ICML 2025

3,330 papers

Reflection-Window Decoding: Text Generation with Selective Refinement

Zeyu Tang, Zhenhao Chen, Xiangchen Song, Loka Li, Yunlong Deng

Vision-Language Model Selection and Reuse for Downstream Adaptation

Hao-Zhe Tan, Zhi Zhou, Yu-feng Li, Lan-Zhe Guo

Cradle: Empowering Foundation Agents towards General Computer Control

Weihao Tan, Wentao Zhang, Xinrun Xu, Haochong Xia, Ziluo Ding

Synthesizing Privacy-Preserving Text Data via Finetuning *without* Finetuning Billion-Scale LLMs

Bowen Tan, Zheng Xu, Eric Xing, Zhiting Hu, Shanshan Wu

WMarkGPT: Watermarked Image Understanding via Multimodal Large Language Models

Songbai Tan, Xuerui Qiu, YAO SHU, Gang Xu, Linrui Xu

BoxLM: Unifying Structures and Semantics of Medical Concepts for Diagnosis Prediction in Healthcare

Yanchao Tan, Hang Lv, Yunfei Zhan, Guofang Ma, Bo Xiong

S^2FGL: Spatial Spectral Federated Graph Learning

Zihan Tan, Suyuan Huang, Guancheng Wan, Wenke Huang, He Li

Actor-Critics Can Achieve Optimal Sample Efficiency

Kevin Tan, Wei Fan, Yuting Wei

Towards Universal Offline Black-Box Optimization via Learning Language Model Embeddings

Rong-Xi Tan, Ming Chen, Ke Xue, Yao Wang, Yaoyuan Wang

Scalable Equilibrium Sampling with Sequential Boltzmann Generators

Charlie B. Tan, Joey Bose, CHEN LIN, Leon Klein, Michael M. Bronstein

FedBEns: One-Shot Federated Learning based on Bayesian Ensemble

Jacopo Talpini, Marco Savi, Giovanni Neglia

Neutral residues: revisiting adapters for model extension

Franck Signe Talla, Edouard Grave, Herve Jegou

Towards Learning to Complete Anything in Lidar

Ayca Takmaz, Cristiano Saltori, Neehar Peri, Tim Meinhardt, Riccardo de Lutio

Yuki Takezawa, Xiaowen Jiang, Anton Rodomanov, Sebastian U Stich

Distributionally Robust Active Learning for Gaussian Process Regression

Shion Takeno, Yoshito Okura, Yu Inatsu, Aoyama Tatsuya, Tomonari Tanaka

Instance-Optimal Pure Exploration for Linear Bandits on Continuous Arms

Sho Takemori, Yuhei Umeda, Aditya Gopalan

Physics-Informed Weakly Supervised Learning For Interatomic Potentials

Makoto Takamoto, Viktor Zaverkin, Mathias Niepert

Training a Generally Curious Agent

Fahim Tajwar, YiDing Jiang, Abitha Thankaraj, Sumaita Sadia Rahman, J Zico Kolter

Selective Response Strategies for GenAI

Boaz Taitler, Omer Ben-Porat

Redundancy Undermines the Trustworthiness of Self-Interpretable GNNs

Wenxin Tai, Ting Zhong, Goce Trajcevski, Fan Zhou

Features are fate: a theory of transfer learning in high-dimensional regression

Javan Tahir, Surya Ganguli, Grant M. Rotskoff

Improving Continual Learning Performance and Efficiency with Auxiliary Classifiers

Filip Szatkowski, Yaoyue Zheng, Fei Yang, Tomasz Trzcinski, Bartłomiej Twardowski

No Soundness in the Real World: On the Challenges of the Verification of Deployed Neural Networks

Attila Szász, Balázs Bánhelyi, Márk Jelasity

Identifying Metric Structures of Deep Latent Variable Models

Stas Syrota, Yevgen Zainchkovskyy, Johnny Xi, Benjamin Bloem-Reddy, Søren Hauberg

