ICML 2025

3,330 papers

The Generalized Skew Spectrum of Graphs

Armando Bellante, Martin Plávala, Alessandro Luongo

Theoretical guarantees on the best-of-n alignment policy

Ahmad Beirami, Alekh Agarwal, Jonathan Berant, Alexander D’Amour, Jacob Eisenstein

Joint Metric Space Embedding by Unbalanced Optimal Transport with Gromov–Wasserstein Marginal Penalization

Florian Beier, Moritz Piening, Robert Beinert, Gabriele Steidl

Best of Both Worlds: Advantages of Hybrid Graph Sequence Models

Ali Behrouz, Ali Parviz, Mahdi Karami, Clayton Sanford, Bryan Perozzi

Counting in Small Transformers: The Delicate Interplay between Attention and Feed-Forward Layers

Freya Behrens, Luca Biggio, Lenka Zdeborová

Correlation Clustering Beyond the Pivot Algorithm

Soheil Behnezhad, Moses Charikar, Vincent Cohen-Addad, Alma Ghafari, Weiyun Ma

Log-Sum-Exponential Estimator for Off-Policy Evaluation and Learning

Armin Behnamnia, Gholamali Aminian, Alireza Aghaei, Chengchun Shi, Vincent Tan

RocketKV: Accelerating Long-Context LLM Inference via Two-Stage KV Cache Compression

Payman Behnam, Yaosheng Fu, Ritchie Zhao, Po-An Tsai, Zhiding Yu

xLSTM 7B: A Recurrent LLM for Fast and Efficient Inference

Maximilian Beck, Korbinian Pöppel, Phillip Lippe, Richard Kurle, Patrick M Blies

Grokking at the Edge of Linear Separability

Alon Beck, Noam Itzhak Levi, Yohai Bar-Sinai

Lower Bounds for Chain-of-Thought Reasoning in Hard-Attention Transformers

Alireza Amiri Bavandpour, Xinting Huang, Mark Rofin, Michael Hahn

Zero Shot Generalization of Vision-Based RL Without Data Augmentation

Sumeet Batra, Gaurav S. Sukhatme

Competing Bandits in Matching Markets via Super Stability

Soumya Basu

Explaining, Fast and Slow: Abstraction and Refinement of Provable Explanations

Shahaf Bassan, Yizhak Yisrael Elboher, Tobias Ladner, Matthias Althoff, Guy Katz

What makes an Ensemble (Un) Interpretable?

Shahaf Bassan, Guy Amir, Meirav Zehavi, Guy Katz

Robust Conformal Outlier Detection under Contaminated Reference Data

Meshi Bashari, Matteo Sesia, Yaniv Romano

A Certified Unlearning Approach without Access to Source Data

Umit Yigit Basaran, Sk Miraj Ahmed, Amit Roy-Chowdhury, Basak Guler

SDE Matching: Scalable and Simulation-Free Training of Latent Stochastic Differential Equations

Grigory Bartosh, Dmitry Vetrov, Christian A. Naesseth

On Volume Minimization in Conformal Regression

Batiste Le Bars, Pierre Humbert

Feature Shift Localization Network

Mı́riam Barrabés, Daniel Mas Montserrat, Kapal Dev, Alexander G. Ioannidis

Stealing That Free Lunch: Exposing the Limits of Dyna-Style Reinforcement Learning

Brett Barkley, David Fridovich-Keil

Ehrenfeucht-Haussler Rank and Chain of Thought

Pablo Barceló, Alexander Kozachinskiy, Tomasz Steifer

QEM-Bench: Benchmarking Learning-based Quantum Error Mitigation and QEMFormer as a Multi-ranged Context Learning Baseline

Tianyi Bao, Ruizhe Zhong, Xinyu Ye, Yehui Tang, Junchi Yan

Visual and Domain Knowledge for Professional-level Graph-of-Thought Medical Reasoning

Rina Bao, Shilong Dong, Zhenfang Chen, Sheng He, Ellen Grant

Enhancing Adversarial Robustness with Conformal Prediction: A Framework for Guaranteed Model Reliability

Jie Bao, Chuangyin Dang, Rui Luo, Hanwei Zhang, Zhixin Zhou

Fully Dynamic Embedding into ℓ_p Spaces

Kiarash Banihashem, Xiang Chen, MohammadTaghi Hajiaghayi, Sungchul Kim, Kanak Mahadik

