ICML 2025

3,330 papers

Breaking the Quadratic Barrier: Robust Cardinality Sketches for Adaptive Queries

Edith Cohen, Mihir Singhal, Uri Stemmer

The Empirical Mean is Minimax Optimal for Local Glivenko-Cantelli

Doron Cohen, Aryeh Kontorovich, Roi Weiss

Two Tickets are Better than One: Fair and Accurate Hiring Under Strategic LLM Manipulations

Lee Cohen, Connie Hong, Jack Hsieh, Judy Hanwen Shen

Collaborative Mean Estimation Among Heterogeneous Strategic Agents: Individual Rationality, Fairness, and Truthful Contribution

Alex Clinton, Yiding Chen, Jerry Zhu, Kirthevasan Kandasamy

Beyond The Rainbow: High Performance Deep Reinforcement Learning on a Desktop PC

Tyler Clark, Mark Towers, Christine Evers, Jonathon Hare

Sample Complexity of Branch-length Estimation by Maximum Likelihood

David Clancy Jr., Hanbaek Lyu, Sebastien Roch

Optimization for Neural Operators can Benefit from Width

Pedro Cisneros-Velarde, Bhavesh Shrimali, Arindam Banerjee

Vector Grimoire: Codebook-based Shape Generation under Raster Image Supervision

Marco Cipriano, Moritz Feuerpfeil, Gerard de Melo

Relational Conformal Prediction for Correlated Time Series

Andrea Cini, Alexander Jenkins, Danilo Mandic, Cesare Alippi, Filippo Maria Bianchi

Objective drives the consistency of representational similarity across datasets

Laure Ciernik, Lorenz Linhardt, Marco Morik, Jonas Dippel, Simon Kornblith

WMAdapter: Adding WaterMark Control to Latent Diffusion Models

Hai Ci, Yiren Song, Pei Yang, Jinheng Xie, Mike Zheng Shou

Unifying Specialized Visual Encoders for Video Language Models

Jihoon Chung, Tyler Zhu, Max Gonzalez Saez-Diez, Juan Carlos Niebles, Honglu Zhou

Learning to Route LLMs with Confidence Tokens

Yu-Neng Chuang, Prathusha Kameswara Sarma, Parikshit Gopalan, John Boccio, Sara Bolouki

SelfCite: Self-Supervised Alignment for Context Attribution in Large Language Models

Yung-Sung Chuang, Benjamin Cohen-Wang, Zejiang Shen, Zhaofeng Wu, Hu Xu

SFT Memorizes, RL Generalizes: A Comparative Study of Foundation Model Post-training

Tianzhe Chu, Yuexiang Zhai, Jihan Yang, Shengbang Tong, Saining Xie

Fine-Grained Captioning of Long Videos through Scene Graph Consolidation

Sanghyeok Chu, Seonguk Seo, Bohyung Han

Provable and Practical Online Learning Rate Adaptation with Hypergradient Descent

Ya-Chi Chu, Wenzhi Gao, Yinyu Ye, Madeleine Udell

Linear convergence of Sinkhorn’s algorithm for generalized static Schrödinger bridge

Rahul Choudhary, Hanbaek Lyu

Feature Learning beyond the Lazy-Rich Dichotomy: Insights from Representational Geometry

Chi-Ning Chou, Hang Le, Yichen Wang, SueYeon Chung

A Hitchhiker’s Guide to Scaling Law Estimation

Leshem Choshen, Yang Zhang, Jacob Andreas

How Contaminated Is Your Benchmark? Measuring Dataset Leakage in Large Language Models with Kernel Divergence

Hyeong Kyu Choi, Maxim Khanov, Hongxin Wei, Yixuan Li

Overcoming Spurious Solutions in Semi-Dual Neural Optimal Transport: A Smoothing Approach for Learning the Optimal Transport Plan

Jaemoo Choi, Jaewoong Choi, Dohyun Kwon

Lightweight Dataset Pruning without Full Training via Example Difficulty and Prediction Uncertainty

Yeseul Cho, Baekrok Shin, Changmin Kang, Chulhee Yun

ARS: Adaptive Reward Scaling for Multi-Task Reinforcement Learning

Myungsik Cho, Jongeui Park, Jeonghye Kim, Youngchul Sung

One-Step Generalization Ratio Guided Optimization for Domain Generalization

Sumin Cho, Dongwon Kim, Kwangsu Kim

Policy-labeled Preference Learning: Is Preference Enough for RLHF?

