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| 2024 | A Coin Has Two Sides: A Novel Detector-Corrector Framework for Chinese Spelling Correction. Xiangke Zeng, Zuchao Li, Lefei Zhang, Ping Wang, Hongqiu Wu, Hai Zhao |
| 2024 | A Comprehensive Sustainable Framework for Machine Learning and Artificial Intelligence. Roberto Pagliari, Peter Hill, Po-Yu Chen, Maciej Dabrowny, Tingsheng Tan, Francois Buet-Golfouse |
| 2024 | A Data-Driven Approach Supporting Location Decisions for Docking Stations in Bike-Sharing Systems. Blerina Spahiu, Daniela Briola, Riccardo Sartori, Giuseppe Vizzari |
| 2024 | A Data-Driven Defense Against Edge-Case Model Poisoning Attacks on Federated Learning. Kiran Purohit, Soumi Das, Sourangshu Bhattacharya, Santu Rana |
| 2024 | A Demonstration of AI Personalized Interactive Fiction for Young Children. Jasmine Lesner, Luke Murayama, Tony Guizar, Poom Phunjamaneechot, Daniel Shapiro |
| 2024 | A Faster Branching Algorithm for the Maximum k-Defective Clique Problem. Chunyu Luo, Yi Zhou, Zhengren Wang, Mingyu Xiao |
| 2024 | A Federated Large Language Model for Long-Term Time Series Forecasting. Raed Abdel Sater, A. Ben Hamza |
| 2024 | A First-Order Multi-Gradient Algorithm for Multi-Objective Bi-Level Optimization. Feiyang Ye, Baijiong Lin, Xiaofeng Cao, Yu Zhang, Ivor W. Tsang |
| 2024 | A Full DAG Score-Based Algorithm for Learning Causal Bayesian Networks with Latent Confounders. Christophe Gonzales, Amir-Hosein Valizadeh |
| 2024 | A Gale-Shapley View of Unique Stable Marriages. Kartik Gokhale, Amit Kumar Mallik, Ankit Kumar Misra, Swaprava Nath |
| 2024 | A Heuristic for Optimal Total-Order HTN Planning Based on Integer Linear Programming. Conny Olz, Alexander Lodemann, Pascal Bercher |
| 2024 | A Hybrid Approach towards Chinese Spelling and Splitting Error Correction. Junhong Liang, Junnan Zhu, Feifei Zhai, Nanchang Cheng, Chengqing Zong, Yu Zhou |
| 2024 | A Language Model as a Design Assistant for UI Design Recommendation and Evaluation. Lin Sheng, Cheng Deng, Junjie Zhang, Fangyuan Chang, Qinghua Sun, Hongyu Liu, Zhenyu Gu |
| 2024 | A Lazy Approach to Neural Numerical Planning with Control Parameters. René Heesch, Alessandro Cimatti, Jonas Ehrhardt, Alexander Diedrich, Oliver Niggemann |
| 2024 | A Logic for Policy Based Resource Exchanges in Multiagent Systems. Lorenzo Ceragioli, Pierpaolo Degano, Letterio Galletta, Luca Viganò |
| 2024 | A Meta-Engine Framework for Interleaved Task and Motion Planning using Topological Refinements. Elisa Tosello, Alessandro Valentini, Andrea Micheli |
| 2024 | A Meta-Learning Approach for Multi-Objective Reinforcement Learning in Sustainable Home Energy Management. Junlin Lu, Patrick Mannion, Karl Mason |
| 2024 | A Methodology Establishing Linear Convergence of Adaptive Gradient Methods under PL Inequality. Kushal Chakrabarti, Mayank Baranwal |
| 2024 | A More Practical Algorithm for Weighted First-Order Model Counting with Linear Order Axiom. Qiaolan Meng, Jan Tóth, Yuanhong Wang, Yuyi Wang, Ondrej Kuzelka |
| 2024 | A Multi-Agent Reinforcement Learning Algorithm Embedded with Opponent Modeling. Shun Li, Xiao Su, Bing Shi |
| 2024 | A Neural Rewriting System to Solve Algorithmic Problems. Flavio Petruzzellis, Alberto Testolin, Alessandro Sperduti |
| 2024 | A Neuro-symbolic Approach for Faceted Search in Digital Libraries. Mutahira Khalid, Sören Auer, Markus Stocker |
| 2024 | A Novel View of Analogical Proportion Between Formulas. Andreas Herzig, Emiliano Lorini, Henri Prade |
| 2024 | A Parallel Gumbel-Softmax VAE Framework with Performance-Based Tuning. Fangshi Zhou, Tianming Zhao, Luan Viet Nguyen, Zhongmei Yao |
| 2024 | A Practical Operational Semantics for Classical Planning in BDI Agents. Mengwei Xu, Tom Lumley, Ramon Fraga Pereira, Felipe Meneguzzi |
| 2024 | A Predictive Model for Risk Management of the Hospitalised Patient as a Clinical Decision Support System. Isabel Benlloch-Blasco, Vicent J. Botti, Stella Heras, M. Isabel Marmol, Isabel Miguel, Javier Palanca, Antonio Ruiz |
| 2024 | A Robust and Scalable Approach to Meet User Preferences in Research Project Planning. Roger Xavier Lera-Leri, Filippo Bistaffa |
| 2024 | A SAM Based Tool for Semi-Automatic Food Annotation. Lubnaa Abdur Rahman, Ioannis Papathanail, Lorenzo Brigato, Stavroula G. Mougiakakou |
| 2024 | A Simple Yet Effective Interpretable Bayesian Personalized Ranking for Cognitive Diagnosis. Arthur Batel, Idir Benouaret, Joan Fruitet, Marc Plantevit, Céline Robardet |
| 2024 | A Single Online Agent Can Efficiently Learn Mean Field Games. Chenyu Zhang, Xu Chen, Xuan Di |
| 2024 | A Study of Prototypical Network Techniques for Cross-Subject EEG Analysis. Wenchao Liu, Guagnyu Wang, Yuhong He, Hongjian Bo, Lin Ma, Haifeng Li |
| 2024 | A Unified Automata-Theoretic Approach to LTL Marco Faella, Gennaro Parlato |
| 2024 | AI Personalized Interactive Fiction for Young Children. Jasmine Lesner, Luke Murayama, Tony Guizar, Poom Phunjamaneechot, Daniel Shapiro |
| 2024 | AI for Declarative Processes: Representation, Mining, Synthesis. Marco Montali |
| 2024 | AI-Powered Immersive Assistance for Interactive Task Execution in Industrial Environments. Tomislav Duricic, Peter Müllner, Nicole Weidinger, Neven A. M. ElSayed, Dominik Kowald, Eduardo E. Veas |
| 2024 | AI-Powered Virtual Reality System for Training Wrist Amputees to Use Advanced Prosthetic Solutions. Vladislav Aksiotis, Oleg Sazonov, Kamila Nasrulina, Daria Medvedeva, Uliya Nekrasova, Alexei Ossadtchi |
| 2024 | ALOE: Boosting Large Language Model Fine-Tuning with Aggressive Loss-Based Elimination of Samples. Alexander Demidovskij, Aleksei Trutnev, Artyom Tugaryov, Igor Salnikov |
| 2024 | ANSPRE: Improving Question-Answering in Large Language Models with Answer-Prefix Generation. Nguyen-Khang Le, Dieu-Hien Nguyen, Le Minh Nguyen |
| 2024 | ANTIDOTE: ArgumeNtaTIon-Driven explainable artificial intelligence fOr digiTal mEdicine. Cristian Cardellino, Theo Alkibiades Collias, Benjamin Molinet, Erwan Hain, Wei Sun, Rodrigo Agerri, Serena Villata, Elena Cabrio |
| 2024 | Abductive and Contrastive Explanations for Scoring Rules in Voting. Clément Contet, Umberto Grandi, Jérôme Mengin |
| 2024 | Accelerating Machine Learning for Trading Using Programmable Switches. Xinpeng Hong, Changgang Zheng, Stefan Zohren, Noa Zilberman |
| 2024 | Actively Learning from Machine Learning Models with Queries and Counterexamples (Extended Abstract). Ana Ozaki |
| 2024 | ActivityGen: Extracting Enabled Activities from Screenshots. Harry H. Beyel, Sovin Manuel, Wil M. P. van der Aalst |
| 2024 | Adapt PointFormer: 3D Point Cloud Analysis via Adapting 2D Visual Transformers. Mengke Li, Da Li, Guoqing Yang, Yiu-ming Cheung, Hui Huang |
| 2024 | Adaptive Context Embedding for Temperature Prediction in Residential Buildings. Sai Sushanth Varma Kalidindi, Hadi Banaee, Hans Karlsson, Amy Loutfi |
| 2024 | Adaptive Fraud Detection on e-Commerce Platforms. Shaowen Tang, Raymond K. Wong |
| 2024 | Adaptive Spectral-Heterophily for Node Classification. Giuseppe Pirrò |
| 2024 | Adjacent Leader Decentralized Stochastic Gradient Descent. Haoze He, Jing Wang, Anna Choromanska |
| 2024 | Advancing ConvNet Architectures: A Novel XGB-based Pruning Algorithm for Transfer Learning Efficiency. Igor Ratajczyk, Adrian Horzyk |
| 2024 | Advancing Topic Segmentation of Broadcasted Speech with Multilingual Semantic Embeddings. Sakshi Deo Shukla, Pavel Denisov, Tugtekin Turan |
| 2024 | Adversarial Attack for Explanation Robustness of Rationalization Models. Yuankai Zhang, Lingxiao Kong, Haozhao Wang, Ruixuan Li, Jun Wang, Yuhua Li, Wei Liu |
| 2024 | Adversarial Erasing Transformer for Weakly Supervised Semantic Segmentation. Bingfeng Zhang, Siyue Yu, Xuru Gao, Mingjie Sun, Eng Gee Lim, Jimin Xiao |
| 2024 | Adversarially Robust Neural Lyapunov Control. Li Wei, Yuankun Jiang, Chenglin Li, Wenrui Dai, Junni Zou, Hongkai Xiong |
| 2024 | Aligning XAI with EU Regulations for Smart Biomedical Devices: A Methodology for Compliance Analysis. Francesco Sovrano, Michael Lognoul, Giulia Vilone |
| 2024 | An Animation-Based Augmentation Approach for Action Recognition from Discontinuous Video. Xingyu Song, Zhan Li, Shi Chen, Xin-Qiang Cai, Kazuyuki Demachi |
| 2024 | An Axiomatic Perspective on Anomaly Detection. Chester Wyke, Ruth Urner |
| 2024 | An Efficient Modular Algorithm for Connected Multi-Agent Path Finding. Victorien Desbois, Ocan Sankur, François Schwarzentruber |
| 2024 | An Empirical Study of Grounding PPDDL Plans for AI-Driven Robots in Social Environment. Gloria Beraldo, Angelo Oddi, Riccardo Rasconi |
| 2024 | An Intelligent Pipeline for Localization of Industrial Components in Robotic Manufacturing Applications. Parth Rawal, Daniel Valencia, Wolfgang Hintze |
| 2024 | An Online Incremental Learning Approach for Configuring Multi-arm Bandits Algorithms. Mohammad Essa Alsomali, Roberto Rodrigues Filho, Leandro Soriano Marcolino, Barry Porter |
| 2024 | Analogical Classifier as a Surrogate for Explanations. Suryani Lim, Henri Prade, Gilles Richard |
| 2024 | Analyzing Incentives and Fairness in Ordered Weighted Average for Facility Location Games. Kento Yoshida, Kei Kimura, Taiki Todo, Makoto Yokoo |
| 2024 | Anatomical Consistency Distillation and Inconsistency Synthesis for Brain Tumor Segmentation with Missing Modalities. Zheyu Zhang, Xinzhao Liu, Zheng Chen, Yueyi Zhang, Huanjing Yue, Yunwei Ou, Xiaoyan Sun |
| 2024 | Annot-Mix: Learning with Noisy Class Labels from Multiple Annotators via a Mixup Extension. Marek Herde, Lukas Lührs, Denis Huseljic, Bernhard Sick |
| 2024 | Answerable Sociotechnical Systems. Dilara Keküllüoglu, Michael Rovatsos, Nadin Kökciyan |
| 2024 | Anti-Matthew FL: Bridging the Performance Gap in Federated Learning to Counteract the Matthew Effect. Jiashi Gao, Xin Yao, Xuetao Wei |
| 2024 | Approximate Estimation of High-Dimension Execution Skill for Dynamic Agents in Continuous Domains. Delma Nieves-Rivera, Christopher Archibald |
| 2024 | Approximate Mechanism Design for Facility Location with Multiple Objectives. Toby Walsh |
| 2024 | Artificial Agents Facilitate Human Cooperation Through Indirect Reciprocity. Alexandre S. Pires, Fernando P. Santos |
| 2024 | Artwork Protection Against Neural Style Transfer Using Locally Adaptive Adversarial Color Attack. Zhongliang Guo, Junhao Dong, Yifei Qian, Kaixuan Wang, Weiye Li, Ziheng Guo, Yuheng Wang, Yanli Li, Ognjen Arandjelovic, Lei Fang |
| 2024 | Assessing Privacy Risks of Attribute Inference Attacks Against Speech-Based Depression Detection System. Basmah Alsenani, Anna Esposito, Alessandro Vinciarelli, Tanaya Guha |
| 2024 | Assisted Debate Builder with Large Language Models. Elliot Faugier, Frédéric Armetta, Angela Bonifati, Bruno Yun |
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| 2024 | Automated Impact Echo Spectrum Anomaly Detection using U-Net Autoencoder. Artur Liebert, Fabian Dethof, Sylvia Keßler, Oliver Niggemann |
| 2024 | Automated Synthesis of Certified Neural Networks. Matteo Zavatteri, Davide Bresolin, Nicolò Navarin |
| 2024 | Automatic Motor Imagery Classification by CNN-Transformer-LSTM Using Multi-Channel EEG Signals. Duc Thien Pham, Roman Moucek |
