ICML 2025

3,330 papers

CTBench: A Library and Benchmark for Certified Training

Yuhao Mao, Stefan Balauca, Martin Vechev

Efficient Diffusion Models for Symmetric Manifolds

Oren Mangoubi, Neil He, Nisheeth K. Vishnoi

Scaffold with Stochastic Gradients: New Analysis with Linear Speed-Up

Paul Mangold, Alain Oliviero Durmus, Aymeric Dieuleveut, Eric Moulines

Learning Latent Graph Structures and their Uncertainty

Alessandro Manenti, Daniele Zambon, Cesare Alippi

Potemkin Understanding in Large Language Models

Marina Mancoridis, Bec Weeks, Keyon Vafa, Sendhil Mullainathan

Emergence in non-neural models: grokking modular arithmetic via average gradient outer product

Neil Rohit Mallinar, Daniel Beaglehole, Libin Zhu, Adityanarayanan Radhakrishnan, Parthe Pandit

Reasoning Limitations of Multimodal Large Language Models. A case study of Bongard Problems

Mikołaj Małkiński, Szymon Pawlonka, Jacek Mańdziuk

Craftium: Bridging Flexibility and Efficiency for Rich 3D Single- and Multi-Agent Environments

Mikel Malagon, Josu Ceberio, Jose A. Lozano

Hypothesis Testing for Generalized Thurstone Models

Anuran Makur, Japneet Singh

Residual Matrix Transformers: Scaling the Size of the Residual Stream

Brian Mak, Jeffrey Flanigan

Regret-Free Reinforcement Learning for Temporal Logic Specifications

R Majumdar, Mahmoud Salamati, Sadegh Soudjani

LETS Forecast: Learning Embedology for Time Series Forecasting

Abrar Majeedi, Viswanatha Reddy Gajjala, Satya Sai Srinath Namburi GNVV, Nada Magdi Elkordi, Yin Li

SecEmb: Sparsity-Aware Secure Federated Learning of On-Device Recommender System with Large Embedding

Peihua Mai, Youlong Ding, Ziyan Lyu, Minxin Du, Yan Pang

Auditing f-differential privacy in one run

Saeed Mahloujifar, Luca Melis, Kamalika Chaudhuri

Sable: a Performant, Efficient and Scalable Sequence Model for MARL

Omayma Mahjoub, Sasha Abramowitz, Ruan John de Kock, Wiem Khlifi, Simon Verster Du Toit

Leveraging Online Olympiad-Level Math Problems for LLMs Training and Contamination-Resistant Evaluation

Sadegh Mahdavi, Muchen Li, Kaiwen Liu, CHRISTOS THRAMPOULIDIS, Leonid Sigal

Compositional Risk Minimization

Divyat Mahajan, Mohammad Pezeshki, Charles Arnal, Ioannis Mitliagkas, Kartik Ahuja

DataDecide: How to Predict Best Pretraining Data with Small Experiments

Ian Magnusson, Nguyen Tai, Ben Bogin, David Heineman, Jena D. Hwang

Learning to Stop: Deep Learning for Mean Field Optimal Stopping

Lorenzo Magnino, Yuchen Zhu, Mathieu Lauriere

Linearization Turns Neural Operators into Function-Valued Gaussian Processes

Emilia Magnani, Marvin Pförtner, Tobias Weber, Philipp Hennig

AKORN: Adaptive Knots generated Online for RegressioN splines

Sunil Madhow, Dheeraj Baby, Yu-Xiang Wang

Inverse problems with experiment-guided AlphaFold

Sai Advaith Maddipatla, Nadav Bojan, Meital Bojan, Sanketh Vedula, Paul Schanda

Compositional Causal Reasoning Evaluation in Language Models

Jacqueline R. M. A. Maasch, Alihan Hüyük, Xinnuo Xu, Aditya V. Nori, Javier Gonzalez

An Online Statistical Framework for Out-of-Distribution Detection

Xinsong Ma, Xin Zou, Weiwei Liu

Behavior-agnostic Task Inference for Robust Offline In-context Reinforcement Learning

Long Ma, Fangwei Zhong, Yizhou Wang

Graph Attention is Not Always Beneficial: A Theoretical Analysis of Graph Attention Mechanisms via Contextual Stochastic Block Models

