ICML 2025

3,330 papers

A Simple Model of Inference Scaling Laws

Noam Itzhak Levi

Attributes Shape the Embedding Space of Face Recognition Models

Pierrick Leroy, Antonio Mastropietro, Marco Nurisso, Francesco Vaccarino

Quantum Optimization via Gradient-Based Hamiltonian Descent

Jiaqi Leng, Bin Shi

iN2V: Bringing Transductive Node Embeddings to Inductive Graphs

Nicolas Lell, Ansgar Scherp

M3-JEPA: Multimodal Alignment via Multi-gate MoE based on the Joint-Embedding Predictive Architecture

Hongyang Lei, Xiaolong Cheng, Qi Qin, Dan Wang, Huazhen Huang

DRAG: Data Reconstruction Attack using Guided Diffusion

Wa-Kin Lei, Jun-Cheng Chen, Shang-Tse Chen

Efficient Distributed Optimization under Heavy-Tailed Noise

Su Hyeong Lee, Manzil Zaheer, Tian Li

Toward Robust Hyper-Detailed Image Captioning: A Multiagent Approach and Dual Evaluation Metrics for Factuality and Coverage

Saehyung Lee, Seunghyun Yoon, Trung Bui, Jing Shi, Sungroh Yoon

RestoreGrad: Signal Restoration Using Conditional Denoising Diffusion Models with Jointly Learned Prior

Ching-Hua Lee, Chouchang Yang, Jaejin Cho, Yashas Malur Saidutta, Rakshith Sharma Srinivasa

Structure Is All You Need: Structural Representation Learning on Hyper-Relational Knowledge Graphs

Jaejun Lee, Joyce Jiyoung Whang

Lightweight Online Adaption for Time Series Foundation Model Forecasts

Thomas L Lee, William Toner, Rajkarn Singh, Artjom Joosen, Martin Asenov

Self-supervised Adversarial Purification for Graph Neural Networks

Woohyun Lee, Hogun Park

From Theory to Practice: Rethinking Green and Martin Kernels for Unleashing Graph Transformers

Yoon Hyeok Lee, Jaemin Park, Taejin Paik, Doyun Kim, Bosun Hwang

Channel Normalization for Time Series Channel Identification

Seunghan Lee, Taeyoung Park, Kibok Lee

Multidimensional Adaptive Coefficient for Inference Trajectory Optimization in Flow and Diffusion

Dohoon Lee, Jaehyun Park, Hyunwoo J. Kim, Kyogu Lee

ReVISE: Learning to Refine at Test-Time via Intrinsic Self-Verification

Hyunseok Lee, Seunghyuk Oh, Jaehyung Kim, Jinwoo Shin, Jihoon Tack

Improved Online Confidence Bounds for Multinomial Logistic Bandits

Joongkyu Lee, Min-hwan Oh

Combinatorial Reinforcement Learning with Preference Feedback

Joongkyu Lee, Min-hwan Oh

Chip Placement with Diffusion Models

Vint Lee, Minh Nguyen, Leena Elzeiny, Chun Deng, Pieter Abbeel

Multi-Marginal Stochastic Flow Matching for High-Dimensional Snapshot Data at Irregular Time Points

Justin Lee, Behnaz Moradijamei, Heman Shakeri

All-Purpose Mean Estimation over R: Optimal Sub-Gaussianity with Outlier Robustness and Low Moments Performance

Jasper C.H. Lee, Walter Mckelvie, Maoyuan Song, Paul Valiant

Chungpa Lee, Sehee Lim, Kibok Lee, Jy-yong Sohn

Hyperspherical Normalization for Scalable Deep Reinforcement Learning

Hojoon Lee, Youngdo Lee, Takuma Seno, Donghu Kim, Peter Stone

Fluctuations of the largest eigenvalues of transformed spiked Wigner matrices

Aro Lee, Ji Oon Lee

SAFE: Finding Sparse and Flat Minima to Improve Pruning

Dongyeop Lee, Kwanhee Lee, Jinseok Chung, Namhoon Lee

ELITE: Enhanced Language-Image Toxicity Evaluation for Safety

WonJun Lee, Doehyeon Lee, Eugene Choi, Sangyoon Yu, Ashkan Yousefpour

Bayesian Neural Scaling Law Extrapolation with Prior-Data Fitted Networks

Dongwoo Lee, Dong Bok Lee, Steven Adriaensen, Juho Lee, Sung Ju Hwang

Temporal Distance-aware Transition Augmentation for Offline Model-based Reinforcement Learning

