AAAI 2025

3,486 papers

GradQ-ViT: Robust and Efficient Gradient Quantization for Vision Transformers

Dahun Choi, Hyun Kim

WatE: A Wasserstein t-distributed Embedding Method for Information-enriched Graph Visualization

Minjie Cheng, Dixin Luo, Hongteng Xu

Community-Aware Variational Autoencoder for Continuous Dynamic Networks

Junwei Cheng, Chaobo He, Pengxing Feng, Weixiong Liu, Kunlin Han

Convergence Rate in a Nonlinear Two-Time-Scale Stochastic Approximation with State (Time)-Dependence

Zixi Chen, Yumin Xu, Ruixun Zhang

Attack-inspired Calibration Loss for Calibrating Crack Recognition

Zhuangzhuang Chen, Qiangyu Chen, Jiahao Zhang, Zhiliang Lin, Xingyu Feng

EditBoard: Towards a Comprehensive Evaluation Benchmark for Text-Based Video Editing Models

Yupeng Chen, Penglin Chen, Xiaoyu Zhang, Yixian Huang, Qian Xie

GeCC: Generalized Contrastive Clustering with Domain Shifts Modeling

yujie Chen, Wenhui Wu, Le Ou-Yang, Ran Wang, Debby D. Wang

A Pioneering Neural Network Method for Efficient and Robust Fuel Sloshing Simulation in Aircraft

Yu Chen, Shuai Zheng, Nianyi Wang, Menglong Jin, Yan Chang

Beyond Homophily: Graph Contrastive Learning with Macro-Micro Message Passing

Yiyuan Chen, Donghai Guan, Weiwei Yuan, Tianzi Zang

Anchor Learning with Potential Cluster Constraints for Multi-view Clustering

Yawei Chen, Huibing Wang, Jinjia Peng, Yang Wang

Novelty-Guided Data Reuse for Efficient and Diversified Multi-Agent Reinforcement Learning

Yangkun Chen, Kai Yang, Jian Tao, Jiafei Lyu

MIETT: Multi-Instance Encrypted Traffic Transformer for Encrypted Traffic Classification

Xu-Yang Chen, Lu Han, De-Chuan Zhan, Han-Jia Ye

Sequence Complementor: Complementing Transformers for Time Series Forecasting with Learnable Sequences

Xiwen Chen, Peijie Qiu, Wenhui Zhu, Huayu Li, Hao Wang

DualGFL: Federated Learning with a Dual-Level Coalition-Auction Game

Xiaobing Chen, Xiangwei Zhou, Songyang Zhang, Mingxuan Sun

The Distributional Reward Critic Framework for Reinforcement Learning Under Perturbed Rewards

Xi Chen, Zhihui Zhu, Andrew Perrault

Debiased Active Learning with Variational Gradient Rectifier

Weiguo Chen, Changjian Wang, Shijun Li, Kele Xu, Yanru Bai

Smoothness Really Matters: A Simple Yet Effective Approach for Unsupervised Graph Domain Adaptation

Wei Chen, Guo Ye, Yakun Wang, Zhao Zhang, Libang Zhang

Make Domain Shift a Catastrophic Forgetting Alleviator in Class-Incremental Learning

Wei Chen, Yi Zhou

Learnware Specification via Label-Aware Neural Embedding

Wei Chen, Jun-Xiang Mao, Min-ling Zhang

SpotDiff: Spatial Gene Expression Imputation Diffusion with Single-Cell RNA Sequencing Data Integration

Tianyi Chen, Yunfei Zhang, Lianxin Xie, Wenjun Shen, Si Wu

Federated Foundation Models on Heterogeneous Time Series

Shengchao Chen, Guodong Long, Jing Jiang, Chengqi Zhang

Robust Logit Adjustment for Learning with Long-Tailed Noisy Data

Mingcai Chen, Yuntao Du, Wenyu Jiang, Baoming Zhang, Shuai Feng

Integrating Sequence and Image Modeling in Irregular Medical Time Series Through Self-Supervised Learning

Liuqing Chen, Shuhong Xiao, Shixian Ding, Shanhai Hu, Lingyun Sun

Semi-Supervised Multimodal Classification Through Learning from Modal and Strategic Complementarities

Junchi Chen, Richong Zhang, Junfan Chen

Error Analysis Affected by Heavy-Tailed Gradients for Non-Convex Pairwise Stochastic Gradient Descent