Taehyun Cho, Seokhun Ju, Seungyub Han, Dohyeong Kim, Kyungjae Lee

Bellman Unbiasedness: Toward Provably Efficient Distributional Reinforcement Learning with General Value Function Approximation

Taehyun Cho, Seungyub Han, Seokhun Ju, Dohyeong Kim, Kyungjae Lee

Mixed-curvature decision trees and random forests

Philippe Chlenski, Quentin Chu, Raiyan R. Khan, Kaizhu Du, Antonio Khalil Moretti

SDP-CROWN: Efficient Bound Propagation for Neural Network Verification with Tightness of Semidefinite Programming

Hong-Ming Chiu, Hao Chen, Huan Zhang, Richard Y. Zhang

Portable Reward Tuning: Towards Reusable Fine-Tuning across Different Pretrained Models

Daiki Chijiwa, Taku Hasegawa, Kyosuke Nishida, Kuniko Saito, Susumu Takeuchi

Quamba2: A Robust and Scalable Post-training Quantization Framework for Selective State Space Models

Hung-Yueh Chiang, Chi-Chih Chang, Natalia Frumkin, Kai-Chiang Wu, Mohamed S. Abdelfattah

Empowering World Models with Reflection for Embodied Video Prediction

Xiaowei Chi, Chun-Kai Fan, Hengyuan Zhang, Xingqun Qi, Rongyu Zhang

Copilot Arena: A Platform for Code LLM Evaluation in the Wild

Wayne Chi, Valerie Chen, Anastasios Nikolas Angelopoulos, Wei-Lin Chiang, Aditya Mittal

Outlier Gradient Analysis: Efficiently Identifying Detrimental Training Samples for Deep Learning Models

Anshuman Chhabra, Bo Li, Jian Chen, Prasant Mohapatra, Hongfu Liu

Clipping Improves Adam-Norm and AdaGrad-Norm when the Noise Is Heavy-Tailed

Savelii Chezhegov, Klyukin Yaroslav, Andrei Semenov, Aleksandr Beznosikov, Alexander Gasnikov

BILBO: BILevel Bayesian Optimization

Ruth Wan Theng Chew, Quoc Phong Nguyen, Bryan Kian Hsiang Low

Adaptive Sample Sharing for Multi Agent Linear Bandits

Hamza Cherkaoui, Merwan Barlier, Igor Colin

SketchDNN: Joint Continuous-Discrete Diffusion for CAD Sketch Generation

Sathvik Reddy Chereddy, John Femiani

EARL-BO: Reinforcement Learning for Multi-Step Lookahead, High-Dimensional Bayesian Optimization

Mujin Cheon, Jay H Lee, Dong-Yeun Koh, Calvin Tsay

Exploiting Presentative Feature Distributions for Parameter-Efficient Continual Learning of Large Language Models

Xin Cheng, Jiabo Ye, Haiyang Xu, Ming Yan, Ji Zhang

Not All Tokens Matter All The Time: Dynamic Token Aggregation Towards Efficient Detection Transformers

Jiacheng Cheng, Xiwen Yao, Xiang Yuan, Junwei Han

Whoever Started the interference Should End It: Guiding Data-Free Model Merging via Task Vectors

Runxi Cheng, Feng Xiong, Yongxian Wei, Wanyun Zhu, Chun Yuan

A Unified Framework for Entropy Search and Expected Improvement in Bayesian Optimization

Nuojin Cheng, Leonard Papenmeier, Stephen Becker, Luigi Nardi

Accelerating PDE-Constrained Optimization by the Derivative of Neural Operators

Ze Cheng, Zhuoyu Li, Wang Xiaoqiang, Jianing Huang, Zhizhou Zhang

TabFSBench: Tabular Benchmark for Feature Shifts in Open Environments

Zi-Jian Cheng, Ziyi Jia, Zhi Zhou, Yu-feng Li, Lan-Zhe Guo

Diff-MoE: Diffusion Transformer with Time-Aware and Space-Adaptive Experts

Kun Cheng, Xiao He, Lei Yu, Zhijun Tu, Mingrui Zhu

Revealing Weaknesses in Text Watermarking Through Self-Information Rewrite Attacks

Yixin Cheng, Hongcheng Guo, Yangming Li, Leonid Sigal

Scaling Video-Language Models to 10K Frames via Hierarchical Differential Distillation