| 2024 | Axiomatic Characterisations of Sample-based Explainers. Leila Amgoud, Martin C. Cooper, Salim Debbaoui |
| 2024 | B2MAPO: A Batch-by-Batch Multi-Agent Policy Optimization to Balance Performance and Efficiency. Wenjing Zhang, Wei Zhang, Wenqing Hu, Yifan Wang |
| 2024 | BOB-YOLO: Balancing Optimization Binarized YOLO via Module-Wise Latency. Xinyu Liu, Wenqiang Zhou, Zhendong Yu, Jiaming Yang, Tao Wang, Chenwei Tang, Jiancheng Lv |
| 2024 | BRECS: Enhanced Binary Representation of Word Embeddings via Cosine Similarity. Rajdeep Sarkar, Sourav Dutta, John P. McCrae |
| 2024 | Back to the Future: Symbolic Reasoning to Combat Malicious Use of Social Media. Maria Vanina Martinez |
| 2024 | Backward Compatibility in Attributive Explanation and Enhanced Model Training Method. Ryuta Matsuno |
| 2024 | Backward Explanations via Redefinition of Predicates. Léo Saulières, Martin C. Cooper, Florence Dupin de Saint-Cyr |
| 2024 | Balancing Efficiency with Equality: Auction Design with Group Fairness Concerns. Fengjuan Jia, Mengxiao Zhang, Jiamou Liu, Bakh Khoussainov |
| 2024 | Barely Decidable Fragments of Planning. Maurice Dekker, Gregor Behnke |
| 2024 | Be Persistent: Towards a Unified Solution for Mitigating Shortcuts in Deep Learning. Hadi M. Dolatabadi, Sarah M. Erfani, Christopher Leckie |
| 2024 | Belief Erasure in Propositional Logic. Nadia Creignou, Raïda Ktari, Odile Papini |
| 2024 | Benchmarking Adversarial Robustness in Speech Emotion Recognition: Insights into Low-Resource Romanian and German Languages. Sebastian-Vasile Echim, Razvan-Alexandru Smadu, Dumitru-Clementin Cercel |
| 2024 | BiLEE: Bi-Level Early Exiting for Generative Document Retrieval. Rui Fang, Chin-Yuan Yeh, Hsi-Wen Chen, Ming-Syan Chen |
| 2024 | Big-Thick Data Generation via Reference and Personal Context Unification. Fausto Giunchiglia, Xiaoyue Li |
| 2024 | Bipartite Time Series Network for Data Imputation. Ilaria Lucrezia Amerise, Valeria Fionda, Giuseppe Pirrò |
| 2024 | Bottlenecked Backpropagation to Train Differentially Private Deep Neural Networks. Arghyadeep Ghosh, Mrinal Das |
| 2024 | Boundary-Enhanced Instance Segmentation. Fangyuan Zhang, Tianxiang Pan, Yu-Wing Tai, Bin Wang |
| 2024 | Breaking the Weak Semantics Bottleneck of Transformers in Time Series Forecasting. Ziang Yang, Biyu Zhou, Xuehai Tang, Ruixuan Li, Songlin Hu |
| 2024 | Bridging Continual Learning of Motion and Self-Supervised Representations. Matteo Tiezzi, Simone Marullo, Alessandro Betti, Michele Casoni, Stefano Melacci |
| 2024 | Bridging the Gap: Generating a Comprehensive Biomedical Knowledge Graph Question Answering Dataset. Xi Yan, Patrick Westphal, Jan Seliger, Ricardo Usbeck |
| 2024 | Building and Assessing a Named Entity Recognition Resource for Ancient Pharmacopeias. Karim El Haff, Wissam Antoun, Agnès Braud, Florence Le Ber, Véronique Pitchon |
| 2024 | CA-SER: Cross-Attention Feature Fusion for Speech Emotion Recognition. Bashar M. Deeb, Andrey V. Savchenko, Ilya Makarov |
| 2024 | CAMAOT: Channel-Aware Multi-Camera Active Object Tracking System. Maolong Yin, Bin Guo, Zhuo Sun, Lei Wu, Zhaotie Hao, Zhiwen Yu |
| 2024 | CBM: Curriculum by Masking. Andrei Jarca, Florinel-Alin Croitoru, Radu Tudor Ionescu |
| 2024 | CLCE: An Approach to Refining Cross-Entropy and Contrastive Learning for Optimized Learning Fusion. Zijun Long, Lipeng Zhuang, George Killick, Zaiqiao Meng, Richard McCreadie, Gerardo Aragon-Camarasa |
| 2024 | CLIP-based Cross-Level Semantic Interaction and Recombination Network for Composed Image Retrieval. Zhihang Liu, Qiang Huang, Yingying Zhu |
| 2024 | CLLMFS: A Contrastive Learning Enhanced Large Language Model Framework for Few-Shot Named Entity Recognition. Yafeng Zhang, Zilan Yu, Yuang Huang, Jing Tang |
| 2024 | CODD: A Decision Diagram-Based Solver for Combinatorial Optimization. Laurent Michel, Willem-Jan van Hoeve |
| 2024 | CPNet: 3D Semantic Relation and Geometry Context Prior Network for Multi-Organ Segmentation. Yuzhu Ji, Mingshan Sun, Yiqun Zhang, Haijun Zhang |
| 2024 | CSAdv: Class-Specific Adversarial Patches for DETR-Style Object Detection. Yue Xu, Chuanming Wang, Xiaolong Zheng, Yi Huang, Peilun Du, Zeyuan Zhou, Liang Liu, Huadong Ma |
| 2024 | Canonical Decision Diagrams Modulo Theories. Massimo Michelutti, Gabriele Masina, Giuseppe Spallitta, Roberto Sebastiani |
| 2024 | Capacitated Online Clustering Algorithm. Shivam Gupta, Shweta Jain, Narayanan C. Krishnan, Ganesh Ghalme, Nandyala Hemachandra |
| 2024 | Cascade Memory for Unsupervised Anomaly Detection. Jiahao Li, Yiqiang Chen, Yunbing Xing, Yang Gu, Xiangyuan Lan |
| 2024 | Causal Diffusion Autoencoders: Toward Counterfactual Generation via Diffusion Probabilistic Models. Aneesh Komanduri, Chen Zhao, Feng Chen, Xintao Wu |
| 2024 | Cautious Calibration in Binary Classification. Mari-Liis Allikivi, Joonas Järve, Meelis Kull |
| 2024 | Caveats and Solutions for Characterising General-Purpose AI. José Hernández-Orallo |
| 2024 | Channel Randomisation Methods for Zero-Shot Communication. Dylan Cope, Nandi Schoots |
| 2024 | Characterising Serialisation Equivalence for Abstract Argumentation. Lars Bengel, Julian Sander, Matthias Thimm |
| 2024 | ChatZero: Zero-Shot Cross-Lingual Dialogue Generation via Pseudo-Target Language. Yongkang Liu, Shi Feng, Daling Wang, Yifei Zhang, Hinrich Schütze |
| 2024 | Class-Aware Sample Weight Learning for Cross-Modal Unsupervised Domain Adaptation in Cross-User Wearable Human Activity Recognition. Tong Wu, Yanbin Liu, Sira Yongchareon |
| 2024 | Classifier Guidance Enhances Diffusion-Based Adversarial Purification by Preserving Predictive Information. Mingkun Zhang, Jianing Li, Wei Chen, Jiafeng Guo, Xueqi Cheng |
| 2024 | Cliff: Leveraging Ambiguous Samples for Enhanced Test-Time Adaptation. Xiao Chen, Qihui Zhang, Yan Wang |
| 2024 | Cluster Exploration Using Informative Manifold Projections. Stavros Gerolymatos, Xenophon Evangelopoulos, Vladimir V. Gusev, John Yannis Goulermas |
| 2024 | CoTran: An LLM-Based Code Translator Using Reinforcement Learning with Feedback from Compiler and Symbolic Execution. Prithwish Jana, Piyush Jha, Haoyang Ju, Gautham Kishore, Aryan Mahajan, Vijay Ganesh |
| 2024 | Comateformer: Combined Attention Transformer for Semantic Sentence Matching. Bo Li, Di Liang, Zixin Zhang |
| 2024 | Combining Active Learning and Learning to Reject for Anomaly Detection. Luca Stradiotti, Lorenzo Perini, Jesse Davis |
| 2024 | Combining Diverse Information for Coordinated Action: Stochastic Bandit Algorithms for Heterogeneous Agents. Lucia Gordon, Esther Rolf, Milind Tambe |
| 2024 | Comparing Lossless Compression Methods for Chess Endgame Data. Dave Gomboc, Christian R. Shelton, Andrew S. Miner, Gianfranco Ciardo |
| 2024 | Complex Multi-Ontology Alignment Through Geometric Operations on Language Embeddings. Marta Contreiras Silva, Daniel Faria, Catia Pesquita |
| 2024 | Complex-Valued Gabor-Attention Residual Fusion Network for Iris Recognition. Zhuoru Li, Jian Xiao, Xiaowei Bai, Xiaodong Wang, Yingxi Li, Zhenyu Fang, Liang Xie, Ye Yan, Erwei Yin |
| 2024 | Complexity Results and Algorithms for Manipulation and Bribery in Judgment Aggregation. Ari Conati, Andreas Niskanen, Ronald de Haan, Matti Järvisalo |
| 2024 | Complexity and Approximation Schemes for Social Welfare Maximization in the High-Multiplicity Setting. Trung Thanh Nguyen, Khaled Elbassioni, Jörg Rothe |
| 2024 | Compromises in Dialogical Argumentation: Aggregated Policies for Biparty Decision Theory. Ivan Donadello, Renan Lirio de Souza, Anthony Hunter, Mauro Dragoni |
| 2024 | Computational Complexity of Standpoint LTL. Stéphane Demri, Przemyslaw Andrzej Walega |
| 2024 | Connecting Permutation Equivariant Neural Networks and Partition Diagrams. Edward Pearce-Crump |
| 2024 | ConspEmoLLM: Conspiracy Theory Detection Using an Emotion-Based Large Language Model. Zhiwei Liu, Boyang Liu, Paul Thompson, Kailai Yang, Sophia Ananiadou |
| 2024 | Constrained LLM-Based Query Generation for Question Answering on Official Statistics. Jonas Kouwenhoven, Lucas Lageweg, Benno Kruit |
| 2024 | Context Enhancement with Reconstruction as Sequence for Unified Unsupervised Anomaly Detection. Hui-Yue Yang, Hui Chen, Lihao Liu, Zijia Lin, Kai Chen, Liejun Wang, Jungong Han, Guiguang Ding |
| 2024 | Context Matters: Leveraging Spatiotemporal Metadata for Semi-Supervised Learning on Remote Sensing Images. Maximilian Bernhard, Tanveer Hannan, Niklas Strauß, Matthias Schubert |
| 2024 | Contextually Adaptive Algorithms for Gaussian Process Bandit Optimization Under Heavy-Tailed Noise. Hyeonjun Park, Kyungjae Lee |
| 2024 | Contribution of V1 Receptive Field Properties to Corruption Robustness in CNNs. Ruxandra Barbulescu, Tiago Marques, Arlindo L. Oliveira |
| 2024 | Contributions to the Journal Track. Gregor Behnke |
| 2024 | Control by Adding Players to Change or Maintain the Shapley-Shubik or the Penrose-Banzhaf Power Index in Weighted Voting Games Is Complete for NP Joanna Kaczmarek, Jörg Rothe |
| 2024 | Convolutional Bypasses Are Better Vision Transformer Adapters. Shibo Jie, Zhi-Hong Deng, Shixuan Chen, Zhijuan Jin |
| 2024 | Coopetition in Heterogeneous Cross-Silo Federated Learning. Chao Huang, Justin Dachille, Xin Liu |
| 2024 | CorrAdaptor: Adaptive Local Context Learning for Correspondence Pruning. Wei Zhu, Yicheng Liu, Yuping He, Tangfei Liao, Kang Zheng, Xiaoqiu Xu, Tao Wang, Tong Lu |
| 2024 | Cost Partitioning for Multiple Sequence Alignment. Mika Skjelnes, Daniel Gnad, Jendrik Seipp |
| 2024 | Counseling Responses for Mental Health Forum Questions with Early Maladaptive Schema Prediction. Sujatha Das Gollapalli, Beng Heng Ang, Mingzhe Du, See-Kiong Ng |
| 2024 | Count-Based Novelty Exploration in Classical Planning. Giacomo Rosa, Nir Lipovetzky |
| 2024 | Counterfactual Thinking in Stochastic Dynamics of Cooperation. António M. Fernandes, Francisco C. Santos, Ana Paiva |
| 2024 | Covered for Life: Lifelong Area Coverage under Spatiotemporal Uncertainty. Charlie Street, Masoumeh Mansouri |
| 2024 | Crafting Lifelike Avatars: Model Compression and Advanced Rendering Techniques. Shengjia Zhang |
| 2024 | Cross-Stage Transfer in Multi-Stage Cascade Ranking and Filtering Systems. Yifan Pan, Guibo Luo, Yuesheng Zhu |
| 2024 | Cube-Based Isomorph-Free Finite Model Finding. Choiwah Chow, Mikolás Janota, João Araújo |
| 2024 | DCTAN: Densely Convolved Transformer Aggregation Networks for Monocular Dense Depth Prediction in Robotic Endoscopy. Wenkang Fan, Wenjing Jiang, Hao Fang, Hong Shi, Jianhua Chen, Xiongbiao Luo |
| 2024 | DINEX: Interpretable NLP via Diversified Natural Language Explanations. Xugang Zhou, Jindian Su, Weizheng Gu |
| 2024 | DSPrompt: Prompt Learning with Relation Abstraction and Context Injection for Distant Supervised Relation Extraction. Zechen Meng, Wenbin Zhang, Mankun Zhao, Tianyi Xu, Jian Yu, Ruiguo Yu, Mei Yu |
| 2024 | DataDetective: Dataset Watermarking for Leaker Identification in ML Training. Noa Wegerhoff, Avishag Shapira, Yuval Elovici, Asaf Shabtai |
| 2024 | DeCoRTAD: Diffusion Based Conditional Representation Learning for Online Trajectory Anomaly Detection. Chen Wang, Sarah M. Erfani, Tansu Alpcan, Christopher Leckie |
| 2024 | Decentralized Unlabeled Multi-Agent Pathfinding Via Target And Priority Swapping. Stepan Dergachev, Konstantin S. Yakovlev |