Jun Chen, Hong Chen, Bin Gu, Guodong Liu, Yingjie Wang

Cross-View Graph Consistency Learning for Invariant Graph Representations

Jie Chen, Hua Mao, Wai Lok Woo, Chuanbin Liu, Xi Peng

Understanding Individual Agent Importance in Multi-Agent System via Counterfactual Reasoning

Jianming Chen, Yawen Wang, Junjie Wang, Xiaofei Xie, Jun Hu

FedPop: Federated Population-based Hyperparameter Tuning

Haokun Chen, Denis Krompaß, Jindong Gu, Volker Tresp

Biased Incomplete Multi-View Learning

Haishun Chen, Cai Xu, Ziyu Guan, Wei Zhao, Jinlong Liu

SemStereo: Semantic-Constrained Stereo Matching Network for Remote Sensing

Chen Chen, Liangjin Zhao, Yuanchun He, Yingxuan Long, Kaiqiang Chen

Pseudo Informative Episode Construction for Few-Shot Class-Incremental Learning

Chaofan Chen, Xiaoshan Yang, Changsheng Xu

JEN-1 DreamStyler: Customized Musical Concept Learning via Pivotal Parameters Tuning

Boyu Chen, Peike Li, Yao Yao, Alex Wang

Efficient Anomaly Detection of Irregular Sequences in Ct-Echo Model Space

Ao Chen, Xiren Zhou, Huanhuan Chen

Constraint-Adaptive Policy Switching for Offline Safe Reinforcement Learning

Yassine Chemingui, Aryan Deshwal, Honghao Wei, Alan Fern, Jana Doppa

Global Graph Propagation with Hierarchical Information Transfer for Incomplete Contrastive Multi-view Clustering

Guoqing Chao, Kaixin Xu, Xijiong Xie, Yongyong Chen

Differentiable Adversarial Attacks for Marked Temporal Point Processes

Pritish Chakraborty, Vinayak Gupta, Rahul R, Srikanta J. Bedathur, Abir De

DiffExp: Efficient Exploration in Reward Fine-tuning for Text-to-Image Diffusion Models

Daewon Chae, June Suk Choi, Jinkyu Kim, Kimin Lee

Flash Diffusion: Accelerating Any Conditional Diffusion Model for Few Steps Image Generation

Clément Chadebec, Onur Tasar, Eyal Benaroche, Benjamin Aubin

Batch Ensemble for Variance Dependent Regret in Stochastic Bandits

Asaf Cassel, Orin Levy, Yishay Mansour

Neural Reasoning Networks: Efficient Interpretable Neural Networks with Automatic Textual Explanations

Stephen Carrow, Kyle Erwin, Olga Vilenskaia, Parikshit Ram, Tim Klinger

Fairness Shields: Safeguarding against Biased Decision Makers

Filip Cano, Thomas A. Henzinger, Bettina Könighofer, Konstantin Kueffner, Kaushik Mallik

ML-GOOD: Towards Multi-Label Graph Out-Of-Distribution Detection

Tingyi Cai, Yunliang Jiang, Ming Li, Changqin Huang, Yi Wang

Disentangling Long-Short Term State Under Unknown Interventions for Online Time Series Forecasting

Ruichu Cai, Haiqin Huang, Zhifan Jiang, Zijian Li, Changze Zhou

Accelerated Methods with Compressed Communications for Distributed Optimization Problems Under Data Similarity

Dmitry Bylinkin, Aleksandr Beznosikov

Generating Counterfactual Explanations Under Temporal Constraints

Andrei Buliga, Chiara Di Francescomarino, Chiara Ghidini, Marco Montali, Massimiliano Ronzani

Leveraging Constraint Violation Signals for Action Constrained Reinforcement Learning

Janaka Chathuranga Brahmanage, Jiajing LING, Akshat Kumar

The Indoor-Training Effect: Unexpected Gains from Distribution Shifts in the Transition Function

Serena Bono, Spandan Madan, Ishaan Grover, Mao Yasueda, Cynthia Breazeal

Conditional Feature Importance with Generative Modeling Using Adversarial Random Forests