Chuanqi Cheng, Jian Guan, Wei Wu, Rui Yan

Tool Unlearning for Tool-Augmented LLMs

Jiali Cheng, Hadi Amiri

ExtPose: Robust and Coherent Pose Estimation by Extending ViTs

Rongyu Chen, Li’an Zhuo, Linlin Yang, Qi Wang, Liefeng Bo

Why Is Spatial Reasoning Hard for VLMs? An Attention Mechanism Perspective on Focus Areas

shiqi chen, Tongyao Zhu, Ruochen Zhou, Jinghan Zhang, Siyang Gao

FIC-TSC: Learning Time Series Classification with Fisher Information Constraint

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

OmniArch: Building Foundation Model for Scientific Computing

Tianyu Chen, Haoyi Zhou, Ying Li, Hao Wang, Chonghan Gao

On the Convergence of Continuous Single-timescale Actor-critic

Xuyang Chen, Lin Zhao

Asymmetric Decision-Making in Online Knowledge Distillation: Unifying Consensus and Divergence

Zhaowei Chen, Borui Zhao, Yuchen Ge, Yuhao Chen, Renjie Song

Bring Reason to Vision: Understanding Perception and Reasoning through Model Merging

shiqi chen, Jinghan Zhang, Tongyao Zhu, Wei Liu, Siyang Gao

Gaussian Mixture Flow Matching Models

Hansheng Chen, Kai Zhang, Hao Tan, Zexiang Xu, Fujun Luan

Convergence of Consistency Model with Multistep Sampling under General Data Assumptions

Yiding Chen, Yiyi Zhang, Owen Oertell, Wen Sun

A Memory Efficient Randomized Subspace Optimization Method for Training Large Language Models

Yiming Chen, yuan zhang, Yin Liu, Kun Yuan, Zaiwen Wen

Assessing Safety Risks and Quantization-aware Safety Patching for Quantized Large Language Models

Kejia Chen, Jiawen Zhang, Jiacong Hu, Yu Wang, Jian Lou

Test-Time Selective Adaptation for Uni-Modal Distribution Shift in Multi-Modal Data

Mingcai Chen, Baoming Zhang, Zongbo Han, Wenyu Jiang, Yanmeng Wang

Core Context Aware Transformers for Long Context Language Modeling

Yaofo Chen, Zeng You, Shuhai Zhang, Haokun Li, Yirui Li

Hierarchical Graph Tokenization for Molecule-Language Alignment

Yongqiang Chen, Quanming Yao, Juzheng Zhang, James Cheng, Yatao Bian

Learning Configurations for Data-Driven Multi-Objective Optimization

Zhiyang Chen, Hailong Yao, Xia Yin

Global Convergence and Rich Feature Learning in L-Layer Infinite-Width Neural Networks under μ Parametrization

Zixiang Chen, Greg Yang, Qingyue Zhao, Quanquan Gu

Learn Singularly Perturbed Solutions via Homotopy Dynamics

Chuqi Chen, Yahong Yang, Yang Xiang, Wenrui Hao

Low-Dimension-to-High-Dimension Generalization and Its Implications for Length Generalization

Yang Chen, Long Yang, Yitao Liang, Zhouchen Lin

Discriminative Policy Optimization for Token-Level Reward Models

Hongzhan Chen, Tao Yang, Shiping Gao, Ruijun Chen, Xiaojun Quan

An All-Atom Generative Model for Designing Protein Complexes

Ruizhe Chen, Dongyu Xue, Xiangxin Zhou, Zaixiang Zheng, Xiangxiang Zeng

Hybrid Batch Normalisation: Resolving the Dilemma of Batch Normalisation in Federated Learning

Hongyao Chen, Tianyang Xu, Xiaojun Wu, Josef Kittler

Do NOT Think That Much for 2+3=? On the Overthinking of Long Reasoning Models

Xingyu Chen, Jiahao Xu, Tian Liang, Zhiwei He, Jianhui Pang

Efficient First-Order Optimization on the Pareto Set for Multi-Objective Learning under Preference Guidance

Lisha Chen, Quan Xiao, Ellen Hidemi Fukuda, Xinyi Chen, Kun Yuan

Identification of Latent Confounders via Investigating the Tensor Ranks of the Nonlinear Observations

