gabriele Corso, Yilun Xu, Valentin De Bortoli, Regina Barzilay, Tommi S. Jaakkola
2024Partitioning Message Passing for Graph Fraud Detection.
Wei Zhuo, Zemin Liu, Bryan Hooi, Bingsheng He, Guang Tan, Rizal Fathony, Jia Chen
2024Patched Denoising Diffusion Models For High-Resolution Image Synthesis.
Zheng Ding, Mengqi Zhang, Jiajun Wu, Zhuowen Tu
2024Path Choice Matters for Clear Attributions in Path Methods.
Borui Zhang, Wenzhao Zheng, Jie Zhou, Jiwen Lu
2024Pathformer: Multi-scale Transformers with Adaptive Pathways for Time Series Forecasting.
Peng Chen, Yingying Zhang, Yunyao Cheng, Yang Shu, Yihang Wang, Qingsong Wen, Bin Yang, Chenjuan Guo
2024PeFLL: Personalized Federated Learning by Learning to Learn.
Jonathan Scott, Hossein Zakerinia, Christoph H. Lampert
2024Peering Through Preferences: Unraveling Feedback Acquisition for Aligning Large Language Models.
Hritik Bansal, John Dang, Aditya Grover
2024PerceptionCLIP: Visual Classification by Inferring and Conditioning on Contexts.
Bang An, Sicheng Zhu, Michael-Andrei Panaitescu-Liess, Chaithanya Kumar Mummadi, Furong Huang
2024Perceptual Group Tokenizer: Building Perception with Iterative Grouping.
Zhiwei Deng, Ting Chen, Yang Li
2024Perceptual Scales Predicted by Fisher Information Metrics.
Jonathan Vacher, Pascal Mamassian
2024Performance Gaps in Multi-view Clustering under the Nested Matrix-Tensor Model.
Hugo Lebeau, Mohamed El Amine Seddik, José Henrique de Morais Goulart
2024Periodicity Decoupling Framework for Long-term Series Forecasting.
Tao Dai, Beiliang Wu, Peiyuan Liu, Naiqi Li, Jigang Bao, Yong Jiang, Shu-Tao Xia
2024Personalize Segment Anything Model with One Shot.
Renrui Zhang, Zhengkai Jiang, Ziyu Guo, Shilin Yan, Junting Pan, Hao Dong, Yu Qiao, Peng Gao, Hongsheng Li
2024Pessimistic Nonlinear Least-Squares Value Iteration for Offline Reinforcement Learning.
Qiwei Di, Heyang Zhao, Jiafan He, Quanquan Gu
2024Phenomenal Yet Puzzling: Testing Inductive Reasoning Capabilities of Language Models with Hypothesis Refinement.
Linlu Qiu, Liwei Jiang, Ximing Lu, Melanie Sclar, Valentina Pyatkin, Chandra Bhagavatula, Bailin Wang, Yoon Kim, Yejin Choi, Nouha Dziri, Xiang Ren
2024PhyloGFN: Phylogenetic inference with generative flow networks.
Ming-Yang Zhou, Zichao Yan, Elliot Layne, Nikolay Malkin, Dinghuai Zhang, Moksh Jain, Mathieu Blanchette, Yoshua Bengio
2024Physics-Regulated Deep Reinforcement Learning: Invariant Embeddings.
Hongpeng Cao, Yanbing Mao, Lui Sha, Marco Caccamo
2024Piecewise Linear Parametrization of Policies: Towards Interpretable Deep Reinforcement Learning.
Maxime Wabartha, Joelle Pineau
2024PixArt-α: Fast Training of Diffusion Transformer for Photorealistic Text-to-Image Synthesis.
Junsong Chen, Jincheng Yu, Chongjian Ge, Lewei Yao, Enze Xie, Zhongdao Wang, James T. Kwok, Ping Luo, Huchuan Lu, Zhenguo Li
2024PlaSma: Procedural Knowledge Models for Language-based Planning and Re-Planning.
Faeze Brahman, Chandra Bhagavatula, Valentina Pyatkin, Jena D. Hwang, Xiang Lorraine Li, Hirona Jacqueline Arai, Soumya Sanyal, Keisuke Sakaguchi, Xiang Ren, Yejin Choi
2024Plan-Seq-Learn: Language Model Guided RL for Solving Long Horizon Robotics Tasks.
Murtaza Dalal, Tarun Chiruvolu, Devendra Singh Chaplot, Ruslan Salakhutdinov
2024Plug-and-Play Policy Planner for Large Language Model Powered Dialogue Agents.
Yang Deng, Wenxuan Zhang, Wai Lam, See-Kiong Ng, Tat-Seng Chua
2024Plug-and-Play Posterior Sampling under Mismatched Measurement and Prior Models.
Marien Renaud, Jiaming Liu, Valentin De Bortoli, Andrés Almansa, Ulugbek Kamilov
2024Plug-and-Play: An Efficient Post-training Pruning Method for Large Language Models.
Yingtao Zhang, Haoli Bai, Haokun Lin, Jialin Zhao, Lu Hou, Carlo Vittorio Cannistraci
2024Plugin estimators for selective classification with out-of-distribution detection.
Harikrishna Narasimhan, Aditya Krishna Menon, Wittawat Jitkrittum, Sanjiv Kumar
2024PnP Inversion: Boosting Diffusion-based Editing with 3 Lines of Code.
Xuan Ju, Ailing Zeng, Yuxuan Bian, Shaoteng Liu, Qiang Xu
2024PoSE: Efficient Context Window Extension of LLMs via Positional Skip-wise Training.
Dawei Zhu, Nan Yang, Liang Wang, Yifan Song, Wenhao Wu, Furu Wei, Sujian Li
2024Point2SSM: Learning Morphological Variations of Anatomies from Point Clouds.
Jadie Adams, Shireen Y. Elhabian
2024Poisoned Forgery Face: Towards Backdoor Attacks on Face Forgery Detection.
Jiawei Liang, Siyuan Liang, Aishan Liu, Xiaojun Jia, Junhao Kuang, Xiaochun Cao
2024Policy Rehearsing: Training Generalizable Policies for Reinforcement Learning.
Chengxing Jia, Chenxiao Gao, Hao Yin, Fuxiang Zhang, Xiong-Hui Chen, Tian Xu, Lei Yuan, Zongzhang Zhang, Zhi-Hua Zhou, Yang Yu
2024Poly-View Contrastive Learning.
Amitis Shidani, R. Devon Hjelm, Jason Ramapuram, Russell Webb, Eeshan Gunesh Dhekane, Dan Busbridge
2024PolyGCL: GRAPH CONTRASTIVE LEARNING via Learnable Spectral Polynomial Filters.
Jingyu Chen, Runlin Lei, Zhewei Wei
2024PolyVoice: Language Models for Speech to Speech Translation.
Qianqian Dong, Zhiying Huang, Qi Tian, Chen Xu, Tom Ko, Yunlong Zhao, Siyuan Feng, Tang Li, Kexin Wang, Xuxin Cheng, Fengpeng Yue, Ye Bai, Xi Chen, Lu Lu, Zejun Ma, Yuping Wang, Mingxuan Wang, Yuxuan Wang
2024Polynomial Width is Sufficient for Set Representation with High-dimensional Features.
Peihao Wang, Shenghao Yang, Shu Li, Zhangyang Wang, Pan Li
2024Polynormer: Polynomial-Expressive Graph Transformer in Linear Time.
Chenhui Deng, Zichao Yue, Zhiru Zhang
2024Pooling Image Datasets with Multiple Covariate Shift and Imbalance.
Sotirios Panagiotis Chytas, Vishnu Suresh Lokhande, Vikas Singh
2024Porf: Pose residual field for accurate Neural surface Reconstruction.
Jia-Wang Bian, Wenjing Bian, Victor Adrian Prisacariu, Philip Torr
2024Pose Modulated Avatars from Video.
Chunjin Song, Bastian Wandt, Helge Rhodin
2024Post-hoc bias scoring is optimal for fair classification.
Wenlong Chen, Yegor Klochkov, Yang Liu
2024Posterior Sampling Based on Gradient Flows of the MMD with Negative Distance Kernel.
Paul Hagemann, Johannes Hertrich, Fabian Altekrüger, Robert Beinert, Jannis Chemseddine, Gabriele Steidl
2024Pre-Training Goal-based Models for Sample-Efficient Reinforcement Learning.
Haoqi Yuan, Zhancun Mu, Feiyang Xie, Zongqing Lu
2024Pre-Training and Fine-Tuning Generative Flow Networks.
Ling Pan, Moksh Jain, Kanika Madan, Yoshua Bengio
2024Pre-training LiDAR-based 3D Object Detectors through Colorization.
Tai-Yu Pan, Chenyang Ma, Tianle Chen, Cheng Perng Phoo, Katie Z. Luo, Yurong You, Mark Campbell, Kilian Q. Weinberger, Bharath Hariharan, Wei-Lun Chao
2024Pre-training Sequence, Structure, and Surface Features for Comprehensive Protein Representation Learning.
Youhan Lee, Hasun Yu, Jaemyung Lee, Jaehoon Kim
2024Pre-training with Random Orthogonal Projection Image Modeling.
Maryam Haghighat, Peyman Moghadam, Shaheer Mohamed, Piotr Koniusz
2024Pre-training with Synthetic Data Helps Offline Reinforcement Learning.
Zecheng Wang, Che Wang, Zixuan Dong, Keith W. Ross
2024Predicting Emergent Abilities with Infinite Resolution Evaluation.
Shengding Hu, Xin Liu, Xu Han, Xinrong Zhang, Chaoqun He, Weilin Zhao, Yankai Lin, Ning Ding, Zebin Ou, Guoyang Zeng, Zhiyuan Liu, Maosong Sun
2024Prediction Error-based Classification for Class-Incremental Learning.
Michal Zajac, Tinne Tuytelaars, Gido M. van de Ven
2024Prediction without Preclusion: Recourse Verification with Reachable Sets.
Avni Kothari, Bogdan Kulynych, Tsui-Wei Weng, Berk Ustun
2024Predictive auxiliary objectives in deep RL mimic learning in the brain.
Ching Fang, Kim Stachenfeld
2024Predictive, scalable and interpretable knowledge tracing on structured domains.
Hanqi Zhou, Robert Bamler, Charley M. Wu, Álvaro Tejero-Cantero
2024Principled Architecture-aware Scaling of Hyperparameters.
Wuyang Chen, Junru Wu, Zhangyang Wang, Boris Hanin
2024Principled Federated Domain Adaptation: Gradient Projection and Auto-Weighting.
Enyi Jiang, Yibo Jacky Zhang, Sanmi Koyejo
2024Prioritized Soft Q-Decomposition for Lexicographic Reinforcement Learning.
Finn Rietz, Erik Schaffernicht, Stefan Heinrich, Johannes A. Stork
2024Privacy Amplification for Matrix Mechanisms.
Christopher A. Choquette-Choo, Arun Ganesh, Thomas Steinke, Abhradeep Guha Thakurta
2024Privacy-Preserving In-Context Learning for Large Language Models.
Tong Wu, Ashwinee Panda, Jiachen T. Wang, Prateek Mittal
2024Privacy-Preserving In-Context Learning with Differentially Private Few-Shot Generation.
Xinyu Tang, Richard Shin, Huseyin A. Inan, Andre Manoel, Fatemehsadat Mireshghallah, Zinan Lin, Sivakanth Gopi, Janardhan Kulkarni, Robert Sim
2024Private Zeroth-Order Nonsmooth Nonconvex Optimization.
Qinzi Zhang, Hoang Tran, Ashok Cutkosky
2024Privately Aligning Language Models with Reinforcement Learning.
Fan Wu, Huseyin A. Inan, Arturs Backurs, Varun Chandrasekaran, Janardhan Kulkarni, Robert Sim
2024Privileged Sensing Scaffolds Reinforcement Learning.
Edward S. Hu, James Springer, Oleh Rybkin, Dinesh Jayaraman
2024Probabilistic Adaptation of Black-Box Text-to-Video Models.
Sherry Yang, Yilun Du, Bo Dai, Dale Schuurmans, Joshua B. Tenenbaum, Pieter Abbeel
2024Probabilistic Self-supervised Representation Learning via Scoring Rules Minimization.
Amirhossein Vahidi, Simon Schoßer, Lisa Wimmer, Yawei Li, Bernd Bischl, Eyke Hüllermeier, Mina Rezaei
2024Probabilistically Rewired Message-Passing Neural Networks.
Chendi Qian, Andrei Manolache, Kareem Ahmed, Zhe Zeng, Guy Van den Broeck, Mathias Niepert, Christopher Morris
2024Procedural Fairness Through Decoupling Objectionable Data Generating Components.
Zeyu Tang, Jialu Wang, Yang Liu, Peter Spirtes, Kun Zhang
2024Progressive Fourier Neural Representation for Sequential Video Compilation.
Haeyong Kang, Jaehong Yoon, Dahyun Kim, Sung Ju Hwang, Chang D. Yoo
2024Progressive3D: Progressively Local Editing for Text-to-3D Content Creation with Complex Semantic Prompts.
Xinhua Cheng, Tianyu Yang, Jianan Wang, Yu Li, Lei Zhang, Jian Zhang, Li Yuan
2024Project and Probe: Sample-Efficient Adaptation by Interpolating Orthogonal Features.
Annie S. Chen, Yoonho Lee, Amrith Setlur, Sergey Levine, Chelsea Finn
2024Prometheus: Inducing Fine-Grained Evaluation Capability in Language Models.
Seungone Kim, Jamin Shin, Yejin Choi, Joel Jang, Shayne Longpre, Hwaran Lee, Sangdoo Yun, Seongjin Shin, Sungdong Kim, James Thorne, Minjoon Seo
2024Prompt Gradient Projection for Continual Learning.
Jingyang Qiao, Zhizhong Zhang, Xin Tan, Chengwei Chen, Yanyun Qu, Yong Peng, Yuan Xie
2024Prompt Learning with Quaternion Networks.
Boya Shi, Zhengqin Xu, Shuai Jia, Chao Ma
2024Prompt Risk Control: A Rigorous Framework for Responsible Deployment of Large Language Models.
Thomas P. Zollo, Todd Morrill, Zhun Deng, Jake Snell, Toniann Pitassi, Richard S. Zemel
2024PromptAgent: Strategic Planning with Language Models Enables Expert-level Prompt Optimization.
Xinyuan Wang, Chenxi Li, Zhen Wang, Fan Bai, Haotian Luo, Jiayou Zhang, Nebojsa Jojic, Eric P. Xing, Zhiting Hu
2024PromptTTS 2: Describing and Generating Voices with Text Prompt.
Yichong Leng, Zhifang Guo, Kai Shen, Zeqian Ju, Xu Tan, Eric Liu, Yufei Liu, Dongchao Yang, Leying Zhang, Kaitao Song, Lei He, Xiangyang Li, Sheng Zhao, Tao Qin, Jiang Bian
2024Proper Laplacian Representation Learning.
Diego Gomez, Michael Bowling, Marlos C. Machado
2024Protein Discovery with Discrete Walk-Jump Sampling.
Nathan C. Frey, Daniel Berenberg, Karina Zadorozhny, Joseph Kleinhenz, Julien Lafrance-Vanasse, Isidro Hötzel, Yan Wu, Stephen Ra, Richard Bonneau, Kyunghyun Cho, Andreas Loukas, Vladimir Gligorijevic, Saeed Saremi
2024Protein Multimer Structure Prediction via Prompt Learning.
Ziqi Gao, Xiangguo Sun, Zijing Liu, Yu Li, Hong Cheng, Jia Li
2024Protein-Ligand Interaction Prior for Binding-aware 3D Molecule Diffusion Models.
Zhilin Huang, Ling Yang, Xiangxin Zhou, Zhilong Zhang, Wentao Zhang, Xiawu Zheng, Jie Chen, Yu Wang, Bin Cui, Wenming Yang
2024Protein-ligand binding representation learning from fine-grained interactions.
Shikun Feng, Minghao Li, Yinjun Jia, Wei-Ying Ma, Yanyan Lan
2024Prototypical Information Bottlenecking and Disentangling for Multimodal Cancer Survival Prediction.
Yilan Zhang, Yingxue Xu, Jianqi Chen, Fengying Xie, Hao Chen
2024Provable Benefits of Multi-task RL under Non-Markovian Decision Making Processes.
Ruiquan Huang, Yuan Cheng, Jing Yang, Vincent Tan, Yingbin Liang
2024Provable Compositional Generalization for Object-Centric Learning.
Thaddäus Wiedemer, Jack Brady, Alexander Panfilov, Attila Juhos, Matthias Bethge, Wieland Brendel
2024Provable Memory Efficient Self-Play Algorithm for Model-free Reinforcement Learning.
Na Li, Yuchen Jiao, Hangguan Shan, Shefeng Yan
2024Provable Offline Preference-Based Reinforcement Learning.
Wenhao Zhan, Masatoshi Uehara, Nathan Kallus, Jason D. Lee, Wen Sun
2024Provable Reward-Agnostic Preference-Based Reinforcement Learning.
Wenhao Zhan, Masatoshi Uehara, Wen Sun, Jason D. Lee
2024Provable Robust Watermarking for AI-Generated Text.
Xuandong Zhao, Prabhanjan Vijendra Ananth, Lei Li, Yu-Xiang Wang
2024Provable and Practical: Efficient Exploration in Reinforcement Learning via Langevin Monte Carlo.
Haque Ishfaq, Qingfeng Lan, Pan Xu, A. Rupam Mahmood, Doina Precup, Anima Anandkumar, Kamyar Azizzadenesheli
2024Provably Efficient CVaR RL in Low-rank MDPs.
Yulai Zhao, Wenhao Zhan, Xiaoyan Hu, Ho-fung Leung, Farzan Farnia, Wen Sun, Jason D. Lee
2024Provably Efficient Iterated CVaR Reinforcement Learning with Function Approximation and Human Feedback.
Yu Chen, Yihan Du, Pihe Hu, Siwei Wang, Desheng Wu, Longbo Huang
2024Provably Efficient UCB-type Algorithms For Learning Predictive State Representations.
Ruiquan Huang, Yingbin Liang, Jing Yang
2024Provably Robust Conformal Prediction with Improved Efficiency.
Ge Yan, Yaniv Romano, Tsui-Wei Weng
2024Proving Test Set Contamination in Black-Box Language Models.