Adaptive Partitioning Schemes for Optimistic Optimization

Raja Sunkara, Ardhendu Tripathy

Stay-Positive: A Case for Ignoring Real Image Features in Fake Image Detection

Anirudh Sundara Rajan, Yong Jae Lee

Parrot: Multilingual Visual Instruction Tuning

Hai-Long Sun, Da-Wei Zhou, Yang Li, Shiyin Lu, Chao Yi

Sample-specific Noise Injection for Diffusion-based Adversarial Purification

Yuhao Sun, Jiacheng Zhang, Zesheng Ye, Chaowei Xiao, Feng Liu

CASE-Bench: Context-Aware SafEty Benchmark for Large Language Models

Guangzhi Sun, Xiao Zhan, Shutong Feng, Phil Woodland, Jose Such

Foundation Molecular Grammar: Multi-Modal Foundation Models Induce Interpretable Molecular Graph Languages

Michael Sun, Weize Yuan, Gang Liu, Wojciech Matusik, Jie Chen

Idiosyncrasies in Large Language Models

Mingjie Sun, Yida Yin, Zhiqiu Xu, J Zico Kolter, Zhuang Liu

A Sample Efficient Conditional Independence Test in the Presence of Discretization

Boyang Sun, Yu Yao, Xinshuai Dong, Zongfang Liu, Tongliang Liu

video-SALMONN-o1: Reasoning-enhanced Audio-visual Large Language Model

Guangzhi Sun, Yudong Yang, Jimin Zhuang, Changli Tang, Yixuan Li

Right Time to Learn: Promoting Generalization via Bio-inspired Spacing Effect in Knowledge Distillation

Guanglong Sun, Hongwei Yan, Liyuan Wang, Qian Li, Bo Lei

Earley-Driven Dynamic Pruning for Efficient Structured Decoding

Xintong Sun, Chi Wei, Minghao Tian, Shiwen Ni

Improved Lower Bounds for First-order Stochastic Non-convex Optimization under Markov Sampling

Zhenyu Sun, Ermin Wei

The Emperor’s New Clothes in Benchmarking? A Rigorous Examination of Mitigation Strategies for LLM Benchmark Data Contamination

Yifan Sun, Han Wang, Dongbai Li, Gang Wang, Huan Zhang

A Stronger Mixture of Low-Rank Experts for Fine-Tuning Foundation Models

Mengyang Sun, Yihao Wang, Tao Feng, Dan Zhang, Yifan Zhu

AsymRnR: Video Diffusion Transformers Acceleration with Asymmetric Reduction and Restoration

Wenhao Sun, Rong-Cheng Tu, Jingyi Liao, Zhao Jin, Dacheng Tao

FlexiReID: Adaptive Mixture of Expert for Multi-Modal Person Re-Identification

Zhen Sun, Lei Tan, Yunhang Shen, Chengmao Cai, Xing Sun

DS-VLM: Diffusion Supervision Vision Language Model

Zhen Sun, Yunhang Shen, Jie Li, Xing Sun, Pingyang Dai

Average Certified Radius is a Poor Metric for Randomized Smoothing

Chenhao Sun, Yuhao Mao, Mark Niklas Mueller, Martin Vechev

Beyond Confidence: Exploiting Homogeneous Pattern for Semi-Supervised Semantic Segmentation

Rui Sun, Huayu Mai, Wangkai Li, Yujia Chen, Naisong Luo

Spherical-Nested Diffusion Model for Panoramic Image Outpainting

Xiancheng Sun, Senmao Ma, Shengxi Li, Mai Xu, Jingyuan Xia

FlatQuant: Flatness Matters for LLM Quantization

Yuxuan Sun, Ruikang Liu, Haoli Bai, Han Bao, Kang Zhao

Task-Gated Multi-Expert Collaboration Network for Degraded Multi-Modal Image Fusion

Yiming Sun, Xin Li, Pengfei Zhu, Qinghua Hu, Dongwei Ren

Scaling Laws for Floating–Point Quantization Training

Xingwu Sun, Shuaipeng Li, Ruobing Xie, Weidong Han, Kan Wu

CAT Merging: A Training-Free Approach for Resolving Conflicts in Model Merging

Wenju Sun, Qingyong Li, Yangliao Geng, Boyang Li

Learning to (Learn at Test Time): RNNs with Expressive Hidden States

Yu Sun, Xinhao Li, Karan Dalal, Jiarui Xu, Arjun Vikram

Is Noise Conditioning Necessary for Denoising Generative Models?

