ICML 2025

3,330 papers

Quantifying Memory Utilization with Effective State-Size

Rom Parnichkun, Neehal Tumma, Armin W Thomas, Alessandro Moro, Qi An

Flexible and Efficient Grammar-Constrained Decoding

Kanghee Park, Timothy Zhou, Loris D’Antoni

Long-Form Speech Generation with Spoken Language Models

Se Jin Park, Julian Salazar, Aren Jansen, Keisuke Kinoshita, Yong Man Ro

Generalizing from SIMPLE to HARD Visual Reasoning: Can We Mitigate Modality Imbalance in VLMs?

Simon Park, Abhishek Panigrahi, Yun Cheng, Dingli Yu, Anirudh Goyal

Ensemble Distribution Distillation via Flow Matching

Jonggeon Park, Giung Nam, Hyunsu Kim, Jongmin Yoon, Juho Lee

Sortformer: A Novel Approach for Permutation-Resolved Speaker Supervision in Speech-to-Text Systems

Taejin Park, Ivan Medennikov, Kunal Dhawan, Weiqing Wang, He Huang

SCENT: Robust Spatiotemporal Learning for Continuous Scientific Data via Scalable Conditioned Neural Fields

David Keetae Park, Xihaier Luo, Guang Zhao, Seungjun Lee, Miruna Oprescu

Flow Q-Learning

Seohong Park, Qiyang Li, Sergey Levine

When Will It Fail?: Anomaly to Prompt for Forecasting Future Anomalies in Time Series

Min-Yeong Park, Won-Jeong Lee, Seong Tae Kim, Gyeong-Moon Park

Tensor Product Neural Networks for Functional ANOVA Model

Seokhun Park, Insung Kong, Yongchan Choi, Chanmoo Park, Yongdai Kim

SECOND: Mitigating Perceptual Hallucination in Vision-Language Models via Selective and Contrastive Decoding

Woohyeon Park, Woojin Kim, Jaeik Kim, Jaeyoung Do

Activation by Interval-wise Dropout: A Simple Way to Prevent Neural Networks from Plasticity Loss

Sangyeon Park, Isaac Han, Seungwon Oh, Kyungjoong Kim

Steer LLM Latents for Hallucination Detection

Seongheon Park, Xuefeng Du, Min-Hsuan Yeh, Haobo Wang, Yixuan Li

Optimization Proxies using Limited Labeled Data and Training Time – A Semi-Supervised Bayesian Neural Network Approach

Parikshit Pareek, Abhijith Jayakumar, Kaarthik Sundar, Sidhant Misra, Deepjyoti Deka

TopoTune: A Framework for Generalized Combinatorial Complex Neural Networks

Mathilde Papillon, Guillermo Bernardez, Claudio Battiloro, Nina Miolane

Understanding High-Dimensional Bayesian Optimization

Leonard Papenmeier, Matthias Poloczek, Luigi Nardi

Geometric Generative Modeling with Noise-Conditioned Graph Networks

Peter Pao-Huang, Mitchell Black, Xiaojie Qiu

Adversarial Perturbations Are Formed by Iteratively Learning Linear Combinations of the Right Singular Vectors of the Adversarial Jacobian

Thomas Paniagua, Chinmay Savadikar, Tianfu Wu

Token Cleaning: Fine-Grained Data Selection for LLM Supervised Fine-Tuning

Jinlong Pang, Na Di, Zhaowei Zhu, Jiaheng Wei, Hao Cheng

QuEST: Stable Training of LLMs with 1-Bit Weights and Activations

Andrei Panferov, Jiale Chen, Soroush Tabesh, Mahdi Nikdan, Dan Alistarh

Pretraining Generative Flow Networks with Inexpensive Rewards for Molecular Graph Generation

Mohit Pandey, Gopeshh Subbaraj, Artem Cherkasov, Martin Ester, Emmanuel Bengio

Variational Control for Guidance in Diffusion Models

Kushagra Pandey, Farrin Marouf Sofian, Felix Draxler, Theofanis Karaletsos, Stephan Mandt

Video-Enhanced Offline Reinforcement Learning: A Model-Based Approach

Minting Pan, Yitao Zheng, Jiajian Li, Yunbo Wang, Xiaokang Yang

Training Software Engineering Agents and Verifiers with SWE-Gym

Jiayi Pan, Xingyao Wang, Graham Neubig, Navdeep Jaitly, Heng Ji

The Hidden Dimensions of LLM Alignment: A Multi-Dimensional Analysis of Orthogonal Safety Directions