Yonatan Oren, Nicole Meister, Niladri S. Chatterji, Faisal Ladhak, Tatsunori Hashimoto
2024Proximal Policy Gradient Arborescence for Quality Diversity Reinforcement Learning.
Sumeet Batra, Bryon Tjanaka, Matthew Christopher Fontaine, Aleksei Petrenko, Stefanos Nikolaidis, Gaurav S. Sukhatme
2024Pseudo-Generalized Dynamic View Synthesis from a Video.
Xiaoming Zhao, Alex Colburn, Fangchang Ma, Miguel Ángel Bautista, Joshua M. Susskind, Alexander G. Schwing
2024PubDef: Defending Against Transfer Attacks From Public Models.
Chawin Sitawarin, Jaewon Chang, David Huang, Wesson Altoyan, David A. Wagner
2024Pushing Boundaries: Mixup's Influence on Neural Collapse.
Quinn LeBlanc Fisher, Haoming Meng, Vardan Papyan
2024Pushing Mixture of Experts to the Limit: Extremely Parameter Efficient MoE for Instruction Tuning.
Ted Zadouri, Ahmet Üstün, Arash Ahmadian, Beyza Ermis, Acyr Locatelli, Sara Hooker
2024Q-Bench: A Benchmark for General-Purpose Foundation Models on Low-level Vision.
Haoning Wu, Zicheng Zhang, Erli Zhang, Chaofeng Chen, Liang Liao, Annan Wang, Chunyi Li, Wenxiu Sun, Qiong Yan, Guangtao Zhai, Weisi Lin
2024QA-LoRA: Quantization-Aware Low-Rank Adaptation of Large Language Models.
Yuhui Xu, Lingxi Xie, Xiaotao Gu, Xin Chen, Heng Chang, Hengheng Zhang, Zhengsu Chen, Xiaopeng Zhang, Qi Tian
2024QLLM: Accurate and Efficient Low-Bitwidth Quantization for Large Language Models.
Jing Liu, Ruihao Gong, Xiuying Wei, Zhiwei Dong, Jianfei Cai, Bohan Zhuang
2024Quadratic models for understanding catapult dynamics of neural networks.
Libin Zhu, Chaoyue Liu, Adityanarayanan Radhakrishnan, Mikhail Belkin
2024Quality-Diversity through AI Feedback.
Herbie Bradley, Andrew Dai, Hannah Benita Teufel, Jenny Zhang, Koen Oostermeijer, Marco Bellagente, Jeff Clune, Kenneth O. Stanley, Grégory Schott, Joel Lehman
2024Quantifying Language Models' Sensitivity to Spurious Features in Prompt Design or: How I learned to start worrying about prompt formatting.
Melanie Sclar, Yejin Choi, Yulia Tsvetkov, Alane Suhr
2024Quantifying and Enhancing Multi-modal Robustness with Modality Preference.
Zequn Yang, Yake Wei, Ce Liang, Di Hu
2024Quantifying the Plausibility of Context Reliance in Neural Machine Translation.
Gabriele Sarti, Grzegorz Chrupala, Malvina Nissim, Arianna Bisazza
2024Quantifying the Sensitivity of Inverse Reinforcement Learning to Misspecification.
Joar Max Viktor Skalse, Alessandro Abate
2024Quasi-Monte Carlo for 3D Sliced Wasserstein.
Khai Nguyen, Nicola Bariletto, Nhat Ho
2024Query-Dependent Prompt Evaluation and Optimization with Offline Inverse RL.
Hao Sun, Alihan Hüyük, Mihaela van der Schaar
2024Query-Policy Misalignment in Preference-Based Reinforcement Learning.
Xiao Hu, Jianxiong Li, Xianyuan Zhan, Qing-Shan Jia, Ya-Qin Zhang
2024Querying Easily Flip-flopped Samples for Deep Active Learning.
Seong Jin Cho, Gwangsu Kim, Junghyun Lee, Jinwoo Shin, Chang D. Yoo
2024Quick-Tune: Quickly Learning Which Pretrained Model to Finetune and How.
Sebastian Pineda-Arango, Fabio Ferreira, Arlind Kadra, Frank Hutter, Josif Grabocka
2024R&B: Region and Boundary Aware Zero-shot Grounded Text-to-image Generation.
Jiayu Xiao, Henglei Lv, Liang Li, Shuhui Wang, Qingming Huang
2024R-EDL: Relaxing Nonessential Settings of Evidential Deep Learning.
Mengyuan Chen, Junyu Gao, Changsheng Xu
2024R-MAE: Regions Meet Masked Autoencoders.
Duy-Kien Nguyen, Yanghao Li, Vaibhav Aggarwal, Martin R. Oswald, Alexander Kirillov, Cees G. M. Snoek, Xinlei Chen
2024RA-DIT: Retrieval-Augmented Dual Instruction Tuning.
Xi Victoria Lin, Xilun Chen, Mingda Chen, Weijia Shi, Maria Lomeli, Richard James, Pedro Rodriguez, Jacob Kahn, Gergely Szilvasy, Mike Lewis, Luke Zettlemoyer, Wen-tau Yih
2024RAIN: Your Language Models Can Align Themselves without Finetuning.
Yuhui Li, Fangyun Wei, Jinjing Zhao, Chao Zhang, Hongyang Zhang
2024RAPPER: Reinforced Rationale-Prompted Paradigm for Natural Language Explanation in Visual Question Answering.
Kai-Po Chang, Chi-Pin Huang, Wei-Yuan Cheng, Fu-En Yang, Chien-Yi Wang, Yung-Hsuan Lai, Yu-Chiang Frank Wang
2024RAPTOR: Recursive Abstractive Processing for Tree-Organized Retrieval.
Parth Sarthi, Salman Abdullah, Aditi Tuli, Shubh Khanna, Anna Goldie, Christopher D. Manning
2024RDesign: Hierarchical Data-efficient Representation Learning for Tertiary Structure-based RNA Design.
Cheng Tan, Yijie Zhang, Zhangyang Gao, Bozhen Hu, Siyuan Li, Zicheng Liu, Stan Z. Li
2024REBAR: Retrieval-Based Reconstruction for Time-series Contrastive Learning.
Maxwell A. Xu, Alexander Moreno, Hui Wei, Benjamin M. Marlin, James Matthew Rehg
2024RECOMBINER: Robust and Enhanced Compression with Bayesian Implicit Neural Representations.
Jiajun He, Gergely Flamich, Zongyu Guo, José Miguel Hernández-Lobato
2024RECOMP: Improving Retrieval-Augmented LMs with Context Compression and Selective Augmentation.
Fangyuan Xu, Weijia Shi, Eunsol Choi
2024REFACTOR: Learning to Extract Theorems from Proofs.
Jin Peng Zhou, Yuhuai Wu, Qiyang Li, Roger Baker Grosse
2024RETSim: Resilient and Efficient Text Similarity.
Marina Zhang, Owen S. Vallis, Aysegul Bumin, Tanay Vakharia, Elie Bursztein
2024REValueD: Regularised Ensemble Value-Decomposition for Factorisable Markov Decision Processes.
David Ireland, Giovanni Montana
2024RLCD: Reinforcement Learning from Contrastive Distillation for LM Alignment.
Kevin Yang, Dan Klein, Asli Celikyilmaz, Nanyun Peng, Yuandong Tian
2024RLIF: Interactive Imitation Learning as Reinforcement Learning.
Jianlan Luo, Perry Dong, Yuexiang Zhai, Yi Ma, Sergey Levine
2024RT-Trajectory: Robotic Task Generalization via Hindsight Trajectory Sketches.
Jiayuan Gu, Sean Kirmani, Paul Wohlhart, Yao Lu, Montserrat Gonzalez Arenas, Kanishka Rao, Wenhao Yu, Chuyuan Fu, Keerthana Gopalakrishnan, Zhuo Xu, Priya Sundaresan, Peng Xu, Hao Su, Karol Hausman, Chelsea Finn, Quan Vuong, Ted Xiao
2024RTFS-Net: Recurrent Time-Frequency Modelling for Efficient Audio-Visual Speech Separation.
Samuel Pegg, Kai Li, Xiaolin Hu
2024Raidar: geneRative AI Detection viA Rewriting.
Chengzhi Mao, Carl Vondrick, Hao Wang, Junfeng Yang
2024Random Sparse Lifts: Construction, Analysis and Convergence of finite sparse networks.
David A. R. Robin, Kevin Scaman, Marc Lelarge
2024Rayleigh Quotient Graph Neural Networks for Graph-level Anomaly Detection.
Xiangyu Dong, Xingyi Zhang, Sibo Wang
2024ReFusion: Improving Natural Language Understanding with Computation-Efficient Retrieval Representation Fusion.
Shangyu Wu, Ying Xiong, Yufei Cui, Xue Liu, Buzhou Tang, Tei-Wei Kuo, Chun Jason Xue
2024ReLU Strikes Back: Exploiting Activation Sparsity in Large Language Models.
Iman Mirzadeh, Keivan Alizadeh-Vahid, Sachin Mehta, Carlo C. del Mundo, Oncel Tuzel, Golnoosh Samei, Mohammad Rastegari, Mehrdad Farajtabar
2024ReLoRA: High-Rank Training Through Low-Rank Updates.
Vladislav Lialin, Sherin Muckatira, Namrata Shivagunde, Anna Rumshisky
2024ReMasker: Imputing Tabular Data with Masked Autoencoding.
Tianyu Du, Luca Melis, Ting Wang
2024ReSimAD: Zero-Shot 3D Domain Transfer for Autonomous Driving with Source Reconstruction and Target Simulation.
Bo Zhang, Xinyu Cai, Jiakang Yuan, Donglin Yang, Jianfei Guo, Xiangchao Yan, Renqiu Xia, Botian Shi, Min Dou, Tao Chen, Si Liu, Junchi Yan, Yu Qiao
2024ReTaSA: A Nonparametric Functional Estimation Approach for Addressing Continuous Target Shift.
Hwanwoo Kim, Xin Zhang, Jiwei Zhao, Qinglong Tian
2024Real-Fake: Effective Training Data Synthesis Through Distribution Matching.
Jianhao Yuan, Jie Zhang, Shuyang Sun, Philip Torr, Bo Zhao
2024Real-time Photorealistic Dynamic Scene Representation and Rendering with 4D Gaussian Splatting.
Zeyu Yang, Hongye Yang, Zijie Pan, Li Zhang
2024Real3D-Portrait: One-shot Realistic 3D Talking Portrait Synthesis.
Zhenhui Ye, Tianyun Zhong, Yi Ren, Jiaqi Yang, Weichuang Li, Jiawei Huang, Ziyue Jiang, Jinzheng He, Rongjie Huang, Jinglin Liu, Chen Zhang, Xiang Yin, Zejun Ma, Zhou Zhao
2024Realistic Evaluation of Semi-supervised Learning Algorithms in Open Environments.
Lin-Han Jia, Lan-Zhe Guo, Zhi Zhou, Yufeng Li
2024Reasoning on Graphs: Faithful and Interpretable Large Language Model Reasoning.
Linhao Luo, Yuan-Fang Li, Gholamreza Haffari, Shirui Pan
2024Reasoning with Latent Diffusion in Offline Reinforcement Learning.
Siddarth Venkatraman, Shivesh Khaitan, Ravi Tej Akella, John M. Dolan, Jeff Schneider, Glen Berseth
2024Reclaiming the Source of Programmatic Policies: Programmatic versus Latent Spaces.
Tales Henrique Carvalho, Kenneth Tjhia, Levi Lelis
2024Reconciling Spatial and Temporal Abstractions for Goal Representation.
Mehdi Zadem, Sergio Mover, Sao Mai Nguyen
2024Recursive Generalization Transformer for Image Super-Resolution.
Zheng Chen, Yulun Zhang, Jinjin Gu, Linghe Kong, Xiaokang Yang
2024Reinforcement Symbolic Regression Machine.
Yilong Xu, Yang Liu, Hao Sun
2024Relaxing the Additivity Constraints in Decentralized No-Regret High-Dimensional Bayesian Optimization.
Anthony Bardou, Patrick Thiran, Thomas Begin
2024Relay Diffusion: Unifying diffusion process across resolutions for image synthesis.
Jiayan Teng, Wendi Zheng, Ming Ding, Wenyi Hong, Jianqiao Wangni, Zhuoyi Yang, Jie Tang
2024Remote Sensing Vision-Language Foundation Models without Annotations via Ground Remote Alignment.
Utkarsh Mall, Cheng Perng Phoo, Meilin Kelsey Liu, Carl Vondrick, Bharath Hariharan, Kavita Bala
2024Removing Biases from Molecular Representations via Information Maximization.
Chenyu Wang, Sharut Gupta, Caroline Uhler, Tommi S. Jaakkola
2024Repeated Random Sampling for Minimizing the Time-to-Accuracy of Learning.
Patrik Okanovic, Roger Waleffe, Vasilis Mageirakos, Konstantinos E. Nikolakakis, Amin Karbasi, Dionysios S. Kalogerias, Nezihe Merve Gürel, Theodoros Rekatsinas
2024Repelling Random Walks.
Isaac Reid, Eli Berger, Krzysztof Marcin Choromanski, Adrian Weller
2024Rephrase, Augment, Reason: Visual Grounding of Questions for Vision-Language Models.
Archiki Prasad, Elias Stengel-Eskin, Mohit Bansal
2024Replay across Experiments: A Natural Extension of Off-Policy RL.
Dhruva Tirumala, Thomas Lampe, José Enrique Chen, Tuomas Haarnoja, Sandy H. Huang, Guy Lever, Ben Moran, Tim Hertweck, Leonard Hasenclever, Martin A. Riedmiller, Nicolas Heess, Markus Wulfmeier
2024RepoBench: Benchmarking Repository-Level Code Auto-Completion Systems.
Tianyang Liu, Canwen Xu, Julian J. McAuley
2024Representation Deficiency in Masked Language Modeling.
Yu Meng, Jitin Krishnan, Sinong Wang, Qifan Wang, Yuning Mao, Han Fang, Marjan Ghazvininejad, Jiawei Han, Luke Zettlemoyer
2024ResFields: Residual Neural Fields for Spatiotemporal Signals.
Marko Mihajlovic, Sergey Prokudin, Marc Pollefeys, Siyu Tang
2024Respect the model: Fine-grained and Robust Explanation with Sharing Ratio Decomposition.
Sangyu Han, Yearim Kim, Nojun Kwak
2024Rethinking Adversarial Policies: A Generalized Attack Formulation and Provable Defense in RL.
Xiangyu Liu, Souradip Chakraborty, Yanchao Sun, Furong Huang
2024Rethinking Backdoor Attacks on Dataset Distillation: A Kernel Method Perspective.
Ming-Yu Chung, Sheng-Yen Chou, Chia-Mu Yu, Pin-Yu Chen, Sy-Yen Kuo, Tsung-Yi Ho
2024Rethinking Branching on Exact Combinatorial Optimization Solver: The First Deep Symbolic Discovery Framework.
Yufei Kuang, Jie Wang, Haoyang Liu, Fangzhou Zhu, Xijun Li, Jia Zeng, Jianye Hao, Bin Li, Feng Wu
2024Rethinking CNN's Generalization to Backdoor Attack from Frequency Domain.
Quanrui Rao, Lin Wang, Wuying Liu
2024Rethinking Channel Dependence for Multivariate Time Series Forecasting: Learning from Leading Indicators.
Lifan Zhao, Yanyan Shen
2024Rethinking Channel Dimensions to Isolate Outliers for Low-bit Weight Quantization of Large Language Models.
Jung Hwan Heo, Jeonghoon Kim, Beomseok Kwon, Byeongwook Kim, Se Jung Kwon, Dongsoo Lee
2024Rethinking Complex Queries on Knowledge Graphs with Neural Link Predictors.
Hang Yin, Zihao Wang, Yangqiu Song
2024Rethinking Information-theoretic Generalization: Loss Entropy Induced PAC Bounds.
Yuxin Dong, Tieliang Gong, Hong Chen, Shujian Yu, Chen Li
2024Rethinking Label Poisoning for GNNs: Pitfalls and Attacks.
Vijay Lingam, Mohammad Sadegh Akhondzadeh, Aleksandar Bojchevski
2024Rethinking Model Ensemble in Transfer-based Adversarial Attacks.
Huanran Chen, Yichi Zhang, Yinpeng Dong, Xiao Yang, Hang Su, Jun Zhu
2024Rethinking and Extending the Probabilistic Inference Capacity of GNNs.
Tuo Xu, Lei Zou
2024Rethinking the Benefits of Steerable Features in 3D Equivariant Graph Neural Networks.
Shih-Hsin Wang, Yung-Chang Hsu, Justin M. Baker, Andrea L. Bertozzi, Jack Xin, Bao Wang
2024Rethinking the Power of Graph Canonization in Graph Representation Learning with Stability.
Zehao Dong, Muhan Zhang, Philip R. O. Payne, Michael A. Province, Carlos Cruchaga, Tianyu Zhao, Fuhai Li, Yixin Chen
2024Rethinking the Uniformity Metric in Self-Supervised Learning.
Xianghong Fang, Jian Li, Qiang Sun, Benyou Wang
2024Rethinking the symmetry-preserving circuits for constrained variational quantum algorithms.
Ge Yan, Hongxu Chen, Kaisen Pan, Junchi Yan
2024Retrieval is Accurate Generation.
Bowen Cao, Deng Cai, Leyang Cui, Xuxin Cheng, Wei Bi, Yuexian Zou, Shuming Shi
2024Retrieval meets Long Context Large Language Models.
Peng Xu, Wei Ping, Xianchao Wu, Lawrence McAfee, Chen Zhu, Zihan Liu, Sandeep Subramanian, Evelina Bakhturina, Mohammad Shoeybi, Bryan Catanzaro
2024Retrieval-Enhanced Contrastive Vision-Text Models.
Ahmet Iscen, Mathilde Caron, Alireza Fathi, Cordelia Schmid
2024Retrieval-Guided Reinforcement Learning for Boolean Circuit Minimization.
Animesh Basak Chowdhury, Marco Romanelli, Benjamin Tan, Ramesh Karri, Siddharth Garg
2024Retrieval-based Disentangled Representation Learning with Natural Language Supervision.