Zhongtian Ma, Qiaosheng Zhang, Bocheng Zhou, Yexin Zhang, Shuyue Hu

Efficient Multi-modal Long Context Learning for Training-free Adaptation

Zehong Ma, Shiliang Zhang, Longhui Wei, Qi Tian

Benchmarking Abstract and Reasoning Abilities Through A Theoretical Perspective

Qingchuan Ma, Yuhang Wu, Xiawu Zheng, Rongrong Ji

A Closer Look at Generalized BH Algorithm for Out-of-Distribution Detection

Xinsong Ma, Jie Wu, Weiwei Liu

Robust Spatio-Temporal Centralized Interaction for OOD Learning

Jiaming Ma, Binwu Wang, Pengkun Wang, Zhengyang Zhou, Xu Wang

COExpander: Adaptive Solution Expansion for Combinatorial Optimization

Jiale Ma, Wenzheng Pan, Yang Li, Junchi Yan

PANDAS: Improving Many-shot Jailbreaking via Positive Affirmation, Negative Demonstration, and Adaptive Sampling

Avery Ma, Yangchen Pan, Amir-massoud Farahmand

TimePro: Efficient Multivariate Long-term Time Series Forecasting with Variable- and Time-Aware Hyper-state

Xiaowen Ma, Zhen-Liang Ni, Shuai Xiao, Xinghao Chen

Learning from Loss Landscape: Generalizable Mixed-Precision Quantization via Adaptive Sharpness-Aware Gradient Aligning

Lianbo Ma, Jianlun Ma, Yuee Zhou, Guoyang Xie, Qiang He

TANGO: Clustering with Typicality-Aware Nonlocal Mode-Seeking and Graph-Cut Optimization

Haowen Ma, Zhiguo Long, Hua Meng

PTTA: Purifying Malicious Samples for Test-Time Model Adaptation

Jing Ma, Hanlin Li, Xiang Xiang

Network Sparsity Unlocks the Scaling Potential of Deep Reinforcement Learning

Guozheng Ma, Lu Li, Zilin Wang, Li Shen, Pierre-Luc Bacon

"Why Is There a Tumor?": Tell Me the Reason, Show Me the Evidence

Mengmeng Ma, Tang Li, Yunxiang Peng, Lu Lin, Volkan Beylergil

Catching Two Birds with One Stone: Reward Shaping with Dual Random Networks for Balancing Exploration and Exploitation

Haozhe Ma, Fangling Li, Jing Yu Lim, Zhengding Luo, Thanh Vinh Vo

HetSSNet: Spatial-Spectral Heterogeneous Graph Learning Network for Panchromatic and Multispectral Images Fusion

Mengting Ma, Yizhen Jiang, Mengjiao Zhao, Jiaxin Li, Wei Zhang

Adversarial Robustness via Deformable Convolution with Stochasticity

Yanxiang Ma, Zixuan Huang, Minjing Dong, Shan You, Chang Xu

SWAN: SGD with Normalization and Whitening Enables Stateless LLM Training

Chao Ma, Wenbo Gong, meyer scetbon, Edward Meeds

Overcoming Non-monotonicity in Transducer-based Streaming Generation

Zhengrui Ma, Yang Feng, Min Zhang

Pruning for GNNs: Lower Complexity with Comparable Expressiveness

Dun Ma, Jianguo Chen, Wenguo Yang, Suixiang Gao, Shengminjie Chen

Efficient Online Reinforcement Learning for Diffusion Policy

Haitong Ma, Tianyi Chen, Kai Wang, Na Li, Bo Dai

Improving Multimodal Learning Balance and Sufficiency through Data Remixing

Xiaoyu Ma, Hao Chen, Yongjian Deng

Meta-Black-Box-Optimization through Offline Q-function Learning

Zeyuan Ma, Zhiguang Cao, Zhou Jiang, Hongshu Guo, Yue-Jiao Gong

Playmate: Flexible Control of Portrait Animation via 3D-Implicit Space Guided Diffusion

Xingpei Ma, Jiaran Cai, Yuansheng Guan, Shenneng Huang, Qiang Zhang

RealRAG: Retrieval-augmented Realistic Image Generation via Self-reflective Contrastive Learning

Yuanhuiyi Lyu, Xu Zheng, Lutao Jiang, Yibo Yan, Xin Zou

Consensus Based Stochastic Optimal Control

Liyao Lyu, Jingrun Chen

Adapting While Learning: Grounding LLMs for Scientific Problems with Tool Usage Adaptation