Wenbo Pan, Zhichao Liu, Qiguang Chen, Xiangyang Zhou, Yu Haining

Preference Optimization for Combinatorial Optimization Problems

Mingjun Pan, Guanquan Lin, You-Wei Luo, Bin Zhu, Zhien Dai

Can Transformers Reason Logically? A Study in SAT Solving

Leyan Pan, Vijay Ganesh, Jacob Abernethy, Chris Esposo, Wenke Lee

How Do Images Align and Complement LiDAR? Towards a Harmonized Multi-modal 3D Panoptic Segmentation

Yining Pan, Qiongjie Cui, Xulei Yang, Na Zhao

DiffAdvMAP: Flexible Diffusion-Based Framework for Generating Natural Unrestricted Adversarial Examples

Zhengzhao Pan, Hua Chen, Xiaogang Zhang

Hierarchical Overlapping Clustering on Graphs: Cost Function, Algorithm and Scalability

Yicheng Pan, Renjie Chen, Pengyu Long, Bingchen Fan

From Logits to Hierarchies: Hierarchical Clustering made Simple

Emanuele Palumbo, Moritz Vandenhirtz, Alain Ryser, Imant Daunhawer, Julia E Vogt

Validating Mechanistic Interpretations: An Axiomatic Approach

Nils Palumbo, Ravi Mangal, Zifan Wang, Saranya Vijayakumar, Corina S. Pasareanu

Enforcing Latent Euclidean Geometry in Single-Cell VAEs for Manifold Interpolation

Alessandro Palma, Sergei Rybakov, Leon Hetzel, Stephan Günnemann, Fabian J Theis

Measuring Variable Importance in Heterogeneous Treatment Effects with Confidence

Joseph Paillard, Angel David REYERO LOBO, Vitaliy Kolodyazhniy, Bertrand Thirion, Denis-Alexander Engemann

SAND: One-Shot Feature Selection with Additive Noise Distortion

Pedram Pad, Hadi Hammoud, Mohamad Dia, Nadim Maamari, Liza Andrea Dunbar

scSSL-Bench: Benchmarking Self-Supervised Learning for Single-Cell Data

Olga Ovcharenko, Florian Barkmann, Philip Toma, Imant Daunhawer, Julia E Vogt

KernelBench: Can LLMs Write Efficient GPU Kernels?

Anne Ouyang, Simon Guo, Simran Arora, Alex L Zhang, William Hu

LieRE: Lie Rotational Positional Encodings

Sophie Ostmeier, Brian Axelrod, Maya Varma, Michael Moseley, Akshay S Chaudhari

Discrete and Continuous Difference of Submodular Minimization

George Orfanides, Tim Hoheisel, Marwa El Halabi

Banyan: Improved Representation Learning with Explicit Structure

Mattia Opper, Siddharth N

Activation Space Interventions Can Be Transferred Between Large Language Models

Narmeen Fatimah Oozeer, Dhruv Nathawani, Nirmalendu Prakash, Michael Lan, Abir Harrasse

TOPLOC: A Locality Sensitive Hashing Scheme for Trustless Verifiable Inference

Jack Min Ong, Matthew Di Ferrante, Aaron Pazdera, Ryan Garner, Sami Jaghouar

Gradual Transition from Bellman Optimality Operator to Bellman Operator in Online Reinforcement Learning

Motoki Omura, Kazuki Ota, Takayuki Osa, Yusuke Mukuta, Tatsuya Harada

Since Faithfulness Fails: The Performance Limits of Neural Causal Discovery

Mateusz Olko, Mateusz Gajewski, Joanna Wojciechowska, Mikołaj Morzy, Piotr Sankowski

Nonlinearly Preconditioned Gradient Methods under Generalized Smoothness

Konstantinos Oikonomidis, Jan Quan, Emanuel Laude, Panagiotis Patrinos

Evaluating Neuron Explanations: A Unified Framework with Sanity Checks

Tuomas Oikarinen, Ge Yan, Tsui-Wei Weng

Compressed Image Generation with Denoising Diffusion Codebook Models

Guy Ohayon, Hila Manor, Tomer Michaeli, Michael Elad

Global Context-aware Representation Learning for Spatially Resolved Transcriptomics

Yunhak Oh, Junseok Lee, Yeongmin Kim, Sangwoo Seo, Namkyeong Lee

Distribution-aware Fairness Learning in Medical Image Segmentation From A Control-Theoretic Perspective