Jiawei Zhou, Xiaoguang Li, Lifeng Shang, Xin Jiang, Qun Liu, Lei Chen
2024Retro-fallback: retrosynthetic planning in an uncertain world.
Austin Tripp, Krzysztof Maziarz, Sarah Lewis, Marwin H. S. Segler, José Miguel Hernández-Lobato
2024RetroBridge: Modeling Retrosynthesis with Markov Bridges.
Ilia Igashov, Arne Schneuing, Marwin H. S. Segler, Michael M. Bronstein, Bruno E. Correia
2024Retroformer: Retrospective Large Language Agents with Policy Gradient Optimization.
Weiran Yao, Shelby Heinecke, Juan Carlos Niebles, Zhiwei Liu, Yihao Feng, Le Xue, Rithesh R. N., Zeyuan Chen, Jianguo Zhang, Devansh Arpit, Ran Xu, Phil Mui, Huan Wang, Caiming Xiong, Silvio Savarese
2024Reverse Diffusion Monte Carlo.
Xunpeng Huang, Hanze Dong, Yifan Hao, Yian Ma, Tong Zhang
2024Reverse Forward Curriculum Learning for Extreme Sample and Demo Efficiency.
Stone Tao, Arth Shukla, Tse-kai Chan, Hao Su
2024Revisit and Outstrip Entity Alignment: A Perspective of Generative Models.
Lingbing Guo, Zhuo Chen, Jiaoyan Chen, Yin Fang, Wen Zhang, Huajun Chen
2024Revisiting Data Augmentation in Deep Reinforcement Learning.
Jianshu Hu, Yunpeng Jiang, Paul Weng
2024Revisiting Deep Audio-Text Retrieval Through the Lens of Transportation.
Manh Luong, Khai Nguyen, Nhat Ho, Gholamreza Haffari, Dinh Phung, Lizhen Qu
2024Revisiting Link Prediction: a data perspective.
Haitao Mao, Juanhui Li, Harry Shomer, Bingheng Li, Wenqi Fan, Yao Ma, Tong Zhao, Neil Shah, Jiliang Tang
2024Revisiting Plasticity in Visual Reinforcement Learning: Data, Modules and Training Stages.
Guozheng Ma, Lu Li, Sen Zhang, Zixuan Liu, Zhen Wang, Yixin Chen, Li Shen, Xueqian Wang, Dacheng Tao
2024Revisiting the Last-Iterate Convergence of Stochastic Gradient Methods.
Zijian Liu, Zhengyuan Zhou
2024Reward Design for Justifiable Sequential Decision-Making.
Aleksa Sukovic, Goran Radanovic
2024Reward Model Ensembles Help Mitigate Overoptimization.
Thomas Coste, Usman Anwar, Robert Kirk, David Krueger
2024Reward-Consistent Dynamics Models are Strongly Generalizable for Offline Reinforcement Learning.
Fan-Ming Luo, Tian Xu, Xingchen Cao, Yang Yu
2024Reward-Free Curricula for Training Robust World Models.
Marc Rigter, Minqi Jiang, Ingmar Posner
2024Rigid Protein-Protein Docking via Equivariant Elliptic-Paraboloid Interface Prediction.
Ziyang Yu, Wenbing Huang, Yang Liu
2024Ring-A-Bell! How Reliable are Concept Removal Methods For Diffusion Models?
Yu-Lin Tsai, Chia-Yi Hsu, Chulin Xie, Chih-Hsun Lin, Jia-You Chen, Bo Li, Pin-Yu Chen, Chia-Mu Yu, Chun-Ying Huang
2024RingAttention with Blockwise Transformers for Near-Infinite Context.
Hao Liu, Matei Zaharia, Pieter Abbeel
2024Risk Bounds of Accelerated SGD for Overparameterized Linear Regression.
Xuheng Li, Yihe Deng, Jingfeng Wu, Dongruo Zhou, Quanquan Gu
2024Robot Fleet Learning via Policy Merging.
Lirui Wang, Kaiqing Zhang, Allan Zhou, Max Simchowitz, Russ Tedrake
2024Robust Adversarial Reinforcement Learning via Bounded Rationality Curricula.
Aryaman Reddi, Maximilian Tölle, Jan Peters, Georgia Chalvatzaki, Carlo D'Eramo
2024Robust Angular Synchronization via Directed Graph Neural Networks.
Yixuan He, Gesine Reinert, David Wipf, Mihai Cucuringu
2024Robust Classification via Regression for Learning with Noisy Labels.
Erik Englesson, Hossein Azizpour
2024Robust Model Based Reinforcement Learning Using L1 Adaptive Control.
Minjun Sung, Sambhu H. Karumanchi, Aditya Gahlawat, Naira Hovakimyan
2024Robust Model-Based Optimization for Challenging Fitness Landscapes.
Saba Ghaffari, Ehsan Saleh, Alexander G. Schwing, Yu-Xiong Wang, Martin D. Burke, Saurabh Sinha
2024Robust NAS under adversarial training: benchmark, theory, and beyond.
Yongtao Wu, Fanghui Liu, Carl-Johann Simon-Gabriel, Grigorios Chrysos, Volkan Cevher
2024Robust Similarity Learning with Difference Alignment Regularization.
Shuo Chen, Gang Niu, Chen Gong, Okan Koc, Jian Yang, Masashi Sugiyama
2024Robust Training of Federated Models with Extremely Label Deficiency.
Yonggang Zhang, Zhiqin Yang, Xinmei Tian, Nannan Wang, Tongliang Liu, Bo Han
2024Robust agents learn causal world models.
Jonathan Richens, Tom Everitt
2024RobustTSF: Towards Theory and Design of Robust Time Series Forecasting with Anomalies.
Hao Cheng, Qingsong Wen, Yang Liu, Liang Sun
2024Robustifying State-space Models for Long Sequences via Approximate Diagonalization.
Annan Yu, Arnur Nigmetov, Dmitriy Morozov, Michael W. Mahoney, N. Benjamin Erichson
2024Robustifying and Boosting Training-Free Neural Architecture Search.
Zhenfeng He, Yao Shu, Zhongxiang Dai, Bryan Kian Hsiang Low
2024Robustness of AI-Image Detectors: Fundamental Limits and Practical Attacks.
Mehrdad Saberi, Vinu Sankar Sadasivan, Keivan Rezaei, Aounon Kumar, Atoosa Malemir Chegini, Wenxiao Wang, Soheil Feizi
2024Role of Locality and Weight Sharing in Image-Based Tasks: A Sample Complexity Separation between CNNs, LCNs, and FCNs.
Aakash Lahoti, Stefani Karp, Ezra Winston, Aarti Singh, Yuanzhi Li
2024Rotation Has Two Sides: Evaluating Data Augmentation for Deep One-class Classification.
Guodong Wang, Yunhong Wang, Xiuguo Bao, Di Huang
2024S2AC: Energy-Based Reinforcement Learning with Stein Soft Actor Critic.
Safa Messaoud, Billel Mokeddem, Zhenghai Xue, Linsey Pang, Bo An, Haipeng Chen, Sanjay Chawla
2024SAFLEX: Self-Adaptive Augmentation via Feature Label Extrapolation.
Mucong Ding, Bang An, Yuancheng Xu, Anirudh Satheesh, Furong Huang
2024SALMON: Self-Alignment with Instructable Reward Models.
Zhiqing Sun, Yikang Shen, Hongxin Zhang, Qinhong Zhou, Zhenfang Chen, David Daniel Cox, Yiming Yang, Chuang Gan
2024SALMONN: Towards Generic Hearing Abilities for Large Language Models.
Changli Tang, Wenyi Yu, Guangzhi Sun, Xianzhao Chen, Tian Tan, Wei Li, Lu Lu, Zejun Ma, Chao Zhang
2024SAN: Inducing Metrizability of GAN with Discriminative Normalized Linear Layer.
Yuhta Takida, Masaaki Imaizumi, Takashi Shibuya, Chieh-Hsin Lai, Toshimitsu Uesaka, Naoki Murata, Yuki Mitsufuji
2024SAS: Structured Activation Sparsification.
Yusuke Sekikawa, Shingo Yashima
2024SCHEMA: State CHangEs MAtter for Procedure Planning in Instructional Videos.
Yulei Niu, Wenliang Guo, Long Chen, Xudong Lin, Shih-Fu Chang
2024SDXL: Improving Latent Diffusion Models for High-Resolution Image Synthesis.
Dustin Podell, Zion English, Kyle Lacey, Andreas Blattmann, Tim Dockhorn, Jonas Müller, Joe Penna, Robin Rombach
2024SE(3)-Stochastic Flow Matching for Protein Backbone Generation.
Avishek Joey Bose, Tara Akhound-Sadegh, Guillaume Huguet, Kilian Fatras, Jarrid Rector-Brooks, Cheng-Hao Liu, Andrei Cristian Nica, Maksym Korablyov, Michael M. Bronstein, Alexander Tong
2024SEA: Sparse Linear Attention with Estimated Attention Mask.
Heejun Lee, Jina Kim, Jeffrey Willette, Sung Ju Hwang
2024SEABO: A Simple Search-Based Method for Offline Imitation Learning.
Jiafei Lyu, Xiaoteng Ma, Le Wan, Runze Liu, Xiu Li, Zongqing Lu
2024SEAL: A Framework for Systematic Evaluation of Real-World Super-Resolution.
Wenlong Zhang, Xiaohui Li, Xiangyu Chen, Xiaoyun Zhang, Yu Qiao, Xiao-Ming Wu, Chao Dong
2024SEGNO: Generalizing Equivariant Graph Neural Networks with Physical Inductive Biases.
Yang Liu, Jiashun Cheng, Haihong Zhao, Tingyang Xu, Peilin Zhao, Fugee Tsung, Jia Li, Yu Rong
2024SEINE: Short-to-Long Video Diffusion Model for Generative Transition and Prediction.
Xinyuan Chen, Yaohui Wang, Lingjun Zhang, Shaobin Zhuang, Xin Ma, Jiashuo Yu, Yali Wang, Dahua Lin, Yu Qiao, Ziwei Liu
2024SEPT: Towards Efficient Scene Representation Learning for Motion Prediction.
Zhiqian Lan, Yuxuan Jiang, Yao Mu, Chen Chen, Shengbo Eben Li
2024SF(DA)2: Source-free Domain Adaptation Through the Lens of Data Augmentation.
Uiwon Hwang, Jonghyun Lee, Juhyeon Shin, Sungroh Yoon
2024SGD Finds then Tunes Features in Two-Layer Neural Networks with near-Optimal Sample Complexity: A Case Study in the XOR problem.
Margalit Glasgow
2024SILO Language Models: Isolating Legal Risk In a Nonparametric Datastore.
Sewon Min, Suchin Gururangan, Eric Wallace, Weijia Shi, Hannaneh Hajishirzi, Noah A. Smith, Luke Zettlemoyer
2024SKILL-MIX: a Flexible and Expandable Family of Evaluations for AI Models.
Dingli Yu, Simran Kaur, Arushi Gupta, Jonah Brown-Cohen, Anirudh Goyal, Sanjeev Arora
2024SLiMe: Segment Like Me.
Aliasghar Khani, Saeid Asgari Taghanaki, Aditya Sanghi, Ali Mahdavi-Amiri, Ghassan Hamarneh
2024SNIP: Bridging Mathematical Symbolic and Numeric Realms with Unified Pre-training.
Kazem Meidani, Parshin Shojaee, Chandan K. Reddy, Amir Barati Farimani
2024SOHES: Self-supervised Open-world Hierarchical Entity Segmentation.
Shengcao Cao, Jiuxiang Gu, Jason Kuen, Hao Tan, Ruiyi Zhang, Handong Zhao, Ani Nenkova, Liangyan Gui, Tong Sun, Yu-Xiong Wang
2024SOInter: A Novel Deep Energy-Based Interpretation Method for Explaining Structured Output Models.
Seyyede Fatemeh Seyyedsalehi, Mahdieh Soleymani Baghshah, Hamid R. Rabiee
2024SOTOPIA: Interactive Evaluation for Social Intelligence in Language Agents.
Xuhui Zhou, Hao Zhu, Leena Mathur, Ruohong Zhang, Haofei Yu, Zhengyang Qi, Louis-Philippe Morency, Yonatan Bisk, Daniel Fried, Graham Neubig, Maarten Sap
2024SPDER: Semiperiodic Damping-Enabled Object Representation.
Kathan Shah, Chawin Sitawarin
2024SPTNet: An Efficient Alternative Framework for Generalized Category Discovery with Spatial Prompt Tuning.
Hongjun Wang, Sagar Vaze, Kai Han
2024SRL: Scaling Distributed Reinforcement Learning to Over Ten Thousand Cores.
Zhiyu Mei, Wei Fu, Jiaxuan Gao, Guangju Wang, Huanchen Zhang, Yi Wu
2024STARC: A General Framework For Quantifying Differences Between Reward Functions.
Joar Max Viktor Skalse, Lucy Farnik, Sumeet Ramesh Motwani, Erik Jenner, Adam Gleave, Alessandro Abate
2024STREAM: Spatio-TempoRal Evaluation and Analysis Metric for Video Generative Models.
Pum Jun Kim, Seojun Kim, Jaejun Yoo
2024STanHop: Sparse Tandem Hopfield Model for Memory-Enhanced Time Series Prediction.
Dennis Wu, Jerry Yao-Chieh Hu, Weijian Li, Bo-Yu Chen, Han Liu
2024SWAP-NAS: Sample-Wise Activation Patterns for Ultra-fast NAS.
Yameng Peng, Andy Song, Haytham M. Fayek, Vic Ciesielski, Xiaojun Chang
2024SWAP: Sparse Entropic Wasserstein Regression for Robust Network Pruning.
Lei You, Hei Victor Cheng
2024SWE-bench: Can Language Models Resolve Real-world Github Issues?
Carlos E. Jimenez, John Yang, Alexander Wettig, Shunyu Yao, Kexin Pei, Ofir Press, Karthik R. Narasimhan
2024SYMBOL: Generating Flexible Black-Box Optimizers through Symbolic Equation Learning.
Jiacheng Chen, Zeyuan Ma, Hongshu Guo, Yining Ma, Jie Zhang, Yue-Jiao Gong
2024SaNN: Simple Yet Powerful Simplicial-aware Neural Networks.
Sravanthi Gurugubelli, Sundeep Prabhakar Chepuri
2024SaProt: Protein Language Modeling with Structure-aware Vocabulary.
Jin Su, Chenchen Han, Yuyang Zhou, Junjie Shan, Xibin Zhou, Fajie Yuan
2024Safe Collaborative Filtering.
Riku Togashi, Tatsushi Oka, Naoto Ohsaka, Tetsuro Morimura
2024Safe Offline Reinforcement Learning with Feasibility-Guided Diffusion Model.
Yinan Zheng, Jianxiong Li, Dongjie Yu, Yujie Yang, Shengbo Eben Li, Xianyuan Zhan, Jingjing Liu
2024Safe RLHF: Safe Reinforcement Learning from Human Feedback.
Josef Dai, Xuehai Pan, Ruiyang Sun, Jiaming Ji, Xinbo Xu, Mickel Liu, Yizhou Wang, Yaodong Yang
2024Safe and Robust Watermark Injection with a Single OoD Image.
Shuyang Yu, Junyuan Hong, Haobo Zhang, Haotao Wang, Zhangyang Wang, Jiayu Zhou
2024SafeDreamer: Safe Reinforcement Learning with World Models.
Weidong Huang, Jiaming Ji, Chunhe Xia, Borong Zhang, Yaodong Yang
2024Safety-Tuned LLaMAs: Lessons From Improving the Safety of Large Language Models that Follow Instructions.
Federico Bianchi, Mirac Suzgun, Giuseppe Attanasio, Paul Röttger, Dan Jurafsky, Tatsunori Hashimoto, James Zou
2024SalUn: Empowering Machine Unlearning via Gradient-based Weight Saliency in Both Image Classification and Generation.
Chongyu Fan, Jiancheng Liu, Yihua Zhang, Eric Wong, Dennis Wei, Sijia Liu
2024Sample Efficient Myopic Exploration Through Multitask Reinforcement Learning with Diverse Tasks.
Ziping Xu, Zifan Xu, Runxuan Jiang, Peter Stone, Ambuj Tewari
2024Sample-Efficiency in Multi-Batch Reinforcement Learning: The Need for Dimension-Dependent Adaptivity.
Emmeran Johnson, Ciara Pike-Burke, Patrick Rebeschini
2024Sample-Efficient Learning of POMDPs with Multiple Observations In Hindsight.
Jiacheng Guo, Minshuo Chen, Huan Wang, Caiming Xiong, Mengdi Wang, Yu Bai
2024Sample-Efficient Linear Representation Learning from Non-IID Non-Isotropic Data.
Thomas T. C. K. Zhang, Leonardo Felipe Toso, James Anderson, Nikolai Matni
2024Sample-Efficient Multi-Agent RL: An Optimization Perspective.
Nuoya Xiong, Zhihan Liu, Zhaoran Wang, Zhuoran Yang
2024Sample-Efficient Quality-Diversity by Cooperative Coevolution.
Ke Xue, Ren-Jian Wang, Pengyi Li, Dong Li, Jianye Hao, Chao Qian
2024Sample-efficient Learning of Infinite-horizon Average-reward MDPs with General Function Approximation.
Jianliang He, Han Zhong, Zhuoran Yang
2024Sampling Multimodal Distributions with the Vanilla Score: Benefits of Data-Based Initialization.
Frederic Koehler, Thuy-Duong Vuong
2024Scalable Diffusion for Materials Generation.
Sherry Yang, KwangHwan Cho, Amil Merchant, Pieter Abbeel, Dale Schuurmans, Igor Mordatch, Ekin Dogus Cubuk
2024Scalable Language Model with Generalized Continual Learning.
Bohao Peng, Zhuotao Tian, Shu Liu, Ming-Chang Yang, Jiaya Jia
2024Scalable Modular Network: A Framework for Adaptive Learning via Agreement Routing.
Minyang Hu, Hong Chang, Bingpeng Ma, Shiguang Shan, Xilin Chen
2024Scalable Monotonic Neural Networks.
Hyunho Kim, Jong-Seok Lee
2024Scalable Neural Network Kernels.
Arijit Sehanobish, Krzysztof Marcin Choromanski, Yunfan Zhao, Kumar Avinava Dubey, Valerii Likhosherstov
2024Scalable and Effective Implicit Graph Neural Networks on Large Graphs.
