ICML 2025

3,330 papers

How Compositional Generalization and Creativity Improve as Diffusion Models are Trained

Alessandro Favero, Antonio Sclocchi, Francesco Cagnetta, Pascal Frossard, Matthieu Wyart

A New Approach to Backtracking Counterfactual Explanations: A Unified Causal Framework for Efficient Model Interpretability

Pouria Fatemi, Ehsan Sharifian, Mohammad Hossein Yassaee

MONA: Myopic Optimization with Non-myopic Approval Can Mitigate Multi-step Reward Hacking

Sebastian Farquhar, Vikrant Varma, David Lindner, David Elson, Caleb Biddulph

Jacobian Sparse Autoencoders: Sparsify Computations, Not Just Activations

Lucy Farnik, Tim Lawson, Conor Houghton, Laurence Aitchison

Speeding up Policy Simulation in Supply Chain RL

Vivek Farias, Joren Gijsbrechts, Aryan I. Khojandi, Tianyi Peng, Andrew Zheng

Zero-Shot Adaptation of Parameter-Efficient Fine-Tuning in Diffusion Models

Farzad Farhadzadeh, Debasmit Das, Shubhankar Borse, Fatih Porikli

Temporal Difference Flows

Jesse Farebrother, Matteo Pirotta, Andrea Tirinzoni, Rémi Munos, Alessandro Lazaric

Reliable Algorithm Selection for Machine Learning-Guided Design

Clara Fannjiang, Ji Won Park

FlexControl: Computation-Aware Conditional Control with Differentiable Router for Text-to-Image Generation

Zheng Fang, Lichuan Xiang, Xu Cai, Kaicheng Zhou, Hongkai Wen

Tackling Dimensional Collapse toward Comprehensive Universal Domain Adaptation

Hung-Chieh Fang, Po-Yi Lu, Hsuan-tien Lin

Catch Your Emotion: Sharpening Emotion Perception in Multimodal Large Language Models

Yiyang Fang, Jian Liang, Wenke Huang, He Li, Kehua Su

Homophily Enhanced Graph Domain Adaptation

Ruiyi Fang, Bingheng Li, Jingyu Zhao, Ruizhi Pu, Qiuhao Zeng

Understanding and Mitigating Memorization in Diffusion Models for Tabular Data

Zhengyu Fang, Zhimeng Jiang, Huiyuan Chen, Xiao Li, Jing Li

FedPHA: Federated Prompt Learning for Heterogeneous Client Adaptation

Chengying Fang, Wenke Huang, Guancheng Wan, Yihao Yang, Mang Ye

Towards a Unified Framework of Clustering-based Anomaly Detection

Zeyu Fang, Ming Gu, Sheng Zhou, Jiawei Chen, Qiaoyu Tan

SAM2Act: Integrating Visual Foundation Model with A Memory Architecture for Robotic Manipulation

Haoquan Fang, Markus Grotz, Wilbert Pumacay, Yi Ru Wang, Dieter Fox

Demeaned Sparse: Efficient Anomaly Detection by Residual Estimate

Yifan Fang, Yifei Fang, Ruizhe Chen, Haote Xu, Xinghao Ding

Adaptive Multi-prompt Contrastive Network for Few-shot Out-of-distribution Detection

Xiang Fang, Arvind Easwaran, Blaise Genest

Safety-Polarized and Prioritized Reinforcement Learning

Ke Fan, Jinpeng Zhang, Xuefeng Zhang, Yunze Wu, Jingyu Cao

On-Device Collaborative Language Modeling via a Mixture of Generalists and Specialists

Dongyang Fan, Bettina Messmer, Nikita Doikov, Martin Jaggi

Make LoRA Great Again: Boosting LoRA with Adaptive Singular Values and Mixture-of-Experts Optimization Alignment

Chenghao Fan, Zhenyi Lu, Sichen Liu, Chengfeng Gu, Xiaoye Qu

Learning Changes in Graphon Attachment Network Models

Xinyuan Fan, Bufan Li, Chenlei Leng, Weichi Wu

Towards LLM Unlearning Resilient to Relearning Attacks: A Sharpness-Aware Minimization Perspective and Beyond

Chongyu Fan, Jinghan Jia, Yihua Zhang, Anil Ramakrishna, Mingyi Hong

Graph Minimum Factorization Distance and Its Application to Large-Scale Graph Data Clustering