Bohan Lyu, Yadi Cao, Duncan Watson-Parris, Leon Bergen, Taylor Berg-Kirkpatrick

Dendritic Localized Learning: Toward Biologically Plausible Algorithm

Changze Lv, Jingwen Xu, Yiyang Lu, Xiaohua Wang, Zhenghua Wang

Autonomy-of-Experts Models

Ang Lv, Ruobing Xie, Yining Qian, Songhao Wu, Xingwu Sun

Runtime Analysis of Evolutionary NAS for Multiclass Classification

Zeqiong Lv, Chao Qian, Yun Liu, Jiahao Fan, Yanan Sun

Enhancing Rating-Based Reinforcement Learning to Effectively Leverage Feedback from Large Vision-Language Models

Tung Minh Luu, Younghwan Lee, Donghoon Lee, Sunho Kim, Min Jun Kim

LADA: Scalable Label-Specific CLIP Adapter for Continual Learning

Mao-Lin Luo, Zi-Hao Zhou, Tong Wei, Min-ling Zhang

Conformity Score Averaging for Classification

Rui Luo, Zhixin Zhou

MERIT: Maximum-normalized Element-wise Ratio for Language Model Large-batch Training

Yang Luo, Zangwei Zheng, Ziheng Qin, Zirui Zhu, Yong Liu

Graph-constrained Reasoning: Faithful Reasoning on Knowledge Graphs with Large Language Models

Linhao Luo, Zicheng Zhao, Gholamreza Haffari, Yuan-Fang Li, Chen Gong

David and Goliath: Small One-step Model Beats Large Diffusion with Score Post-training

Weijian Luo, Colin Zhang, Debing Zhang, Zhengyang Geng

Hi-Patch: Hierarchical Patch GNN for Irregular Multivariate Time Series

Yicheng Luo, Bowen Zhang, Zhen Liu, Qianli Ma

Causal Attribution Analysis for Continuous Outcomes

Shanshan Luo, Yu Yixuan, Chunchen Liu, Feng Xie, Zhi Geng

Learning to Trust Bellman Updates: Selective State-Adaptive Regularization for Offline RL

Qin-Wen Luo, Ming-Kun Xie, Ye-Wen Wang, Sheng-jun Huang

Transolver++: An Accurate Neural Solver for PDEs on Million-Scale Geometries

Huakun Luo, Haixu Wu, Hang Zhou, Lanxiang Xing, Yichen Di

Locality Preserving Markovian Transition for Instance Retrieval

Jifei Luo, Wenzheng Wu, Hantao Yao, Lu Yu, Changsheng Xu

One-dimensional Path Convolution

Xuanshu Luo, Martin Werner

Efficient and Scalable Density Functional Theory Hamiltonian Prediction through Adaptive Sparsity

Erpai Luo, Xinran Wei, Lin Huang, Yunyang Li, Han Yang

Beyond One-Hot Labels: Semantic Mixing for Model Calibration

Haoyang Luo, Linwei Tao, Minjing Dong, Chang Xu

Sparse Causal Discovery with Generative Intervention for Unsupervised Graph Domain Adaptation

Junyu Luo, Yuhao Tang, Yiwei Fu, Xiao Luo, Zhizhuo Kou

Sparsing Law: Towards Large Language Models with Greater Activation Sparsity

Yuqi Luo, Chenyang Song, Xu Han, Yingfa Chen, Chaojun Xiao

Can Classic GNNs Be Strong Baselines for Graph-level Tasks? Simple Architectures Meet Excellence

Yuankai Luo, Lei Shi, Xiao-ming Wu

Fast and Low-Cost Genomic Foundation Models via Outlier Removal

Haozheng Luo, Chenghao Qiu, Maojiang Su, Zhihan Zhou, Zoe Mehta

Occult: Optimizing Collaborative Communications across Experts for Accelerated Parallel MoE Training and Inference

Shuqing Luo, Pingzhi Li, Jie Peng, Yang Zhao, Yu Cao

Quantum Algorithms for Finite-horizon Markov Decision Processes

Bin Luo, Yuwen Huang, Jonathan Allcock, Xiaojun Lin, Shengyu Zhang

KBQA-o1: Agentic Knowledge Base Question Answering with Monte Carlo Tree Search

Haoran Luo, Haihong E, Yikai Guo, Qika Lin, Xiaobao Wu

Vision-Language Models Create Cross-Modal Task Representations

Grace Luo, Trevor Darrell, Amir Bar

Probing Visual Language Priors in VLMs

Tiange Luo, Ang Cao, Gunhee Lee, Justin Johnson, Honglak Lee

Stacey: Promoting Stochastic Steepest Descent via Accelerated ℓ_p-Smooth Nonconvex Optimization

