ICML 2025

3,330 papers

Positional Encoding meets Persistent Homology on Graphs

Yogesh Verma, Amauri H Souza, Vikas K Garg

GRAIL: Graph Edit Distance and Node Alignment using LLM-Generated Code

Samidha Verma, Arushi Goyal, Ananya Mathur, Ankit Anand, Sayan Ranu

Improving Diversity in Language Models: When Temperature Fails, Change the Loss

Alexandre Verine, Florian Le Bronnec, Kunhao Zheng, Alexandre Allauzen, Yann Chevaleyre

Automated Benchmark Generation for Repository-Level Coding Tasks

Konstantinos Vergopoulos, Mark Niklas Mueller, Martin Vechev

Outsourced Diffusion Sampling: Efficient Posterior Inference in Latent Spaces of Generative Models

Siddarth Venkatraman, Mohsin Hasan, Minsu Kim, Luca Scimeca, Marcin Sendera

Softmax is not Enough (for Sharp Size Generalisation)

Petar Veličković, Christos Perivolaropoulos, Federico Barbero, Razvan Pascanu

PyTDC: A multimodal machine learning training, evaluation, and inference platform for biomedical foundation models

Alejandro Velez-Arce, Marinka Zitnik

Approximate Forest Completion and Learning-Augmented Algorithms for Metric Minimum Spanning Trees

Nate Veldt, Thomas Stanley, Benjamin W Priest, Trevor Steil, Keita Iwabuchi

Canonical Rank Adaptation: An Efficient Fine-Tuning Strategy for Vision Transformers

Lokesh Veeramacheneni, Moritz Wolter, Hilde Kuehne, Juergen Gall

Towards Understanding Gradient Dynamics of the Sliced-Wasserstein Distance via Critical Point Analysis

Christophe Vauthier, Anna Korba, Quentin Mérigot

Armijo Line-search Can Make (Stochastic) Gradient Descent Provably Faster

Sharan Vaswani, Reza Babanezhad Harikandeh

Covered Forest: Fine-grained generalization analysis of graph neural networks

Antonis Vasileiou, Ben Finkelshtein, Floris Geerts, Ron Levie, Christopher Morris

Teaching Transformers Causal Reasoning through Axiomatic Training

Aniket Vashishtha, Abhinav Kumar, Atharva Pandey, Abbavaram Gowtham Reddy, Kabir Ahuja

Learning In-context n-grams with Transformers: Sub-n-grams Are Near-Stationary Points

Aditya Varre, Gizem Yüce, Nicolas Flammarion

Rapid Overfitting of Multi-Pass SGD in Stochastic Convex Optimization

Shira Vansover-Hager, Tomer Koren, Roi Livni

AutoCATE: End-to-End, Automated Treatment Effect Estimation

Toon Vanderschueren, Tim Verdonck, Mihaela van der Schaar, Wouter Verbeke

Dimension-Independent Rates for Structured Neural Density Estimation

Robert A. Vandermeulen, Wai Ming Tai, Bryon Aragam

From Pixels to Perception: Interpretable Predictions via Instance-wise Grouped Feature Selection

Moritz Vandenhirtz, Julia E Vogt

When to Forget? Complexity Trade-offs in Machine Unlearning

Martin Van Waerebeke, Marco Lorenzi, Giovanni Neglia, Kevin Scaman

Low-distortion and GPU-compatible Tree Embeddings in Hyperbolic Space

Max van Spengler, Pascal Mettes

Algorithm Development in Neural Networks: Insights from the Streaming Parity Task

Loek Van Rossem, Andrew M Saxe

Generalized Venn and Venn-Abers Calibration with Applications in Conformal Prediction

Lars van der Laan, Ahmed Alaa

What Has a Foundation Model Found? Using Inductive Bias to Probe for World Models

Keyon Vafa, Peter G. Chang, Ashesh Rambachan, Sendhil Mullainathan

Clustering via Self-Supervised Diffusion

Roy Uziel, Irit Chelly, Oren Freifeld, Ari Pakman

A Theoretical Study of (Hyper) Self-Attention through the Lens of Interactions: Representation, Training, Generalization

Muhammed Ustaomeroglu, Guannan Qu

Predicting High-precision Depth on Low-Precision Devices Using 2D Hilbert Curves

Mykhail Uss, Ruslan Yermolenko, Oleksii Shashko, Olena Kolodiazhna, Ivan Safonov

Does Data Scaling Lead to Visual Compositional Generalization?