Yujin Oh, Pengfei Jin, Sangjoon Park, Sekeun Kim, Siyeop Yoon

Understanding Multimodal LLMs Under Distribution Shifts: An Information-Theoretic Approach

Changdae Oh, Zhen Fang, Shawn Im, Xuefeng Du, Yixuan Li

Finite-Sample Convergence Bounds for Trust Region Policy Optimization in Mean Field Games

Antonio Ocello, Daniil Tiapkin, Lorenzo Mancini, Mathieu Lauriere, Eric Moulines

Compute Optimal Inference and Provable Amortisation Gap in Sparse Autoencoders

Charles O’Neill, Alim Gumran, David Klindt

TuCo: Measuring the Contribution of Fine-Tuning to Individual Responses of LLMs

Felipe Pinto Coelho Nuti, Tim Franzmeyer, João F. Henriques

Improved Algorithm for Deep Active Learning under Imbalance via Optimal Separation

Shyam Nuggehalli, Jifan Zhang, Lalit K Jain, Robert D Nowak

Stochastic Encodings for Active Feature Acquisition

Alexander Luke Ian Norcliffe, Changhee Lee, Fergus Imrie, Mihaela van der Schaar, Pietro Lió

High-Dimensional Prediction for Sequential Decision Making

Georgy Noarov, Ramya Ramalingam, Aaron Roth, Stephan Xie

Stronger Neyman Regret Guarantees for Adaptive Experimental Design

Georgy Noarov, Riccardo Fogliato, Martin Andres Bertran, Aaron Roth

LangTime: A Language-Guided Unified Model for Time Series Forecasting with Proximal Policy Optimization

Wenzhe Niu, Zongxia Xie, Yanru Sun, Wei He, Man Xu

Pre-training Auto-regressive Robotic Models with 4D Representations

Dantong Niu, Yuvan Sharma, Haoru Xue, Giscard Biamby, Junyi Zhang

Fundamental Bias in Inverting Random Sampling Matrices with Application to Sub-sampled Newton

Chengmei Niu, Zhenyu Liao, Zenan Ling, Michael W. Mahoney

Test-Time Multimodal Backdoor Detection by Contrastive Prompting

Yuwei Niu, Shuo He, Qi Wei, Zongyu Wu, Feng Liu

Self-Bootstrapping for Versatile Test-Time Adaptation

Shuaicheng Niu, Guohao Chen, Peilin Zhao, Tianyi Wang, Pengcheng Wu

Propagation of Chaos for Mean-Field Langevin Dynamics and its Application to Model Ensemble

Atsushi Nitanda, Anzelle Lee, Damian Tan Xing Kai, Mizuki Sakaguchi, Taiji Suzuki

Nonlinear transformers can perform inference-time feature learning

Naoki Nishikawa, Yujin Song, Kazusato Oko, Denny Wu, Taiji Suzuki

Representation Shattering in Transformers: A Synthetic Study with Knowledge Editing

Kento Nishi, Rahul Ramesh, Maya Okawa, Mikail Khona, Hidenori Tanaka

DCTdiff: Intriguing Properties of Image Generative Modeling in the DCT Space

Mang Ning, Mingxiao Li, Jianlin Su, Jia Haozhe, Lanmiao Liu

MVA: Linear Attention with High-order Query-Keys Integration and Multi-level Vocabulary Decomposition

Wang Ning, Zekun Li, Tongxin Bai, Man Yao, Zhen Qin

Graph4MM: Weaving Multimodal Learning with Structural Information

Xuying Ning, Dongqi Fu, Tianxin Wei, Wujiang Xu, Jingrui He

Latent Action Learning Requires Supervision in the Presence of Distractors

Alexander Nikulin, Ilya Zisman, Denis Tarasov, Lyubaykin Nikita, Andrei Polubarov

The Jailbreak Tax: How Useful are Your Jailbreak Outputs?

Kristina Nikolić, Luze Sun, Jie Zhang, Florian Tramer

Towards a Mechanistic Explanation of Diffusion Model Generalization

Matthew Niedoba, Berend Zwartsenberg, Kevin Patrick Murphy, Frank Wood

Decomposition of Graphic Design with Unified Multimodal Model

Hui Nie, Zhao Zhang, Yutao Cheng, Maoke Yang, Gonglei Shi

EVOLvE: Evaluating and Optimizing LLMs For In-Context Exploration

Allen Nie, Yi Su, Bo Chang, Jonathan Lee, Ed H. Chi

FactTest: Factuality Testing in Large Language Models with Finite-Sample and Distribution-Free Guarantees