Xinyu Luo, Site Bai, Bolian Li, Petros Drineas, Ruqi Zhang

Bipartite Ranking From Multiple Labels: On Loss Versus Label Aggregation

MICHAL LUKASIK, Lin Chen, Harikrishna Narasimhan, Aditya Krishna Menon, Wittawat Jitkrittum

Joint MoE Scaling Laws: Mixture of Experts Can Be Memory Efficient

Jan Ludziejewski, Maciej Pióro, Jakub Krajewski, Maciej Stefaniak, Michał Krutul

Learning with Expected Signatures: Theory and Applications

Lorenzo Lucchese, Mikko S. Pakkanen, Almut E. D. Veraart

Constrained Exploitability Descent: An Offline Reinforcement Learning Method for Finding Mixed-Strategy Nash Equilibrium

Runyu Lu, Yuanheng Zhu, Dongbin Zhao

Sparse Autoencoders, Again?

Yin Lu, Xuening Zhu, Tong He, David Wipf

ToMA: Token Merge with Attention for Diffusion Models

Wenbo Lu, Shaoyi Zheng, Yuxuan Xia, Shengjie Wang

FedSMU: Communication-Efficient and Generalization-Enhanced Federated Learning through Symbolic Model Updates

Xinyi Lu, Hao Zhang, Chenglin Li, Weijia Lu, Zhifei Yang

Rethinking the Stability-Plasticity Trade-off in Continual Learning from an Architectural Perspective

Aojun Lu, Hangjie Yuan, Tao Feng, Yanan Sun

LLaVA-ReID: Selective Multi-image Questioner for Interactive Person Re-Identification

Yiding Lu, Mouxing Yang, Dezhong Peng, Peng Hu, Yijie Lin

Linear Transformers as VAR Models: Aligning Autoregressive Attention Mechanisms with Autoregressive Forecasting

Jiecheng Lu, Shihao Yang

Learning Initial Basis Selection for Linear Programming via Duality-Inspired Tripartite Graph Representation and Comprehensive Supervision

Anqi Lu, Junchi Yan

Agent Reviewers: Domain-specific Multimodal Agents with Shared Memory for Paper Review

Kai Lu, Shixiong Xu, Jinqiu Li, Kun Ding, GAOFENG MENG

OptMATH: A Scalable Bidirectional Data Synthesis Framework for Optimization Modeling

Hongliang Lu, Zhonglin Xie, Yaoyu Wu, Can Ren, Yuxuan Chen

Stochastic Forward–Backward Deconvolution: Training Diffusion Models with Finite Noisy Datasets

Haoye Lu, Qifan Wu, Yaoliang Yu

DAMA: Data- and Model-aware Alignment of Multi-modal LLMs

Jinda Lu, Junkang Wu, Jinghan Li, Xiaojun Jia, Shuo Wang

Smoothed Preference Optimization via ReNoise Inversion for Aligning Diffusion Models with Varied Human Preferences

Yunhong Lu, Qichao Wang, Hengyuan Cao, Xiaoyin Xu, Min Zhang

TSP: A Two-Sided Smoothed Primal-Dual Method for Nonconvex Bilevel Optimization

Songtao Lu

Overcoming the Curse of Dimensionality in Reinforcement Learning Through Approximate Factorization

Chenbei Lu, Laixi Shi, Zaiwei Chen, Chenye Wu, Adam Wierman

Habitizing Diffusion Planning for Efficient and Effective Decision Making

Haofei Lu, Yifei Shen, Dongsheng Li, Junliang Xing, Dongqi Han

System-Aware Unlearning Algorithms: Use Lesser, Forget Faster

Linda Lu, Ayush Sekhari, Karthik Sridharan

Safe Delta: Consistently Preserving Safety when Fine-Tuning LLMs on Diverse Datasets

Ning Lu, Shengcai Liu, Jiahao Wu, Weiyu Chen, Zhirui Zhang

Towards Practical Defect-Focused Automated Code Review

Junyi Lu, Lili Jiang, Xiaojia Li, Jianbing Fang, Fengjun Zhang