BounDr.E: Predicting Drug-likeness via Biomedical Knowledge Alignment and EM-like One-Class Boundary Optimization

Dongmin Bang, Inyoung Sung, Yinhua Piao, Sangseon Lee, Sun Kim

CRANE: Reasoning with constrained LLM generation

Debangshu Banerjee, Tarun Suresh, Shubham Ugare, Sasa Misailovic, Gagandeep Singh

Differentiable Structure Learning with Ancestral Constraints

Taiyu Ban, Changxin Rong, Xiangyu Wang, Lyuzhou Chen, Xin Wang

Polynomial Time Learning Augmented Algorithms for NP-hard Permutation Problems

Evripidis Bampis, Bruno Escoffier, Dimitris Fotakis, Panagiotis Patsilinakos, Michalis Xefteris

On Measuring Long-Range Interactions in Graph Neural Networks

Jacob Bamberger, Benjamin Gutteridge, Scott Le Roux, Michael M. Bronstein, Xiaowen Dong

MathConstruct: Challenging LLM Reasoning with Constructive Proofs

Mislav Balunovic, Jasper Dekoninck, Nikola Jovanović, Ivo Petrov, Martin Vechev

Causal Discovery from Conditionally Stationary Time Series

Carles Balsells-Rodas, Xavier Sumba, Tanmayee Narendra, Ruibo Tu, Gabriele Schweikert

Discovering Global False Negatives On the Fly for Self-supervised Contrastive Learning

Vicente Balmaseda, Bokun Wang, Ching-Long Lin, Tianbao Yang

Bayesian Basis Function Approximation for Scalable Gaussian Process Priors in Deep Generative Models

Mehmet Yiğit Balık, Maksim Sinelnikov, Priscilla Ong, Harri Lahdesmaki

InfAlign: Inference-aware language model alignment

Ananth Balashankar, Ziteng Sun, Jonathan Berant, Jacob Eisenstein, Michael Collins

Fixing the Loose Brake: Exponential-Tailed Stopping Time in Best Arm Identification

Kapilan Balagopalan, Ngo Tuan Nguyen, Yao Zhao, Kwang-Sung Jun

Kandinsky Conformal Prediction: Beyond Class- and Covariate-Conditional Coverage

Konstantina Bairaktari, Jiayun Wu, Steven Wu

Rethinking Latent Redundancy in Behavior Cloning: An Information Bottleneck Approach for Robot Manipulation

Shuanghao Bai, Wanqi Zhou, Pengxiang Ding, Wei Zhao, Donglin Wang

Multivariate Conformal Selection

Tian Bai, Yue Zhao, Xiang Yu, Archer Y. Yang

SKIM: Any-bit Quantization Pushing The Limits of Post-Training Quantization

Runsheng Bai, Bo Liu, Qiang Liu

KoNODE: Koopman-Driven Neural Ordinary Differential Equations with Evolving Parameters for Time Series Analysis

Hanru Bai, Weiyang Ding

Impossible Videos

Zechen Bai, Hai Ci, Mike Zheng Shou

SMART-PC: Skeletal Model Adaptation for Robust Test-Time Training in Point Clouds

Ali Bahri, Moslem Yazdanpanah, Sahar Dastani, Mehrdad Noori, Gustavo Adolfo Vargas Hakim

Active Fine-Tuning of Multi-Task Policies

Marco Bagatella, Jonas Hübotter, Georg Martius, Andreas Krause

Graph-Assisted Stitching for Offline Hierarchical Reinforcement Learning

Seungho Baek, Taegeon Park, Jongchan Park, Seungjun Oh, Yusung Kim

Positional Attention: Expressivity and Learnability of Algorithmic Computation

Artur Back de Luca, George Giapitzakis, Shenghao Yang, Petar Veličković, Kimon Fountoulakis

Layer-wise Alignment: Examining Safety Alignment Across Image Encoder Layers in Vision Language Models