Arnas Uselis, Andrea Dittadi, Seong Joon Oh

Online Curvature-Aware Replay: Leveraging $\mathbf2^nd$ Order Information for Online Continual Learning

Edoardo Urettini, Antonio Carta

Boost-and-Skip: A Simple Guidance-Free Diffusion for Minority Generation

Soobin Um, Beomsu Kim, Jong Chul Ye

Propagate and Inject: Revisiting Propagation-Based Feature Imputation for Graphs with Partially Observed Features

Daeho Um, Sunoh Kim, Jiwoong Park, Jongin Lim, Seong Jin Ahn

Reward-Guided Iterative Refinement in Diffusion Models at Test-Time with Applications to Protein and DNA Design

Masatoshi Uehara, Xingyu Su, Yulai Zhao, Xiner Li, Aviv Regev

Toward a Unified Theory of Gradient Descent under Generalized Smoothness

Alexander Tyurin

Dynamic Sparse Training of Diagonally Sparse Networks

Abhishek Tyagi, Arjun Iyer, William H Renninger, Christopher Kanan, Yuhao Zhu

The Batch Complexity of Bandit Pure Exploration

Adrienne Tuynman, Rémy Degenne

SafeArena: Evaluating the Safety of Autonomous Web Agents

Ada Defne Tur, Nicholas Meade, Xing Han Lu, Alejandra Zambrano, Arkil Patel

Subgoal-Guided Policy Heuristic Search with Learned Subgoals

Jake Tuero, Michael Buro, Levi Lelis

Ranked from Within: Ranking Large Multimodal Models Without Labels

Weijie Tu, Weijian Deng, Dylan Campbell, Yu Yao, Jiyang Zheng

On the Impact of Performative Risk Minimization for Binary Random Variables

Nikita Tsoy, Ivan Kirev, Negin Rahimiyazdi, Nikola Konstantinov

Set Valued Predictions For Robust Domain Generalization

Ron Tsibulsky, Daniel Nevo, Uri Shalit

Galileo: Learning Global & Local Features of Many Remote Sensing Modalities

Gabriel Tseng, Anthony Fuller, Marlena Reil, Henry Herzog, Patrick Beukema

MuseControlLite: Multifunctional Music Generation with Lightweight Conditioners

Fang-Duo Tsai, Shih-Lun Wu, Weijaw Lee, Sheng-Ping Yang, Bo-Rui Chen

Reliable and Efficient Amortized Model-based Evaluation

Sang T. Truong, Yuheng Tu, Percy Liang, Bo Li, Sanmi Koyejo

Improving Generalization with Flat Hilbert Bayesian Inference

Tuan Truong, Quyen Tran, Ngoc-Quan Pham, nhật Hồ, Dinh Phung

RepLoRA: Reparameterizing Low-rank Adaptation via the Perspective of Mixture of Experts

Tuan Truong, Chau Nguyen, Huy Nguyen, Minh Le, Trung Le

Fundamental limits of learning in sequence multi-index models and deep attention networks: high-dimensional asymptotics and sharp thresholds

Emanuele Troiani, Hugo Cui, Yatin Dandi, Florent Krzakala, Lenka Zdeborová

AutoML-Agent: A Multi-Agent LLM Framework for Full-Pipeline AutoML

Patara Trirat, Wonyong Jeong, Sung Ju Hwang

Counterfactual Effect Decomposition in Multi-Agent Sequential Decision Making

Stelios Triantafyllou, Aleksa Sukovic, Yasaman Zolfimoselo, Goran Radanovic

Variance-Reduced Forward-Reflected-Backward Splitting Methods for Nonmonotone Generalized Equations

Quoc Tran-Dinh

Tree-Sliced Wasserstein Distance with Nonlinear Projection

Thanh Tran, Hoang V. Tran, Thanh Chu, Huyen Trang Pham, Laurent El Ghaoui

Tree-Sliced Wasserstein Distance: A Geometric Perspective

Hoang V. Tran, Huyen Trang Pham, Tho Tran Huu, Minh-Khoi Nguyen-Nhat, Thanh Chu

Identifying Causal Direction via Variational Bayesian Compression

Quang-Duy Tran, Bao Duong, Phuoc Nguyen, Thin Nguyen

Causal Effect Identification in lvLiNGAM from Higher-Order Cumulants

Daniele Tramontano, Yaroslav Kivva, Saber Salehkaleybar, Negar Kiyavash, Mathias Drton