| 2024 | Decision-Focused Learning to Predict Action Costs for Planning. Jayanta Mandi, Marco Foschini, Daniel Höller, Sylvie Thiébaux, Jörg Hoffmann, Tias Guns |
| 2024 | Decoupled Competitive Framework for Semi-Supervised Medical Image Segmentation. Jiahe Chen, Jiahe Ying, Shen Wang, Jianwei Zheng |
| 2024 | Deep Generative Models for Subgraph Prediction. Erfaneh Mahmoudzadeh, Parmis Naddaf, Kiarash Zahirnia, Oliver Schulte |
| 2024 | Deep Learning for in vivo Bronchial Carinae Detection in Flexible Bronchoscopy. Robin Ghyselinck, Valentin Delchevalerie, Pierre Poitier, Benoît Frénay, Bruno Dumas |
| 2024 | Deep Mapper: Efficient Visualization of Plausible Conformational Pathways. Ziyad Oulhaj, Yoshiyuki Ishii, Kento Ohga, Kimihiro Yamazaki, Mutsuyo Wada, Yuhei Umeda, Takashi Katoh, Yuichiro Wada, Hiroaki Kurihara |
| 2024 | DeepDFA: Automata Learning through Neural Probabilistic Relaxations. Elena Umili, Roberto Capobianco |
| 2024 | Defending Our Privacy with Backdoors. Dominik Hintersdorf, Lukas Struppek, Daniel Neider, Kristian Kersting |
| 2024 | Designing an XAI Interface for Tree-Based ML Models. Gilles Audemard, Sylvie Coste-Marquis, Pierre Marquis, Mehdi Sabiri, Nicolas Szczepanski |
| 2024 | Detect Closer Surfaces That Can be Seen: New Modeling and Evaluation in Cross-Domain 3D Object Detection. Ruixiao Zhang, Yihong Wu, Juheon Lee, Xiaohao Cai, Adam Prügel-Bennett |
| 2024 | Detecting Hidden Triggers: Mapping Non-Markov Reward Functions to Markov. Gregory Hyde, Eugene Santos Jr. |
| 2024 | Detecting Objects as Cascade Corners. Chenglong Liu, Jintao Liu, Haorao Wei, Jinze Yang, Liangyu Xu, Yuchen Guo, Lu Fang |
| 2024 | Detecting Patterns of Attacks to Network Security in Urban Air Mobility with Answer Set Programming. Gioacchino Sterlicchio, Francesca Alessandra Lisi |
| 2024 | Development of an Interpretable Uni-Null Neuron-Based Evolving Fuzzy Neural Network for Age Group Identification in Respondents with Diabetes. Paulo Vitor de Campos Souza, Mauro Dragoni |
| 2024 | Device-Specific Facial Descriptors: Winning a Lottery with a SuperNet. Andrey V. Savchenko, Dmitry Maslov, Ilya Makarov |
| 2024 | Differentiable Logic Programming for Distant Supervision. Akihiro Takemura, Katsumi Inoue |
| 2024 | Differentiable Neural Network for Assembling Blocks. Zhiwei Liu, Qiang Lu, Yibo Zhao, Yanhong Zhao, Jake Luo |
| 2024 | Differentiating Choices via Commonality for Multiple-Choice Question Answering. Wenqing Deng, Zhe Wang, Kewen Wang, Shirui Pan, Xiaowang Zhang, Zhiyong Feng |
| 2024 | Dirichlet Logistic Gaussian Processes for Evaluation of Black-Box Stochastic Systems under Complex Requirements. Ryohei Oura, Yuji Ito |
| 2024 | Discovering Bayesian Networks when Few Variables Matter. Madhumita Kundu, Pekka Parviainen, Saket Saurabh |
| 2024 | Dissecting Scorpion: Ablation Study of an Optimal Classical Planner. Jendrik Seipp |
| 2024 | Distilling the Effects of Language Model Contamination. Behzad Mehrbakhsh, Fernando Martínez-Plumed, José Hernández-Orallo |
| 2024 | Distribution of Chores with Information Asymmetry. Hadi Hosseini, Joshua Kavner, Tomasz Was, Lirong Xia |
| 2024 | DiverTEAM: An Effective Evolutionary Algorithm for Diversified Top-k (Weight) Clique Search Problems. Jinghui Xue, Jiongzhi Zheng, Kun He, Chu-Min Li, Yanli Liu |
| 2024 | Diversifying the Mixture-of-Experts Representation for Language Models with Orthogonal Optimizer. Boan Liu, Liang Ding, Li Shen, Keqin Peng, Yu Cao, Dazhao Cheng, Dacheng Tao |
| 2024 | Diversity-Enhanced Learning for Unsupervised Syntactically Controlled Paraphrase Generation. Shaojuan Wu, Jitong Li, Yue Sun, Xiaowang Zhang, Zhiyong Feng |
| 2024 | Do We Care About Poll Manipulation in Political Elections? Vincent Mousseau, Henri Surugue, Anaëlle Wilczynski |
| 2024 | Does Serendipity Enhance Recommendation Quality? Measuring Accuracy and Beyond-Accuracy Objectives of Serendipitous POI Suggestions. Imen Ben Sassi, Priit Järv, Sadok Ben Yahia |
| 2024 | Domain Adaptational Steganographic Text Detection Using Few-Shot Adversary-Refinement Framework. Ziwei Zhang, Juan Wen, Yinghan Zhou, Liting Gao, Yiming Xue |
| 2024 | Domain Feature Perturbation for Domain Generalization. Chenguang Wang, Zijun Zhang, Zhidan Zhou |
| 2024 | Domain Generalised Cell Nuclei Segmentation in Histopathology Images Using Domain-Aware Curriculum Learning and Colour-Perceived Meta Learning. Kunzi Xie, Ruoyu Guo, Cong Cong, Maurice Pagnucco, Yang Song |
| 2024 | Domain-Specific Long Text Classification from Sparse Relevant Information. Célia D'Cruz, Jean-Marc Bereder, Frédéric Precioso, Michel Riveill |
| 2024 | DrDiff: Drug Response Prediction Through Controllable Diffusion-GE and Graph Attention Network. Seungyeon Choi, Sangmin Seo, Jonghwan Choi, Chihyun Park, Sanghyun Park |
| 2024 | Dual Attention Encoder with Joint Preservation for Medical Image Segmentation. Shijie Li, Yunbin Tu, Yu Gong, Bowen Zhong, Zheng Li |
| 2024 | Dynamic Multimodal Prompt Tuning: Boost Few-Shot Learning with VLM-Guided Point Cloud Models. Xiang Gu, Shuchao Pang, Anan Du, Yifei Wang, Jixiang Miao, Jorge Díez |
| 2024 | ECAI 2024 - 27th European Conference on Artificial Intelligence, 19-24 October 2024, Santiago de Compostela, Spain - Including 13th Conference on Prestigious Applications of Intelligent Systems (PAIS 2024) Ulle Endriss, Francisco S. Melo, Kerstin Bach, Alberto José Bugarín Diz, Jose Maria Alonso-Moral, Senén Barro, Fredrik Heintz |
| 2024 | EEG-Based fMRI Digital Twin: Towards a Cheap and Ecological Approach to Measure Subcortical Brain Activity. Nikolay Dagaev, Ilia Semenkov, Alexei Ossadtchi |
| 2024 | EVIDENT: Enhanced Visualization and Design Integration from Textual Edits and Prompts. Miguel Escarda-Fernández, Xin Lin, Iñigo López-Riobóo Botana, Sonia González-Vázquez |
| 2024 | EXPLAIN, AGREE, LEARN: Scaling Learning for Neural Probabilistic Logic. Victor Verreet, Lennert De Smet, Luc De Raedt, Emanuele Sansone |
| 2024 | EdgeNAT: Transformer for Efficient Edge Detection. Jinghuai Jie, Yan Guo, Guixing Wu, Junmin Wu, Baojian Hua |
| 2024 | Efficient Initial Data Selection and Labeling for Multi-Class Classification Using Topological Analysis. Lies Hadjadj, Emilie Devijver, Rémi Molinier, Massih-Reza Amini |
| 2024 | Efficient Model-Stealing Attacks Against Inductive Graph Neural Networks. Marcin Podhajski, Jan Dubinski, Franziska Boenisch, Adam Dziedzic, Agnieszka Pregowska, Tomasz P. Michalak |
| 2024 | Embedding Knowledge Graphs in Degenerate Clifford Algebras. Louis Mozart Kamdem Teyou, Caglar Demir, Axel-Cyrille Ngonga Ngomo |
| 2024 | Empirical Evaluation of Concept Probing for Game-Playing Agents. Aðalsteinn Pálsson, Yngvi Björnsson |
| 2024 | Empowering Biomedical Named Entity Recognition through Multi-Tagger Collaboration. Jin Zhao, Jian Xie, Tinghui Zhu, Qian Guo, Zhixu Li, Yanghua Xiao |
| 2024 | Enabling Causal Discovery in Post-Nonlinear Models with Normalizing Flows. Nu Hoang, Bao Duong, Thin Nguyen |
| 2024 | Enabling MCTS Explainability for Sequential Planning Through Computation Tree Logic. Ziyan An, Hendrik Baier, Abhishek Dubey, Ayan Mukhopadhyay, Meiyi Ma |
| 2024 | Enhancing Decision-Making in Energy Management Systems Through Action-Independent Dynamics Learning. Théo Zangato, Aomar Osmani, Pegah Alizadeh |
| 2024 | Enhancing Discourse Coherence to Improve Cross-Document Event Coreference Resolution. Xinyu Chen, Sheng Xu, Peifeng Li, Qiaoming Zhu |
| 2024 | Enhancing Fairness through Reweighting: A Path to Attain the Sufficiency Rule. Xuan Zhao, Klaus Broelemann, Salvatore Ruggieri, Gjergji Kasneci |
| 2024 | Enhancing Hate Speech Annotations with Background Semantics. Paula Reyero Lobo, Enrico Daga, Harith Alani, Miriam Fernández |
| 2024 | Enhancing Manufacturing Knowledge Access with LLMs and Context-Aware Prompting. Sebastian Monka, Irlán Grangel-González, Stefan Schmid, Lavdim Halilaj, Marc Rickart, Oliver Rudolph, Rui Dias |
| 2024 | Enhancing Node Representations for Real-World Complex Networks with Topological Augmentation. Xiangyu Zhao, Zehui Li, Mingzhu Shen, Guy-Bart Stan, Pietro Liò, Yiren Zhao |
| 2024 | Enhancing Reinforcement Learning Through Guided Search. Jérôme Arjonilla, Abdallah Saffidine, Tristan Cazenave |
| 2024 | Enhancing Retrieval and Managing Retrieval: A Four-Module Synergy for Improved Quality and Efficiency in RAG Systems. Yunxiao Shi, Xing Zi, Zijing Shi, Haimin Zhang, Qiang Wu, Min Xu |
| 2024 | Enhancing Stance Detection on Social Media via Core Views Discovery. Yu Yan, Yinghan Shen, Teli Liu, Xuhui Jiang, Dechun Yin |
| 2024 | Enhancing Text-to-SQL Capabilities of Large Language Models via Domain Database Knowledge Injection. Xingyu Ma, Xin Tian, Lingxiang Wu, Xuepeng Wang, Xueming Tang, Jinqiao Wang |
| 2024 | Entity Matching Across Small Networks Using Node Attributes. Zahra Ahmadi, Zijian Zhang, Hoang H. Nguyen, Sergio Burdisso, Srikanth R. Madikeri, Petr Motlícek, Erinç Dikici, Gerhard Backfried, Marek Kovác, Kvetoslav Malý, Daniel Kudenko |
| 2024 | EquinorQA: Large Language Models for Question Answering Over Proprietary Data. Darío Garigliotti, Bjarte Johansen, Jakob Vigerust Kallestad, Seong-Eun Cho, Cèsar Ferri |
| 2024 | Equipment Condition-Integrated Predictive Modeling for Optimized Scheduling of Ion Implantation in Semiconductor Manufacturing. Andreas Laber, Martin Gebser, Konstantin Schekotihin |
| 2024 | Error-Driven Uncertainty Aware Training. Pedro Mendes, Paolo Romano, David Garlan |
| 2024 | Escape Sensing Games: Detection-vs-Evasion in Security Applications. Niclas Boehmer, Minbiao Han, Haifeng Xu, Milind Tambe |
| 2024 | Estimating Causal Effects from Learned Causal Networks. Anna Raichev, Jin Tian, Alexander Ihler, Rina Dechter |
| 2024 | Estimating the Robustness Radius for Randomized Smoothing with 100× Sample Efficiency. Emmanouil Seferis, Stefanos Kollias, Chih-Hong Cheng |
| 2024 | Estimating the Time of Arrival of a Shipment with Machine Learning. Francesco Gibellini, Bart van Gool, Murat Firat, Stefano Bromuri |
| 2024 | EthiX: A Dataset for Argument Scheme Classification in Ethical Debates. Elfia Bezou-Vrakatseli, Oana Cocarascu, Sanjay Modgil |
| 2024 | Every Node Counts: Improving the Training of Graph Neural Networks on Node Classification. Moshe Eliasof, Eldad Haber, Eran Treister |
| 2024 | Evolutionary Reinforcement Learning via Cooperative Coevolution. Chengpeng Hu, Jialin Liu, Xin Yao |
| 2024 | Evolving A* to Efficiently Solve the κ Shortest-Path Problem. Carlos Linares López, Ian Herman |
| 2024 | Exemplar-Free Incremental Deepfake Detection. Wuti Xiong, Guoying Zhao, Xiaobai Li |
| 2024 | Existence of MMS Allocations of Mixed Manna. Kevin Hsu |
| 2024 | Explaining Text Classifiers with Counterfactual Representations. Pirmin Lemberger, Antoine Saillenfest |
| 2024 | Explaining a Probabilistic Prediction on the Simplex with Shapley Compositions. Paul-Gauthier Noé, Miquel Perelló-Nieto, Jean-François Bonastre, Peter A. Flach |
| 2024 | Explaining an Agent's Future Beliefs Through Temporally Decomposing Future Reward Estimators. Mark Towers, Yali Du, Christopher T. Freeman, Timothy J. Norman |
| 2024 | Explaining the Lack of Locally Envy-Free Allocations. Aurélie Beynier, Jean-Guy Mailly, Nicolas Maudet, Anaëlle Wilczynski |