Juncheng Liu, Bryan Hooi, Kenji Kawaguchi, Yiwei Wang, Chaosheng Dong, Xiaokui Xiao
2024Scale-Adaptive Diffusion Model for Complex Sketch Synthesis.
Jijin Hu, Ke Li, Yonggang Qi, Yi-Zhe Song
2024ScaleCrafter: Tuning-free Higher-Resolution Visual Generation with Diffusion Models.
Yingqing He, Shaoshu Yang, Haoxin Chen, Xiaodong Cun, Menghan Xia, Yong Zhang, Xintao Wang, Ran He, Qifeng Chen, Ying Shan
2024Scaling Convex Neural Networks with Burer-Monteiro Factorization.
Arda Sahiner, Tolga Ergen, Batu Ozturkler, John M. Pauly, Morteza Mardani, Mert Pilanci
2024Scaling Laws for Associative Memories.
Vivien Cabannes, Elvis Dohmatob, Alberto Bietti
2024Scaling Laws for Sparsely-Connected Foundation Models.
Elias Frantar, Carlos Riquelme Ruiz, Neil Houlsby, Dan Alistarh, Utku Evci
2024Scaling Laws of RoPE-based Extrapolation.
Xiaoran Liu, Hang Yan, Chenxin An, Xipeng Qiu, Dahua Lin
2024Scaling Supervised Local Learning with Augmented Auxiliary Networks.
Chenxiang Ma, Jibin Wu, Chenyang Si, Kay Chen Tan
2024Scaling for Training Time and Post-hoc Out-of-distribution Detection Enhancement.
Kai Xu, Rongyu Chen, Gianni Franchi, Angela Yao
2024Scaling physics-informed hard constraints with mixture-of-experts.
Nithin Chalapathi, Yiheng Du, Aditi S. Krishnapriyan
2024Score Models for Offline Goal-Conditioned Reinforcement Learning.
Harshit Sikchi, Rohan Chitnis, Ahmed Touati, Alborz Geramifard, Amy Zhang, Scott Niekum
2024Score Regularized Policy Optimization through Diffusion Behavior.
Huayu Chen, Cheng Lu, Zhengyi Wang, Hang Su, Jun Zhu
2024Score-based generative models break the curse of dimensionality in learning a family of sub-Gaussian distributions.
Frank Cole, Yulong Lu
2024Searching for High-Value Molecules Using Reinforcement Learning and Transformers.
Raj Ghugare, Santiago Miret, Adriana Hugessen, Mariano Phielipp, Glen Berseth
2024Seeking Neural Nuggets: Knowledge Transfer in Large Language Models from a Parametric Perspective.
Ming Zhong, Chenxin An, Weizhu Chen, Jiawei Han, Pengcheng He
2024Seer: Language Instructed Video Prediction with Latent Diffusion Models.
Xianfan Gu, Chuan Wen, Weirui Ye, Jiaming Song, Yang Gao
2024Select to Perfect: Imitating desired behavior from large multi-agent data.
Tim Franzmeyer, Edith Elkind, Philip Torr, Jakob Nicolaus Foerster, João F. Henriques
2024Selective Mixup Fine-Tuning for Optimizing Non-Decomposable Objectives.
Shrinivas Ramasubramanian, Harsh Rangwani, Sho Takemori, Kunal Samanta, Yuhei Umeda, Venkatesh Babu Radhakrishnan
2024Selective Visual Representations Improve Convergence and Generalization for Embodied AI.
Ainaz Eftekhar, Kuo-Hao Zeng, Jiafei Duan, Ali Farhadi, Aniruddha Kembhavi, Ranjay Krishna
2024Self-Alignment with Instruction Backtranslation.
Xian Li, Ping Yu, Chunting Zhou, Timo Schick, Omer Levy, Luke Zettlemoyer, Jason Weston, Mike Lewis
2024Self-Consuming Generative Models Go MAD.
Sina Alemohammad, Josue Casco-Rodriguez, Lorenzo Luzi, Ahmed Imtiaz Humayun, Hossein Babaei, Daniel LeJeune, Ali Siahkoohi, Richard G. Baraniuk
2024Self-Guided Masked Autoencoders for Domain-Agnostic Self-Supervised Learning.
Johnathan Xie, Yoonho Lee, Annie S. Chen, Chelsea Finn
2024Self-RAG: Learning to Retrieve, Generate, and Critique through Self-Reflection.
Akari Asai, Zeqiu Wu, Yizhong Wang, Avirup Sil, Hannaneh Hajishirzi
2024Self-Supervised Contrastive Learning for Long-term Forecasting.
Junwoo Park, Daehoon Gwak, Jaegul Choo, Edward Choi
2024Self-Supervised Dataset Distillation for Transfer Learning.
Dong Bok Lee, Seanie Lee, Joonho Ko, Kenji Kawaguchi, Juho Lee, Sung Ju Hwang
2024Self-Supervised Heterogeneous Graph Learning: a Homophily and Heterogeneity View.
Yujie Mo, Feiping Nie, Ping Hu, Heng Tao Shen, Zheng Zhang, Xinchao Wang, Xiaofeng Zhu
2024Self-Supervised High Dynamic Range Imaging with Multi-Exposure Images in Dynamic Scenes.
Zhilu Zhang, Haoyu Wang, Shuai Liu, Xiaotao Wang, Lei Lei, Wangmeng Zuo
2024Self-Supervised Speech Quality Estimation and Enhancement Using Only Clean Speech.
Szu-Wei Fu, Kuo-Hsuan Hung, Yu Tsao, Yu-Chiang Frank Wang
2024Self-contradictory Hallucinations of Large Language Models: Evaluation, Detection and Mitigation.
Niels Mündler, Jingxuan He, Slobodan Jenko, Martin T. Vechev
2024Self-supervised Pocket Pretraining via Protein Fragment-Surroundings Alignment.
Bowen Gao, Yinjun Jia, Yuanle Mo, Yuyan Ni, Wei-Ying Ma, Zhi-Ming Ma, Yanyan Lan
2024Self-supervised Representation Learning from Random Data Projectors.
Yi Sui, Tongzi Wu, Jesse C. Cresswell, Ga Wu, George Stein, Xiao Shi Huang, Xiaochen Zhang, Maksims Volkovs
2024SelfCheck: Using LLMs to Zero-Shot Check Their Own Step-by-Step Reasoning.
Ning Miao, Yee Whye Teh, Tom Rainforth
2024Semantic Flow: Learning Semantic Fields of Dynamic Scenes from Monocular Videos.
Fengrui Tian, Yueqi Duan, Angtian Wang, Jianfei Guo, Shaoyi Du
2024SemiReward: A General Reward Model for Semi-supervised Learning.
Siyuan Li, Weiyang Jin, Zedong Wang, Fang Wu, Zicheng Liu, Cheng Tan, Stan Z. Li
2024Sentence-level Prompts Benefit Composed Image Retrieval.
Yang Bai, Xinxing Xu, Yong Liu, Salman Khan, Fahad Khan, Wangmeng Zuo, Rick Siow Mong Goh, Chun-Mei Feng
2024Separate and Diffuse: Using a Pretrained Diffusion Model for Better Source Separation.
Shahar Lutati, Eliya Nachmani, Lior Wolf
2024Separating common from salient patterns with Contrastive Representation Learning.
Robin Louiset, Edouard Duchesnay, Antoine Grigis, Pietro Gori
2024SequenceMatch: Imitation Learning for Autoregressive Sequence Modelling with Backtracking.
Chris Cundy, Stefano Ermon
2024Set Learning for Accurate and Calibrated Models.
Lukas Muttenthaler, Robert A. Vandermeulen, Qiuyi Zhang, Thomas Unterthiner, Klaus-Robert Müller
2024SetCSE: Set Operations using Contrastive Learning of Sentence Embeddings.
Kang Liu
2024Shadow Cones: A Generalized Framework for Partial Order Embeddings.
Tao Yu, Toni J. B. Liu, Albert Tseng, Christopher De Sa
2024Sharpness-Aware Data Poisoning Attack.
Pengfei He, Han Xu, Jie Ren, Yingqian Cui, Shenglai Zeng, Hui Liu, Charu C. Aggarwal, Jiliang Tang
2024Sharpness-Aware Minimization Enhances Feature Quality via Balanced Learning.
Jacob Mitchell Springer, Vaishnavh Nagarajan, Aditi Raghunathan
2024Sheared LLaMA: Accelerating Language Model Pre-training via Structured Pruning.
Mengzhou Xia, Tianyu Gao, Zhiyuan Zeng, Danqi Chen
2024Sign2GPT: Leveraging Large Language Models for Gloss-Free Sign Language Translation.
Ryan Wong, Necati Cihan Camgöz, Richard Bowden
2024Simple Hierarchical Planning with Diffusion.
Chang Chen, Fei Deng, Kenji Kawaguchi, Caglar Gulcehre, Sungjin Ahn
2024Simple Minimax Optimal Byzantine Robust Algorithm for Nonconvex Objectives with Uniform Gradient Heterogeneity.
Tomoya Murata, Kenta Niwa, Takumi Fukami, Iifan Tyou
2024Simplicial Representation Learning with Neural k-Forms.
Kelly Maggs, Celia Hacker, Bastian Rieck
2024Simplifying Transformer Blocks.
Bobby He, Thomas Hofmann
2024Sin3DM: Learning a Diffusion Model from a Single 3D Textured Shape.
Rundi Wu, Ruoshi Liu, Carl Vondrick, Changxi Zheng
2024SineNet: Learning Temporal Dynamics in Time-Dependent Partial Differential Equations.
Xuan Zhang, Jacob Helwig, Yuchao Lin, Yaochen Xie, Cong Fu, Stephan Wojtowytsch, Shuiwang Ji
2024Single Motion Diffusion.
Sigal Raab, Inbal Leibovitch, Guy Tevet, Moab Arar, Amit Haim Bermano, Daniel Cohen-Or
2024Skeleton-of-Thought: Prompting LLMs for Efficient Parallel Generation.
Xuefei Ning, Zinan Lin, Zixuan Zhou, Zifu Wang, Huazhong Yang, Yu Wang
2024Skill Machines: Temporal Logic Skill Composition in Reinforcement Learning.
Geraud Nangue Tasse, Devon Jarvis, Steven James, Benjamin Rosman
2024Skill or Luck? Return Decomposition via Advantage Functions.
Hsiao-Ru Pan, Bernhard Schölkopf
2024Skip-Attention: Improving Vision Transformers by Paying Less Attention.
Shashanka Venkataramanan, Amir Ghodrati, Yuki M. Asano, Fatih Porikli, Amirhossein Habibian
2024SliceGPT: Compress Large Language Models by Deleting Rows and Columns.
Saleh Ashkboos, Maximilian L. Croci, Marcelo Gennari Do Nascimento, Torsten Hoefler, James Hensman
2024Sliced Denoising: A Physics-Informed Molecular Pre-Training Method.
Yuyan Ni, Shikun Feng, Wei-Ying Ma, Zhi-Ming Ma, Yanyan Lan
2024Sliced Wasserstein Estimation with Control Variates.
Khai Nguyen, Nhat Ho
2024Small-scale proxies for large-scale Transformer training instabilities.
Mitchell Wortsman, Peter J. Liu, Lechao Xiao, Katie E. Everett, Alexander A. Alemi, Ben Adlam, John D. Co-Reyes, Izzeddin Gur, Abhishek Kumar, Roman Novak, Jeffrey Pennington, Jascha Sohl-Dickstein, Kelvin Xu, Jaehoon Lee, Justin Gilmer, Simon Kornblith
2024SmartPlay : A Benchmark for LLMs as Intelligent Agents.
Yue Wu, Xuan Tang, Tom M. Mitchell, Yuanzhi Li
2024Smooth ECE: Principled Reliability Diagrams via Kernel Smoothing.
Jaroslaw Blasiok, Preetum Nakkiran
2024Social Reward: Evaluating and Enhancing Generative AI through Million-User Feedback from an Online Creative Community.
Arman Isajanyan, Artur Shatveryan, David Kocharian, Zhangyang Wang, Humphrey Shi
2024Social-Transmotion: Promptable Human Trajectory Prediction.
Saeed Saadatnejad, Yang Gao, Kaouther Messaoud, Alexandre Alahi
2024SocioDojo: Building Lifelong Analytical Agents with Real-world Text and Time Series.
Junyan Cheng, Peter Chin
2024Soft Contrastive Learning for Time Series.
Seunghan Lee, Taeyoung Park, Kibok Lee
2024Soft Mixture Denoising: Beyond the Expressive Bottleneck of Diffusion Models.
Yangming Li, Boris van Breugel, Mihaela van der Schaar
2024Soft Robust MDPs and Risk-Sensitive MDPs: Equivalence, Policy Gradient, and Sample Complexity.
Runyu Zhang, Yang Hu, Na Li
2024Solving Challenging Math Word Problems Using GPT-4 Code Interpreter with Code-based Self-Verification.
Aojun Zhou, Ke Wang, Zimu Lu, Weikang Shi, Sichun Luo, Zipeng Qin, Shaoqing Lu, Anya Jia, Linqi Song, Mingjie Zhan, Hongsheng Li
2024Solving Diffusion ODEs with Optimal Boundary Conditions for Better Image Super-Resolution.
Yiyang Ma, Huan Yang, Wenhan Yang, Jianlong Fu, Jiaying Liu
2024Solving High Frequency and Multi-Scale PDEs with Gaussian Processes.
Shikai Fang, Madison Cooley, Da Long, Shibo Li, Mike Kirby, Shandian Zhe
2024Solving Homogeneous and Heterogeneous Cooperative Tasks with Greedy Sequential Execution.
Shanqi Liu, Dong Xing, Pengjie Gu, Xinrun Wang, Bo An, Yong Liu
2024Solving Inverse Problems with Latent Diffusion Models via Hard Data Consistency.
Bowen Song, Soo Min Kwon, Zecheng Zhang, Xinyu Hu, Qing Qu, Liyue Shen
2024Some Fundamental Aspects about Lipschitz Continuity of Neural Networks.
Grigory Khromov, Sidak Pal Singh
2024Sophia: A Scalable Stochastic Second-order Optimizer for Language Model Pre-training.
Hong Liu, Zhiyuan Li, David Leo Wright Hall, Percy Liang, Tengyu Ma
2024Source-Free and Image-Only Unsupervised Domain Adaptation for Category Level Object Pose Estimation.
Prakhar Kaushik, Aayush Mishra, Adam Kortylewski, Alan L. Yuille
2024SpQR: A Sparse-Quantized Representation for Near-Lossless LLM Weight Compression.
Tim Dettmers, Ruslan Svirschevski, Vage Egiazarian, Denis Kuznedelev, Elias Frantar, Saleh Ashkboos, Alexander Borzunov, Torsten Hoefler, Dan Alistarh
2024SpaCE: The Spatial Confounding Environment.
Mauricio Tec, Ana Trisovic, Michelle Audirac, Sophie Woodward, Jie Kate Hu, Naeem Khoshnevis, Francesca Dominici
2024Space Group Constrained Crystal Generation.
Rui Jiao, Wenbing Huang, Yu Liu, Deli Zhao, Yang Liu
2024Space and time continuous physics simulation from partial observations.
Steeven Janny, Madiha Nadri, Julie Digne, Christian Wolf
2024Sparse Autoencoders Find Highly Interpretable Features in Language Models.
Robert Huben, Hoagy Cunningham, Logan Riggs Smith, Aidan Ewart, Lee Sharkey
2024Sparse MoE with Language Guided Routing for Multilingual Machine Translation.
Xinyu Zhao, Xuxi Chen, Yu Cheng, Tianlong Chen
2024Sparse Model Soups: A Recipe for Improved Pruning via Model Averaging.
Max Zimmer, Christoph Spiegel, Sebastian Pokutta
2024Sparse Spiking Neural Network: Exploiting Heterogeneity in Timescales for Pruning Recurrent SNN.
Biswadeep Chakraborty, Beomseok Kang, Harshit Kumar, Saibal Mukhopadhyay
2024Sparse Weight Averaging with Multiple Particles for Iterative Magnitude Pruning.
Moonseok Choi, Hyungi Lee, Giung Nam, Juho Lee
2024SparseDFF: Sparse-View Feature Distillation for One-Shot Dexterous Manipulation.
Qianxu Wang, Haotong Zhang, Congyue Deng, Yang You, Hao Dong, Yixin Zhu, Leonidas J. Guibas
2024SparseFormer: Sparse Visual Recognition via Limited Latent Tokens.
Ziteng Gao, Zhan Tong, Limin Wang, Mike Zheng Shou
2024Sparsistency for inverse optimal transport.
Francisco Andrade, Gabriel Peyré, Clarice Poon
2024Spatially-Aware Transformers for Embodied Agents.
Junmo Cho, Jaesik Yoon, Sungjin Ahn
2024Spatio-Temporal Approximation: A Training-Free SNN Conversion for Transformers.
Yizhou Jiang, Kunlin Hu, Tianren Zhang, Haichuan Gao, Yuqian Liu, Ying Fang, Feng Chen
2024Spatio-Temporal Few-Shot Learning via Diffusive Neural Network Generation.
Yuan Yuan, Chenyang Shao, Jingtao Ding, Depeng Jin, Yong Li
2024Spectrally Transformed Kernel Regression.
Runtian Zhai, Rattana Pukdee, Roger Jin, Maria-Florina Balcan, Pradeep Kumar Ravikumar
2024SpeechTokenizer: Unified Speech Tokenizer for Speech Language Models.
Xin Zhang, Dong Zhang, Shimin Li, Yaqian Zhou, Xipeng Qiu
2024Spike-driven Transformer V2: Meta Spiking Neural Network Architecture Inspiring the Design of Next-generation Neuromorphic Chips.
Man Yao, Jiakui Hu, Tianxiang Hu, Yifan Xu, Zhaokun Zhou, Yonghong Tian, Bo Xu, Guoqi Li
2024SpikePoint: An Efficient Point-based Spiking Neural Network for Event Cameras Action Recognition.
Hongwei Ren, Yue Zhou, Xiaopeng Lin, Yulong Huang, Haotian Fu, Jie Song, Bojun Cheng
2024Spoken Question Answering and Speech Continuation Using Spectrogram-Powered LLM.