Dongsu Lee, Minhae Kwon

GenMol: A Drug Discovery Generalist with Discrete Diffusion

Seul Lee, Karsten Kreis, Srimukh Prasad Veccham, Meng Liu, Danny Reidenbach

Aggregation Buffer: Revisiting DropEdge with a New Parameter Block

Dooho Lee, Myeong Kong, Sagad Hamid, Cheonwoo Lee, Jaemin Yoo

ETTA: Elucidating the Design Space of Text-to-Audio Models

Sang-gil Lee, Zhifeng Kong, Arushi Goel, Sungwon Kim, Rafael Valle

FlashTP: Fused, Sparsity-Aware Tensor Product for Machine Learning Interatomic Potentials

Seung Yul Lee, Hojoon Kim, Yutack Park, Dawoon Jeong, Seungwu Han

Enhancing Ligand Validity and Affinity in Structure-Based Drug Design with Multi-Reward Optimization

Seungbeom Lee, Munsun Jo, Jungseul Ok, Dongwoo Kim

How to Move Your Dragon: Text-to-Motion Synthesis for Large-Vocabulary Objects

Wonkwang Lee, Jongwon Jeong, Taehong Moon, Hyeon-Jong Kim, Jaehyeon Kim

Wolfpack Adversarial Attack for Robust Multi-Agent Reinforcement Learning

Sunwoo Lee, Jaebak Hwang, Yonghyeon Jo, Seungyul Han

Test-Time Adaptation with Binary Feedback

Taeckyung Lee, Sorn Chottananurak, Junsu Kim, Jinwoo Shin, Taesik Gong

Local Manifold Approximation and Projection for Manifold-Aware Diffusion Planning

Kyowoon Lee, Jaesik Choi

Unpaired Point Cloud Completion via Unbalanced Optimal Transport

Taekyung Lee, Jaemoo Choi, Jaewoong Choi, Myungjoo Kang

Self-Improving Transformers Overcome Easy-to-Hard and Length Generalization Challenges

Nayoung Lee, Ziyang Cai, Avi Schwarzschild, Kangwook Lee, Dimitris Papailiopoulos

Near-Optimal Sample Complexity for MDPs via Anchoring

Jongmin Lee, Mario Bravo, Roberto Cominetti

Bayesian Weight Enhancement with Steady-State Adaptation for Test-time Adaptation in Dynamic Environments

Jae-Hong Lee

Are Large Brainwave Foundation Models Capable Yet ? Insights from Fine-Tuning

Na Lee, Konstantinos Barmpas, Yannis Panagakis, Dimitrios Adamos, Nikolaos Laskaris

On the Learnability of Distribution Classes with Adaptive Adversaries

Tosca Lechner, Alex Bie, Gautam Kamath

Generalization Bounds via Meta-Learned Model Representations: PAC-Bayes and Sample Compression Hypernetworks

Benjamin Leblanc, Mathieu Bazinet, Nathaniel D’Amours, Alexandre Drouin, Pascal Germain

Inference-Time Decomposition of Activations (ITDA): A Scalable Approach to Interpreting Large Language Models

Patrick Leask, Neel Nanda, Noura Al Moubayed

Scalable Sobolev IPM for Probability Measures on a Graph

Tam Le, Truyen Nguyen, Hideitsu Hino, Kenji Fukumizu

Learning Utilities from Demonstrations in Markov Decision Processes

Filippo Lazzati, Alberto Maria Metelli

Fixed-Confidence Multiple Change Point Identification under Bandit Feedback

Joseph Lazzaro, Ciara Pike-Burke

Understanding Fixed Predictions via Confined Regions

Connor Lawless, Tsui-Wei Weng, Berk Ustun, Madeleine Udell

Adaptive kernel predictors from feature-learning infinite limits of neural networks