| 2024 | Explicit Modelling of Theory of Mind for Belief Prediction in Nonverbal Social Interactions. Matteo Bortoletto, Constantin Ruhdorfer, Lei Shi, Andreas Bulling |
| 2024 | Exploiting Hierarchical Symmetry in Multi-Agent Reinforcement Learning. Yongkai Tian, Xin Yu, Yirong Qi, Li Wang, Pu Feng, Wenjun Wu, Rongye Shi, Jie Luo |
| 2024 | Explorative Imitation Learning: A Path Signature Approach for Continuous Environments. Nathan Gavenski, Juarez Monteiro, Felipe Meneguzzi, Michael Luck, Odinaldo Rodrigues |
| 2024 | Exploring Large Language Models Text Style Transfer Capabilities. Weijie Li, Zhentao Gu, Xiaochao Fan, Wenjun Deng, Yong Yang, Xinyuan Zhao, Yufeng Diao, Liang Yang |
| 2024 | Extending Context Window of Attention Based Knowledge Tracing Models via Length Extrapolation. Xueyi Li, Youheng Bai, Teng Guo, Ying Zheng, Mingliang Hou, Bojun Zhan, Yaying Huang, Zitao Liu, Boyu Gao, Weiqi Luo |
| 2024 | FL-GNN: Efficient Fusion of Fuzzy Neural Network and Graph Neural Network. Boyu Du, Jingya Zhou, Ling Liu, Xiaolong She |
| 2024 | FMViT: A Multiple-Frequency Mixing Vision Transformer. Wei Tan, Yifeng Geng, Xuansong Xie |
| 2024 | Fact Probability Vector Based Goal Recognition. Nils Wilken, Lea Cohausz, Christian Bartelt, Heiner Stuckenschmidt |
| 2024 | Fair-OBNC: Correcting Label Noise for Fairer Datasets. Inês Oliveira e Silva, Sérgio M. Jesus, Hugo M. Ferreira, Pedro Saleiro, Inês Sousa, Pedro Bizarro, Carlos Soares |
| 2024 | FairCognizer: A Model for Accurate Predictions with Inherent Fairness Evaluation. Adda-Akram Bendoukha, Nesrine Kaaniche, Aymen Boudguiga, Renaud Sirdey |
| 2024 | FairUS - UpSampling Optimized Method for Boosting Fairness. Nurit Cohen-Inger, Guy Rozenblatt, Seffi Cohen, Lior Rokach, Bracha Shapira |
| 2024 | Fairness Auditing with Multi-Agent Collaboration. Martijn de Vos, Akash Balasaheb Dhasade, Jade Garcia Bourrée, Anne-Marie Kermarrec, Erwan Le Merrer, Benoît Rottembourg, Gilles Trédan |
| 2024 | Fairness in Repeated House Allocation. Karl Jochen Micheel, Anaëlle Wilczynski |
| 2024 | FedMTL: Privacy-Preserving Federated Multi-Task Learning. Pritam Sen, Cristian Borcea |
| 2024 | FedReMa: Improving Personalized Federated Learning via Leveraging the Most Relevant Clients. Han Liang, Ziwei Zhan, Weijie Liu, Xiaoxi Zhang, Chee Wei Tan, Xu Chen |
| 2024 | FedSeProto: Learning Semantic Prototype in Federated Learning. Yanyi Lai, Lele Fu, Tianchi Liao, Chuan Chen, Zibin Zheng |
| 2024 | FedStale: leveraging Stale Updates in Federated Learning. Angelo Rodio, Giovanni Neglia |
| 2024 | Federated Learning with Hybrid Knowledge Distillations on Long-Tailed Heterogeneous Client Data. Senbin Liu, Yuanting Zhang, Kunhua Zhang, Yi Wang |
| 2024 | Federated Online Learning for Heavy Hitter Detection. Paula Raissa Silva, João Vinagre, João Gama |
| 2024 | Federation-Paced Learning: Towards Efficient Federated Learning with Synchronized Pace. Tingting Zhang, Mei Cao, Zhenge Jia, Jianbo Lu, Zhaoyan Shen, Dongxiao Yu, Mengying Zhao |
| 2024 | FenGe-An Interactive Framework for Improving the Utility of Deep Dune Segmentation in Geographical Tasks. Zheng Jiang, Anqi Lu, Zifeng Wu, Wei Wang, Gaowei Zhang, Eerdun Hasi, Yi Wang |
| 2024 | Few-Shot Object Detection with Instance Feature Generation and Hybrid Contrastive Learning. Yuhui Wang, Bo Peng, Tianyi Qin, Jiahui Song, Xu Zhang |
| 2024 | FilFL: Client Filtering for Optimized Client Participation in Federated Learning. Fares Fourati, Salma Kharrat, Vaneet Aggarwal, Mohamed-Slim Alouini, Marco Canini |
| 2024 | Finding Optimal Deterministic Policies for Constrained Stochastic Shortest Path Problems. Johannes Schmalz, Felipe W. Trevizan |
| 2024 | First Creating Backgrounds Then Rendering Texts: A New Paradigm for Visual Text Blending. Zhenhang Li, Yan Shu, Weichao Zeng, Dongbao Yang, Yu Zhou |
| 2024 | FlexSSL : A Generic and Efficient Framework for Semi-Supervised Learning. Huiling Qin, Xianyuan Zhan, Yuanxun Li, Yu Zheng |
| 2024 | FlowLearn: Evaluating Large Vision-Language Models on Flowchart Understanding. Huitong Pan, Qi Zhang, Cornelia Caragea, Eduard C. Dragut, Longin Jan Latecki |
| 2024 | FltLM: An Intergrated Long-Context Large Language Model for Effective Context Filtering and Understanding. Jingyang Deng, Zhengyang Shen, Boyang Wang, Lixin Su, Suqi Cheng, Ying Nie, Junfeng Wang, Dawei Yin, Jinwen Ma |
| 2024 | Frisbees and Dogs: Domain Adaptation for Object Detection with Limited Labels in Rugby Data. Will Connors, Ellen Rushe, Anthony Ventresque |
| 2024 | From Document to Program Embeddings: Can Distributional Hypothesis Really Be Used on Programming Languages? Thibaut Martinet, Guillaume Cleuziou, Matthieu Exbrayat, Frédéric Flouvat |
| 2024 | FsPONER: Few-Shot Prompt Optimization for Named Entity Recognition in Domain-Specific Scenarios. Yongjian Tang, Rakebul Hasan, Thomas A. Runkler |
| 2024 | Fully Hyperbolic Rotation for Knowledge Graph Embedding. Qiuyu Liang, Weihua Wang, Feilong Bao, Guanglai Gao |
| 2024 | Fuzzy Ensemble Learning and Lightweight CNN for Stress Classification. Katarzyna R. Baran |
| 2024 | GABInsight: Exploring Gender-Activity Binding Bias in Vision-Language Models. Ali Abdollahi, Mahdi Ghaznavi, Mohammad Reza Karimi Nejad, Arash Mari Oriyad, Reza Abbasi, Ali Salesi, Melika Behjati, Mohammad Hossein Rohban, Mahdieh Soleymani Baghshah |
| 2024 | GIF: An Automated Genomic Information Finder to Extract Data from Reports. Pavithra Rajendran, Alexandros Zenonos, Sebin Sabu, Anastasia Spiridou, Helena Spiridou Goncalves, Nastazja Laskowski, Daniel Key, Shiren Patel, Rebecca Pope, Neil Sebire |
| 2024 | GLIMMER: Incorporating Graph and Lexical Features in Unsupervised Multi-Document Summarization. Ran Liu, Ming Liu, Min Yu, Jianguo Jiang, Gang Li, Dan Zhang, Jingyuan Li, Xiang Meng, Weiqing Huang |
| 2024 | GRIF-DM: Generation of Rich Impression Fonts Using Diffusion Models. Lei Kang, Fei Yang, Kai Wang, Mohamed Ali Souibgui, Lluís Gómez, Alicia Fornés, Ernest Valveny, Dimosthenis Karatzas |
| 2024 | Gas Grid Copilot: Can a MORL Agent Assist a Dispatcher in Managing a Gas Grid? Alexander Schiendorfer, Gheorghe Lisca, Karima Outafraout, Lilia Michailov, Pascal Kätzel, Rudolf Felix |
| 2024 | General Lipschitz: Certified Robustness Against Resolvable Semantic Transformations via Transformation-Dependent Randomized Smoothing. Dmitrii Korzh, Mikhail Pautov, Olga Tsymboi, Ivan V. Oseledets |
| 2024 | Generalized Face Anti-Spoofing via Finer Domain Partition and Disentangling Liveness-Irrelevant Factors. Jingyi Yang, Zitong Yu, Xiuming Ni, Jia He, Hui Li |
| 2024 | Generalizing Visual Question Answering from Synthetic to Human-Written Questions via a Chain of QA with a Large Language Model. Taehee Kim, Yeongjae Cho, Heejun Shin, Yohan Jo, Dongmyung Shin |
| 2024 | Generating Fair Solutions of Minimal Cost. Mohammed Bachir Bederina, Djamal Chaabane, Thibaut Lust |
| 2024 | Generating SROI Yunjie He, Daniel Hernández, Mojtaba Nayyeri, Bo Xiong, Yuqicheng Zhu, Evgeny Kharlamov, Steffen Staab |
| 2024 | Generative LLMs for Multilingual Temporal Expression Normalization. Alejandro Sánchez-de-Castro-Fernández, Lourdes Araujo, Juan Martínez-Romo |
| 2024 | Generative Pretrained Embedding and Hierarchical Irregular Time Series Representation for Daily Living Activity Recognition. Damien Bouchabou, Sao Mai Nguyen |
| 2024 | Global Optimisation of Black-Box Functions with Generative Models in the Wasserstein Space. Tigran Ramazyan, Mikhail Hushchyn, Denis Derkach |
| 2024 | Global Structural-Temporal Graph Network with Public Opinion for Online Rumor Detection. Tiening Sun, Zhong Qian, Peifeng Li, Qiaoming Zhu |
| 2024 | Good Things Come to Those Who Wait: The Power of Sensing in Social Laws. Alexander Tuisov, Alexander Shleyfman, Erez Karpas |
| 2024 | Gotta Catch 'Em All! Sequence Flaws in CEGAR for Classical Planning. Martín Pozo, Álvaro Torralba, Carlos Linares López |
| 2024 | Graph Classification with GNNs: Optimisation, Representation & Inductive Bias. P. Krishna Kumar, Harish G. Ramaswamy |
| 2024 | Graph Continual Learning with Debiased Lossless Memory Replay. Chaoxi Niu, Guansong Pang, Ling Chen |
| 2024 | GraphFSA: A Finite State Automaton Framework for Algorithmic Learning on Graphs. Florian Grötschla, Joël Mathys, Christoffer Raun, Roger Wattenhofer |
| 2024 | Graphite: A Graph-Based Extreme Multi-Label Short Text Classifier for Keyphrase Recommendation. Ashirbad Mishra, Soumik Dey, Jinyu Zhao, Marshall Wu, Binbin Li, Kamesh Madduri |
| 2024 | Group Fairness with Individual and Censorship Constraints. Zichong Wang, Wenbin Zhang |
| 2024 | Grouped Logit Distillation Enhanced with Superclass Awareness for Efficient Knowledge Transfer. Shuoxi Zhang, Hanpeng Liu, Yuyi Wang, Kun He |
| 2024 | HAIformer: Human-AI Collaboration Framework for Disease Diagnosis via Doctor-Enhanced Transformer. Xuehan Zhao, Jiaqi Liu, Yao Zhang, Zhiwen Yu, Bin Guo |
| 2024 | HBIC: A Biclustering Algorithm for Heterogeneous Datasets. Adán José García, Julie Jacques, Clément Chauvet, Vincent Sobanski, Clarisse Dhaenens |
| 2024 | Hard to Explain: On the Computational Hardness of In-Distribution Model Interpretation. Guy Amir, Shahaf Bassan, Guy Katz |
| 2024 | Harnessing Orthogonality to Train Low-Rank Neural Networks. Daniel Coquelin, Katharina Flügel, Marie Weiel, Nicholas Kiefer, Charlotte Debus, Achim Streit, Markus Götz |
| 2024 | Heuristics for Partially Observable Stochastic Contingent Planning. Guy Shani |
| 2024 | Hidden States in LLMs Improve EEG Representation Learning and Visual Decoding. Aoyang Liu, Haodong Jing, Yulong Liu, Yongqiang Ma, Nanning Zheng |
| 2024 | Hierarchical Average-Reward Linearly-Solvable Markov Decision Processes. Guillermo Infante, Anders Jonsson, Vicenç Gómez |
| 2024 | Hierarchical Planning for Resource-Constrained Long-Term Monitoring Missions in Time-Varying Environments. Alex Stephens, Bruno Lacerda, Nick Hawes |
| 2024 | High-Dimensional Causal Bayesian Optimization. Yupeng Wu, Weiye Wang, Yangwenhui Zhang, Mingjia Li, Yuanhao Liu, Hong Qian, Aimin Zhou |
| 2024 | High-Quality Human Motion Prediction Using Size Invariant Motion Space. Haichuan Zhao, Xudong Ru, Peng Du, Shaolong Liu, Na Liu, Xingce Wang, Zhongke Wu |
| 2024 | Hop-based Heterogeneous Graph Transformer. Zixuan Yang, Xiao Wang, Yanhua Yu, Yuling Wang, Kangkang Lu, Zirui Guo, Xiting Qin, Yunshan Ma, Tat-Seng Chua |
| 2024 | How to Guide a Present-Biased Agent Through Prescribed Tasks? Tatiana Belova, Yuriy Dementiev, Fedor V. Fomin, Petr A. Golovach, Artur Ignatiev |
| 2024 | HyenaPixel: Global Image Context with Convolutions. Julian Spravil, Sebastian Houben, Sven Behnke |
| 2024 | Hyperbolic Contrastive Learning for Document Representations - A Multi-View Approach with Paragraph-level Similarities. JaeEun Nam, Ilias Chalkidis, Mina Rezaei |
| 2024 | Hyperparameter Importance Analysis for Multi-Objective AutoML. Daphne Theodorakopoulos, Frederic T. Stahl, Marius Lindauer |
| 2024 | I-Adapt: Using IoU Adapter to Improve Pseudo Labels in Cross-Domain Object Detection. Qifeng Zhang, Changjian Chen, Zhizhong Liu, Zhuo Tang |
| 2024 | IFH: A Diffusion Framework for Flexible Design of Graph Generative Models. Samuel Cognolato, Alessandro Sperduti, Luciano Serafini |