Saketh Bachu, Erfan Shayegani, Rohit Lal, Trishna Chakraborty, Arindam Dutta

A Parametric Contextual Online Learning Theory of Brokerage

Francois Bachoc, Tommaso Cesari, Roberto Colomboni

FlexTok: Resampling Images into 1D Token Sequences of Flexible Length

Roman Bachmann, Jesse Allardice, David Mizrahi, Enrico Fini, Oğuzhan Fatih Kar

Sampling Binary Data by Denoising through Score Functions

Francis Bach, Saeed Saremi

Contract Design Under Approximate Best Responses

Francesco Bacchiocchi, Jiarui Gan, Matteo Castiglioni, Alberto Marchesi, Nicola Gatti

Adaptive Estimation and Learning under Temporal Distribution Shift

Dheeraj Baby, Yifei Tang, Hieu Duy Nguyen, Yu-Xiang Wang, Rohit Pyati

Near-Optimal Decision Trees in a SPLIT Second

Varun Babbar, Hayden McTavish, Cynthia Rudin, Margo Seltzer

Visual Graph Arena: Evaluating Visual Conceptualization of Vision and Multimodal Large Language Models

Zahra Babaiee, Peyman Kiasari, Daniela Rus, Radu Grosu

Beyond Topological Self-Explainable GNNs: A Formal Explainability Perspective

Steve Azzolin, Sagar Malhotra, Andrea Passerini, Stefano Teso

The Global Convergence Time of Stochastic Gradient Descent in Non-Convex Landscapes: Sharp Estimates via Large Deviations

Waı̈ss Azizian, Franck Iutzeler, Jérôme Malick, Panayotis Mertikopoulos

PAC Learning with Improvements

Idan Attias, Avrim Blum, Keziah Naggita, Donya Saless, Dravyansh Sharma

Faster Stochastic Optimization with Arbitrary Delays via Adaptive Asynchronous Mini-Batching

Amit Attia, Ofir Gaash, Tomer Koren

Risk and cross validation in ridge regression with correlated samples

Alexander Atanasov, Jacob A Zavatone-Veth, Cengiz Pehlevan

Autoformulation of Mathematical Optimization Models Using LLMs

Nicolás Astorga, Tennison Liu, Yuanzhang Xiao, Mihaela van der Schaar

Improving the Scaling Laws of Synthetic Data with Deliberate Practice

Reyhane Askari-Hemmat, Mohammad Pezeshki, Elvis DOHMATOB, Florian Bordes, Pietro Astolfi

Faster Rates for Private Adversarial Bandits

Hilal Asi, Vinod Raman, Kunal Talwar

Tracking The Best Expert Privately

Hilal Asi, Vinod Raman, Aadirupa Saha

LLMs can see and hear without any training

Kumar Ashutosh, Yossi Gandelsman, Xinlei Chen, Ishan Misra, Rohit Girdhar

Gridded Transformer Neural Processes for Spatio-Temporal Data

Matthew Ashman, Cristiana Diaconu, Eric Langezaal, Adrian Weller, Richard E Turner

Aligning LLMs by Predicting Preferences from User Writing Samples

Stéphane Aroca-Ouellette, Natalie Mackraz, Barry-John Theobald, Katherine Metcalf

Revisiting Instance-Optimal Cluster Recovery in the Labeled Stochastic Block Model

Kaito Ariu, Alexandre Proutiere, Se-Young Yun

Online Conformal Prediction via Online Optimization

Felipe Areces, Christopher Mohri, Tatsunori Hashimoto, John Duchi

Improving Multi-Class Calibration through Normalization-Aware Isotonic Techniques

Alon Arad, Saharon Rosset

A Reasoning-Based Approach to Cryptic Crossword Clue Solving

Martin Andrews, Sam Witteveen

Private Lossless Multiple Release

Joel Daniel Andersson, Lukas Retschmeier, Boel Nelson, Rasmus Pagh

Pixel-level Certified Explanations via Randomized Smoothing

Alaa Anani, Tobias Lorenz, Mario Fritz, Bernt Schiele

Graph-Based Algorithms for Diverse Similarity Search

Piyush Anand, Piotr Indyk, Ravishankar Krishnaswamy, Sepideh Mahabadi, Vikas C. Raykar

Raptor: Scalable Train-Free Embeddings for 3D Medical Volumes Leveraging Pretrained 2D Foundation Models