Clarissa Lauditi, Blake Bordelon, Cengiz Pehlevan

Analyze Feature Flow to Enhance Interpretation and Steering in Language Models

Daniil Laptev, Nikita Balagansky, Yaroslav Aksenov, Daniil Gavrilov

Robust and Conjugate Spatio-Temporal Gaussian Processes

William Laplante, Matias Altamirano, Andrew B. Duncan, Jeremias Knoblauch, François-Xavier Briol

Feedforward Few-shot Species Range Estimation

Christian Lange, Max Hamilton, Elijah Cole, Alexander Shepard, Samuel Heinrich

Gradient-based Explanations for Deep Learning Survival Models

Sophie Hanna Langbein, Niklas Koenen, Marvin N. Wright

Near-optimal Regret Using Policy Optimization in Online MDPs with Aggregate Bandit Feedback

Tal Lancewicki, Yishay Mansour

Liger: Linearizing Large Language Models to Gated Recurrent Structures

Disen Lan, Weigao Sun, Jiaxi Hu, Jusen Du, Yu Cheng

A Meta-learner for Heterogeneous Effects in Difference-in-Differences

Hui Lan, Haoge Chang, Eleanor Wiske Dillon, Vasilis Syrgkanis

Simple Randomized Rounding for Max-Min Eigenvalue Augmentation

Jourdain Lamperski, Haeseong Yang, Oleg Prokopyev

A Theoretical Justification for Asymmetric Actor-Critic Algorithms

Gaspard Lambrechts, Damien Ernst, Aditya Mahajan

Focus On This, Not That! Steering LLMs with Adaptive Feature Specification

Tom A. Lamb, Adam Davies, Alasdair Paren, Philip Torr, Francesco Pinto

On the Private Estimation of Smooth Transport Maps

Clément Lalanne, Franck Iutzeler, Jean-Michel Loubes, Julien Chhor

AssistanceZero: Scalably Solving Assistance Games

Cassidy Laidlaw, Eli Bronstein, Timothy Guo, Dylan Feng, Lukas Berglund

Enhancing Certified Robustness via Block Reflector Orthogonal Layers and Logit Annealing Loss

Bo-Han Lai, Pin-Han Huang, Bo-Han Kung, Shang-Tse Chen

FairICP: Encouraging Equalized Odds via Inverse Conditional Permutation

Yuheng Lai, Leying Guan

Joint Localization and Activation Editing for Low-Resource Fine-Tuning

Wen Lai, Alexander Fraser, Ivan Titov

Scalable Approximation Algorithms for p-Wasserstein Distance and Its Variants

Nathaniel Lahn, Sharath Raghvendra, Emma Saarinen, Pouyan Shirzadian

An Efficient Search-and-Score Algorithm for Ancestral Graphs using Multivariate Information Scores for Complex Non-linear and Categorical Data

Nikita Lagrange, Herve Isambert

Steinar Laenen, Peter Macgregor, He Sun

High-Fidelity Simultaneous Speech-To-Speech Translation

Tom Labiausse, Laurent Mazare, Edouard Grave, Alexandre Defossez, Neil Zeghidour

Fairness Overfitting in Machine Learning: An Information-Theoretic Perspective

Firas Laakom, Haobo Chen, Jürgen Schmidhuber, Yuheng Bu

QuRe: Query-Relevant Retrieval through Hard Negative Sampling in Composed Image Retrieval

Jaehyun Kwak, Ramahdani Muhammad Izaaz Inhar, Se-Young Yun, Sung-Ju Lee

Dynamical phases of short-term memory mechanisms in RNNs

Bariscan Kurtkaya, Fatih Dinc, Mert Yuksekgonul, Marta Blanco-Pozo, Ege Cirakman

Steerable Transformers for Volumetric Data

Soumyabrata Kundu, Risi Kondor

Weisfeiler and Leman Go Gambling: Why Expressive Lottery Tickets Win

Lorenz Kummer, Samir Moustafa, Anatol Ehrlich, Franka Bause, Nikolaus Suess

A Likelihood Based Approach to Distribution Regression Using Conditional Deep Generative Models