Kristin Blesch, Niklas Koenen, Jan Kapar, Pegah Golchian, Lukas Burk

Weighted Embeddings for Low-Dimensional Graph Representation

Thomas Bläsius, Jean-Pierre von der Heydt, Maximilian Katzmann, Nikolai Maas

Neural Conjugate Flows: A Physics-Informed Architecture with Flow Structure

Arthur Bizzi, Lucas Nissenbaum, João M. Pereira

Unsupervised Audio-Visual Segmentation with Modality Alignment

Swapnil Bhosale, Haosen Yang, Diptesh Kanojia, Jiankang Deng, Xiatian Zhu

Learnability of Parameter-Bounded Bayes Nets

Arnab Bhattacharyya, Davin Choo, Sutanu Gayen, Dimitrios Myrisiotis

Teaching Models to Improve on Tape

Liat Bezalel, Eyal Orgad, Amir Globerson

Langevin Monte Carlo Beyond Lipschitz Gradient Continuity

Matej Benko, Iwona Chlebicka, Jorgen Endal, Błażej Miasojedow

Inverse Reinforcement Learning by Estimating Expertise of Demonstrators

Mark Beliaev, Ramtin Pedarsani

Generalized Convergence Analysis of Tsetlin Automaton Based Algorithms: A Probabilistic Approach to Concept Learning

Mohamed-Bachir Belaid, Jivitesh Sharma, Lei Jiao, Ole-Christoffer Granmo, Per-Arne Andersen

A (1+ε)-Approximation for Ultrametric Embedding in Subquadratic Time

Gabriel Bathie, Guillaume Lagarde

Deep-Union Completion

Siddharth Baskar, Karan Vikyath Veeranna Rupashree, Daniel L. Pimentel-Alarcón

On the Trainability and Classical Simulability of Learning Matrix Product States Variationally

Afrad Basheer, Yuan Feng, Christopher Ferrie, Sanjiang Li, Hakop Pashayan

EFSkip: A New Error Feedback with Linear Speedup for Compressed Federated Learning with Arbitrary Data Heterogeneity

Hongyan Bao, Pengwen Chen, Ying Sun, Zhize Li

Improved Fixed-Parameter Bounds for Min-Sum-Radii and Diameters k-Clustering and Their Fair Variants

Sandip Banerjee, Yair Bartal, Lee-Ad Gottlieb, Alon Hovav

How Not to Stitch Representations to Measure Similarity: Task Loss Matching Versus Direct Matching

András Balogh, Márk Jelasity

FSL-Rectifier: Rectify Outliers in Few-Shot Learning via Test-Time Augmentation

Yunwei Bai, Ying Kiat Tan, Shiming Chen, YAO SHU, Tsuhan Chen

RAT: Adversarial Attacks on Deep Reinforcement Agents for Targeted Behaviors

Fengshuo Bai, Runze Liu, Yali Du, Ying Wen, Yaodong Yang

Cradle-VAE: Enhancing Single-Cell Gene Perturbation Modeling with Counterfactual Reasoning-based Artifact Disentanglement

Seungheun Baek, Soyon Park, Yan Ting Chok, Junhyun Lee, Jueon Park

List Update with Prediction

Yossi Azar, Shahar Lewkowicz, Varun Suriyanarayana

Parallel-Learning of Invariant and Tempo-variant Attributes of Single-Lead Cardiac Signals: PLITA

Adrian Atienza, Jakob E. Bardram, Sadasivan Puthusserypady

Neural Combinatorial Clustered Bandits for Recommendation Systems

Baran Atalar, Carlee Joe-Wong

When Witnesses Defend: A Witness Graph Topological Layer for Adversarial Graph Learning

Naheed Anjum Arafat, Debabrota Basu, Yulia Gel, Yuzhou Chen

When Can We Approximate Wide Contrastive Models with Neural Tangent Kernels and Principal Component Analysis?

Gautham Govind Anil, Pascal Esser, Debarghya Ghoshdastidar

Gaussian Graphical Modelling Without Independence Assumptions for Uncentered Data

Bailey Andrew, David R. Westhead, Luisa Cutillo

On the Robustness of Distributed Machine Learning Against Transfer Attacks

Sébastien Andreina, Pascal Zimmer, Ghassan Karame

Approximating Metric Magnitude of Point Sets

Rayna Andreeva, James Ward, Primoz Skraba, Jie Gao, Rik Sarkar

Unleashing the Potential of Model Bias for Generalized Category Discovery

Wenbin An, Haonan Lin, Jiahao Nie, Feng Tian, Wenkai Shi

Masked Language Modeling Becomes Conditional Density Estimation for Tabular Data Synthesis