Jicong Fan

SAH-Drive: A Scenario-Aware Hybrid Planner for Closed-Loop Vehicle Trajectory Generation

Yuqi Fan, Zhiyong Cui, Zhenning Li, Yilong Ren, Haiyang Yu

De-AntiFake: Rethinking the Protective Perturbations Against Voice Cloning Attacks

Wei Fan, Kejiang Chen, Chang Liu, Weiming Zhang, Nenghai Yu

Task-Agnostic Pre-training and Task-Guided Fine-tuning for Versatile Diffusion Planner

Chenyou Fan, Chenjia Bai, Zhao Shan, Haoran He, Yang Zhang

MedRAX: Medical Reasoning Agent for Chest X-ray

Adibvafa Fallahpour, Jun Ma, Alif Munim, Hongwei Lyu, Bo Wang

Learning Mean Field Control on Sparse Graphs

Christian Fabian, Kai Cui, Heinz Koeppl

Understanding Complexity in VideoQA via Visual Program Generation

Cristobal Eyzaguirre, Igor Vasiljevic, Achal Dave, Jiajun Wu, Rares Andrei Ambrus

Regression for the Mean: Auto-Evaluation and Inference with Few Labels through Post-hoc Regression

Benjamin Eyre, David Madras

Avoiding Leakage Poisoning: Concept Interventions Under Distribution Shifts

Mateo Espinosa Zarlenga, Gabriele Dominici, Pietro Barbiero, Zohreh Shams, Mateja Jamnik

Multi-Stage Manipulation with Demonstration-Augmented Reward, Policy, and World Model Learning

Adrià López Escoriza, Nicklas Hansen, Stone Tao, Tongzhou Mu, Hao Su

Beyond Sensor Data: Foundation Models of Behavioral Data from Wearables Improve Health Predictions

Eray Erturk, Fahad Kamran, Salar Abbaspourazad, Sean Jewell, Harsh Sharma

Adaptive Message Passing: A General Framework to Mitigate Oversmoothing, Oversquashing, and Underreaching

Federico Errica, Henrik Christiansen, Viktor Zaverkin, Takashi Maruyama, Mathias Niepert

Reinforcement Learning for Quantum Control under Physical Constraints

Jan Ole Ernst, Aniket Chatterjee, Tim Franzmeyer, Axel Kuhn

Plan-and-Act: Improving Planning of Agents for Long-Horizon Tasks

Lutfi Eren Erdogan, Nicholas Lee, Sehoon Kim, Suhong Moon, Hiroki Furuta

Distributed Event-Based Learning via ADMM

Guner Dilsad Er, Sebastian Trimpe, Michael Muehlebach

Grammar-Forced Translation of Natural Language to Temporal Logic using LLMs

William H English, Dominic Simon, Sumit Kumar Jha, Rickard Ewetz

Maximum Coverage in Turnstile Streams with Applications to Fingerprinting Measures

Alina Ene, Alessandro Epasto, Vahab Mirrokni, Hoai-An Nguyen, Huy Nguyen

Observation Interference in Partially Observable Assistance Games

Scott Emmons, Caspar Oesterheld, Vincent Conitzer, Stuart Russell

In-Context Learning and Occam’s Razor

Eric Elmoznino, Tom Marty, Tejas Kasetty, Leo Gagnon, Sarthak Mittal

Towards a Formal Theory of Representational Compositionality

Eric Elmoznino, Thomas Jiralerspong, Yoshua Bengio, Guillaume Lajoie

Graph Adaptive Autoregressive Moving Average Models

Moshe Eliasof, Alessio Gravina, Andrea Ceni, Claudio Gallicchio, Davide Bacciu

any4: Learned 4-bit Numeric Representation for LLMs

Mostafa Elhoushi, Jeff Johnson

Learn to Vaccinate: Combining Structure Learning and Effective Vaccination for Epidemic and Outbreak Control

Sepehr Elahi, Paula Mürmann, Patrick Thiran

Solving Linear-Gaussian Bayesian Inverse Problems with Decoupled Diffusion Sequential Monte Carlo

Filip Ekström Kelvinius, Zheng Zhao, Fredrik Lindsten

WyckoffDiff – A Generative Diffusion Model for Crystal Symmetry

Filip Ekström Kelvinius, Oskar B. Andersson, Abhijith S Parackal, Dong Qian, Rickard Armiento