Qiao Sun, Zhicheng Jiang, Hanhong Zhao, Kaiming He

Invariant Deep Uplift Modeling for Incentive Assignment in Online Marketing via Probability of Necessity and Sufficiency

Zexu Sun, Qiyu Han, Hao Yang, Anpeng Wu, Minqin Zhu

Wait-Less Offline Tuning and Re-solving for Online Decision Making

Jingruo Sun, Wenzhi Gao, Ellen Vitercik, Yinyu Ye

Directed Graph Grammars for Sequence-based Learning

Michael Sun, Orion Foo, Gang Liu, Wojciech Matusik, Jie Chen

Score-Based Diffusion Policy Compatible with Reinforcement Learning via Optimal Transport

Mingyang Sun, Pengxiang Ding, Weinan Zhang, Donglin Wang

ShadowKV: KV Cache in Shadows for High-Throughput Long-Context LLM Inference

Hanshi Sun, Li-Wen Chang, Wenlei Bao, Size Zheng, Ningxin Zheng

Analytical Construction on Geometric Architectures: Transitioning from Static to Temporal Link Prediction

Yadong Sun, Xiaofeng Cao, Ivor Tsang, Heng Tao Shen

Tracking Most Significant Shifts in Infinite-Armed Bandits

Joe Suk, Jung-hun Kim

Unified Analysis of Continuous Weak Features Learning with Applications to Learning from Missing Data

Kosuke Sugiyama, Masato Uchida

A Unified Framework for Generalization Error Analysis of Learning with Arbitrary Discrete Weak Features

Kosuke Sugiyama, Masato Uchida

COGNATE: Acceleration of Sparse Tensor Programs on Emerging Hardware using Transfer Learning

Chamika Sudusinghe, Gerasimos Gerogiannis, Damitha Lenadora, Charles Block, Josep Torrellas

A Generalization Result for Convergence in Learning-to-Optimize

Michael Sucker, Peter Ochs

Fixing the Double Penalty in Data-Driven Weather Forecasting Through a Modified Spherical Harmonic Loss Function

Christopher Subich, Syed Zahid Husain, Leo Separovic, Jing Yang

On the Benefits of Active Data Collection in Operator Learning

UNIQUE SUBEDI, Ambuj Tewari

Token Assorted: Mixing Latent and Text Tokens for Improved Language Model Reasoning

DiJia Su, Hanlin Zhu, Yingchen Xu, Jiantao Jiao, Yuandong Tian

Reinforcement Learning with Adaptive Reward Modeling for Expensive-to-Evaluate Systems

Hongyuan Su, Yu Zheng, Yuan Yuan, Yuming Lin, Depeng Jin

SBGD: Improving Graph Diffusion Generative Model via Stochastic Block Diffusion

Junwei Su, Shan Wu

On the Interplay between Graph Structure and Learning Algorithms in Graph Neural Networks

Junwei Su, Chuan Wu

A Non-Asymptotic Convergent Analysis for Scored-Based Graph Generative Model via a System of Stochastic Differential Equations

Junwei Su, Chuan Wu

Multimodal Medical Code Tokenizer

Xiaorui Su, Shvat Messica, Yepeng Huang, Ruth Johnson, Lukas Fesser

SK-VQA: Synthetic Knowledge Generation at Scale for Training Context-Augmented Multimodal LLMs

Xin Su, Man Luo, Kris W Pan, Tien Pei Chou, VASUDEV LAL

LapSum - One Method to Differentiate Them All: Ranking, Sorting and Top-k Selection

Łukasz Struski, Michal B. Bednarczyk, Igor T. Podolak, Jacek Tabor

Policy Optimization for CMDPs with Bandit Feedback: Learning Stochastic and Adversarial Constraints

Francesco Emanuele Stradi, Anna Lunghi, Matteo Castiglioni, Alberto Marchesi, Nicola Gatti

Learning Adversarial MDPs with Stochastic Hard Constraints

Francesco Emanuele Stradi, Matteo Castiglioni, Alberto Marchesi, Nicola Gatti

Prediction models that learn to avoid missing values

Lena Stempfle, Anton Matsson, Newton Mwai, Fredrik D. Johansson

Integration-free Kernels for Equivariant Gaussian Process Modelling

Tim Steinert, David Ginsbourger, August Lykke-Møller, Ove Christiansen, Henry Moss