Shivam Kumar, Yun Yang, Lizhen Lin

The Complexity of Learning Sparse Superposed Features with Feedback

Akash Kumar

A Model of Place Field Reorganization During Reward Maximization

M Ganesh Kumar, Blake Bordelon, Jacob A Zavatone-Veth, Cengiz Pehlevan

Positive-unlabeled AUC Maximization under Covariate Shift

Atsutoshi Kumagai, Tomoharu Iwata, Hiroshi Takahashi, Taishi Nishiyama, Kazuki Adachi

Optimizing Social Network Interventions via Hypergradient-Based Recommender System Design

Marino Kühne, Panagiotis D. Grontas, Giulia De Pasquale, Giuseppe Belgioioso, Florian Dorfler

Patch-wise Structural Loss for Time Series Forecasting

Dilfira Kudrat, Zongxia Xie, Yanru Sun, Tianyu Jia, Qinghua Hu

How to Train Your Multi-Exit Model? Analyzing the Impact of Training Strategies

Piotr Kubaty, Bartosz Wójcik, Bartłomiej Tomasz Krzepkowski, Monika Michaluk, Tomasz Trzcinski

Reconstructing Cell Lineage Trees from Phenotypic Features with Metric Learning

Da Kuang, Guanwen Qiu, Junhyong Kim

Customizing the Inductive Biases of Softmax Attention using Structured Matrices

Yilun Kuang, Noah Amsel, Sanae Lotfi, Shikai Qiu, Andres Potapczynski

Categorical Schrödinger Bridge Matching

Grigoriy Ksenofontov, Alexander Korotin

Improved Learning via k-DTW: A Novel Dissimilarity Measure for Curves

Amer Krivosija, Alexander Munteanu, André Nusser, Chris Schwiegelshohn

Privacy Attacks on Image AutoRegressive Models

Antoni Kowalczuk, Jan Dubiński, Franziska Boenisch, Adam Dziedzic

EQ-VAE: Equivariance Regularized Latent Space for Improved Generative Image Modeling

Theodoros Kouzelis, Ioannis Kakogeorgiou, Spyros Gidaris, Nikos Komodakis

CFPT: Empowering Time Series Forecasting through Cross-Frequency Interaction and Periodic-Aware Timestamp Modeling

Feifei Kou, Jiahao Wang, Lei Shi, Yuhan Yao, Yawen Li

Orthus: Autoregressive Interleaved Image-Text Generation with Modality-Specific Heads

Siqi Kou, Jiachun Jin, Zhihong Liu, Chang Liu, Ye Ma

Sharp Optimality of Simple, Plug-in Estimation of the Fisher Information of a Smoothed Density

Subhodh Kotekal

Laplace Transform Based Low-Complexity Learning of Continuous Markov Semigroups

Vladimir R Kostic, Karim Lounici, Hélène Halconruy, Timothée Devergne, Pietro Novelli

Improved Sample Complexity for Private Nonsmooth Nonconvex Optimization

Guy Kornowski, Daogao Liu, Kunal Talwar

Phase transitions for the existence of unregularized M-estimators in single index models

Takuya Koriyama, Pierre C Bellec

Identifiable Object Representations under Spatial Ambiguities

Avinash Kori, Francesca Toni, Ben Glocker

FlowDrag: 3D-aware Drag-based Image Editing with Mesh-guided Deformation Vector Flow Fields

Gwanhyeong Koo, Sunjae Yoon, Younghwan Lee, Ji Woo Hong, Chang D. Yoo

Enhancing Cooperative Multi-Agent Reinforcement Learning with State Modelling and Adversarial Exploration

Andreas Kontogiannis, Konstantinos Papathanasiou, Yi Shen, Giorgos Stamou, Michael M. Zavlanos

Latent Thought Models with Variational Bayes Inference-Time Computation

Deqian Kong, Minglu Zhao, Dehong Xu, Bo Pang, Shu Wang

UniMoMo: Unified Generative Modeling of 3D Molecules for De Novo Binder Design

Xiangzhe Kong, Zishen Zhang, Ziting Zhang, Rui Jiao, Jianzhu Ma

Mastering Massive Multi-Task Reinforcement Learning via Mixture-of-Expert Decision Transformer

Yilun Kong, Guozheng Ma, Qi Zhao, Haoyu Wang, Li Shen

Constrained Pareto Set Identification with Bandit Feedback

Cyrille KONE, Emilie Kaufmann, Laura Richert