Eliya Nachmani, Alon Levkovitch, Roy Hirsch, Julian Salazar, Chulayuth Asawaroengchai, Soroosh Mariooryad, Ehud Rivlin, R. J. Skerry-Ryan, Michelle Tadmor Ramanovich
2024Spurious Feature Diversification Improves Out-of-distribution Generalization.
Yong Lin, Lu Tan, Yifan Hao, Honam Wong, Hanze Dong, Weizhong Zhang, Yujiu Yang, Tong Zhang
2024Stabilizing Backpropagation Through Time to Learn Complex Physics.
Patrick Schnell, Nils Thuerey
2024Stabilizing Contrastive RL: Techniques for Robotic Goal Reaching from Offline Data.
Chongyi Zheng, Benjamin Eysenbach, Homer Rich Walke, Patrick Yin, Kuan Fang, Ruslan Salakhutdinov, Sergey Levine
2024Stable Anisotropic Regularization.
William Rudman, Carsten Eickhoff
2024Stable Neural Stochastic Differential Equations in Analyzing Irregular Time Series Data.
YongKyung Oh, Dongyoung Lim, Sungil Kim
2024Stack Attention: Improving the Ability of Transformers to Model Hierarchical Patterns.
Brian DuSell, David Chiang
2024State Representation Learning Using an Unbalanced Atlas.
Li Meng, Morten Goodwin, Anis Yazidi, Paal E. Engelstad
2024Statistical Perspective of Top-K Sparse Softmax Gating Mixture of Experts.
Huy Nguyen, Pedram Akbarian, Fanqi Yan, Nhat Ho
2024Statistical Rejection Sampling Improves Preference Optimization.
Tianqi Liu, Yao Zhao, Rishabh Joshi, Misha Khalman, Mohammad Saleh, Peter J. Liu, Jialu Liu
2024Statistically Optimal K-means Clustering via Nonnegative Low-rank Semidefinite Programming.
Yubo Zhuang, Xiaohui Chen, Yun Yang, Richard Y. Zhang
2024Steve-Eye: Equipping LLM-based Embodied Agents with Visual Perception in Open Worlds.
Sipeng Zheng, Jiazheng Liu, Yicheng Feng, Zongqing Lu
2024Stochastic Controlled Averaging for Federated Learning with Communication Compression.
Xinmeng Huang, Ping Li, Xiaoyun Li
2024Stochastic Gradient Descent for Gaussian Processes Done Right.
Jihao Andreas Lin, Shreyas Padhy, Javier Antorán, Austin Tripp, Alexander Terenin, Csaba Szepesvári, José Miguel Hernández-Lobato, David Janz
2024Stochastic Modified Equations and Dynamics of Dropout Algorithm.
Zhongwang Zhang, Yuqing Li, Tao Luo, Zhi-Qin John Xu
2024Str2Str: A Score-based Framework for Zero-shot Protein Conformation Sampling.
Jiarui Lu, Bozitao Zhong, Zuobai Zhang, Jian Tang
2024Strategic Preys Make Acute Predators: Enhancing Camouflaged Object Detectors by Generating Camouflaged Objects.
Chunming He, Kai Li, Yachao Zhang, Yulun Zhang, Chenyu You, Zhenhua Guo, Xiu Li, Martin Danelljan, Fisher Yu
2024StructComp: Substituting propagation with Structural Compression in Training Graph Contrastive Learning.
Shengzhong Zhang, Wenjie Yang, Xinyuan Cao, Hongwei Zhang, Zengfeng Huang
2024Structural Estimation of Partially Observed Linear Non-Gaussian Acyclic Model: A Practical Approach with Identifiability.
Songyao Jin, Feng Xie, Guangyi Chen, Biwei Huang, Zhengming Chen, Xinshuai Dong, Kun Zhang
2024Structural Fairness-aware Active Learning for Graph Neural Networks.
Haoyu Han, Xiaorui Liu, Li Ma, MohamadAli Torkamani, Hui Liu, Jiliang Tang, Makoto Yamada
2024Structural Inference with Dynamics Encoding and Partial Correlation Coefficients.
Aoran Wang, Jun Pang
2024Structured Video-Language Modeling with Temporal Grouping and Spatial Grounding.
Yuanhao Xiong, Long Zhao, Boqing Gong, Ming-Hsuan Yang, Florian Schroff, Ting Liu, Cho-Jui Hsieh, Liangzhe Yuan
2024Structuring Representation Geometry with Rotationally Equivariant Contrastive Learning.
Sharut Gupta, Joshua Robinson, Derek Lim, Soledad Villar, Stefanie Jegelka
2024Stylized Offline Reinforcement Learning: Extracting Diverse High-Quality Behaviors from Heterogeneous Datasets.
Yihuan Mao, Chengjie Wu, Xi Chen, Hao Hu, Ji Jiang, Tianze Zhou, Tangjie Lv, Changjie Fan, Zhipeng Hu, Yi Wu, Yujing Hu, Chongjie Zhang
2024SuRe: Summarizing Retrievals using Answer Candidates for Open-domain QA of LLMs.
Jaehyung Kim, Jaehyun Nam, Sangwoo Mo, Jongjin Park, Sang-Woo Lee, Minjoon Seo, Jung-Woo Ha, Jinwoo Shin
2024Submodular Reinforcement Learning.
Manish Prajapat, Mojmir Mutny, Melanie N. Zeilinger, Andreas Krause
2024Subtractive Mixture Models via Squaring: Representation and Learning.
Lorenzo Loconte, Aleksanteri M. Sladek, Stefan Mengel, Martin Trapp, Arno Solin, Nicolas Gillis, Antonio Vergari
2024Successor Heads: Recurring, Interpretable Attention Heads In The Wild.
Rhys Gould, Euan Ong, George Ogden, Arthur Conmy
2024Sudden Drops in the Loss: Syntax Acquisition, Phase Transitions, and Simplicity Bias in MLMs.
Angelica Chen, Ravid Shwartz-Ziv, Kyunghyun Cho, Matthew L. Leavitt, Naomi Saphra
2024Sufficient conditions for offline reactivation in recurrent neural networks.
Nanda H. Krishna, Colin Bredenberg, Daniel Levenstein, Blake Aaron Richards, Guillaume Lajoie
2024Sum-Product-Set Networks: Deep Tractable Models for Tree-Structured Graphs.
Milan Papez, Martin Rektoris, Václav Smídl, Tomás Pevný
2024Supervised Knowledge Makes Large Language Models Better In-context Learners.
Linyi Yang, Shuibai Zhang, Zhuohao Yu, Guangsheng Bao, Yidong Wang, Jindong Wang, Ruochen Xu, Wei Ye, Xing Xie, Weizhu Chen, Yue Zhang
2024SweetDreamer: Aligning Geometric Priors in 2D diffusion for Consistent Text-to-3D.
Weiyu Li, Rui Chen, Xuelin Chen, Ping Tan
2024Symbol as Points: Panoptic Symbol Spotting via Point-based Representation.
Wenlong Liu, Tianyu Yang, Yuhan Wang, Qizhi Yu, Lei Zhang
2024Symmetric Basis Convolutions for Learning Lagrangian Fluid Mechanics.
Rene Winchenbach, Nils Thuerey
2024Symmetric Mean-field Langevin Dynamics for Distributional Minimax Problems.
Juno Kim, Kakei Yamamoto, Kazusato Oko, Zhuoran Yang, Taiji Suzuki
2024Symmetric Neural-Collapse Representations with Supervised Contrastive Loss: The Impact of ReLU and Batching.
Ganesh Ramachandra Kini, Vala Vakilian, Tina Behnia, Jaidev Gill, Christos Thrampoulidis
2024Symmetric Single Index Learning.
Aaron Zweig, Joan Bruna
2024Symphony: Symmetry-Equivariant Point-Centered Spherical Harmonics for 3D Molecule Generation.
Ameya Daigavane, Song Kim, Mario Geiger, Tess E. Smidt
2024Synapse: Trajectory-as-Exemplar Prompting with Memory for Computer Control.
Longtao Zheng, Rundong Wang, Xinrun Wang, Bo An
2024Synaptic Weight Distributions Depend on the Geometry of Plasticity.
Roman Pogodin, Jonathan Cornford, Arna Ghosh, Gauthier Gidel, Guillaume Lajoie, Blake Aaron Richards
2024SyncDreamer: Generating Multiview-consistent Images from a Single-view Image.
Yuan Liu, Cheng Lin, Zijiao Zeng, Xiaoxiao Long, Lingjie Liu, Taku Komura, Wenping Wang
2024Synergistic Patch Pruning for Vision Transformer: Unifying Intra- & Inter-Layer Patch Importance.
Yuyao Zhang, Lan Wei, Nikolaos M. Freris
2024T-MARS: Improving Visual Representations by Circumventing Text Feature Learning.
Pratyush Maini, Sachin Goyal, Zachary Chase Lipton, J. Zico Kolter, Aditi Raghunathan
2024T-Rep: Representation Learning for Time Series using Time-Embeddings.
Archibald Fraikin, Adrien Bennetot, Stéphanie Allassonnière
2024TAB: Temporal Accumulated Batch Normalization in Spiking Neural Networks.
Haiyan Jiang, Vincent Zoonekynd, Giulia De Masi, Bin Gu, Huan Xiong
2024TACTiS-2: Better, Faster, Simpler Attentional Copulas for Multivariate Time Series.
Arjun Ashok, Étienne Marcotte, Valentina Zantedeschi, Nicolas Chapados, Alexandre Drouin
2024TAIL: Task-specific Adapters for Imitation Learning with Large Pretrained Models.
Zuxin Liu, Jesse Zhang, Kavosh Asadi, Yao Liu, Ding Zhao, Shoham Sabach, Rasool Fakoor
2024TD-MPC2: Scalable, Robust World Models for Continuous Control.
Nicklas Hansen, Hao Su, Xiaolong Wang
2024TEDDY: Trimming Edges with Degree-based Discrimination Strategy.
Hyunjin Seo, Jihun Yun, Eunho Yang
2024TEMPO: Prompt-based Generative Pre-trained Transformer for Time Series Forecasting.
Defu Cao, Furong Jia, Sercan Ö. Arik, Tomas Pfister, Yixiang Zheng, Wen Ye, Yan Liu
2024TEST: Text Prototype Aligned Embedding to Activate LLM's Ability for Time Series.
Chenxi Sun, Hongyan Li, Yaliang Li, Shenda Hong
2024TESTAM: A Time-Enhanced Spatio-Temporal Attention Model with Mixture of Experts.
Hyunwook Lee, Sungahn Ko
2024TOSS: High-quality Text-guided Novel View Synthesis from a Single Image.
Yukai Shi, Jianan Wang, He Cao, Boshi Tang, Xianbiao Qi, Tianyu Yang, Yukun Huang, Shilong Liu, Lei Zhang, Heung-Yeung Shum
2024TRAM: Bridging Trust Regions and Sharpness Aware Minimization.
Tom Sherborne, Naomi Saphra, Pradeep Dasigi, Hao Peng
2024TUVF: Learning Generalizable Texture UV Radiance Fields.
An-Chieh Cheng, Xueting Li, Sifei Liu, Xiaolong Wang
2024TabR: Tabular Deep Learning Meets Nearest Neighbors.
Yury Gorishniy, Ivan Rubachev, Nikolay Kartashev, Daniil Shlenskii, Akim Kotelnikov, Artem Babenko
2024Tackling the Data Heterogeneity in Asynchronous Federated Learning with Cached Update Calibration.
Yujia Wang, Yuanpu Cao, Jingcheng Wu, Ruoyu Chen, Jinghui Chen
2024Tag2Text: Guiding Vision-Language Model via Image Tagging.
Xinyu Huang, Youcai Zhang, Jinyu Ma, Weiwei Tian, Rui Feng, Yuejie Zhang, Yaqian Li, Yandong Guo, Lei Zhang
2024Tailoring Self-Rationalizers with Multi-Reward Distillation.
Sahana Ramnath, Brihi Joshi, Skyler Hallinan, Ximing Lu, Liunian Harold Li, Aaron Chan, Jack Hessel, Yejin Choi, Xiang Ren
2024Take a Step Back: Evoking Reasoning via Abstraction in Large Language Models.
Huaixiu Steven Zheng, Swaroop Mishra, Xinyun Chen, Heng-Tze Cheng, Ed H. Chi, Quoc V. Le, Denny Zhou
2024Talk like a Graph: Encoding Graphs for Large Language Models.
Bahare Fatemi, Jonathan Halcrow, Bryan Perozzi
2024Tangent Transformers for Composition, Privacy and Removal.
Tian Yu Liu, Aditya Golatkar, Stefano Soatto
2024TapMo: Shape-aware Motion Generation of Skeleton-free Characters.
Jiaxu Zhang, Shaoli Huang, Zhigang Tu, Xin Chen, Xiaohang Zhan, Gang Yu, Ying Shan
2024Task Adaptation from Skills: Information Geometry, Disentanglement, and New Objectives for Unsupervised Reinforcement Learning.
Yucheng Yang, Tianyi Zhou, Qiang He, Lei Han, Mykola Pechenizkiy, Meng Fang
2024Task Planning for Visual Room Rearrangement under Partial Observability.
Karan Mirakhor, Sourav Ghosh, Dipanjan Das, Brojeshwar Bhowmick
2024Task structure and nonlinearity jointly determine learned representational geometry.
Matteo Alleman, Jack W. Lindsey, Stefano Fusi
2024Teach LLMs to Phish: Stealing Private Information from Language Models.
Ashwinee Panda, Christopher A. Choquette-Choo, Zhengming Zhang, Yaoqing Yang, Prateek Mittal
2024Teaching Arithmetic to Small Transformers.
Nayoung Lee, Kartik Sreenivasan, Jason D. Lee, Kangwook Lee, Dimitris Papailiopoulos
2024Teaching Language Models to Hallucinate Less with Synthetic Tasks.
Erik Jones, Hamid Palangi, Clarisse Simões, Varun Chandrasekaran, Subhabrata Mukherjee, Arindam Mitra, Ahmed Hassan Awadallah, Ece Kamar
2024Teaching Large Language Models to Self-Debug.
Xinyun Chen, Maxwell Lin, Nathanael Schärli, Denny Zhou
2024Tell Your Model Where to Attend: Post-hoc Attention Steering for LLMs.
Qingru Zhang, Chandan Singh, Liyuan Liu, Xiaodong Liu, Bin Yu, Jianfeng Gao, Tuo Zhao
2024Temporal Generalization Estimation in Evolving Graphs.
Bin Lu, Tingyan Ma, Xiaoying Gan, Xinbing Wang, Yunqiang Zhu, Chenghu Zhou, Shiyu Liang
2024Tensor Programs VI: Feature Learning in Infinite Depth Neural Networks.
Greg Yang, Dingli Yu, Chen Zhu, Soufiane Hayou
2024Tensor Trust: Interpretable Prompt Injection Attacks from an Online Game.
Sam Toyer, Olivia Watkins, Ethan Adrian Mendes, Justin Svegliato, Luke Bailey, Tiffany Wang, Isaac Ong, Karim Elmaaroufi, Pieter Abbeel, Trevor Darrell, Alan Ritter, Stuart Russell
2024Test-Time Adaptation with CLIP Reward for Zero-Shot Generalization in Vision-Language Models.
Shuai Zhao, Xiaohan Wang, Linchao Zhu, Yi Yang
2024Test-Time Training on Nearest Neighbors for Large Language Models.
Moritz Hardt, Yu Sun
2024Test-time Adaptation against Multi-modal Reliability Bias.
Mouxing Yang, Yunfan Li, Changqing Zhang, Peng Hu, Xi Peng
2024Text-to-3D with Classifier Score Distillation.
Xin Yu, Yuan-Chen Guo, Yangguang Li, Ding Liang, Song-Hai Zhang, Xiaojuan Qi
2024Text2Reward: Reward Shaping with Language Models for Reinforcement Learning.
Tianbao Xie, Siheng Zhao, Chen Henry Wu, Yitao Liu, Qian Luo, Victor Zhong, Yanchao Yang, Tao Yu
2024TextField3D: Towards Enhancing Open-Vocabulary 3D Generation with Noisy Text Fields.
Tianyu Huang, Yihan Zeng, Bowen Dong, Hang Xu, Songcen Xu, Rynson W. H. Lau, Wangmeng Zuo
2024The Alignment Problem from a Deep Learning Perspective.
Richard Ngo, Lawrence Chan, Sören Mindermann
2024The All-Seeing Project: Towards Panoptic Visual Recognition and Understanding of the Open World.
Weiyun Wang, Min Shi, Qingyun Li, Wenhai Wang, Zhenhang Huang, Linjie Xing, Zhe Chen, Hao Li, Xizhou Zhu, Zhiguo Cao, Yushi Chen, Tong Lu, Jifeng Dai, Yu Qiao
2024The Blessing of Randomness: SDE Beats ODE in General Diffusion-based Image Editing.
Shen Nie, Hanzhong Allan Guo, Cheng Lu, Yuhao Zhou, Chenyu Zheng, Chongxuan Li
2024The Consensus Game: Language Model Generation via Equilibrium Search.
Athul Paul Jacob, Yikang Shen, Gabriele Farina, Jacob Andreas
2024The Cost of Scaling Down Large Language Models: Reducing Model Size Affects Memory before In-context Learning.
Tian Jin, Nolan Clement, Xin Dong, Vaishnavh Nagarajan, Michael Carbin, Jonathan Ragan-Kelley, Gintare Karolina Dziugaite
2024The Curse of Diversity in Ensemble-Based Exploration.
Zhixuan Lin, Pierluca D'Oro, Evgenii Nikishin, Aaron C. Courville
2024The Devil is in the Neurons: Interpreting and Mitigating Social Biases in Language Models.
Yan Liu, Yu Liu, Xiaokang Chen, Pin-Yu Chen, Daoguang Zan, Min-Yen Kan, Tsung-Yi Ho
2024The Devil is in the Object Boundary: Towards Annotation-free Instance Segmentation using Foundation Models.
Cheng Shi, Sibei Yang
2024The Effect of Intrinsic Dataset Properties on Generalization: Unraveling Learning Differences Between Natural and Medical Images.
Nicholas Konz, Maciej A. Mazurowski
2024The Effective Horizon Explains Deep RL Performance in Stochastic Environments.
Cassidy Laidlaw, Banghua Zhu, Stuart Russell, Anca D. Dragan
2024The Effectiveness of Random Forgetting for Robust Generalization.