Enhancing Parallelism in Decentralized Stochastic Convex Optimization

Ofri Eisen, Ron Dorfman, Kfir Yehuda Levy

A Market for Accuracy: Classification Under Competition

Ohad Einav, Nir Rosenfeld

Controlled Generation with Equivariant Variational Flow Matching

Floor Eijkelboom, Heiko Zimmermann, Sharvaree Vadgama, Erik J Bekkers, Max Welling

Mind the Gap: A Practical Attack on GGUF Quantization

Kazuki Egashira, Robin Staab, Mark Vero, Jingxuan He, Martin Vechev

On the Importance of Gaussianizing Representations

Daniel Eftekhari, Vardan Papyan

Aligned Multi Objective Optimization

Yonathan Efroni, Ben Kretzu, Daniel R. Jiang, Jalaj Bhandari, Zheqing Zhu

MF-LAL: Drug Compound Generation Using Multi-Fidelity Latent Space Active Learning

Peter Eckmann, Dongxia Wu, Germano Heinzelmann, Michael K Gilson, Rose Yu

Not All Wrong is Bad: Using Adversarial Examples for Unlearning

Ali Ebrahimpour-Boroojeny, Hari Sundaram, Varun Chandrasekaran

Partially Observable Reinforcement Learning with Memory Traces

Onno Eberhard, Michael Muehlebach, Claire Vernade

Intersectional Fairness in Reinforcement Learning with Large State and Constraint Spaces

Eric Eaton, Marcel Hussing, Michael Kearns, Aaron Roth, Sikata Bela Sengupta

LASER: Attention with Exponential Transformation

Sai Surya Duvvuri, Inderjit S Dhillon

SPHINX: Structural Prediction using Hypergraph Inference Network

Iulia Duta, Pietro Lió

IT$^3$: Idempotent Test-Time Training

Nikita Durasov, Assaf Shocher, Doruk Oner, Gal Chechik, Alexei A Efros

Weakly Supervised Anomaly Detection via Dual-Tailed Kernel

Walid Durani, Tobias Nitzl, Claudia Plant, Christian Böhm

DIS-CO: Discovering Copyrighted Content in VLMs Training Data

André V. Duarte, Xuandong Zhao, Arlindo L. Oliveira, Lei Li

MxMoE: Mixed-precision Quantization for MoE with Accuracy and Performance Co-Design

Haojie Duanmu, Xiuhong Li, Zhihang Yuan, Size Zheng, Jiangfei Duan

Unnatural Languages Are Not Bugs but Features for LLMs

Keyu Duan, Yiran Zhao, Zhili Feng, Jinjie Ni, Tianyu Pang

CoPINN: Cognitive Physics-Informed Neural Networks

Siyuan Duan, Wenyuan Wu, Peng Hu, Zhenwen Ren, Dezhong Peng

Deep Fuzzy Multi-view Learning for Reliable Classification

Siyuan Duan, Yuan Sun, Dezhong Peng, Guiduo Duan, Xi Peng

Retrieval Augmented Zero-Shot Enzyme Generation for Specified Substrate

Jiahe Du, Kaixiong Zhou, Xinyu Hong, Zhaozhuo Xu, Jinbo Xu

Unsupervised Learning for Class Distribution Mismatch

Pan Du, Wangbo Zhao, Xinai Lu, Nian Liu, Zhikai Li

Latent Imputation before Prediction: A New Computational Paradigm for De Novo Peptide Sequencing

Ye Du, chen yang, Nanxi Yu, Wanyu Lin, Qian Zhao

Optimizing Temperature for Language Models with Multi-Sample Inference

Weihua Du, Yiming Yang, Sean Welleck

Reinforcement Learning with Segment Feedback

Yihan Du, Anna Winnicki, Gal Dalal, Shie Mannor, R. Srikant

Textual Unlearning Gives a False Sense of Unlearning

Jiacheng Du, Zhibo Wang, Jie Zhang, Xiaoyi Pang, Jiahui Hu

Telling Peer Direct Effects from Indirect Effects in Observational Network Data

Xiaojing Du, Jiuyong Li, Debo Cheng, Lin Liu, Wentao Gao

Enabling Optimal Decisions in Rehearsal Learning under CARE Condition

Wen-Bo Du, Hao-Yi Lei, Lue Tao, Tian-Zuo Wang, Zhi-Hua Zhou

Long-Short Alignment for Effective Long-Context Modeling in LLMs

Tianqi Du, Haotian Huang, Yifei Wang, Yisen Wang

Towards Theoretical Understanding of Sequential Decision Making with Preference Feedback