| 2024 | IPA-NeRF: Illusory Poisoning Attack Against Neural Radiance Fields. Wenxiang Jiang, Hanwei Zhang, Shuo Zhao, Zhongwen Guo, Hao Wang |
| 2024 | Identifying the Best Arm in the Presence of Global Environment Shifts. Phurinut Srisawad, Juergen Branke, Long Tran-Thanh |
| 2024 | Improving Aspect-Based Sentiment Analysis via Tuple-Order Learning. Gongzhen Hu, Yuanjun Liu, Xiabing Zhou, Min Zhang |
| 2024 | Improving Calibration by Relating Focal Loss, Temperature Scaling, and Properness. Viacheslav Komisarenko, Meelis Kull |
| 2024 | Improving Non-Autoregressive Sign Language Translation with Random Ordering Progressive Prediction Pretraining. Pei Yu, Changhao Lai, Cong Hu, Shan Liu, Liang Zhang, Biao Fu, Yidong Chen |
| 2024 | Improving Process Yield Through Manufacturing Digital Twin Using Conditional Synthetic Data Engine (COSYNE). Shantanu Chandra, Matthieu Duvinage, PKS Prakash, Patrick Davis, Sander Timmer |
| 2024 | Improving the Performance of Transformer-Based Models Over Classical Baselines in Multiple Transliterated Languages. Fahim Ahmed, Md Fahim, Md. Ashraful Amin, Amin Ahsan Ali, AKM Mahbubur Rahman |
| 2024 | In-Network Machine Learning for Real-Time Transaction Fraud Detection. Xinpeng Hong, Changgang Zheng, Noa Zilberman |
| 2024 | IndMask: Inductive Explanation for Multivariate Time Series Black-Box Models. Seham Nasr, Sandipan Sikdar |
| 2024 | Individual Fairness with Group Constraints in Graph Neural Networks. Zichong Wang, David Ulloa, Tongjia Yu, Raju Rangaswami, Roland H. C. Yap, Wenbin Zhang |
| 2024 | Informed Spectral Normalized Gaussian Processes for Trajectory Prediction. Christian Schlauch, Christian Wirth, Nadja Klein |
| 2024 | Inside the Black Box: Detecting Data Leakage in Pre-Trained Language Encoders. Yuan Xin, Zheng Li, Ning Yu, Dingfan Chen, Mario Fritz, Michael Backes, Yang Zhang |
| 2024 | InsideOut: Unifying Emotional LLMs to Foster Empathy. Mikhail Mozikov, Nikita Severin, Maria Glushanina, Mikhail Baklashkin, Andrey V. Savchenko, Ilya Makarov |
| 2024 | Instruction Following with Goal-Conditioned Reinforcement Learning in Virtual Environments. Zoya Volovikova, Alexey Skrynnik, Petr Kuderov, Aleksandr I. Panov |
| 2024 | Interactive Example-Based Explanations to Improve Health Professionals' Onboarding with AI for Human-AI Collaborative Decision Making. Min Hun Lee, Renee Bao Xuan Ng, Silvana Xin Yi Choo, Shamala D/O Thilarajah |
| 2024 | Interactive and Iterative Peer Assessment. Lihi Dery |
| 2024 | Interpretable Graph Neural Networks for Tabular Data. Amr Alkhatib, Sofiane Ennadir, Henrik Boström, Michalis Vazirgiannis |
| 2024 | Interpretable Image Classification Through an Argumentative Dialog Between Encoders. Dao Thauvin, Stéphane Herbin, Wassila Ouerdane, Céline Hudelot |
| 2024 | Interpretation of the Intent Detection Problem as Dynamics in a Low-Dimensional Space. Eduardo Sánchez-Karhunen, Jose F. Quesada-Moreno, Miguel A. Gutiérrez-Naranjo |
| 2024 | Is Contrasting All You Need? Contrastive Learning for the Detection and Attribution of AI-generated Text. Lucio La Cava, Davide Costa, Andrea Tagarelli |
| 2024 | Iterative Oversubscription Planning with Goal-Conflict Explanations: Scaling Up Through Policy-Guidance Approximation. Rebecca Eifler, Daniel Fiser, Aleena Siji, Jörg Hoffmann |
| 2024 | Iteratively Calibrating Prompts for Unsupervised Diverse Opinion Summarization. Jian Wang, Yuqing Sun, Yanjie Liang, Xin Li, Bin Gong |
| 2024 | JOSAL: Joint Learning Framework for Open-Set Active Learning. Jun Xie, Xiaohui Song, Yangjie Cao, Zhi Liu, Weiping Wang, Hongli Xu |
| 2024 | KGPRUNE: A Web Application to Extract Subgraphs of Interest from Wikidata with Analogical Pruning. Pierre Monnin, Cherif-Hassan Nousradine, Lucas Jarnac, Laurel Zuckerman, Miguel Couceiro |
| 2024 | LGAD: Local and Global Attention Distillation for Efficient Semantic Segmentation. Chen Wang, Yafei Qi, Qi Li, Huawen Liu |
| 2024 | Label Attention Network for Temporal Sets Prediction: You Were Looking at a Wrong Self-Attention. Elizaveta Kovtun, Galina Boeva, Andrey Shulga, Alexey Zaytsev |
| 2024 | Laner-GNN: Adapting to Long-Tail Degree Distribution with Latent Neighborhood Restorers. Lingjun Xu, Haowen Li, Guojie Song, Liang Wang, Bo Zheng |
| 2024 | Language Task Difficulty Prediction Through LLM-Annotated Meta-Features. Yael Moros-Daval, Fernando Martínez-Plumed, José Hernández-Orallo |
| 2024 | Large Language Model Agentic Approach to Fact Checking and Fake News Detection. Xinyi Li, Yongfeng Zhang, Edward C. Malthouse |
| 2024 | Large Language Model Prompting with Episodic Memory. Dai Do, Quan Tran, Svetha Venkatesh, Hung Le |
| 2024 | Large Language Models Understand Layout. Weiming Li, Manni Duan, Dong An, Yan Shao |
| 2024 | Learning A Closed-Loop Bidirectional Scale-Recurrent Network for Image Deraining. Peizhou Huang, Zixuan Zhong, Pengjie Wang, Xiangyu Wang, Xiang Chen |
| 2024 | Learning After Learning: Positive Backward Transfer in Continual Learning. Wernsen Wong, Yun Sing Koh, Gillian Dobbie |
| 2024 | Learning Backdoors for Mixed Integer Linear Programs with Contrastive Learning. Junyang Cai, Taoan Huang, Bistra Dilkina |
| 2024 | Learning Brave Assumption-Based Argumentation Frameworks via ASP. Emanuele De Angelis, Maurizio Proietti, Francesca Toni |
| 2024 | Learning Compact Neural Networks via Generalized Structured Sparsity. Ke Bian, Lu Sun, Dengji Zhao |
| 2024 | Learning Compositional, Time-Varying Neural Barrier Contracts. Matthew Low, Timothy E. Wang, Pierluigi Nuzzo |
| 2024 | Learning Confidence Bounds for Classification with Imbalanced Data. Matthew Clifford, Jonathan Erskine, Alexander Hepburn, Raúl Santos-Rodríguez, Dario García-García |
| 2024 | Learning Interpretable Classifiers for PDDL Planning. Arnaud Lequen |
| 2024 | Learning Joint Models of Prediction and Optimization. James Kotary, Vincenzo Di Vito, Jacob Christopher, Pascal Van Hentenryck, Ferdinando Fioretto |
| 2024 | Learning Logic Programs by Finding Minimal Unsatisfiable Subprograms. Andrew Cropper, Céline Hocquette |
| 2024 | Learning Order Forest for Qualitative-Attribute Data Clustering. Mingjie Zhao, Sen Feng, Yiqun Zhang, Mengke Li, Yang Lu, Yiu-ming Cheung |
| 2024 | Learning Reward Structure with Subtasks in Reinforcement Learning. Shuai Han, Mehdi Dastani, Shihan Wang |
| 2024 | Learning Uncertainty Tubes via Recurrent Neural Networks for Planning Robust Robot Motions. Simon Wasiela, Smail Ait Bouhsain, Marco Cognetti, Juan Cortés, Thierry Siméon |
| 2024 | Learning a Mini-Batch Graph Transformer via Two-Stage Interaction Augmentation. Wenda Li, Kaixuan Chen, Shunyu Liu, Tongya Zheng, Wenjie Huang, Mingli Song |
| 2024 | Learning and Optimizing with an SSB Representation of Intransitive Preferences on Sets. Hugo Gilbert, Mohamed Ouaguenouni, Olivier Spanjaard |
| 2024 | Learning in Multi-Objective Public Goods Games with Non-Linear Utilities. Nicole Orzan, Erman Acar, Davide Grossi, Patrick Mannion, Roxana Radulescu |
| 2024 | Less is More: Efficient Brain-Inspired Learning for Autonomous Driving Trajectory Prediction. Haicheng Liao, Yongkang Li, Zhenning Li, Chengyue Wang, Guofa Li, Chunlin Tian, Zilin Bian, Kaiqun Zhu, Zhiyong Cui, Jia Hu |
| 2024 | Leveraging Foundation Models for Zero-Shot IoT Sensing. Dinghao Xue, Xiaoran Fan, Tao Chen, Guohao Lan, Qun Song |
| 2024 | Leveraging User-Generated Reviews for Recommender Systems with Dynamic Headers. Shanu Vashishtha, Abhay Kumar, Lalitesh Morishetti, Kaushiki Nag, Kannan Achan |
| 2024 | License Plate Images Generation with Diffusion Models. Mariia Shpir, Nadiya Shvai, Amir Nakib |
| 2024 | LightFF: Lightweight Inference for Forward-Forward Algorithm. Amin Aminifar, Baichuan Huang, Azra Abtahi, Amir Aminifar |
| 2024 | Lightweight Transformer for sEMG Gesture Recognition with Feature Distilled Variational Information Bottleneck. Zefeng Wang, Bingbing Hu, Junfeng Yao, Jinsong Su |
| 2024 | Limited Voting for Better Representation? Maaike Venema-Los, Zoé Christoff, Davide Grossi |
| 2024 | Link Prediction Without Learning. Simon Delarue, Thomas Bonald, Tiphaine Viard |
| 2024 | LoCa: Logit Calibration for Knowledge Distillation. Runming Yang, Taiqiang Wu, Yujiu Yang |
| 2024 | Locally-Minimal Probabilistic Explanations. Yacine Izza, Kuldeep S. Meel, João Marques-Silva |
| 2024 | LoginMEA: Local-to-Global Interaction Network for Multi-Modal Entity Alignment. Taoyu Su, Xinghua Zhang, Jiawei Sheng, Zhenyu Zhang, Tingwen Liu |
| 2024 | MAMO: Multi-Task Architecture Learning via Multi-Objective and Gradients Mediative Kernel. Yuzheng Tan, Guangneng Hu, Shuxin Zhang |
| 2024 | MC-SORT: A Motion Correction-Based Framework for Long-Term Multiple Object Tracking. Xiangyu Li, Yunchuan Qin, Ruihui Li, Guanghua Tan, Zhuo Tang, Kenli Li |
| 2024 | MCAHNN: Multi-Channel EEG Emotion Recognition Using Attention Mechanism Based on Householder Reflection. Qinglong Liu, Wenhao Jiang, Shihang Ding, Kaixuan Wang, Hongjian Bo, Cong Xu, Lin Ma, Haifeng Li |
| 2024 | MEFusion: Unsupervised Mutual Enhancement for Multimodal Image Fusion. Yushe Cao, Siwen Jiao, Penghao Sun, Baoyun Peng, Dianxi Shi, Yuanchun Shi |
| 2024 | MFF-YOLO: Multi-scale Feature Fusion Network for Small Ship Detection in Night Scenes. Guangyu Li, Jun Li, Hai Cao, Houjun Wang, Weili Guo, Chen Gong |
| 2024 | MIM-HD: Making Smaller Masked Autoencoder Better with Efficient Distillation. Zherui Zhang, Changwei Wang, Rongtao Xu, Wenhao Xu, Shibiao Xu, Li Guo, Jiguang Zhang, Xiaoqiang Teng, Wenbo Xu |
| 2024 | MLGAT: Multi-Scale Line Graph Attention Network for Emotion Recognition in Conversation. Xiujuan Xu, Xiaoxiao Shi, Zhehuan Zhao, Yu Liu |
| 2024 | MPT4LM: Multi-Modal Prompt Tuning Makes Pre-Trained Large Language Models Better Vision-Language Learners. Yongzhu Miao, Jintao Tang, Shasha Li, Ting Wang |
| 2024 | Machine Learning for Quantifier Selection in cvc5. Jan Jakubuv, Mikolás Janota, Jelle Piepenbrock, Josef Urban |
| 2024 | MakeupAttack: Feature Space Black-Box Backdoor Attack on Face Recognition via Makeup Transfer. Ming Sun, Lihua Jing, Zixuan Zhu, Rui Wang |
| 2024 | Making Fair Classification via Correlation Alignment. Jingran Yang, Lingfeng Zhang, Min Zhang |
| 2024 | Mask-Encoded Sparsification: Mitigating Biased Gradients in Communication-Efficient Split Learning. Wenxuan Zhou, Zhihao Qu, Shen-Huan Lyu, Miao Cai, Baoliu Ye |
| 2024 | Match'In - Pilot Project of an Algorithm-Based Decision Support System for Individualized Recommendations of Municipalities for the Integration of Refugees. Christian Sauer, Carsten Wenzel, Katharina Euler, Sonja Reinhold, Frank Wuttke, Björn Oitmann |
| 2024 | Matching Gains with Pays: Effective and Fair Learning in Multi-Agent Public Goods Dilemmas. Yitian Chen, Xuan Liu, Shigeng Zhang, Xinning Chen, Song Guo |
| 2024 | Maximally Permissive Reward Machines. Giovanni Varricchione, Natasha Alechina, Mehdi Dastani, Brian Logan |
| 2024 | Measuring User Understanding in Dialogue-Based xAI Systems. Dimitry Mindlin, Amelie Sophie Robrecht, Michael Morasch, Philipp Cimiano |
| 2024 | Mechanism Design for Extending the Accessibility of Facilities. Hau Chan, Jianan Lin, Chenhao Wang, Yanxi Xie |