Seunghwan An, Gyeongdong Woo, Jaesung Lim, ChangHyun Kim, Sungchul Hong

Even-if Explanations: Formal Foundations, Priorities and Complexity

Gianvincenzo Alfano, Sergio Greco, Domenico Mandaglio, Francesco Parisi, Reza Shahbazian

Improving Deep Learning Speed and Performance Through Synaptic Neural Balance

Antonios Alexos, Ian Domingo, Pierre Baldi

Active Fourier Auditor for Estimating Distributional Properties of ML Models

Ayoub Ajarra, Bishwamittra Ghosh, Debabrota Basu

Walking the Web of Concept-Class Relationships in Incrementally Trained Interpretable Models

Susmit Agrawal, Deepika Vemuri, Sri Siddarth Chakaravarthy P, Vineeth N. Balasubramanian

Markov Balance Satisfaction Improves Performance in Strictly Batch Offline Imitation Learning

Rishabh Agrawal, Nathan Dahlin, Rahul Jain, Ashutosh Nayyar

Bootstrapped Reward Shaping

Jacob Adamczyk, Volodymyr Makarenko, Stas Tiomkin, Rahul V. Kulkarni

Little Is Enough: Boosting Privacy by Sharing Only Hard Labels in Federated Semi-Supervised Learning

Amr Abourayya, Jens Kleesiek, Kanishka Rao, Erman Ayday, Bharat Rao

Exponential-Family Harmoniums with Neural Sufficient Statistics

Azwar Abdulsalam, Joseph G. Makin

SVasP: Self-Versatility Adversarial Style Perturbation for Cross-Domain Few-Shot Learning

Wenqian Li, Pengfei Fang, hui xue

Counterfactual Debiasing for Physical Audiovisual Commonsense Reasoning

Daoming Zong, Chaoyue Ding, Kaitao Chen, Yinsheng Li, Shuaiyu Wang

A Theory of Formalisms for Representing Knowledge

Heng Zhang, Guifei Jiang, Donghui Quan

What Is a Good Question? Assessing Question Quality via Meta-Fact Checking

Bo Zhang, Jianghua Zhu, Chaozhuo Li, Hao Yu, Li Kong

Knowledge Graph Completion with Relation-Aware Anchor Enhancement

Duanyang Yuan, sihang zhou, Xiaoshu Chen, Dong Wang, Ke Liang

SPAC: Sparse Partitioning and Adaptive Core Tensor Pruning Model for Knowledge Graph Completion

Chuhong Yang, Bin Li, Nan Wu

Temporal Conjunctive Query Answering via Rewriting

Lukas Westhofen, Jean Christoph Jung, Daniel Neider

Eliciting Causal Abilities in Large Language Models for Reasoning Tasks

Yajing Wang, Zongwei Luo, Jingzhe Wang, Zhanke Zhou, Yongqiang Chen

Goal-Driven Reasoning in DatalogMTL with Magic Sets

Shaoyu Wang, Kaiyue Zhao, Dongliang Wei, Przemysław Andrzej Wałęga, Dingmin Wang

Traffic Scenario Logic: A Spatial-Temporal Logic for Modeling and Reasoning of Urban Traffic Scenarios

Ruolin Wang, Yuejiao Xu, Jianmin Ji

SR-FoT: A Syllogistic-Reasoning Framework of Thought for Large Language Models Tackling Knowledge-based Reasoning Tasks

Wentao Wan, Zhuojie Yang, Yongcan Chen, Chenglin Luo, Ruilin Wang

Column-Oriented Datalog on the GPU

Yihao Sun, Sidharth Kumar, Thomas Gilray, Kristopher Micinski

MTVHunter: Smart Contracts Vulnerability Detection Based on Multi-Teacher Knowledge Translation

Guokai Sun, Yuan Zhuang, Shuo Zhang, Xiaoyu Feng, Zhenguang Liu

Joint Knowledge Editing for Information Enrichment and Probability Promotion

Wenhang Shi, Yiren Chen, Shuqing Bian, Xinyi Zhang, Zhe Zhao

Learning Theorem Rationale for Improving the Mathematical Reasoning Capability of Large Language Models

Yu Sheng, Linjing Li, Daniel Dajun Zeng

A Variable Occurrence-Centric Framework for Inconsistency Handling

Yakoub Salhi

Shield Synthesis for LTL Modulo Theories

Andoni Rodríguez, Guy Amir, Davide Corsi, César Sánchez, Guy Katz