Zhengming Chen, Yewei Xia, Feng Xie, Jie Qiao, Zhifeng Hao

Oscillation-Reduced MXFP4 Training for Vision Transformers

Yuxiang Chen, Haocheng Xi, Jun Zhu, Jianfei Chen

Learning without Isolation: Pathway Protection for Continual Learning

Zhikang Chen, Abudukelimu Wuerkaixi, Sen Cui, Haoxuan Li, Ding Li

Stable Fair Graph Representation Learning with Lipschitz Constraint

Qiang Chen, Zhongze Wu, Xiu Su, Xi Lin, Zhe Qu

Voronoi-grid-based Pareto Front Learning and Its Application to Collaborative Federated Learning

Mengmeng Chen, Xiaohu Wu, Qiqi Liu, Tiantian He, Yew-Soon Ong

De-mark: Watermark Removal in Large Language Models

Ruibo Chen, Yihan Wu, Junfeng Guo, Heng Huang

AutoGFM: Automated Graph Foundation Model with Adaptive Architecture Customization

Haibo Chen, Xin Wang, Zeyang Zhang, Haoyang Li, Ling Feng

MAPLE: Many-Shot Adaptive Pseudo-Labeling for In-Context Learning

Zihan Chen, Song Wang, Zhen Tan, Jundong Li, Cong Shen

Online Detection of LLM-Generated Texts via Sequential Hypothesis Testing by Betting

Can Chen, Jun-Kun Wang

Data-Juicer Sandbox: A Feedback-Driven Suite for Multimodal Data-Model Co-development

Daoyuan Chen, Haibin Wang, Yilun Huang, Ce Ge, Yaliang Li

Graph Generative Pre-trained Transformer

Xiaohui Chen, Yinkai Wang, Jiaxing He, Yuanqi Du, Soha Hassoun

Causal Logistic Bandits with Counterfactual Fairness Constraints

Jiajun Chen, Jin Tian, Christopher John Quinn

OWLS: Scaling Laws for Multilingual Speech Recognition and Translation Models

William Chen, Jinchuan Tian, Yifan Peng, Brian Yan, Chao-Han Huck Yang

Unbiased Evaluation of Large Language Models from a Causal Perspective

Meilin Chen, Jian Tian, Liang Ma, Di Xie, Weijie Chen

Rethinking Time Encoding via Learnable Transformation Functions

Xi Chen, Yateng Tang, Jiarong Xu, Jiawei Zhang, Siwei Zhang

Generalists vs. Specialists: Evaluating LLMs on Highly-Constrained Biophysical Sequence Optimization Tasks

Angelica Chen, Samuel Don Stanton, Frances Ding, Robert G Alberstein, Andrew Martin Watkins

SepLLM: Accelerate Large Language Models by Compressing One Segment into One Separator

Guoxuan Chen, Han Shi, Jiawei Li, Yihang Gao, Xiaozhe Ren

VisionTS: Visual Masked Autoencoders Are Free-Lunch Zero-Shot Time Series Forecasters

Mouxiang Chen, Lefei Shen, Zhuo Li, Xiaoyun Joy Wang, Jianling Sun

Conformal Tail Risk Control for Large Language Model Alignment

Catherine Chen, Jingyan Shen, Zhun Deng, Lihua Lei

Mixture of Hidden-Dimensions: Not All Hidden-States’ Dimensions are Needed in Transformer

Yilong Chen, Junyuan Shang, Zhenyu Zhang, Jiawei Sheng, Tingwen Liu

Rethinking the Bias of Foundation Model under Long-tailed Distribution

Jiahao Chen, Bin Qin, Jiangmeng Li, Hao Chen, Bing Su

DyCodeEval: Dynamic Benchmarking of Reasoning Capabilities in Code Large Language Models Under Data Contamination

Simin Chen, Pranav Pusarla, Baishakhi Ray

An Effective and Secure Federated Multi-View Clustering Method with Information-Theoretic Perspective

Xinyue Chen, Jinfeng Peng, Yuhao Li, Xiaorong Pu, Yang Yang

Optimal Survey Design for Private Mean Estimation

Yu-Wei Chen, Raghu Pasupathy, Jordan Awan

Information Bottleneck-guided MLPs for Robust Spatial-temporal Forecasting

Min Chen, Guansong Pang, Wenjun Wang, Cheng Yan

Multiple-policy Evaluation via Density Estimation

Yilei Chen, Aldo Pacchiano, Ioannis Paschalidis

Nested Expectations with Kernel Quadrature

Zonghao Chen, Masha Naslidnyk, François-Xavier Briol

TRUST-VLM: Thorough Red-Teaming for Uncovering Safety Threats in Vision-Language Models

Kangjie Chen, Li Muyang, Guanlin Li, Shudong Zhang, Shangwei Guo