| 2024 | Memory Adaptive and Spatially Specialized Model Ensembles for Industrial Anomaly Detection. Marco Wagenstetter, Niklas Landerer, Johannes Thyroff, Thomas Aicher, Arvid Hellmich, Steffen Ihlenfeldt |
| 2024 | Merge-and-Shrink Heuristics for SSPs with Prune Transformations. Thorsten Klößner, Álvaro Torralba, Marcel Steinmetz, Silvan Sievers |
| 2024 | Merit-Based Fair Combinatorial Semi-Bandit with Unrestricted Feedback Delays. Ziqun Chen, Kechao Cai, Zhuoyue Chen, Jinbei Zhang, John C. S. Lui |
| 2024 | Meta-Mechanisms for Combinatorial Auctions over Social Networks. Yuan Fang, Mengxiao Zhang, Jiamou Liu, Bakh Khoussainov |
| 2024 | Mind the Model, Not the Agent: The Primacy Bias in Model-Based RL. Zhongjian Qiao, Jiafei Lyu, Xiu Li |
| 2024 | MindScope: Exploring Cognitive Biases in Large Language Models Through Multi-Agent Systems. Zhentao Xie, Jiabao Zhao, Yilei Wang, Jinxin Shi, Yanhong Bai, Xingjiao Wu, Liang He |
| 2024 | Mitigating Bias: Model Pruning for Enhanced Model Fairness and Efficiency. Harsh Kasyap, Ugur-Ilker Atmaca, Michela Iezzi, Toby Walsh, Carsten Maple |
| 2024 | MixCon: A Hybrid Architecture for Efficient and Adaptive Sequence Modeling. Xin Xu, Zhouchen Lin |
| 2024 | Mixup Your Own Latent: Efficient and Robust Self-Supervised Learning on Small Images. Eugene Yang, Hao Chen, Seokho Kang |
| 2024 | MoSt-DSA: Modeling Motion and Structural Interactions for Direct Multi-Frame Interpolation in DSA Images. Ziyang Xu, Huangxuan Zhao, Ziwei Cui, Wenyu Liu, Chuansheng Zheng, Xinggang Wang |
| 2024 | Modality-Aware and Shift Mixer for Multi-Modal Brain Tumor Segmentation. Zhongzhen Huang, Linda Wei, Shaoting Zhang, Xiaofan Zhang |
| 2024 | Model Priming with Triplet Loss for Few-Shot Emotion Classification in Text. Jens Lemmens, Walter Daelemans |
| 2024 | Model Provenance via Model DNA. Xin Mu, Yu Wang, Yehong Zhang, Jiaqi Zhang, Hui Wang, Yang Xiang, Yue Yu |
| 2024 | Modelling Brain Connectomes Networks: Solv is a Worthy Competitor to Hyperbolic Geometry! Dorota Celinska-Kopczynska, Eryk Kopczynski |
| 2024 | Modelling Diffusion of Dependent and Conflicting Behaviours with Dynamic Logic. Gabriel de Senne Amorim, Marlo Souza, Álvaro Freitas Moreira |
| 2024 | Molecular Topological Profile (MOLTOP) - Simple and Strong Baseline for Molecular Graph Classification. Jakub Adamczyk, Wojciech Czech |
| 2024 | Monte Carlo Tree Search with State Merging for Reinforcement Learning in Regular Decision Processes. Gabriel Paludo Licks, Fabio Patrizi, Giuseppe De Giacomo |
| 2024 | More (Enough) Is Better: Towards Few-Shot Illegal Landfill Waste Segmentation. Matías Molina, Bruno Veloso, Carlos Abreu Ferreira, Rita P. Ribeiro, João Gama |
| 2024 | Multi-Agent Path Finding with Real Robot Dynamics and Interdependent Tasks for Automated Warehouses. Vassilissa Lehoux-Lebacque, Tomi Silander, Christelle Loiodice, Seungjoon Lee, Albert Wang, Sofia Michel |
| 2024 | Multi-Agent Path Finding with Task Assignment and Supporting Constraints. Caroline Bonhomme, Christophe Grand, Charles Lesire, Jean-Louis Dufour, Christophe Guettier |
| 2024 | Multi-Agent Planning Using Visual Language Models. Michele Brienza, Francesco Argenziano, Vincenzo Suriani, Domenico Daniele Bloisi, Daniele Nardi |
| 2024 | Multi-Agent Reinforcement Learning for Alternating-Time Logic. Ernst Moritz Hahn, Mateo Perez, Sven Schewe, Fabio Somenzi, Ashutosh Trivedi, Dominik Wojtczak |
| 2024 | Multi-View Prompt for Fine-Grained Multimodal Named Entity Recognition and Grounding. Jintao Liu, Chenglong Liu, Kaiwen Wei |
| 2024 | MultiCounter: Multiple Action Agnostic Repetition Counting in Untrimmed Videos. Yin Tang, Wei Luo, Jinrui Zhang, Wei Huang, Ruihai Jing, Deyu Zhang |
| 2024 | Multiwinner Temporal Voting with Aversion to Change. Valentin Zech, Niclas Boehmer, Edith Elkind, Nicholas Teh |
| 2024 | Mutual Local Consistency Learning for Face Forgery Detection. Bosheng Yan, Chang-Tsun Li |
| 2024 | Natural Mitigation of Catastrophic Interference: Continual Learning in Power-Law Learning Environments. Atith Gandhi, Raj Sanjay Shah, Sashank Vijay, Marupudia Varma |
| 2024 | Navigating Trade-offs: Policy Summarization for Multi-Objective Reinforcement Learning. Zuzanna Osika, Jazmin Zatarain Salazar, Frans A. Oliehoek, Pradeep K. Murukannaiah |
| 2024 | NeSIG: A Neuro-Symbolic Method for Learning to Generate Planning Problems. Carlos Núñez-Molina, Pablo Mesejo, Juan Fernández-Olivares |
| 2024 | NeurCAM: Interpretable Neural Clustering via Additive Models. Nakul Upadhya, Eldan Cohen |
| 2024 | Neural Reward Machines. Elena Umili, Francesco Argenziano, Roberto Capobianco |
| 2024 | Night-to-Day: Unpaired Image-to-Image Translation for Nighttime Pedestrian Detection. Afnan Althoupety, Li-Yun Wang, Wu-chi Feng, Banafsheh Rekabdar |
| 2024 | Nissist: An Incident Mitigation Copilot based on Troubleshooting Guides. Kaikai An, Fangkai Yang, Junting Lu, Liqun Li, Zhixing Ren, Hao Huang, Lu Wang, Pu Zhao, Yu Kang, Hua Ding, Qingwei Lin, Saravan Rajmohan, Dongmei Zhang, Qi Zhang |
| 2024 | No Transaction Fees? No Problem! Achieving Fairness in Transaction Fee Mechanism Design. Sankarshan Damle, Varul Srivastava, Sujit Gujar |
| 2024 | Noise-Free Explanation for Driving Action Prediction. Hongbo Zhu, Theodor Wulff, Rahul Singh Maharjan, Jinpei Han, Angelo Cangelosi |
| 2024 | Novelty Accommodating Multi-Agent Planning in High Fidelity Simulated Open World. James Chao, Wiktor Piotrowski, Roni Stern, Héctor J. Ortiz-Peña, Mitch Manzanares, Shiwali Mohan, Douglas S. Lange |
| 2024 | Objective-Informed Diversity for Multi-Objective Multiagent Coordination. Gaurav Dixit, Kagan Tumer |
| 2024 | Offline Model-Based Reinforcement Learning with Anti-Exploration. Padmanaba Srinivasan, William Knottenbelt |
| 2024 | OmniCLIP: Adapting CLIP for Video Recognition with Spatial-Temporal Omni-Scale Feature Learning. Mushui Liu, Bozheng Li, Yunlong Yu |
| 2024 | On Connected Strongly-Proportional Cake-Cutting. Zsuzsanna Jankó, Attila Joó, Erel Segal-Halevi, Sheung Man Yuen |
| 2024 | On Explaining with Attention Matrices. Omar Naim, Nicholas Asher |
| 2024 | On Parallel External-Memory Bidirectional Search. Lior Siag, Shahaf S. Shperberg, Ariel Felner, Nathan R. Sturtevant |
| 2024 | On the Computation of Contrastive Explanations for Boosted Regression Trees. Gilles Audemard, Jean-Marie Lagniez, Pierre Marquis |
| 2024 | On the Cultural Gap in Text-to-Image Generation. Bingshuai Liu, Longyue Wang, Chenyang Lyu, Yong Zhang, Jinsong Su, Shuming Shi, Zhaopeng Tu |
| 2024 | On the Discovery of Conceptual Clustering Models Through Pattern Mining. Motaz Ben Hassine, Saïd Jabbour, Mourad Kmimech, Badran Raddaoui, Mohamed Graiet |
| 2024 | On the Effects of Irrelevant Variables in Treatment Effect Estimation with Deep Disentanglement. Ahmad Saeed Khan, Erik Schaffernicht, Johannes Andreas Stork |
| 2024 | On the Improvement of Generalization and Stability of Forward-Only Learning via Neural Polarization. Erik B. Terres-Escudero, Javier Del Ser, Pablo García Bringas |
| 2024 | One-Shot Collaborative Data Distillation. William Holland, Chandra Thapa, Wei Shao, Seyit Camtepe, Sarah Ali Siddiqui |
| 2024 | Online Friends Partitioning Under Uncertainty. Saar Cohen, Noa Agmon |
| 2024 | Ontology Text Alignment: Aligning Textual Content to Terminological Axioms. Jieying Chen, Hang Dong, Jiaoyan Chen, Ian Horrocks |
| 2024 | Open-Set Multivariate Time-Series Anomaly Detection. Thomas Lai, Thi Kieu Khanh Ho, Narges Armanfard |
| 2024 | Optimal Diffusion Auctions. Yao Zhang, Shanshan Zheng, Dengji Zhao |
| 2024 | Optimal Layout-Aware CNOT Circuit Synthesis with Qubit Permutation. Irfansha Shaik, Jaco van de Pol |
| 2024 | Optimizing Multi-Robot Task Allocation in Dynamic Environments via Heuristic-Guided Reinforcement Learning. Aritra Pal, Anandsingh Chauhan, Mayank Baranwal, Ankush Ojha |
| 2024 | PAGE: Parametric Generative Explainer for Graph Neural Network. Yang Qiu, Wei Liu, Jun Wang, Ruixuan Li |
| 2024 | PEACE: Providing Explanations and Analysis for Combating Hate Expressions. Greta Damo, Nicolás Benjamín Ocampo, Elena Cabrio, Serena Villata |
| 2024 | PLACO: A Multi-Stage Framework for Cost-Effective Performance in Human-AI Teams. Pranavkumar Mallela, Vinay Kumar, Shashi Shekhar Jha, Shweta Jain |
| 2024 | PUFFLE: Balancing Privacy, Utility, and Fairness in Federated Learning. Luca Corbucci, Mikko A. Heikkilä, David Solans Noguero, Anna Monreale, Nicolas Kourtellis |
| 2024 | Parameter Estimation of Long Memory Stochastic Processes with Deep Neural Networks. Bálint Csanády, Lóránt Nagy, Dániel Boros, Iván Ivkovic, Dávid Kovács, Dalma Tóth-Lakits, Zsolt László Márkus, András Lukács |
| 2024 | Parameterized Algorithms for Optimal Refugee Resettlement. Jiehua Chen, Ildikó Schlotter, Sofia Simola |
| 2024 | Partial Label Learning via Cost-Guided Retraining. Zhaoyuan Zhang, Zhenbing Liu, Haoxiang Lu |
| 2024 | Perturb-and-Compare Approach for Detecting Out-of-Distribution Samples in Constrained Access Environments. Heeyoung Lee, Hoyoon Byun, Changdae Oh, JinYeong Bak, Kyungwoo Song |
| 2024 | Pessimistic Off-Policy Optimization for Learning to Rank. Matej Cief, Branislav Kveton, Michal Kompan |
| 2024 | Phy-CoCo: Physical Constraint-Based Correlation Learning for Tropical Cyclone Intensity and Size Estimation. Hanting Yan, Pan Mu, Cheng Huang, Jinglin Zhang, Cong Bai |
| 2024 | Physics-Assisted Explainable Anomaly Detection in Power Systems. Matthew Lau, Fahad Alsaeed, Kayla Thames, Nano Suresettakul, Saman A. Zonouz, Wenke Lee, Athanasios P. Meliopoulos |
| 2024 | Pixel-wise Reclassification with Prototypes for Enhancing Weakly Supervised Semantic Segmentation. Yujie Diao, Ruiguo Yu, Xuewei Li, Yilong Fan, Zhiqiang Liu, Mei Yu, Chenhan Wang, Jie Gao |
| 2024 | Placement Aware Grasp Planning for Efficient Sequential Manipulation. Juhan Park, Daejong Jin, Kyungjae Lee |
| 2024 | Planning for Human-Robot Collaboration Scenarios with Heterogeneous Costs and Durations. Silvia Izquierdo-Badiola, Gerard Canal, Guillem Alenyà, Carlos Rizzo, Andrew Coles |
| 2024 | Planning to be Healthy: Towards Personalized Medication Planning. Lee-or Alon, Hana Weitman, Alexander Shleyfman, Gal A. Kaminka |
| 2024 | Planning with Logical Graph-Based Language Model for Instruction Generation. Fan Zhang, Kebing Jin, Hankz Hankui Zhuo |
| 2024 | Planning with OWL-DL Ontologies. Tobias John, Patrick Koopmann |
| 2024 | Post-hoc Explanation of Extension Semantics. Leila Amgoud |
| 2024 | Predicting Solar Heat Production to Optimize Renewable Energy Usage. Tatiana Boura, Natalia Koliou, George Meramveliotakis, Stasinos Konstantopoulos, George Kosmadakis |
| 2024 | Preserving the Privacy of Reward Functions in MDPs through Deception. Shashank Reddy Chirra, Pradeep Varakantham, Praveen Paruchuri |
| 2024 | Principled Explanations for Robust Redistributive Decisions. Hénoïk Willot, Khaled Belahcène, Sébastien Destercke |
| 2024 | Probabilistically Plausible Counterfactual Explanations with Normalizing Flows. Patryk Wielopolski, Oleksii Furman, Jerzy Stefanowski, Maciej Zieba |
| 2024 | Progressive Artistic Aesthetic Enhancement For Chinese Ink Painting Style Transfer. Chihan Huang |
| 2024 | Prompt-Based Data Augmentation Using Contrastive Learning Under Scarcity of Annotated Data. Muhammad Uzair-Ul-Haq, Davide Rigoni, Alessandro Sperduti |