Vijaya Raghavan T. Ramkumar, Bahram Zonooz, Elahe Arani
2024The Expressive Leaky Memory Neuron: an Efficient and Expressive Phenomenological Neuron Model Can Solve Long-Horizon Tasks.
Aaron Spieler, Nasim Rahaman, Georg Martius, Bernhard Schölkopf, Anna Levina
2024The Expressive Power of Low-Rank Adaptation.
Yuchen Zeng, Kangwook Lee
2024The Expressive Power of Transformers with Chain of Thought.
William Merrill, Ashish Sabharwal
2024The False Promise of Imitating Proprietary Language Models.
Arnav Gudibande, Eric Wallace, Charlie Snell, Xinyang Geng, Hao Liu, Pieter Abbeel, Sergey Levine, Dawn Song
2024The Generalization Gap in Offline Reinforcement Learning.
Ishita Mediratta, Qingfei You, Minqi Jiang, Roberta Raileanu
2024The Generative AI Paradox: "What It Can Create, It May Not Understand".
Peter West, Ximing Lu, Nouha Dziri, Faeze Brahman, Linjie Li, Jena D. Hwang, Liwei Jiang, Jillian Fisher, Abhilasha Ravichander, Khyathi Raghavi Chandu, Benjamin Newman, Pang Wei Koh, Allyson Ettinger, Yejin Choi
2024The Hedgehog & the Porcupine: Expressive Linear Attentions with Softmax Mimicry.
Michael Zhang, Kush Bhatia, Hermann Kumbong, Christopher Ré
2024The Hidden Language of Diffusion Models.
Hila Chefer, Oran Lang, Mor Geva, Volodymyr Polosukhin, Assaf Shocher, Michal Irani, Inbar Mosseri, Lior Wolf
2024The Human-AI Substitution game: active learning from a strategic labeler.
Tom Yan, Chicheng Zhang
2024The Joint Effect of Task Similarity and Overparameterization on Catastrophic Forgetting - An Analytical Model.
Daniel Goldfarb, Itay Evron, Nir Weinberger, Daniel Soudry, Paul Hand
2024The LLM Surgeon.
Tycho F. A. van der Ouderaa, Markus Nagel, Mart van Baalen, Tijmen Blankevoort
2024The Lipschitz-Variance-Margin Tradeoff for Enhanced Randomized Smoothing.
Blaise Delattre, Alexandre Araujo, Quentin Barthélemy, Alexandre Allauzen
2024The Marginal Value of Momentum for Small Learning Rate SGD.
Runzhe Wang, Sadhika Malladi, Tianhao Wang, Kaifeng Lyu, Zhiyuan Li
2024The Need for Speed: Pruning Transformers with One Recipe.
Samir Khaki, Konstantinos N. Plataniotis
2024The Reasonableness Behind Unreasonable Translation Capability of Large Language Model.
Tingchen Fu, Lemao Liu, Deng Cai, Guoping Huang, Shuming Shi, Rui Yan
2024The Reversal Curse: LLMs trained on "A is B" fail to learn "B is A".
Lukas Berglund, Meg Tong, Maximilian Kaufmann, Mikita Balesni, Asa Cooper Stickland, Tomasz Korbak, Owain Evans
2024The Trickle-down Impact of Reward Inconsistency on RLHF.
Lingfeng Shen, Sihao Chen, Linfeng Song, Lifeng Jin, Baolin Peng, Haitao Mi, Daniel Khashabi, Dong Yu
2024The Truth is in There: Improving Reasoning in Language Models with Layer-Selective Rank Reduction.
Pratyusha Sharma, Jordan T. Ash, Dipendra Misra
2024The Twelfth International Conference on Learning Representations, ICLR 2024, Vienna, Austria, May 7-11, 2024
2024The Unlocking Spell on Base LLMs: Rethinking Alignment via In-Context Learning.
Bill Yuchen Lin, Abhilasha Ravichander, Ximing Lu, Nouha Dziri, Melanie Sclar, Khyathi Raghavi Chandu, Chandra Bhagavatula, Yejin Choi
2024The Unreasonable Effectiveness of Linear Prediction as a Perceptual Metric.
Daniel Severo, Lucas Theis, Johannes Ballé
2024The Update-Equivalence Framework for Decision-Time Planning.
Samuel Sokota, Gabriele Farina, David J. Wu, Hengyuan Hu, Kevin A. Wang, J. Zico Kolter, Noam Brown
2024The Wasserstein Believer: Learning Belief Updates for Partially Observable Environments through Reliable Latent Space Models.
Raphaël Avalos, Florent Delgrange, Ann Nowé, Guillermo A. Pérez, Diederik M. Roijers
2024The importance of feature preprocessing for differentially private linear optimization.
Ziteng Sun, Ananda Theertha Suresh, Aditya Krishna Menon
2024The mechanistic basis of data dependence and abrupt learning in an in-context classification task.
Gautam Reddy
2024The optimality of kernel classifiers in Sobolev space.
Jianfa Lai, Zhifan Li, Dongming Huang, Qian Lin
2024Theoretical Analysis of Robust Overfitting for Wide DNNs: An NTK Approach.
Shaopeng Fu, Di Wang
2024Theoretical Understanding of Learning from Adversarial Perturbations.
Soichiro Kumano, Hiroshi Kera, Toshihiko Yamasaki
2024Thin-Shell Object Manipulations With Differentiable Physics Simulations.
Yian Wang, Juntian Zheng, Zhehuan Chen, Zhou Xian, Gu Zhang, Chao Liu, Chuang Gan
2024Think before you speak: Training Language Models With Pause Tokens.
Sachin Goyal, Ziwei Ji, Ankit Singh Rawat, Aditya Krishna Menon, Sanjiv Kumar, Vaishnavh Nagarajan
2024Think-on-Graph: Deep and Responsible Reasoning of Large Language Model on Knowledge Graph.
Jiashuo Sun, Chengjin Xu, Lumingyuan Tang, Saizhuo Wang, Chen Lin, Yeyun Gong, Lionel M. Ni, Heung-Yeung Shum, Jian Guo
2024Thought Propagation: an Analogical Approach to Complex Reasoning with Large Language Models.
Junchi Yu, Ran He, Zhitao Ying
2024Threaten Spiking Neural Networks through Combining Rate and Temporal Information.
Zecheng Hao, Tong Bu, Xinyu Shi, Zihan Huang, Zhaofei Yu, Tiejun Huang
2024Threshold-Consistent Margin Loss for Open-World Deep Metric Learning.
Qin Zhang, Linghan Xu, Jun Fang, Qingming Tang, Ying Nian Wu, Joseph Tighe, Yifan Xing
2024TiC-CLIP: Continual Training of CLIP Models.
Saurabh Garg, Mehrdad Farajtabar, Hadi Pouransari, Raviteja Vemulapalli, Sachin Mehta, Oncel Tuzel, Vaishaal Shankar, Fartash Faghri
2024Tight Rates in Supervised Outlier Transfer Learning.
Mohammadreza M. Kalan, Samory Kpotufe
2024Time Fairness in Online Knapsack Problems.
Adam Lechowicz, Rik Sengupta, Bo Sun, Shahin Kamali, Mohammad Hajiesmaili
2024Time Travel in LLMs: Tracing Data Contamination in Large Language Models.
Shahriar Golchin, Mihai Surdeanu
2024Time-Efficient Reinforcement Learning with Stochastic Stateful Policies.
Firas Al-Hafez, Guoping Zhao, Jan Peters, Davide Tateo
2024Time-LLM: Time Series Forecasting by Reprogramming Large Language Models.
Ming Jin, Shiyu Wang, Lintao Ma, Zhixuan Chu, James Y. Zhang, Xiaoming Shi, Pin-Yu Chen, Yuxuan Liang, Yuan-Fang Li, Shirui Pan, Qingsong Wen
2024Time-Varying Propensity Score to Bridge the Gap between the Past and Present.
Rasool Fakoor, Jonas Mueller, Zachary Chase Lipton, Pratik Chaudhari, Alex Smola
2024TimeMixer: Decomposable Multiscale Mixing for Time Series Forecasting.
Shiyu Wang, Haixu Wu, Xiaoming Shi, Tengge Hu, Huakun Luo, Lintao Ma, James Y. Zhang, Jun Zhou
2024To Grok or not to Grok: Disentangling Generalization and Memorization on Corrupted Algorithmic Datasets.
Darshil Doshi, Aritra Das, Tianyu He, Andrey Gromov
2024To the Cutoff... and Beyond? A Longitudinal Perspective on LLM Data Contamination.
Manley Roberts, Himanshu Thakur, Christine Herlihy, Colin White, Samuel Dooley
2024ToRA: A Tool-Integrated Reasoning Agent for Mathematical Problem Solving.
Zhibin Gou, Zhihong Shao, Yeyun Gong, Yelong Shen, Yujiu Yang, Minlie Huang, Nan Duan, Weizhu Chen
2024TokenFlow: Consistent Diffusion Features for Consistent Video Editing.
Michal Geyer, Omer Bar-Tal, Shai Bagon, Tali Dekel
2024Tool-Augmented Reward Modeling.
Lei Li, Yekun Chai, Shuohuan Wang, Yu Sun, Hao Tian, Ningyu Zhang, Hua Wu
2024ToolChain*: Efficient Action Space Navigation in Large Language Models with A* Search.
Yuchen Zhuang, Xiang Chen, Tong Yu, Saayan Mitra, Victor S. Bursztyn, Ryan A. Rossi, Somdeb Sarkhel, Chao Zhang
2024ToolLLM: Facilitating Large Language Models to Master 16000+ Real-world APIs.
Yujia Qin, Shihao Liang, Yining Ye, Kunlun Zhu, Lan Yan, Yaxi Lu, Yankai Lin, Xin Cong, Xiangru Tang, Bill Qian, Sihan Zhao, Lauren Hong, Runchu Tian, Ruobing Xie, Jie Zhou, Mark Gerstein, Dahai Li, Zhiyuan Liu, Maosong Sun
2024Topic Modeling as Multi-Objective Contrastive Optimization.
Thong Thanh Nguyen, Xiaobao Wu, Xinshuai Dong, Cong-Duy T. Nguyen, See-Kiong Ng, Anh Tuan Luu
2024TopoMLP: A Simple yet Strong Pipeline for Driving Topology Reasoning.
Dongming Wu, Jiahao Chang, Fan Jia, Yingfei Liu, Tiancai Wang, Jianbing Shen
2024Topological data analysis on noisy quantum computers.
Ismail Yunus Akhalwaya, Shashanka Ubaru, Kenneth L. Clarkson, Mark S. Squillante, Vishnu Jejjala, Yang-Hui He, Kugendran Naidoo, Vasileios Kalantzis, Lior Horesh
2024TorchRL: A data-driven decision-making library for PyTorch.
Albert Bou, Matteo Bettini, Sebastian Dittert, Vikash Kumar, Shagun Sodhani, Xiaomeng Yang, Gianni De Fabritiis, Vincent Moens
2024Toward Optimal Policy Population Growth in Two-Player Zero-Sum Games.
Stephen Marcus McAleer, JB Lanier, Kevin A. Wang, Pierre Baldi, Tuomas Sandholm, Roy Fox
2024Toward Student-oriented Teacher Network Training for Knowledge Distillation.
Chengyu Dong, Liyuan Liu, Jingbo Shang
2024Toward effective protection against diffusion-based mimicry through score distillation.
Haotian Xue, Chumeng Liang, Xiaoyu Wu, Yongxin Chen
2024Towards 3D Molecule-Text Interpretation in Language Models.
Sihang Li, Zhiyuan Liu, Yanchen Luo, Xiang Wang, Xiangnan He, Kenji Kawaguchi, Tat-Seng Chua, Qi Tian
2024Towards Aligned Layout Generation via Diffusion Model with Aesthetic Constraints.
Jian Chen, Ruiyi Zhang, Yufan Zhou, Changyou Chen
2024Towards Assessing and Benchmarking Risk-Return Tradeoff of Off-Policy Evaluation.
Haruka Kiyohara, Ren Kishimoto, Kosuke Kawakami, Ken Kobayashi, Kazuhide Nakata, Yuta Saito
2024Towards Best Practices of Activation Patching in Language Models: Metrics and Methods.
Fred Zhang, Neel Nanda
2024Towards Category Unification of 3D Single Object Tracking on Point Clouds.
Jiahao Nie, Zhiwei He, Xudong Lv, Xueyi Zhou, Dong-Kyu Chae, Fei Xie
2024Towards Characterizing Domain Counterfactuals for Invertible Latent Causal Models.
Zeyu Zhou, Ruqi Bai, Sean Kulinski, Murat Kocaoglu, David I. Inouye
2024Towards Cheaper Inference in Deep Networks with Lower Bit-Width Accumulators.
Yaniv Blumenfeld, Itay Hubara, Daniel Soudry
2024Towards Codable Watermarking for Injecting Multi-Bits Information to LLMs.
Lean Wang, Wenkai Yang, Deli Chen, Hao Zhou, Yankai Lin, Fandong Meng, Jie Zhou, Xu Sun
2024Towards Cross Domain Generalization of Hamiltonian Representation via Meta Learning.
Yeongwoo Song, Hawoong Jeong
2024Towards Diverse Behaviors: A Benchmark for Imitation Learning with Human Demonstrations.
Xiaogang Jia, Denis Blessing, Xinkai Jiang, Moritz Reuss, Atalay Donat, Rudolf Lioutikov, Gerhard Neumann
2024Towards Eliminating Hard Label Constraints in Gradient Inversion Attacks.
Yanbo Wang, Jian Liang, Ran He
2024Towards Energy Efficient Spiking Neural Networks: An Unstructured Pruning Framework.
Xinyu Shi, Jianhao Ding, Zecheng Hao, Zhaofei Yu
2024Towards Enhancing Time Series Contrastive Learning: A Dynamic Bad Pair Mining Approach.
Xiang Lan, Hanshu Yan, Shenda Hong, Mengling Feng
2024Towards Establishing Guaranteed Error for Learned Database Operations.
Sepanta Zeighami, Cyrus Shahabi
2024Towards Faithful Explanations: Boosting Rationalization with Shortcuts Discovery.
Linan Yue, Qi Liu, Yichao Du, Li Wang, Weibo Gao, Yanqing An
2024Towards Faithful XAI Evaluation via Generalization-Limited Backdoor Watermark.
Mengxi Ya, Yiming Li, Tao Dai, Bin Wang, Yong Jiang, Shu-Tao Xia
2024Towards Few-Shot Adaptation of Foundation Models via Multitask Finetuning.
Zhuoyan Xu, Zhenmei Shi, Junyi Wei, Fangzhou Mu, Yin Li, Yingyu Liang
2024Towards Foundation Models for Knowledge Graph Reasoning.
Mikhail Galkin, Xinyu Yuan, Hesham Mostafa, Jian Tang, Zhaocheng Zhu
2024Towards Foundational Models for Molecular Learning on Large-Scale Multi-Task Datasets.
Dominique Beaini, Shenyang Huang, Joao Alex Cunha, Zhiyi Li, Gabriela Moisescu-Pareja, Oleksandr Dymov, Samuel Maddrell-Mander, Callum McLean, Frederik Wenkel, Luis Müller, Jama Hussein Mohamud, Ali Parviz, Michael Craig, Michal Koziarski, Jiarui Lu, Zhaocheng Zhu, Cristian Gabellini, Kerstin Klaser, Josef Dean, Cas Wognum, Maciej Sypetkowski, Guillaume Rabusseau, Reihaneh Rabbany, Jian Tang, Christopher Morris, Mirco Ravanelli, Guy Wolf, Prudencio Tossou, Hadrien Mary, Therence Bois, Andrew W. Fitzgibbon, Blazej Banaszewski, Chad Martin, Dominic Masters
2024Towards Generative Abstract Reasoning: Completing Raven's Progressive Matrix via Rule Abstraction and Selection.
Fan Shi, Bin Li, Xiangyang Xue
2024Towards Green AI in Fine-tuning Large Language Models via Adaptive Backpropagation.
Kai Huang, Hanyun Yin, Heng Huang, Wei Gao
2024Towards Identifiable Unsupervised Domain Translation: A Diversified Distribution Matching Approach.
Sagar Shrestha, Xiao Fu
2024Towards Imitation Learning to Branch for MIP: A Hybrid Reinforcement Learning based Sample Augmentation Approach.
Changwen Zhang, Wenli Ouyang, Hao Yuan, Liming Gong, Yong Sun, Ziao Guo, Zhichen Dong, Junchi Yan
2024Towards LLM4QPE: Unsupervised Pretraining of Quantum Property Estimation and A Benchmark.
Yehui Tang, Hao Xiong, Nianzu Yang, Tailong Xiao, Junchi Yan
2024Towards Lossless Dataset Distillation via Difficulty-Aligned Trajectory Matching.
Ziyao Guo, Kai Wang, George Cazenavette, Hui Li, Kaipeng Zhang, Yang You
2024Towards Meta-Pruning via Optimal Transport.
Alexander Theus, Olin Geimer, Friedrich Wicke, Thomas Hofmann, Sotiris Anagnostidis, Sidak Pal Singh
2024Towards Non-Asymptotic Convergence for Diffusion-Based Generative Models.
Gen Li, Yuting Wei, Yuxin Chen, Yuejie Chi
2024Towards Offline Opponent Modeling with In-context Learning.
Yuheng Jing, Kai Li, Bingyun Liu, Yifan Zang, Haobo Fu, Qiang Fu, Junliang Xing, Jian Cheng
2024Towards Optimal Feature-Shaping Methods for Out-of-Distribution Detection.
Qinyu Zhao, Ming Xu, Kartik Gupta, Akshay Asthana, Liang Zheng, Stephen Gould
2024Towards Optimal Regret in Adversarial Linear MDPs with Bandit Feedback.
Haolin Liu, Chen-Yu Wei, Julian Zimmert
2024Towards Poisoning Fair Representations.
Tianci Liu, Haoyu Wang, Feijie Wu, Hengtong Zhang, Pan Li, Lu Su, Jing Gao
2024Towards Principled Representation Learning from Videos for Reinforcement Learning.
Dipendra Misra, Akanksha Saran, Tengyang Xie, Alex Lamb, John Langford
2024Towards Reliable and Efficient Backdoor Trigger Inversion via Decoupling Benign Features.