PaperBench: Evaluating AI’s Ability to Replicate AI Research

Giulio Starace, Oliver Jaffe, Dane Sherburn, James Aung, Jun Shern Chan

The Polynomial Stein Discrepancy for Assessing Moment Convergence

Narayan Srinivasan, Matthew Sutton, Christopher Drovandi, Leah F South

Online Learning with Unknown Constraints

Karthik Sridharan, Seung Won Wilson Yoo

Overtrained Language Models Are Harder to Fine-Tune

Jacob Mitchell Springer, Sachin Goyal, Kaiyue Wen, Tanishq Kumar, Xiang Yue

An Asymptotically Optimal Approximation Algorithm for Multiobjective Submodular Maximization at Scale

Fabian Christian Spaeh, Atsushi Miyauchi

CombiMOTS: Combinatorial Multi-Objective Tree Search for Dual-Target Molecule Generation

Thibaud Southiratn, Bonil Koo, Yijingxiu Lu, Sun Kim

Balancing Efficiency and Expressiveness: Subgraph GNNs with Walk-Based Centrality

Joshua Southern, Yam Eitan, Guy Bar-Shalom, Michael M. Bronstein, Haggai Maron

Prices, Bids, Values: One ML-Powered Combinatorial Auction to Rule Them All

Ermis Soumalias, Jakob Heiss, Jakob Weissteiner, Sven Seuken

DocVXQA: Context-Aware Visual Explanations for Document Question Answering

Mohamed Ali Souibgui, Changkyu Choi, Andrey Barsky, Kangsoo Jung, Ernest Valveny

Learning Distances from Data with Normalizing Flows and Score Matching

Peter Sorrenson, Daniel Behrend-Uriarte, Christoph Schnoerr, Ullrich Koethe

PDE-Controller: LLMs for Autoformalization and Reasoning of PDEs

Mauricio Soroco, Jialin Song, Mengzhou Xia, Kye Emond, Weiran Sun

Deep Ridgelet Transform and Unified Universality Theorem for Deep and Shallow Joint-Group-Equivariant Machines

Sho Sonoda, Yuka Hashimoto, Isao Ishikawa, Masahiro Ikeda

Multi-Timescale Dynamics Model Bayesian Optimization for Plasma Stabilization in Tokamaks

Rohit Sonker, Alexandre Capone, Andrew Rothstein, Hiro Josep Farre Kaga, Egemen Kolemen

Learning Invariant Causal Mechanism from Vision-Language Models

Zeen Song, Siyu Zhao, Xingyu Zhang, Jiangmeng Li, Changwen Zheng

Deep Unsupervised Hashing via External Guidance

Qihong Song, Xiting Liu, Hongyuan Zhu, Joey Tianyi Zhou, Xi Peng

Modularized Self-Reflected Video Reasoner for Multimodal LLM with Application to Video Question Answering

Zihan Song, Xin Wang, Zi Qian, Hong Chen, Longtao Huang

Smooth Interpolation for Improved Discrete Graph Generative Models

Yuxuan Song, Juntong Shi, Jingjing Gong, Minkai Xu, Stefano Ermon

Domain-Adapted Diffusion Model for PROTAC Linker Design Through the Lens of Density Ratio in Chemical Space

Zixing Song, Ziqiao Meng, José Miguel Hernández-Lobato

PPDiff: Diffusing in Hybrid Sequence-Structure Space for Protein-Protein Complex Design

Zhenqiao Song, Tianxiao Li, Lei Li, Martin Renqiang Min

Distributed Retraction-Free and Communication-Efficient Optimization on the Stiefel Manifold

Yilong Song, Peijin Li, Bin Gao, Kun Yuan

History-Guided Video Diffusion

Kiwhan Song, Boyuan Chen, Max Simchowitz, Yilun Du, Russ Tedrake

LipsNet++: Unifying Filter and Controller into a Policy Network

Xujie Song, Liangfa Chen, Tong Liu, Wenxuan Wang, Yinuo Wang

Right Now, Wrong Then: Non-Stationary Direct Preference Optimization under Preference Drift

Seongho Son, William Bankes, Sayak Ray Chowdhury, Brooks Paige, Ilija Bogunovic

Learning Classifiers That Induce Markets

Yonatan Sommer, Ivri Hikri, Lotan Amit, Nir Rosenfeld

Inducing, Detecting and Characterising Neural Modules: A Pipeline for Functional Interpretability in Reinforcement Learning

Anna Soligo, Pietro Ferraro, David Boyle