Fan Nie, Xiaotian Hou, Shuhang Lin, James Zou, Huaxiu Yao

Faster Global Minimum Cut with Predictions

Helia Niaparast, Benjamin Moseley, Karan Singh

RollingQ: Reviving the Cooperation Dynamics in Multimodal Transformer

Haotian Ni, Yake Wei, Hang Liu, Gong Chen, Chong Peng

Time-Aware World Model for Adaptive Prediction and Control

Anh N Nhu, Sanghyun Son, Ming Lin

Policy-Regret Minimization in Markov Games with Function Approximation

Thanh Nguyen-Tang, Raman Arora

Theoretically Unmasking Inference Attacks Against LDP-Protected Clients in Federated Vision Models

Quan Minh Nguyen, Minh N. Vu, Truc Nguyen, My T. Thai

Beyond Low-rank Decomposition: A Shortcut Approach for Efficient On-Device Learning

Le-Trung Nguyen, Aël Quélennec, Van-Tam Nguyen, Enzo Tartaglione

Provably Improving Generalization of Few-shot models with Synthetic Data

Lan-Cuong Nguyen, Quan Nguyen-Tri, Bang Tran Khanh, Dung D. Le, Long Tran-Thanh

Lightspeed Geometric Dataset Distance via Sliced Optimal Transport

Khai Nguyen, Hai Nguyen, Tuan Pham, nhật Hồ

Lean and Mean Adaptive Optimization via Subset-Norm and Subspace-Momentum with Convergence Guarantees

Thien Hang Nguyen, Huy Nguyen

Beyond Minimax Rates in Group Distributionally Robust Optimization via a Novel Notion of Sparsity

Quan M. Nguyen, Nishant A Mehta, Cristóbal A Guzmán

Layer-wise Quantization for Quantized Optimistic Dual Averaging

Anh Duc Nguyen, Ilia Markov, Zhengqing Wu, Ali Ramezani-Kebrya, Kimon Antonakopoulos

Synthetic Text Generation for Training Large Language Models via Gradient Matching

Dang Nguyen, Zeman Li, Mohammadhossein Bateni, Vahab Mirrokni, Meisam Razaviyayn

Explicit Exploration for High-Welfare Equilibria in Game-Theoretic Multiagent Reinforcement Learning

Austin A. Nguyen, Anri Gu, Michael P. Wellman

Time to Spike? Understanding the Representational Power of Spiking Neural Networks in Discrete Time

Duc Anh Nguyen, Ernesto Araya, Adalbert Fono, Gitta Kutyniok

Multi-band Frequency Reconstruction for Neural Psychoacoustic Coding

Dianwen Ng, Kun Zhou, Yi-Wen Chao, Zhiwei Xiong, Bin Ma

A General Representation-Based Approach to Multi-Source Domain Adaptation

Ignavier Ng, Yan Li, Zijian Li, Yujia Zheng, Guangyi Chen

Optimistic Algorithms for Adaptive Estimation of the Average Treatment Effect

Ojash Neopane, Aaditya Ramdas, Aarti Singh

Identifying Neural Dynamics Using Interventional State Space Models

Amin Nejatbakhsh, Yixin Wang

WILTing Trees: Interpreting the Distance Between MPNN Embeddings

Masahiro Negishi, Thomas Gärtner, Pascal Welke

UI-Vision: A Desktop-centric GUI Benchmark for Visual Perception and Interaction

Shravan Nayak, Xiangru Jian, Kevin Qinghong Lin, Juan A. Rodriguez, Montek Kalsi

A Sub-Problem Quantum Alternating Operator Ansatz for Correlation Clustering

Lucas Fabian Naumann, Jannik Irmai, Bjoern Andres

Kernel Quantile Embeddings and Associated Probability Metrics

Masha Naslidnyk, Siu Lun Chau, François-Xavier Briol, Krikamol Muandet

Unified Screening for Multiple Diseases

Yiğit Narter, Alihan Hüyük, Mihaela van der Schaar, Cem Tekin

$\mathrmμ$nit Scaling: Simple and Scalable FP8 LLM Training

Saaketh Narayan, Abhay Gupta, Mansheej Paul, Davis Blalock

Cost-efficient Collaboration between On-device and Cloud Language Models

Avanika Narayan, Dan Biderman, Sabri Eyuboglu, Avner May, Scott Linderman

Theoretical Performance Guarantees for Partial Domain Adaptation via Partial Optimal Transport

Jayadev Naram, Fredrik Hellström, Ziming Wang, Rebecka Jörnsten, Giuseppe Durisi