ADIOS: Antibody Development via Opponent Shaping

Sebastian Rene Towers, Aleksandra Kalisz, Philippe A. Robert, Alicia Higueruelo, Francesca Vianello

Accelerating Spectral Clustering under Fairness Constraints

Francesco Tonin, Alex Lambert, Johan Suykens, Volkan Cevher

Self-Disentanglement and Re-Composition for Cross-Domain Few-Shot Segmentation

Jintao Tong, Yixiong Zou, Guangyao Chen, Yuhua Li, Ruixuan Li

Latent Score-Based Reweighting for Robust Classification on Imbalanced Tabular Data

Yunze Tong, Fengda Zhang, Zihao Tang, Kaifeng Gao, Kai Huang

Adapter Naturally Serves as Decoupler for Cross-Domain Few-Shot Semantic Segmentation

Jintao Tong, Ran Ma, Yixiong Zou, Guangyao Chen, Yuhua Li

Non-Asymptotic and Non-Lipschitzian Bounds on Optimal Values in Stochastic Optimization Under Heavy Tails

Jindong Tong, Hongcheng Liu, Johannes O. Royset

Understanding Chain-of-Thought in LLMs through Information Theory

Jean-Francois Ton, Muhammad Faaiz Taufiq, Yang Liu

Diverse Prototypical Ensembles Improve Robustness to Subpopulation Shift

Nguyen Nhat Minh To, Paul F R Wilson, Viet Nguyen, Mohamed Harmanani, Michael Cooper

Understanding the Emergence of Multimodal Representation Alignment

Megan Tjandrasuwita, Chanakya Ekbote, Liu Ziyin, Paul Pu Liang

LangDAug: Langevin Data Augmentation for Multi-Source Domain Generalization in Medical Image Segmentation

Piyush Tiwary, Kinjawl Bhattacharyya, Prathosh AP

QuantSpec: Self-Speculative Decoding with Hierarchical Quantized KV Cache

Rishabh Tiwari, Haocheng Xi, Aditya Tomar, Coleman Richard Charles Hooper, Sehoon Kim

Latent Mamba Operator for Partial Differential Equations

Karn Tiwari, Niladri Dutta, N M Anoop Krishnan, Prathosh AP

New Bounds for Sparse Variational Gaussian Processes

Michalis Titsias

Accelerating LLM Inference with Lossless Speculative Decoding Algorithms for Heterogeneous Vocabularies

Nadav Timor, Jonathan Mamou, Daniel Korat, Moshe Berchansky, Gaurav Jain

Learnable Spatial-Temporal Positional Encoding for Link Prediction

Katherine Tieu, Dongqi Fu, Zihao Li, Ross Maciejewski, Jingrui He

On Teacher Hacking in Language Model Distillation

Daniil Tiapkin, Daniele Calandriello, Johan Ferret, Sarah Perrin, Nino Vieillard

Selective Prompt Anchoring for Code Generation

Yuan Tian, Tianyi Zhang

Optimal transport-based conformal prediction

Gauthier Thurin, Kimia Nadjahi, Claire Boyer

MixMin: Finding Data Mixtures via Convex Minimization

Anvith Thudi, Evianne Rovers, Yangjun Ruan, Tristan Thrush, Chris J. Maddison

NTK-DFL: Enhancing Decentralized Federated Learning in Heterogeneous Settings via Neural Tangent Kernel

Gabriel Thompson, Kai Yue, Chau-Wai Wong, Huaiyu Dai

Hidden No More: Attacking and Defending Private Third-Party LLM Inference

Rahul Krishna Thomas, Louai Zahran, Erica Choi, Akilesh Potti, Micah Goldblum

What can large language models do for sustainable food?