| 2024 | Prompt-Based Domain Incremental Learning with Modular Classification Layer. Boyu Wang, Yue Ma, Qinru Qiu |
| 2024 | PromptCD: Coupled and Decoupled Prompt Learning for Vision-Language Models. Junjie Wu, Mingjie Sun, Chen Gong, Nan Yu, Guohong Fu |
| 2024 | Proportional Representation for Artificial Intelligence. Dominik Peters |
| 2024 | QFMTS: Generating Query-Focused Summaries over Multi-Table Inputs. Weijia Zhang, Vaishali Pal, Jia-Hong Huang, Evangelos Kanoulas, Maarten de Rijke |
| 2024 | Quantifying a Causal Effect from a CPDAG with Targeted Exogenous Causal Knowledge. Mahdi Hadj Ali, Yann Le Biannic, Pierre-Henri Wuillemin |
| 2024 | Quater-GCN: Enhancing 3D Human Pose Estimation with Orientation and Semi-Supervised Training. Xingyu Song, Zhan Li, Shi Chen, Kazuyuki Demachi |
| 2024 | R Taolin Zhang, Dongyang Li, Qizhou Chen, Chengyu Wang, Longtao Huang, Hui Xue, Xiaofeng He, Jun Huang |
| 2024 | RADAr: A Transformer-Based Autoregressive Decoder Architecture for Hierarchical Text Classification. Yousef Younes, Lukas Galke, Ansgar Scherp |
| 2024 | REFINE-LM: Mitigating Language Model Stereotypes via Reinforcement Learning. Rameez Qureshi, Naïm Es-Sebbani, Luis Galárraga, Yvette Graham, Miguel Couceiro, Zied Bouraoui |
| 2024 | RETRO-LI: Small-Scale Retrieval Augmented Generation Supporting Noisy Similarity Searches and Domain Shift Generalization. Gentiana Rashiti, Geethan Karunaratne, Mrinmaya Sachan, Abu Sebastian, Abbas Rahimi |
| 2024 | RFDFM: A Deep Factorization Machine Network Model for Invasive Lung Adenocarcinoma Screening in CT Images. Jing Zhou, Chengcheng Guo, Ying Ji |
| 2024 | RTSR: A Real-Time Table Structure Recognition Approach. Nam Quan Nguyen, Xuan Phong Pham, Tuan Anh Tran |
| 2024 | Reaching New Heights in Multi-Agent Collective Construction. Martin Rames, Pavel Surynek |
| 2024 | ReactAIvate: A Deep Learning Approach to Predicting Reaction Mechanisms and Unmasking Reactivity Hotspots. Ajnabiul Hoque, Manajit Das, Mayank Baranwal, Raghavan B. Sunoj |
| 2024 | Real-Time Goal Recognition Using Approximations in Euclidean Space. Douglas Antunes Tesch, Leonardo Amado, Felipe Meneguzzi |
| 2024 | Real-Time Indoor Object Detection Based on Hybrid CNN-Transformer Approach. Salah-eddine Laidoudi, Madjid Maidi, Samir Otmane |
| 2024 | Reasonable Gradients for Online Training Algorithms in Spiking Neural Networks. Lang Xue, Hanwen Liu, Jing Wang, Hong Qu |
| 2024 | Reassessing Non-Autoregressive Neural Machine Translation with a Fine-Grained Error Taxonomy. Yan Liu, Longyue Wang, Zhaopeng Tu, Deyi Xiong |
| 2024 | Recovering Implicit Physics Model Under Real-World Constraints. Ayan Banerjee, Sandeep K. S. Gupta |
| 2024 | Recurrent Task Specialization Network for Segmentation-aided Vascular Landmarks Detection in Retinal Images. Álvaro S. Hervella, José Rouco, Jorge Novo, Clara I. Sánchez, Marcos Ortega |
| 2024 | Reduce, Reuse, Recycle: Categories for Compositional Reinforcement Learning. Georgios Bakirtzis, Michail Savvas, Ruihan Zhao, Sandeep Chinchali, Ufuk Topcu |
| 2024 | Reducing Systemic Risk in Financial Networks through Donations. Jinyun Tong, Bart de Keijzer, Carmine Ventre |
| 2024 | Reducing Texture Bias of Deep Neural Networks via Edge Enhancing Diffusion. Edgar Heinert, Matthias Rottmann, Kira Maag, Karsten Kahl |
| 2024 | Rejection in Abstract Argumentation: Harder Than Acceptance? Johannes Klaus Fichte, Markus Hecher, Yasir Mahmood, Arne Meier |
| 2024 | Relation Time-Aware Heterogeneous Dynamic Graph Neural Networks. Yili Wang, Jiamin Chen, Qiutong Li, Changlong He, Jianliang Gao |
| 2024 | Representation Matters for Mastering Chess: Improved Feature Representation in AlphaZero Outperforms Switching to Transformers. Johannes Czech, Jannis Blüml, Kristian Kersting, Hedinn Steingrimsson |
| 2024 | Reset It and Forget It: Relearning Last-Layer Weights Improves Continual and Transfer Learning. Lapo Frati, Neil Traft, Jeff Clune, Nick Cheney |
| 2024 | Resilient Graph Neural Networks: A Coupled Dynamical Systems Approach. Moshe Eliasof, Davide Murari, Ferdia Sherry, Carola-Bibiane Schönlieb |
| 2024 | Resistance Against Manipulative AI: Key Factors and Possible Actions. Piotr Wilczynski, Wiktoria Mieleszczenko-Kowszewicz, Przemyslaw Biecek |
| 2024 | Rethinking Domain Generalization from Perspective of Gradient Granularity. Yujie Zhou, Haigen Hu, Qianwei Zhou, Qiu Guan, Mingfeng Jiang |
| 2024 | Reverse Engineering of Vinyl Acetate Polymerizations by Genetic Algorithm-Based Multi-Objective Optimization. Jelena Fiosina, Philipp Sievers, Marco Drache, Sabine Beuermann |
| 2024 | Revisiting Under-Represented Knowledge of Latin American Literature in Large Language Models. Jinsung Kim, Seonmin Koo, Heuiseok Lim |
| 2024 | Revisiting Vacuous Reduct Semantics for Abstract Argumentation. Lydia Blümel, Matthias Thimm |
| 2024 | Revisiting the Dataset Bias Problem from a Statistical Perspective. Kien Do, Dung Nguyen, Hung Le, Thao Le, Dang Nguyen, Haripriya Harikumar, Truyen Tran, Santu Rana, Svetha Venkatesh |
| 2024 | Revocable Backdoor for Deep Model Trading. Yiran Xu, Nan Zhong, Zhenxing Qian, Xinpeng Zhang |
| 2024 | Rigorous Probabilistic Guarantees for Robust Counterfactual Explanations. Luca Marzari, Francesco Leofante, Ferdinando Cicalese, Alessandro Farinelli |
| 2024 | Robust Deep Hawkes Process Under Label Noise of Both Event and Occurrence. Xiaoyu Tan, Bin Li, Xihe Qiu, Jingjing Huang, Yinghui Xu, Wei Chu |
| 2024 | Robust Monocular Depth Estimation in Adverse Weather Conditions by Unsupervised Domain Adaptation. Jihui Lee, Quoc-Vinh Lai-Dang, Neha Sengar, Dongsoo Har |
| 2024 | SAIE Framework: Support Alone Isn't Enough - Advancing LLM Training with Adversarial Remarks. Mengsay Loem, Masahiro Kaneko, Naoaki Okazaki |
| 2024 | SAT-Based Approaches to Reasoning in Choice Logics. Tuomo Lehtonen, Andreas Niskanen, Matti Järvisalo |
| 2024 | SETTP: Style Extraction and Tunable Inference via Dual-Level Transferable Prompt Learning. Chunzhen Jin, Yongfeng Huang, Yaqi Wang, Peng Cao, Osmar Zaïane |
| 2024 | SF-SER: An Efficient Speech-Only Model with Semantic Funnel for Speech Emotion Recognition. Xiaoke Li, Zufan Zhang |
| 2024 | SFDFusion: An Efficient Spatial-Frequency Domain Fusion Network for Infrared and Visible Image Fusion. Kun Hu, Qingle Zhang, Maoxun Yuan, Yitian Zhang |
| 2024 | SPIN: SE(3)-Invariant Physics Informed Network for Binding Affinity Prediction. Seungyeon Choi, Sangmin Seo, Sanghyun Park |
| 2024 | STPDN: Spatio-Temporal Pattern Decomposition Network with Fluctuation Awareness for Robust Traffic Flow Forecasting. Xudong Zhang, Peng Peng, Xuewen Chen, Yulei Wu, Lingdong Shen, Haina Tang |
| 2024 | STV+FLY: On-the-Fly Model Checking of Strategic Ability in Multi-Agent Systems. Damian Kurpiewski, Mateusz Kaminski, Wojciech Jamroga |
| 2024 | SUBER: An RL Environment with Simulated Human Behavior for Recommender Systems. Nathan Corecco, Giorgio Piatti, Luca A. Lanzendörfer, Flint Xiaofeng Fan, Roger Wattenhofer |
| 2024 | SUBLLM: A Novel Efficient Architecture with Token Sequence Subsampling for LLM. Quandong Wang, Yuxuan Yuan, Xiaoyu Yang, Ruike Zhang, Kang Zhao, Wei Liu, Jian Luan, Daniel Povey, Bin Wang |
| 2024 | SaGess: A Sampling Graph Denoising Diffusion Model for Scalable Graph Generation. Stratis Limnios, Praveen Selvaraj, Mihai Cucuringu, Carsten Maple, Gesine Reinert, Andrew Elliott |
| 2024 | SaccadeMOT: Enhancing Object Detection and Tracking in Gigapixel Images via Scale-Aware Density Estimation. Wenxi Li, Ruxin Zhang, Haozhe Lin, Yuchen Guo, Chao Ma, Xiaokang Yang |
| 2024 | Safety Verification of Tree-Ensemble Policies via Predicate Abstraction. Chaahat Jain, Lorenzo Cascioli, Laurens Devos, Marcel Vinzent, Marcel Steinmetz, Jesse Davis, Jörg Hoffmann |
| 2024 | Sampling-Based Teacher Guided Method to Boost Transferable Attack on SAR Image Classification. Aoyang Zhou, Yasmeen M. Khedr, Xin Liu, Kun He |
| 2024 | Sanitizing Hidden Information with Diffusion Models. Preston K. Robinette, Daniel Moyer, Taylor T. Johnson |
| 2024 | Scalable Variational Causal Discovery Unconstrained by Acyclicity. Nu Hoang, Bao Duong, Thin Nguyen |
| 2024 | Scale-Adaptive Balancing of Exploration and Exploitation in Classical Planning. Stephen Wissow, Masataro Asai |
| 2024 | Scale-Invariant Variations of Max Regret. Nic Wilson |
| 2024 | Search, Examine and Early-Termination: Fake News Detection with Annotation-Free Evidences. Yuzhou Yang, Yangming Zhou, Qichao Ying, Zhenxing Qian, Xinpeng Zhang |
| 2024 | SecPE: Secure Prompt Ensembling for Private and Robust Large Language Models. Jiawen Zhang, Kejia Chen, Zunlei Feng, Jian Lou, Mingli Song |
| 2024 | Segmentation-Driven Image Enhancement Based on Deep Reinforcement Learning. Yihong Liu, Zishang Chen, Yukang Cui, Piji Li |
| 2024 | SelfBC: Self Behavior Cloning for Offline Reinforcement Learning. Shirong Liu, Chenjia Bai, Zixian Guo, Hao Zhang, Gaurav Sharma, Yang Liu |
| 2024 | Selfishly Cancelling Debts Can Reduce Systemic Risk. Jinyun Tong, Bart de Keijzer, Carmine Ventre |
| 2024 | Semantic Augmentation on Motion Manifold for Single-Stream Unsupervised Action Recognition. Haichuan Zhao, Peng Du, Xudong Ru, Zhongke Wu, Xingce Wang |
| 2024 | Semantic Similarity Driven Multi-Modal Model for Rumor Detection. Chenyang Li, Bo Xu, Meng Wang, Kun He |
| 2024 | Sentinel: An Aggregation Function to Secure Decentralized Federated Learning. Chao Feng, Alberto Huertas Celdrán, Janosch Baltensperger, Enrique Tomás Martínez Beltrán, Pedro Miguel Sánchez Sánchez, Gérôme Bovet, Burkhard Stiller |
| 2024 | Shielded FOND: Planning with Safety Constraints in Pure-Past Linear Temporal Logic. Luigi Bonassi, Giuseppe De Giacomo, Alfonso Emilio Gerevini, Enrico Scala |
| 2024 | SibylSat: Using SAT as an Oracle to Perform a Greedy Search on TOHTN Planning. Gaspard Quenard, Damien Pellier, Humbert Fiorino |
| 2024 | SinLane: Siamese Visual Transformer via Pyramid Feature Integration for Lane Detection. Zinan Lv, Dong Han, Wenzhe Wang, Danny Z. Chen |
| 2024 | Sinogram-Image Dual-Domain Network for Robust Metal Artifact Reduction in CT Image. Chong Liu, Yuhan Huang, Bo Li, Hui Ding |
| 2024 | Solving PDEs on Point Clouds by Physics-Informed Learning with Graph Neural Networks. Rakhoon Hwang, Junseung Ryu, Seungtae Park, Hyung Ju Hwang |
| 2024 | Sparse Convolutional Neural Network for Localization and Orientation Prediction and Application to Drone Control. Jan Rodziewicz-Bielewicz, Marcin Korzen |
| 2024 | Spatial and Frequency-Based Feature Reconstruction for Cross-Database Micro-Expression Recognition. Zhi Feng, C. L. Philip Chen, Shiting Xu, Tong Zhang |
| 2024 | Spatially Constrained Transformer with Efficient Global Relation Modelling for Spatio-Temporal Prediction. Ashutosh Sao, Simon Gottschalk |
| 2024 | Structure and Reduction of MCTS for Explainable-AI. Ronit Bustin, Claudia V. Goldman |
| 2024 | StyleMamba: State Space Model for Efficient Text-Driven Image Style Transfer. Zijia Wang, Zhi-Song Liu |
| 2024 | Sub-SA: Strengthen In-Context Learning via Submodular Selective Annotation. Jian Qian, Miao Sun, Sifan Zhou, Ziyu Zhao, Ruizhi Hun, Patrick Chiang |