Simone Drago, Marco Mussi, Alberto Maria Metelli

Sleeping Reinforcement Learning

Simone Drago, Marco Mussi, Alberto Maria Metelli

On the Importance of Embedding Norms in Self-Supervised Learning

Andrew Draganov, Sharvaree Vadgama, Sebastian Damrich, Jan Niklas Böhm, Lucas Maes

Harmonizing Geometry and Uncertainty: Diffusion with Hyperspheres

Muskan Dosi, Chiranjeev Chiranjeev, Kartik Thakral, Mayank Vatsa, Richa Singh

ADDQ: Adaptive distributional double Q-learning

Leif Döring, Benedikt Wille, Maximilian Birr, Mihail Bı̂rsan, Martin Slowik

Towards scientific discovery with dictionary learning: Extracting biological concepts from microscopy foundation models

Konstantin Donhauser, Kristina Ulicna, Gemma Elyse Moran, Aditya Ravuri, Kian Kenyon-Dean

Emergent Response Planning in LLMs

Zhichen Dong, Zhanhui Zhou, Zhixuan Liu, Chao Yang, Chaochao Lu

ERICT: Enhancing Robustness by Identifying Concept Tokens in Zero-Shot Vision Language Models

Xinpeng Dong, Min Zhang, Didi Zhu, Ye Jun Jian, Zhang Keli

A Lens into Interpretable Transformer Mistakes via Semantic Dependency

Ruo-Jing Dong, Yu Yao, Bo Han, Tongliang Liu

Efficient Curvature-Aware Hypergradient Approximation for Bilevel Optimization

Youran Dong, Junfeng Yang, Wei Yao, Jin Zhang

TypyBench: Evaluating LLM Type Inference for Untyped Python Repositories

Honghua Dong, Jiacheng Yang, Xun Deng, Yuhe Jiang, Gennady Pekhimenko

Can Compressed LLMs Truly Act? An Empirical Evaluation of Agentic Capabilities in LLM Compression

Peijie Dong, Zhenheng Tang, Xiang Liu, Lujun Li, Xiaowen Chu

Maintaining Proportional Committees with Dynamic Candidate Sets

Chris Dong, Jannik Peters

Permutation-based Rank Test in the Presence of Discretization and Application in Causal Discovery with Mixed Data

Xinshuai Dong, Ignavier Ng, Boyang Sun, Haoyue Dai, Guang-Yuan Hao

STP: Self-play LLM Theorem Provers with Iterative Conjecturing and Proving

Kefan Dong, Tengyu Ma

Discrepancies are Virtue: Weak-to-Strong Generalization through Lens of Intrinsic Dimension

Yijun Dong, Yicheng Li, Yunai Li, Jason D. Lee, Qi Lei

Improving Zero-Shot Adversarial Robustness in Vision-Language Models by Closed-form Alignment of Adversarial Path Simplices

Junhao Dong, Piotr Koniusz, Yifei Zhang, Hao Zhu, Weiming Liu

Exactly Tight Information-theoretic Generalization Bounds via Binary Jensen-Shannon Divergence

Yuxin Dong, Haoran Guo, Tieliang Gong, Wen Wen, Chen Li

In-Context Reinforcement Learning From Suboptimal Historical Data

Juncheng Dong, Moyang Guo, Ethan X Fang, Zhuoran Yang, Vahid Tarokh

Enhancing Decision-Making of Large Language Models via Actor-Critic

Heng Dong, Kefei Duan, Chongjie Zhang

Maximum Entropy Reinforcement Learning with Diffusion Policy

Xiaoyi Dong, Jian Cheng, Xi Sheryl Zhang

Leveraging Randomness in Model and Data Partitioning for Privacy Amplification

Andy Dong, Wei-Ning Chen, Ayfer Ozgur

Ad-Hoc Human-AI Coordination Challenge

Tin Dizdarevic, Ravi Hammond, Tobias Gessler, Anisoara Calinescu, Jonathan Cook

LBI-FL: Low-Bit Integerized Federated Learning with Temporally Dynamic Bit-Width Allocation

Li Ding, Hao Zhang, Wenrui Dai, Chenglin Li, Weijia Lu