Ulzee An, Moonseong Jeong, Simon Austin Lee, Aditya Gorla, Yuzhe Yang

Generalization and Robustness of the Tilted Empirical Risk

Gholamali Aminian, Amir R. Asadi, Tian Li, Ahmad Beirami, Gesine Reinert

Training Flexible Models of Genetic Variant Effects from Functional Annotations using Accelerated Linear Algebra

Alan Nawzad Amin, Andres Potapczynski, Andrew Gordon Wilson

Determinant Estimation under Memory Constraints and Neural Scaling Laws

Siavash Ameli, Chris van der Heide, Liam Hodgkinson, Fred Roosta, Michael W. Mahoney

Continuously Updating Digital Twins using Large Language Models

Harry Amad, Nicolás Astorga, Mihaela van der Schaar

The Butterfly Effect: Neural Network Training Trajectories Are Highly Sensitive to Initial Conditions

Gül Sena Altıntaş, Devin Kwok, Colin Raffel, David Rolnick

Explaining the role of Intrinsic Dimensionality in Adversarial Training

Enes Altinisik, Safa Messaoud, Husrev Taha Sencar, Hassan Sajjad, Sanjay Chawla

Disentangling and Integrating Relational and Sensory Information in Transformer Architectures

Awni Altabaa, John Lafferty

Aligning Multimodal Representations through an Information Bottleneck

Antonio Almudévar, José Miguel Hernández-Lobato, Sameer Khurana, Ricard Marxer, Alfonso Ortega

Subgroups Matter for Robust Bias Mitigation

Anissa Alloula, Charles Jones, Ben Glocker, Bartlomiej Papiez

Towards Trustworthy Federated Learning with Untrusted Participants

Youssef Allouah, Rachid Guerraoui, John Stephan

Direct Motion Models for Assessing Generated Videos

Kelsey R Allen, Carl Doersch, Guangyao Zhou, Mohammed Suhail, Danny Driess

SITCOM: Step-wise Triple-Consistent Diffusion Sampling For Inverse Problems

Ismail Alkhouri, Shijun Liang, Cheng-Han Huang, Jimmy Dai, Qing Qu

Differentiable Quadratic Optimization For the Maximum Independent Set Problem

Ismail Alkhouri, Cedric Le Denmat, Yingjie Li, Cunxi Yu, Jia Liu

Prediction via Shapley Value Regression

Amr Alkhatib, Roman Bresson, Henrik Boström, Michalis Vazirgiannis

NETS: A Non-equilibrium Transport Sampler

Michael Samuel Albergo, Eric Vanden-Eijnden

A Tale of Two Structures: Do LLMs Capture the Fractal Complexity of Language?

Ibrahim Alabdulmohsin, Andreas Peter Steiner

The Surprising Effectiveness of Test-Time Training for Few-Shot Learning

Ekin Akyürek, Mehul Damani, Adam Zweiger, Linlu Qiu, Han Guo

When, Where and Why to Average Weights?

Niccoló Ajroldi, Antonio Orvieto, Jonas Geiping

Nesterov Method for Asynchronous Pipeline Parallel Optimization

Thalaiyasingam Ajanthan, Sameera Ramasinghe, Yan Zuo, Gil Avraham, Alexander Long

Implicit degree bias in the link prediction task

Rachith Aiyappa, Xin Wang, Munjung Kim, Ozgur Can Seckin, Yong-Yeol Ahn

Simple Path Structural Encoding for Graph Transformers

Louis Airale, Antonio Longa, Mattia Rigon, Andrea Passerini, Roberto Passerone

An Instrumental Value for Data Production and its Application to Data Pricing

Rui Ai, Boxiang Lyu, Zhaoran Wang, Zhuoran Yang, Haifeng Xu

Vision Graph Prompting via Semantic Low-Rank Decomposition

Zixiang Ai, Zichen Liu, Jiahuan Zhou

GAPrompt: Geometry-Aware Point Cloud Prompt for 3D Vision Model

Zixiang Ai, Zichen Liu, Yuanhang Lei, Zhenyu Cui, Xu Zou

General framework for online-to-nonconvex conversion: Schedule-free SGD is also effective for nonconvex optimization

Kwangjun Ahn, Gagik Magakyan, Ashok Cutkosky