Xiong Xu, Kunzhe Huang, Yiming Li, Zhan Qin, Kui Ren
2024Towards Robust Fidelity for Evaluating Explainability of Graph Neural Networks.
Xu Zheng, Farhad Shirani, Tianchun Wang, Wei Cheng, Zhuomin Chen, Haifeng Chen, Hua Wei, Dongsheng Luo
2024Towards Robust Multi-Modal Reasoning via Model Selection.
Xiangyan Liu, Rongxue Li, Wei Ji, Tao Lin
2024Towards Robust Offline Reinforcement Learning under Diverse Data Corruption.
Rui Yang, Han Zhong, Jiawei Xu, Amy Zhang, Chongjie Zhang, Lei Han, Tong Zhang
2024Towards Robust Out-of-Distribution Generalization Bounds via Sharpness.
Yingtian Zou, Kenji Kawaguchi, Yingnan Liu, Jiashuo Liu, Mong-Li Lee, Wynne Hsu
2024Towards Robust and Efficient Cloud-Edge Elastic Model Adaptation via Selective Entropy Distillation.
Yaofo Chen, Shuaicheng Niu, Yaowei Wang, Shoukai Xu, Hengjie Song, Mingkui Tan
2024Towards Seamless Adaptation of Pre-trained Models for Visual Place Recognition.
Feng Lu, Lijun Zhang, Xiangyuan Lan, Shuting Dong, Yaowei Wang, Chun Yuan
2024Towards Training Without Depth Limits: Batch Normalization Without Gradient Explosion.
Alexandru Meterez, Amir Joudaki, Francesco Orabona, Alexander Immer, Gunnar Rätsch, Hadi Daneshmand
2024Towards Transparent Time Series Forecasting.
Krzysztof Kacprzyk, Tennison Liu, Mihaela van der Schaar
2024Towards Understanding Factual Knowledge of Large Language Models.
Xuming Hu, Junzhe Chen, Xiaochuan Li, Yufei Guo, Lijie Wen, Philip S. Yu, Zhijiang Guo
2024Towards Understanding Sycophancy in Language Models.
Mrinank Sharma, Meg Tong, Tomasz Korbak, David Duvenaud, Amanda Askell, Samuel R. Bowman, Esin Durmus, Zac Hatfield-Dodds, Scott R. Johnston, Shauna Kravec, Timothy Maxwell, Sam McCandlish, Kamal Ndousse, Oliver Rausch, Nicholas Schiefer, Da Yan, Miranda Zhang, Ethan Perez
2024Towards Unified Multi-Modal Personalization: Large Vision-Language Models for Generative Recommendation and Beyond.
Tianxin Wei, Bowen Jin, Ruirui Li, Hansi Zeng, Zhengyang Wang, Jianhui Sun, Qingyu Yin, Hanqing Lu, Suhang Wang, Jingrui He, Xianfeng Tang
2024Towards a statistical theory of data selection under weak supervision.
Germain Kolossov, Andrea Montanari, Pulkit Tandon
2024Towards domain-invariant Self-Supervised Learning with Batch Styles Standardization.
Marin Scalbert, Maria Vakalopoulou, Florent Couzinie-Devy
2024Towards image compression with perfect realism at ultra-low bitrates.
Marlène Careil, Matthew J. Muckley, Jakob Verbeek, Stéphane Lathuilière
2024Towards the Fundamental Limits of Knowledge Transfer over Finite Domains.
Qingyue Zhao, Banghua Zhu
2024Tractable MCMC for Private Learning with Pure and Gaussian Differential Privacy.
Yingyu Lin, Yian Ma, Yu-Xiang Wang, Rachel Redberg, Zhiqi Bu
2024Tractable Probabilistic Graph Representation Learning with Graph-Induced Sum-Product Networks.
Federico Errica, Mathias Niepert
2024Training Bayesian Neural Networks with Sparse Subspace Variational Inference.
Junbo Li, Zichen Miao, Qiang Qiu, Ruqi Zhang
2024Training Diffusion Models with Reinforcement Learning.
Kevin Black, Michael Janner, Yilun Du, Ilya Kostrikov, Sergey Levine
2024Training Graph Transformers via Curriculum-Enhanced Attention Distillation.
Yisong Huang, Jin Li, Xinlong Chen, Yang-Geng Fu
2024Training Socially Aligned Language Models on Simulated Social Interactions.
Ruibo Liu, Ruixin Yang, Chenyan Jia, Ge Zhang, Diyi Yang, Soroush Vosoughi
2024Training Unbiased Diffusion Models From Biased Dataset.
Yeongmin Kim, Byeonghu Na, Minsang Park, JoonHo Jang, Dongjun Kim, Wanmo Kang, Il-Chul Moon
2024Training-free Multi-objective Diffusion Model for 3D Molecule Generation.
Xu Han, Caihua Shan, Yifei Shen, Can Xu, Han Yang, Xiang Li, Dongsheng Li
2024Trajeglish: Traffic Modeling as Next-Token Prediction.
Jonah Philion, Xue Bin Peng, Sanja Fidler
2024Transferring Labels to Solve Annotation Mismatches Across Object Detection Datasets.
Yuan-Hong Liao, David Acuna, Rafid Mahmood, James Lucas, Viraj Prabhu, Sanja Fidler
2024Transferring Learning Trajectories of Neural Networks.
Daiki Chijiwa
2024Transformer Fusion with Optimal Transport.
Moritz Imfeld, Jacopo Graldi, Marco Giordano, Thomas Hofmann, Sotiris Anagnostidis, Sidak Pal Singh
2024Transformer-Modulated Diffusion Models for Probabilistic Multivariate Time Series Forecasting.
Yuxin Li, Wenchao Chen, Xinyue Hu, Bo Chen, Baolin Sun, Mingyuan Zhou
2024Transformer-VQ: Linear-Time Transformers via Vector Quantization.
Lucas D. Lingle
2024Transformers as Decision Makers: Provable In-Context Reinforcement Learning via Supervised Pretraining.
Licong Lin, Yu Bai, Song Mei
2024Transformers can optimally learn regression mixture models.
Reese Pathak, Rajat Sen, Weihao Kong, Abhimanyu Das
2024Transport meets Variational Inference: Controlled Monte Carlo Diffusions.
Francisco Vargas, Shreyas Padhy, Denis Blessing, Nikolas Nüsken
2024Traveling Waves Encode The Recent Past and Enhance Sequence Learning.
T. Anderson Keller, Lyle Muller, Terrence J. Sejnowski, Max Welling
2024Treatment Effects Estimation By Uniform Transformer.
Ruoqi Yu, Shulei Wang
2024Tree Cross Attention.
Leo Feng, Frederick Tung, Hossein Hajimirsadeghi, Yoshua Bengio, Mohamed Osama Ahmed
2024Tree Search-Based Policy Optimization under Stochastic Execution Delay.
David Valensi, Esther Derman, Shie Mannor, Gal Dalal
2024Tree-Planner: Efficient Close-loop Task Planning with Large Language Models.
Mengkang Hu, Yao Mu, Xinmiao Yu, Mingyu Ding, Shiguang Wu, Wenqi Shao, Qiguang Chen, Bin Wang, Yu Qiao, Ping Luo
2024True Knowledge Comes from Practice: Aligning Large Language Models with Embodied Environments via Reinforcement Learning.
Weihao Tan, Wentao Zhang, Shanqi Liu, Longtao Zheng, Xinrun Wang, Bo An
2024Tuning LayerNorm in Attention: Towards Efficient Multi-Modal LLM Finetuning.
Bingchen Zhao, Haoqin Tu, Chen Wei, Jieru Mei, Cihang Xie
2024Turning large language models into cognitive models.
Marcel Binz, Eric Schulz
2024Two-stage LLM Fine-tuning with Less Specialization and More Generalization.
Yihan Wang, Si Si, Daliang Li, Michal Lukasik, Felix X. Yu, Cho-Jui Hsieh, Inderjit S. Dhillon, Sanjiv Kumar
2024Two-timescale Extragradient for Finding Local Minimax Points.
Jiseok Chae, Kyuwon Kim, Donghwan Kim
2024UC-NERF: Neural Radiance Field for Under-Calibrated Multi-View Cameras in Autonomous Driving.
Kai Cheng, Xiaoxiao Long, Wei Yin, Jin Wang, Zhiqiang Wu, Yuexin Ma, Kaixuan Wang, Xiaozhi Chen, Xuejin Chen
2024UNR-Explainer: Counterfactual Explanations for Unsupervised Node Representation Learning Models.
Hyunju Kang, Geonhee Han, Hogun Park
2024USB-NeRF: Unrolling Shutter Bundle Adjusted Neural Radiance Fields.
Moyang Li, Peng Wang, Lingzhe Zhao, Bangyan Liao, Peidong Liu
2024Un-Mixing Test-Time Normalization Statistics: Combatting Label Temporal Correlation.
Devavrat Tomar, Guillaume Vray, Jean-Philippe Thiran, Behzad Bozorgtabar
2024Unbalancedness in Neural Monge Maps Improves Unpaired Domain Translation.
Luca Eyring, Dominik Klein, Théo Uscidda, Giovanni Palla, Niki Kilbertus, Zeynep Akata, Fabian J. Theis
2024Unbiased Watermark for Large Language Models.
Zhengmian Hu, Lichang Chen, Xidong Wu, Yihan Wu, Hongyang Zhang, Heng Huang
2024Uncertainty Quantification via Stable Distribution Propagation.
Felix Petersen, Aashwin Ananda Mishra, Hilde Kuehne, Christian Borgelt, Oliver Deussen, Mikhail Yurochkin
2024Uncertainty-aware Constraint Inference in Inverse Constrained Reinforcement Learning.
Sheng Xu, Guiliang Liu
2024Uncertainty-aware Graph-based Hyperspectral Image Classification.
Linlin Yu, Yifei Lou, Feng Chen
2024Unconstrained Stochastic CCA: Unifying Multiview and Self-Supervised Learning.
James Chapman, Lennie Wells, Ana Lawry Aguila
2024Understanding Addition in Transformers.
Philip Quirke, Fazl Barez
2024Understanding Augmentation-based Self-Supervised Representation Learning via RKHS Approximation and Regression.
Runtian Zhai, Bingbin Liu, Andrej Risteski, J. Zico Kolter, Pradeep Kumar Ravikumar
2024Understanding Catastrophic Forgetting in Language Models via Implicit Inference.
Suhas Kotha, Jacob Mitchell Springer, Aditi Raghunathan
2024Understanding Certified Training with Interval Bound Propagation.
Yuhao Mao, Mark Niklas Müller, Marc Fischer, Martin T. Vechev
2024Understanding Convergence and Generalization in Federated Learning through Feature Learning Theory.
Wei Huang, Ye Shi, Zhongyi Cai, Taiji Suzuki
2024Understanding Domain Generalization: A Noise Robustness Perspective.
Rui Qiao, Bryan Kian Hsiang Low
2024Understanding Expressivity of GNN in Rule Learning.
Haiquan Qiu, Yongqi Zhang, Yong Li, Quanming Yao
2024Understanding In-Context Learning from Repetitions.
Jianhao Yan, Jin Xu, Chiyu Song, Chenming Wu, Yafu Li, Yue Zhang
2024Understanding In-Context Learning in Transformers and LLMs by Learning to Learn Discrete Functions.
Satwik Bhattamishra, Arkil Patel, Phil Blunsom, Varun Kanade
2024Understanding Reconstruction Attacks with the Neural Tangent Kernel and Dataset Distillation.
Noel Loo, Ramin M. Hasani, Mathias Lechner, Alexander Amini, Daniela Rus
2024Understanding Transferable Representation Learning and Zero-shot Transfer in CLIP.
Zixiang Chen, Yihe Deng, Yuanzhi Li, Quanquan Gu
2024Understanding and Mitigating the Label Noise in Pre-training on Downstream Tasks.
Hao Chen, Jindong Wang, Ankit Shah, Ran Tao, Hongxin Wei, Xing Xie, Masashi Sugiyama, Bhiksha Raj
2024Understanding prompt engineering may not require rethinking generalization.
Victor Akinwande, Yiding Jiang, Dylan Sam, J. Zico Kolter
2024Understanding the Effects of RLHF on LLM Generalisation and Diversity.
Robert Kirk, Ishita Mediratta, Christoforos Nalmpantis, Jelena Luketina, Eric Hambro, Edward Grefenstette, Roberta Raileanu
2024Understanding the Robustness of Multi-modal Contrastive Learning to Distribution Shift.
Yihao Xue, Siddharth Joshi, Dang Nguyen, Baharan Mirzasoleiman
2024Understanding the Robustness of Randomized Feature Defense Against Query-Based Adversarial Attacks.
Nguyen Hung-Quang, Yingjie Lao, Tung Pham, Kok-Seng Wong, Khoa D. Doan
2024Understanding when Dynamics-Invariant Data Augmentations Benefit Model-free Reinforcement Learning Updates.
Nicholas Corrado, Josiah P. Hanna
2024Uni-O4: Unifying Online and Offline Deep Reinforcement Learning with Multi-Step On-Policy Optimization.
Kun Lei, Zhengmao He, Chenhao Lu, Kaizhe Hu, Yang Gao, Huazhe Xu
2024Uni-RLHF: Universal Platform and Benchmark Suite for Reinforcement Learning with Diverse Human Feedback.
Yifu Yuan, Jianye Hao, Yi Ma, Zibin Dong, Hebin Liang, Jinyi Liu, Zhixin Feng, Kai Zhao, Yan Zheng
2024Uni3D: Exploring Unified 3D Representation at Scale.
Junsheng Zhou, Jinsheng Wang, Baorui Ma, Yu-Shen Liu, Tiejun Huang, Xinlong Wang
2024UniAdapter: Unified Parameter-Efficient Transfer Learning for Cross-modal Modeling.
Haoyu Lu, Yuqi Huo, Guoxing Yang, Zhiwu Lu, Wei Zhan, Masayoshi Tomizuka, Mingyu Ding
2024UniTabE: A Universal Pretraining Protocol for Tabular Foundation Model in Data Science.
Yazheng Yang, Yuqi Wang, Guang Liu, Ledell Wu, Qi Liu
2024Unified Generative Modeling of 3D Molecules with Bayesian Flow Networks.
Yuxuan Song, Jingjing Gong, Hao Zhou, Mingyue Zheng, Jingjing Liu, Wei-Ying Ma
2024Unified Human-Scene Interaction via Prompted Chain-of-Contacts.
Zeqi Xiao, Tai Wang, Jingbo Wang, Jinkun Cao, Wenwei Zhang, Bo Dai, Dahua Lin, Jiangmiao Pang
2024Unified Language-Vision Pretraining in LLM with Dynamic Discrete Visual Tokenization.
Yang Jin, Kun Xu, Liwei Chen, Chao Liao, Jianchao Tan, Quzhe Huang, Bin Chen, Chengru Song, Dai Meng, Di Zhang, Wenwu Ou, Kun Gai, Yadong Mu
2024Unified Projection-Free Algorithms for Adversarial DR-Submodular Optimization.
Mohammad Pedramfar, Yididiya Y. Nadew, Christopher John Quinn, Vaneet Aggarwal
2024Unifying Feature and Cost Aggregation with Transformers for Semantic and Visual Correspondence.
Sunghwan Hong, Seokju Cho, Seungryong Kim, Stephen Lin
2024Universal Backdoor Attacks.
Benjamin Schneider, Nils Lukas, Florian Kerschbaum
2024Universal Guidance for Diffusion Models.
Arpit Bansal, Hong-Min Chu, Avi Schwarzschild, Soumyadip Sengupta, Micah Goldblum, Jonas Geiping, Tom Goldstein
2024Universal Humanoid Motion Representations for Physics-Based Control.
Zhengyi Luo, Jinkun Cao, Josh Merel, Alexander Winkler, Jing Huang, Kris M. Kitani, Weipeng Xu
2024Universal Jailbreak Backdoors from Poisoned Human Feedback.
Javier Rando, Florian Tramèr
2024UniversalNER: Targeted Distillation from Large Language Models for Open Named Entity Recognition.
Wenxuan Zhou, Sheng Zhang, Yu Gu, Muhao Chen, Hoifung Poon
2024Unknown Domain Inconsistency Minimization for Domain Generalization.
Seungjae Shin, HeeSun Bae, Byeonghu Na, Yoon-Yeong Kim, Il-Chul Moon
2024Unleashing Large-Scale Video Generative Pre-training for Visual Robot Manipulation.
Hongtao Wu, Ya Jing, Chilam Cheang, Guangzeng Chen, Jiafeng Xu, Xinghang Li, Minghuan Liu, Hang Li, Tao Kong
2024Unleashing the Potential of Fractional Calculus in Graph Neural Networks with FROND.
Qiyu Kang, Kai Zhao, Qinxu Ding, Feng Ji, Xuhao Li, Wenfei Liang, Yang Song, Wee Peng Tay
2024Unleashing the Power of Pre-trained Language Models for Offline Reinforcement Learning.
Ruizhe Shi, Yuyao Liu, Yanjie Ze, Simon Shaolei Du, Huazhe Xu
2024Unlocking the Power of Representations in Long-term Novelty-based Exploration.
Alaa Saade, Steven Kapturowski, Daniele Calandriello, Charles Blundell, Pablo Sprechmann, Leopoldo Sarra, Oliver Groth, Michal Valko, Bilal Piot
2024Unmasking and Improving Data Credibility: A Study with Datasets for Training Harmless Language Models.
Zhaowei Zhu, Jialu Wang, Hao Cheng, Yang Liu
2024Unpaired Image-to-Image Translation via Neural Schrödinger Bridge.
Beomsu Kim, Gihyun Kwon, Kwanyoung Kim, Jong Chul Ye
2024Unprocessing Seven Years of Algorithmic Fairness.
André F. Cruz, Moritz Hardt
2024Unraveling the Enigma of Double Descent: An In-depth Analysis through the Lens of Learned Feature Space.
Yufei Gu, Xiaoqing Zheng, Tomaso Aste
2024Unraveling the Key Components of OOD Generalization via Diversification.
Harold Benoit, Liangze Jiang, Andrei Atanov, Oguzhan Fatih Kar, Mattia Rigotti, Amir Zamir
2024Unsupervised Order Learning.