| 2024 | Subsystem Discovery in High-Dimensional Time-Series Using Masked Autoencoders. Teemu Sarapisto, Haoyu Wei, Keijo Heljanko, Arto Klami, Laura Ruotsalainen |
| 2024 | Survival of the Fittest: Evolutionary Adaptation of Policies for Environmental Shifts. Sheryl Paul, Jyotirmoy V. Deshmukh |
| 2024 | Symmetry-Breaking Constraints for Directed Graphs. Jussi Rintanen, Masood Feyzbakhsh Rankooh |
| 2024 | Synthesis of Reward Machines for Multi-Agent Equilibrium Design. Muhammad Najib, Giuseppe Perelli |
| 2024 | Synthetically Augmented Self-Supervised Fine-Tuning for Diverse Text OCR Correction. Shuhao Guan, Derek Greene |
| 2024 | TDCL: Dense Semantic Contrastive Learning for Vision-Language Tracking. Zheng Wang, Xiankang He, Kaiyang Lan, Ying Cui, Dongyan Guo |
| 2024 | TED: Accelerate Model Training by Internal Generalization. Jinying Xiao, Ping Li, Jie Nie |
| 2024 | TEOcc: Radar-Camera Multi-Modal Occupancy Prediction via Temporal Enhancement. Zhiwei Lin, Hongbo Jin, Yongtao Wang, Yufei Wei, Nan Dong |
| 2024 | TIGER: Temporally Improved Graph Entity Linker. Pengyu Zhang, Congfeng Cao, Paul Groth |
| 2024 | TP-GMOT: Tracking Generic Multiple Object by Textual Prompt with Motion-Appearance Cost (MAC) SORT. Duy Le Dinh Anh, Kim Hoang Tran, Ngan Hoang Le |
| 2024 | TSFool: Crafting Highly-Imperceptible Adversarial Time Series Through Multi-Objective Attack. Yanyun Wang, Dehui Du, Haibo Hu, Zi Liang, Yuanhao Liu |
| 2024 | TabCGOK: Intra-Class Groups Retrieval and Inter-Class Ordinal Knowledge Augmented Network for Ordinal Tabular Data Prediction. Zhengdong Luo, Abibulla Atawulla, Fengyi Yang, Yongqing Zhu, Yixiao Ren, Yunfei Han, Xi Zhou |
| 2024 | TabMedBERT: A Tabular Knowledge Enhanced Biomedical Pretrained Language Model. Xu Yan, Lei Geng, Ziqiang Cao, Juntao Li, Wenjie Li, Sujian Li, Xinjie Zhou, Yang Yang, Jun Zhang |
| 2024 | Tackling Selfish Clients in Federated Learning. Andrea Augello, Ashish Gupta, Giuseppe Lo Re, Sajal K. Das |
| 2024 | Tailored-LLaMA: Optimizing Few-Shot Learning in Pruned LLaMA Models with Task-Specific Prompts. Steven Davy, Danyal Aftab |
| 2024 | Take a Step and Reconsider: Sequence Decoding for Self-Improved Neural Combinatorial Optimization. Jonathan Pirnay, Dominik G. Grimm |
| 2024 | Talos: A More Effective and Efficient Adversarial Defense for GNN Models Based on the Global Homophily of Graphs. Duanyu Li, Huijun Wu, Min Xie, Xugang Wu, Zhenwei Wu, Wenzhe Zhang |
| 2024 | Target-driven Attack for Large Language Models. Chong Zhang, Mingyu Jin, Dong Shu, Taowen Wang, Dongfang Liu, Xiaobo Jin |
| 2024 | Task-Aware Dynamic Transformer for Efficient Arbitrary-Scale Image Super-Resolution. Tianyi Xu, Yijie Zhou, Xiaotao Hu, Kai Zhang, Anran Zhang, Xingye Qiu, Jun Xu |
| 2024 | Taylor Expansion in Neural Networks: How Higher Orders Yield Better Predictions. Pavel Zwerschke, Arvid Weyrauch, Markus Götz, Charlotte Debus |
| 2024 | Temporal Elections: Welfare, Strategyproofness, and Proportionality. Edith Elkind, Tzeh Yuan Neoh, Nicholas Teh |
| 2024 | Temporal Fairness in Decision Making Problems. Manuel R. Torres, Parisa Zehtabi, Michael Cashmore, Daniele Magazzeni, Manuela Veloso |
| 2024 | Text-Based Geolocation with a Byte-Level Language Model. Mikhail Orzhenovskii, Alina Pak, Roman Kane, Arina Razmyslovich |
| 2024 | The Complexity of Manipulation of k-Coalitional Games on Graphs. Hodaya Barr, Yohai Trabelsi, Sarit Kraus, Liam Roditty, Noam Hazon |
| 2024 | The Degree of Fairness in Efficient House Allocation. Hadi Hosseini, Medha Kumar, Sanjukta Roy |
| 2024 | The Distributional Uncertainty of the SHAP Score in Explainable Machine Learning. Santiago Cifuentes, Leopoldo E. Bertossi, Nina Pardal, Sergio Abriola, Maria Vanina Martinez, Miguel Romero |
| 2024 | The Form and the Content: Non-Monotonic Reasoning with Syntactic Contextual Filtering. Florence Dupin de Saint-Cyr, Pierre Bisquert |
| 2024 | The Propensity for Density in Feed-Forward Models. Nandi Schoots, Alex Jackson, Ali Kholmovia, Peter McBurney, Murray Shanahan |
| 2024 | The Role of Depth, Width, and Tree Size in Expressiveness of Deep Forest. Shen-Huan Lyu, Jin-Hui Wu, Qin-Cheng Zheng, Baoliu Ye |
| 2024 | The World is a Multi-Objective Multi-Agent System: Now What? Roxana Radulescu |
| 2024 | Theoretical Proportion Label Perturbation for Learning from Label Proportions in Large Bags. Shunsuke Kubo, Shinnosuke Matsuo, Daiki Suehiro, Kazuhiro Terada, Hiroaki Ito, Akihiko Yoshizawa, Ryoma Bise |
| 2024 | Thresholded Lexicographic Ordered Multiobjective Reinforcement Learning. Alperen Tercan, Vinayak S. Prabhu |
| 2024 | Time Series Imputation with Multivariate Radial Basis Function Neural Network. Chanyoung Jung, Yun Jang |
| 2024 | TimeMachine: A Time Series is Worth 4 Mambas for Long-Term Forecasting. Md. Atik Ahamed, Qiang Shawn Cheng |
| 2024 | TopFormer: Topology-Aware Authorship Attribution of Deepfake Texts with Diverse Writing Styles. Adaku Uchendu, Thai Le, Dongwon Lee |
| 2024 | Towards Unsupervised Validation of Anomaly-Detection Models. Lihi Idan |
| 2024 | Towards the New XAI: A Hypothesis-Driven Approach to Decision Support Using Evidence. Thao Le, Tim Miller, Liz Sonenberg, Ronal Singh |
| 2024 | TransFeat-TPP: An Interpretable Deep Covariate Temporal Point Processes. Zizhuo Meng, Boyu Li, Xuhui Fan, Zhidong Li, Yang Wang, Fang Chen, Feng Zhou |
| 2024 | Transfer Learning Can Introduce Bias. Parisa Salmani, Peter R. Lewis |
| 2024 | Translation and Transliteration Based Data Augmentation for Multilingual Semantic Parsing. Sarthak Jauhari, Massimo Nicosia, Ankush Chatterjee, Rahul Goel |
| 2024 | Transparent Explainable Logic Layers. Alessio Ragno, Marc Plantevit, Céline Robardet, Roberto Capobianco |
| 2024 | TrustFed: Navigating Trade-offs Between Performance, Fairness, and Privacy in Federated Learning. Maryam Badar, Sandipan Sikdar, Wolfgang Nejdl, Marco Fisichella |
| 2024 | TrustMIS: Trust-Enhanced Inference Framework for Medical Image Segmentation. Fuyi Wang, Jinzhi Ouyang, Lei Pan, Leo Yu Zhang, Xiaoning Liu, Yanping Wang, Robin Doss |
| 2024 | TwinDiffusion: Enhancing Coherence and Efficiency in Panoramic Image Generation with Diffusion Models. Teng Zhou, Yongchuan Tang |
| 2024 | UCCIX: Irish-eXcellence Large Language Model. Khanh-Tung Tran, Barry O'Sullivan, Hoang D. Nguyen |
| 2024 | UDUC: An Uncertainty-Driven Approach for Learning-Based Robust Control. Yuan Zhang, Jasper Hoffmann, Joschka Boedecker |
| 2024 | Uncertainty in Real-World Vehicle Routing. Václav Sobotka, Hana Rudová |
| 2024 | Uncertainty-Guided Dual Task Framework for Semi-Supervised Segmentation of Thyroid Nodules. Xiang Ying, Jizhe Zhang, Jie Gao, Mei Yu, Ruixuan Zhang, Jialin Zhu, Xuewei Li, Ruiguo Yu |
| 2024 | Understanding XAI Through the Philosopher's Lens: A Historical Perspective. Martina Mattioli, Antonio Emanuele Cinà, Marcello Pelillo |
| 2024 | Understanding the Impact of Human Oversight on Discriminatory Outcomes in AI-Supported Decision-Making. Alexia Gaudeul, Ottla Arrigoni, Vicky Charisi, Marina Escobar-Planas, Isabelle Hupont |
| 2024 | Unidirectional Cross-Modal Fusion for RGB-T Tracking. Xiao Guo, Hangfei Li, Yufei Zha, Peng Zhang |
| 2024 | Unified Video and Image Representation for Boosted Video Face Forgery Detection. Haotian Liu, Chenhui Pan, Yang Liu, Guoying Zhao, Xiaobai Li |
| 2024 | United We Stand: Decentralized Multi-Agent Planning with Attrition. Nhat Nguyen, Duong Nguyen, Gianluca Rizzo, Hung Nguyen |
| 2024 | Unlocking Efficiency: Adaptive Masking for Gene Transformer Models. Soumyadeep Roy, Shamik Sural, Niloy Ganguly |
| 2024 | Unveiling Learner Dynamics: The ECLIPSE Dataset and NeuralGaze Framework for Prolonged Engagement Assessment in Online Learning. Avinash Anand, Avni Mittal, Laavanaya Dhawan, Mahisha Ramesh, Juhi Krishnamurthy, Naman Lal, Raj Jaiswal, Pijush Bhuyan, Himani, Astha Verma, Rajiv Ratn Shah, Roger Zimmermann, Shin'ichi Satoh |
| 2024 | Unveiling the Power of Sparse Neural Networks for Feature Selection. Zahra Atashgahi, Tennison Liu, Mykola Pechenizkiy, Raymond N. J. Veldhuis, Decebal Constantin Mocanu, Mihaela van der Schaar |
| 2024 | Using Backdoors to Generate Learnt Information in SAT Solving. Alexander Andreev, Konstantin Chukharev, Stepan Kochemazov, Alexander A. Semenov |
| 2024 | VANER: Leveraging Large Language Model for Versatile and Adaptive Biomedical Named Entity Recognition. Junyi Bian, Weiqi Zhai, Xiaodi Huang, Jiaxuan Zheng, Shanfeng Zhu |
| 2024 | VMFTransformer: An Angle-Preserving and Auto-Scaling Machine for Multi-Horizon Probabilistic Forecasting. Yunyi Zhou, Ruohan Gao, Xinping Zheng, Yuchen Huang, Zhixuan Chu |
| 2024 | Value-Based Rationales Improve Social Experience: A Multiagent Simulation Study. Sz-Ting Tzeng, Nirav Ajmeri, Munindar P. Singh |
| 2024 | Vanilla Gradient Descent for Oblique Decision Trees. Subrat Prasad Panda, Blaise Genest, Arvind Easwaran, Ponnuthurai Nagaratnam Suganthan |
| 2024 | Verification of Geometric Robustness of Neural Networks via Piecewise Linear Approximation and Lipschitz Optimisation. Ben Batten, Yang Zheng, Alessandro De Palma, Panagiotis Kouvaros, Alessio Lomuscio |
| 2024 | Verifying the Selected Completely at Random Assumption in Positive-Unlabeled Learning. Pawel Teisseyre, Konrad Furmanczyk, Jan Mielniczuk |
| 2024 | Video2Reward: Generating Reward Function from Videos for Legged Robot Behavior Learning. Runhao Zeng, Dingjie Zhou, Qiwei Liang, Junlin Liu, Hui Li, Changxin Huang, Jianqiang Li, Xiping Hu, Fuchun Sun |
| 2024 | WPN: An Unlearning Method Based on N-pair Contrastive Learning in Language Models. Guitao Chen, Yunshen Wang, Hongye Sun, Guang Chen |
| 2024 | Weight Scope Alignment: A Frustratingly Easy Method for Model Merging. Yichu Xu, Xin-Chun Li, Le Gan, De-Chuan Zhan |
| 2024 | What Model Does MuZero Learn? Jinke He, Thomas M. Moerland, Joery A. de Vries, Frans A. Oliehoek |
| 2024 | Winning the 2023 CityLearn Challenge: A Community-Based Hierarchical Energy Systems Coordination Algorithm. Andoni I. Garmendia, Francesco Morri, Quentin Cappart, Hélène Le Cadre |
| 2024 | Worst- and Average-Case Robustness of Stable Matchings: (Counting) Complexity and Experiments. Kimon Boehmer, Niclas Boehmer |
| 2024 | X-Vent: ICU Ventilation with Explainable Model-Based Reinforcement Learning. Farhad Safaei, Milos Nenadovic, Roman Liessner, Raphael Theilen, Jakob Wittenstein, Jens Lehmann, Sahar Vahdati |
| 2024 | Zero-Shot Relabeling of Weak Labels for Fine-Grained Semantic Indexing of Biomedical Literature. Anastasios Nentidis, Anastasia Krithara, Grigorios Tsoumakas, Georgios Paliouras |
| 2024 | Zero-Waste Machine Learning. Tomasz Trzcinski, Bartlomiej Twardowski, Bartosz Zielinski, Kamil Adamczewski, Bartosz Wójcik |
| 2024 | iSee: Advancing Multi-Shot Explainable AI Using Case-Based Recommendations. Anjana Wijekoon, Nirmalie Wiratunga, David Corsar, Kyle Martin, Ikechukwu Nkisi-Orji, Chamath Palihawadana, Marta Caro-Martínez, Belén Díaz-Agudo, Derek G. Bridge, Anne Liret |
| 2024 | stl2vec: Semantic and Interpretable Vector Representation of Temporal Logic. Gaia Saveri, Laura Nenzi, Luca Bortolussi, Jan Kretínský |
| 2024 | u-LLaVA: Unifying Multi-Modal Tasks via Large Language Model. Jinjin Xu, Liwu Xu, Yuzhe Yang, Xiang Li, Fanyi Wang, Yanchun Xie, Yi-Jie Huang, Yaqian Li |