Anna Thomas, Adam Yee, Andrew Mayne, Maya B. Mathur, Dan Jurafsky

Comparing Few to Rank Many: Active Human Preference Learning Using Randomized Frank-Wolfe Method

Kiran Koshy Thekumparampil, Gaurush Hiranandani, Kousha Kalantari, Shoham Sabach, Branislav Kveton

WikiBigEdit: Understanding the Limits of Lifelong Knowledge Editing in LLMs

Lukas Thede, Karsten Roth, Matthias Bethge, Zeynep Akata, Thomas Hartvigsen

Universal Sparse Autoencoders: Interpretable Cross-Model Concept Alignment

Harrish Thasarathan, Julian Forsyth, Thomas FEL, Matthew Kowal, Konstantinos G. Derpanis

Harnessing Heterogeneous Statistical Strength for Personalized Federated Learning via Hierarchical Bayesian Inference

Mahendra Singh Thapa, Rui Li

Geometric Contact Flows: Contactomorphisms for Dynamics and Control

Andrea Testa, Søren Hauberg, Tamim Asfour, Leonel Rozo

A Physics-Informed Machine Learning Framework for Safe and Optimal Control of Autonomous Systems

Manan Tayal, Aditya Singh, Shishir Kolathaya, Somil Bansal

Aequa: Fair Model Rewards in Collaborative Learning via Slimmable Networks

Nurbek Tastan, Samuel Horváth, Karthik Nandakumar

Deep Bayesian Filter for Bayes-Faithful Data Assimilation

Yuta Tarumi, Keisuke Fukuda, Shin-ichi Maeda

Explainable Concept Generation through Vision-Language Preference Learning for Understanding Neural Networks’ Internal Representations

Aditya Taparia, Som Sagar, Ransalu Senanayake

Unisoma: A Unified Transformer-based Solver for Multi-Solid Systems

Shilong Tao, Zhe Feng, Haonan Sun, Zhanxing Zhu, Yunhuai Liu

(How) Can Transformers Predict Pseudo-Random Numbers?

Tao Tao, Darshil Doshi, Dayal Singh Kalra, Tianyu He, Maissam Barkeshli

S2-Track: A Simple yet Strong Approach for End-to-End 3D Multi-Object Tracking

Tao Tang, Lijun Zhou, Pengkun Hao, Zihang He, Kalok Ho

Optimizing Language Models for Inference Time Objectives using Reinforcement Learning

Yunhao Tang, Kunhao Zheng, Gabriel Synnaeve, Rémi Munos

PepTune: De Novo Generation of Therapeutic Peptides with Multi-Objective-Guided Discrete Diffusion

Sophia Tang, Yinuo Zhang, Pranam Chatterjee

Multi-Session Budget Optimization for Forward Auction-based Federated Learning

Xiaoli Tang, Han Yu, Zengxiang Li, Xiaoxiao Li

Sorbet: A Neuromorphic Hardware-Compatible Transformer-Based Spiking Language Model

Kaiwen Tang, Zhanglu Yan, Weng-Fai Wong

Controllable Data Generation with Hierarchical Neural Representations

Sheyang Tang, Xiaoyu Xu, Jiayan Qiu, Zhou Wang

LOGO — Long cOntext aliGnment via efficient preference Optimization

Zecheng Tang, Zechen Sun, Juntao Li, Qiaoming Zhu, Min Zhang

Efficient Heterogeneity-Aware Federated Active Data Selection

Ying-Peng Tang, Chao Ren, Xiaoli Tang, Sheng-jun Huang, Lizhen Cui

Inference-Time Alignment of Diffusion Models with Direct Noise Optimization

Zhiwei Tang, Jiangweizhi Peng, Jiasheng Tang, Mingyi Hong, Fan Wang

Mitigating Plasticity Loss in Continual Reinforcement Learning by Reducing Churn

Hongyao Tang, Johan Obando-Ceron, Pablo Samuel Castro, Aaron Courville, Glen Berseth

Robust Offline Reinforcement Learning with Linearly Structured f-Divergence Regularization

Cheng Tang, Zhishuai Liu, Pan Xu

Concentration Distribution Learning from Label Distributions

Jiawei Tang, Yuheng Jia

Investigating the Overlooked Hessian Structure: From CNNs to LLMs

Qian-Yuan Tang, Yufei Gu, Yunfeng Cai, Mingming Sun, Ping Li

Learning Monotonic Probabilities with a Generative Cost Model

Yongxiang Tang, Yanhua Cheng, Xiaocheng Liu, Chenchen Jiao, Yanxiang Zeng

Learning Single Index Models with Diffusion Priors

Anqi Tang, Youming Chen, Shuchen Xue, Zhaoqiang Liu