Seon-Ho Lee, Nyeong-Ho Shin, Chang-Su Kim
2024Unsupervised Pretraining for Fact Verification by Language Model Distillation.
Adrián Bazaga, Pietro Lio, Gos Micklem
2024Unveiling Options with Neural Network Decomposition.
Mahdi Alikhasi, Levi Lelis
2024Unveiling and Manipulating Prompt Influence in Large Language Models.
Zijian Feng, Hanzhang Zhou, Zixiao Zhu, Junlang Qian, Kezhi Mao
2024Unveiling the Pitfalls of Knowledge Editing for Large Language Models.
Zhoubo Li, Ningyu Zhang, Yunzhi Yao, Mengru Wang, Xi Chen, Huajun Chen
2024Unveiling the Unseen: Identifiable Clusters in Trained Depthwise Convolutional Kernels.
Zahra Babaiee, Peyman M. Kiasari, Daniela Rus, Radu Grosu
2024V-DETR: DETR with Vertex Relative Position Encoding for 3D Object Detection.
Yichao Shen, Zigang Geng, Yuhui Yuan, Yutong Lin, Ze Liu, Chunyu Wang, Han Hu, Nanning Zheng, Baining Guo
2024VBH-GNN: Variational Bayesian Heterogeneous Graph Neural Networks for Cross-subject Emotion Recognition.
Chenyu Liu, Xinliang Zhou, Zhengri Zhu, Liming Zhai, Ziyu Jia, Yang Liu
2024VCR-Graphormer: A Mini-batch Graph Transformer via Virtual Connections.
Dongqi Fu, Zhigang Hua, Yan Xie, Jin Fang, Si Zhang, Kaan Sancak, Hao Wu, Andrey Malevich, Jingrui He, Bo Long
2024VDC: Versatile Data Cleanser based on Visual-Linguistic Inconsistency by Multimodal Large Language Models.
Zihao Zhu, Mingda Zhang, Shaokui Wei, Bingzhe Wu, Baoyuan Wu
2024VDT: General-purpose Video Diffusion Transformers via Mask Modeling.
Haoyu Lu, Guoxing Yang, Nanyi Fei, Yuqi Huo, Zhiwu Lu, Ping Luo, Mingyu Ding
2024VFLAIR: A Research Library and Benchmark for Vertical Federated Learning.
Tianyuan Zou, Zixuan Gu, Yu He, Hideaki Takahashi, Yang Liu, Ya-Qin Zhang
2024VONet: Unsupervised Video Object Learning With Parallel U-Net Attention and Object-wise Sequential VAE.
Haonan Yu, Wei Xu
2024VQ-TR: Vector Quantized Attention for Time Series Forecasting.
Kashif Rasul, Andrew Bennett, Pablo Vicente, Umang Gupta, Hena Ghonia, Anderson Schneider, Yuriy Nevmyvaka
2024VQGraph: Rethinking Graph Representation Space for Bridging GNNs and MLPs.
Ling Yang, Ye Tian, Minkai Xu, Zhongyi Liu, Shenda Hong, Wei Qu, Wentao Zhang, Bin Cui, Muhan Zhang, Jure Leskovec
2024ValUES: A Framework for Systematic Validation of Uncertainty Estimation in Semantic Segmentation.
Kim-Celine Kahl, Carsten T. Lüth, Maximilian Zenk, Klaus H. Maier-Hein, Paul F. Jaeger
2024Vanishing Gradients in Reinforcement Finetuning of Language Models.
Noam Razin, Hattie Zhou, Omid Saremi, Vimal Thilak, Arwen Bradley, Preetum Nakkiran, Joshua M. Susskind, Etai Littwin
2024Variance Reduced Halpern Iteration for Finite-Sum Monotone Inclusions.
Xufeng Cai, Ahmet Alacaoglu, Jelena Diakonikolas
2024Variance-aware Regret Bounds for Stochastic Contextual Dueling Bandits.
Qiwei Di, Tao Jin, Yue Wu, Heyang Zhao, Farzad Farnoud, Quanquan Gu
2024Variance-enlarged Poisson Learning for Graph-based Semi-Supervised Learning with Extremely Sparse Labeled Data.
Xiong Zhou, Xianming Liu, Hao Yu, Jialiang Wang, Zeke Xie, Junjun Jiang, Xiangyang Ji
2024Variational Bayesian Last Layers.
James Harrison, John Willes, Jasper Snoek
2024Variational Inference for SDEs Driven by Fractional Noise.
Rembert Daems, Manfred Opper, Guillaume Crevecoeur, Tolga Birdal
2024VeRA: Vector-based Random Matrix Adaptation.
Dawid Jan Kopiczko, Tijmen Blankevoort, Yuki M. Asano
2024VersVideo: Leveraging Enhanced Temporal Diffusion Models for Versatile Video Generation.
Jinxi Xiang, Ricong Huang, Jun Zhang, Guanbin Li, Xiao Han, Yang Wei
2024VertiBench: Advancing Feature Distribution Diversity in Vertical Federated Learning Benchmarks.
Zhaomin Wu, Junyi Hou, Bingsheng He
2024ViDA: Homeostatic Visual Domain Adapter for Continual Test Time Adaptation.
Jiaming Liu, Senqiao Yang, Peidong Jia, Renrui Zhang, Ming Lu, Yandong Guo, Wei Xue, Shanghang Zhang
2024ViLMA: A Zero-Shot Benchmark for Linguistic and Temporal Grounding in Video-Language Models.
Ilker Kesen, Andrea Pedrotti, Mustafa Dogan, Michele Cafagna, Emre Can Acikgoz, Letitia Parcalabescu, Iacer Calixto, Anette Frank, Albert Gatt, Aykut Erdem, Erkut Erdem
2024Video Decomposition Prior: Editing Videos Layer by Layer.
Gaurav Shrivastava, Ser-Nam Lim, Abhinav Shrivastava
2024Video Language Planning.
Yilun Du, Sherry Yang, Pete Florence, Fei Xia, Ayzaan Wahid, Brian Ichter, Pierre Sermanet, Tianhe Yu, Pieter Abbeel, Joshua B. Tenenbaum, Leslie Pack Kaelbling, Andy Zeng, Jonathan Tompson
2024Views Can Be Deceiving: Improved SSL Through Feature Space Augmentation.
Kimia Hamidieh, Haoran Zhang, Swami Sankaranarayanan, Marzyeh Ghassemi
2024Vision Transformers Need Registers.
Timothée Darcet, Maxime Oquab, Julien Mairal, Piotr Bojanowski
2024Vision-Language Foundation Models as Effective Robot Imitators.
Xinghang Li, Minghuan Liu, Hanbo Zhang, Cunjun Yu, Jie Xu, Hongtao Wu, Chilam Cheang, Ya Jing, Weinan Zhang, Huaping Liu, Hang Li, Tao Kong
2024Vision-Language Models are Zero-Shot Reward Models for Reinforcement Learning.
Juan Rocamonde, Victoriano Montesinos, Elvis Nava, Ethan Perez, David Lindner
2024Vision-by-Language for Training-Free Compositional Image Retrieval.
Shyamgopal Karthik, Karsten Roth, Massimiliano Mancini, Zeynep Akata
2024Visual Data-Type Understanding does not emerge from scaling Vision-Language Models.
Vishaal Udandarao, Max F. Burg, Samuel Albanie, Matthias Bethge
2024Vocos: Closing the gap between time-domain and Fourier-based neural vocoders for high-quality audio synthesis.
Hubert Siuzdak
2024Waxing-and-Waning: a Generic Similarity-based Framework for Efficient Self-Supervised Learning.
Sheng Li, Chao Wu, Ao Li, Yanzhi Wang, Xulong Tang, Geng Yuan
2024Weaker MVI Condition: Extragradient Methods with Multi-Step Exploration.
Yifeng Fan, Yongqiang Li, Bo Chen
2024Weakly Supervised Virus Capsid Detection with Image-Level Annotations in Electron Microscopy Images.
Hannah Kniesel, Leon Sick, Tristan Payer, Tim Bergner, Kavitha Shaga Devan, Clarissa Read, Paul Walther, Timo Ropinski, Pedro Hermosilla
2024Weakly-supervised Audio Separation via Bi-modal Semantic Similarity.
Tanvir Mahmud, Saeed Amizadeh, Kazuhito Koishida, Diana Marculescu
2024Weatherproofing Retrieval for Localization with Generative AI and Geometric Consistency.
Yannis Kalantidis, Mert Bülent Sariyildiz, Rafael S. Rezende, Philippe Weinzaepfel, Diane Larlus, Gabriela Csurka
2024WebArena: A Realistic Web Environment for Building Autonomous Agents.
Shuyan Zhou, Frank F. Xu, Hao Zhu, Xuhui Zhou, Robert Lo, Abishek Sridhar, Xianyi Cheng, Tianyue Ou, Yonatan Bisk, Daniel Fried, Uri Alon, Graham Neubig
2024What Algorithms can Transformers Learn? A Study in Length Generalization.
Hattie Zhou, Arwen Bradley, Etai Littwin, Noam Razin, Omid Saremi, Joshua M. Susskind, Samy Bengio, Preetum Nakkiran
2024What Makes Good Data for Alignment? A Comprehensive Study of Automatic Data Selection in Instruction Tuning.
Wei Liu, Weihao Zeng, Keqing He, Yong Jiang, Junxian He
2024What Makes a Good Prune? Maximal Unstructured Pruning for Maximal Cosine Similarity.
Gabryel Mason-Williams, Fredrik Dahlqvist
2024What Matters to You? Towards Visual Representation Alignment for Robot Learning.
Thomas Tian, Chenfeng Xu, Masayoshi Tomizuka, Jitendra Malik, Andrea Bajcsy
2024What does automatic differentiation compute for neural networks?
Sejun Park, Sanghyuk Chun, Wonyeol Lee
2024What does the Knowledge Neuron Thesis Have to do with Knowledge?
Jingcheng Niu, Andrew Liu, Zining Zhu, Gerald Penn
2024What's In My Big Data?
Yanai Elazar, Akshita Bhagia, Ian Magnusson, Abhilasha Ravichander, Dustin Schwenk, Alane Suhr, Evan Pete Walsh, Dirk Groeneveld, Luca Soldaini, Sameer Singh, Hannaneh Hajishirzi, Noah A. Smith, Jesse Dodge
2024What's in a Prior? Learned Proximal Networks for Inverse Problems.
Zhenghan Fang, Sam Buchanan, Jeremias Sulam
2024When Do Prompting and Prefix-Tuning Work? A Theory of Capabilities and Limitations.
Aleksandar Petrov, Philip Torr, Adel Bibi
2024When Scaling Meets LLM Finetuning: The Effect of Data, Model and Finetuning Method.
Biao Zhang, Zhongtao Liu, Colin Cherry, Orhan Firat
2024When Semantic Segmentation Meets Frequency Aliasing.
Linwei Chen, Lin Gu, Ying Fu
2024When can transformers reason with abstract symbols?
Enric Boix-Adserà, Omid Saremi, Emmanuel Abbe, Samy Bengio, Etai Littwin, Joshua M. Susskind
2024When should we prefer Decision Transformers for Offline Reinforcement Learning?
Prajjwal Bhargava, Rohan Chitnis, Alborz Geramifard, Shagun Sodhani, Amy Zhang
2024Where We Have Arrived in Proving the Emergence of Sparse Interaction Primitives in DNNs.
Qihan Ren, Jiayang Gao, Wen Shen, Quanshi Zhang
2024Whittle Index with Multiple Actions and State Constraint for Inventory Management.
Chuheng Zhang, Xiangsen Wang, Wei Jiang, Xianliang Yang, Siwei Wang, Lei Song, Jiang Bian
2024Whole-Song Hierarchical Generation of Symbolic Music Using Cascaded Diffusion Models.
Ziyu Wang, Lejun Min, Gus Xia
2024Why is SAM Robust to Label Noise?
Christina Baek, J. Zico Kolter, Aditi Raghunathan
2024WildChat: 1M ChatGPT Interaction Logs in the Wild.
Wenting Zhao, Xiang Ren, Jack Hessel, Claire Cardie, Yejin Choi, Yuntian Deng
2024WildFusion: Learning 3D-Aware Latent Diffusion Models in View Space.
Katja Schwarz, Seung Wook Kim, Jun Gao, Sanja Fidler, Andreas Geiger, Karsten Kreis
2024Win-Win: Training High-Resolution Vision Transformers from Two Windows.
Vincent Leroy, Jérôme Revaud, Thomas Lucas, Philippe Weinzaepfel
2024Window Attention is Bugged: How not to Interpolate Position Embeddings.
Daniel Bolya, Chaitanya Ryali, Judy Hoffman, Christoph Feichtenhofer
2024WizardCoder: Empowering Code Large Language Models with Evol-Instruct.
Ziyang Luo, Can Xu, Pu Zhao, Qingfeng Sun, Xiubo Geng, Wenxiang Hu, Chongyang Tao, Jing Ma, Qingwei Lin, Daxin Jiang
2024WizardLM: Empowering Large Pre-Trained Language Models to Follow Complex Instructions.
Can Xu, Qingfeng Sun, Kai Zheng, Xiubo Geng, Pu Zhao, Jiazhan Feng, Chongyang Tao, Qingwei Lin, Daxin Jiang
2024Würstchen: An Efficient Architecture for Large-Scale Text-to-Image Diffusion Models.
Pablo Pernias, Dominic Rampas, Mats L. Richter, Christopher Pal, Marc Aubreville
2024Xformer: Hybrid X-Shaped Transformer for Image Denoising.
Jiale Zhang, Yulun Zhang, Jinjin Gu, Jiahua Dong, Linghe Kong, Xiaokang Yang
2024YaRN: Efficient Context Window Extension of Large Language Models.
Bowen Peng, Jeffrey Quesnelle, Honglu Fan, Enrico Shippole
2024Yet Another ICU Benchmark: A Flexible Multi-Center Framework for Clinical ML.
Robin Van De Water, Hendrik Schmidt, Paul W. G. Elbers, Patrick Thoral, Bert Arnrich, Patrick Rockenschaub
2024You Only Query Once: An Efficient Label-Only Membership Inference Attack.
Yutong Wu, Han Qiu, Shangwei Guo, Jiwei Li, Tianwei Zhang
2024ZeRO++: Extremely Efficient Collective Communication for Large Model Training.
Guanhua Wang, Heyang Qin, Sam Ade Jacobs, Xiaoxia Wu, Connor Holmes, Zhewei Yao, Samyam Rajbhandari, Olatunji Ruwase, Feng Yan, Lei Yang, Yuxiong He
2024Zero Bubble (Almost) Pipeline Parallelism.
Penghui Qi, Xinyi Wan, Guangxing Huang, Min Lin
2024Zero and Few-shot Semantic Parsing with Ambiguous Inputs.
Elias Stengel-Eskin, Kyle Rawlins, Benjamin Van Durme
2024Zero-Mean Regularized Spectral Contrastive Learning: Implicitly Mitigating Wrong Connections in Positive-Pair Graphs.
Xiong Zhou, Xianming Liu, Feilong Zhang, Gang Wu, Deming Zhai, Junjun Jiang, Xiangyang Ji
2024Zero-Shot Continuous Prompt Transfer: Generalizing Task Semantics Across Language Models.
Zijun Wu, Yongkang Wu, Lili Mou
2024Zero-Shot Robotic Manipulation with Pre-Trained Image-Editing Diffusion Models.
Kevin Black, Mitsuhiko Nakamoto, Pranav Atreya, Homer Rich Walke, Chelsea Finn, Aviral Kumar, Sergey Levine
2024Zero-Shot Robustification of Zero-Shot Models.
Dyah Adila, Changho Shin, Linrong Cai, Frederic Sala
2024ZeroFlow: Scalable Scene Flow via Distillation.
Kyle Vedder, Neehar Peri, Nathaniel Chodosh, Ishan Khatri, Eric Eaton, Dinesh Jayaraman, Yang Liu, Deva Ramanan, James Hays
2024Zeroth-Order Optimization Meets Human Feedback: Provable Learning via Ranking Oracles.
Zhiwei Tang, Dmitry Rybin, Tsung-Hui Chang
2024ZipIt! Merging Models from Different Tasks without Training.
George Stoica, Daniel Bolya, Jakob Bjorner, Pratik Ramesh, Taylor Hearn, Judy Hoffman
2024Zipformer: A faster and better encoder for automatic speech recognition.
Zengwei Yao, Liyong Guo, Xiaoyu Yang, Wei Kang, Fangjun Kuang, Yifan Yang, Zengrui Jin, Long Lin, Daniel Povey
2024Zoology: Measuring and Improving Recall in Efficient Language Models.
Simran Arora, Sabri Eyuboglu, Aman Timalsina, Isys Johnson, Michael Poli, James Zou, Atri Rudra, Christopher Ré
2024f-FERM: A Scalable Framework for Robust Fair Empirical Risk Minimization.
Sina Baharlouei, Shivam Patel, Meisam Razaviyayn
2024fairret: a Framework for Differentiable Fairness Regularization Terms.
Maarten Buyl, MaryBeth Defrance, Tijl De Bie
2024iGraphMix: Input Graph Mixup Method for Node Classification.
Jongwon Jeong, Hoyeop Lee, Hyui Geon Yoon, Beomyoung Lee, Junhee Heo, Geonsoo Kim, Kim Jin Seon
2024iTransformer: Inverted Transformers Are Effective for Time Series Forecasting.
Yong Liu, Tengge Hu, Haoran Zhang, Haixu Wu, Shiyu Wang, Lintao Ma, Mingsheng Long
2024lpNTK: Better Generalisation with Less Data via Sample Interaction During Learning.
Shangmin Guo, Yi Ren, Stefano V. Albrecht, Kenny Smith
2024sRGB Real Noise Modeling via Noise-Aware Sampling with Normalizing Flows.
Dongjin Kim, Donggoo Jung, Sungyong Baik, Tae Hyun Kim
2024αTC-VAE: On the relationship between Disentanglement and Diversity.
Cristian Meo, Louis Mahon, Anirudh Goyal, Justin Dauwels
2024π2vec: Policy Representation with Successor Features.
Gianluca Scarpellini, Ksenia Konyushkova, Claudio Fantacci, Thomas Paine, Yutian Chen, Misha Denil
2024∞-Diff: Infinite Resolution Diffusion with Subsampled Mollified States.
Sam Bond-Taylor, Chris G. Willcocks