ICLR 2025

3,703 papers

MIA-Bench: Towards Better Instruction Following Evaluation of Multimodal LLMs

Yusu Qian, Hanrong Ye, Jean-Philippe Fauconnier, Peter Grasch, Yinfei Yang

ToddlerDiffusion: Interactive Structured Image Generation with Cascaded Schrödinger Bridge

Eslam Mohamed Bakr, Liangbing Zhao, Vincent Tao Hu, Matthieu Cord, Patrick Pérez

GNNs Getting ComFy: Community and Feature Similarity Guided Rewiring

Celia Rubio-Madrigal, Adarsh Jamadandi, Rebekka Burkholz

Javier Abad, Konstantin Donhauser, Francesco Pinto, Fanny Yang

Simplifying Deep Temporal Difference Learning

Matteo Gallici, Mattie Fellows, Benjamin Ellis, Bartomeu Pou, Ivan Masmitja

API Pack: A Massive Multi-Programming Language Dataset for API Call Generation

Zhen Guo, Adriana Meza Soria, Wei Sun, Yikang Shen, Rameswar Panda

Uncertainty Modeling in Graph Neural Networks via Stochastic Differential Equations

Richard Bergna, Sergio Calvo Ordoñez, Felix Opolka, Pietro Lió, José Miguel Hernández-Lobato

MorphoDiff: Cellular Morphology Painting with Diffusion Models

Zeinab Navidi, Jun Ma, Esteban Miglietta, Le Liu, Anne E Carpenter

Positive-Unlabeled Diffusion Models for Preventing Sensitive Data Generation

Hiroshi Takahashi, Tomoharu Iwata, Atsutoshi Kumagai, Yuuki Yamanaka, Tomoya Yamashita

Bayesian Experimental Design Via Contrastive Diffusions

Jacopo Iollo, Christophe Heinkelé, Pierre Alliez, Florence Forbes

TypedThinker: Diversify Large Language Model Reasoning with Typed Thinking

Danqing Wang, Jianxin Ma, Fei Fang, Lei Li

Repetition Improves Language Model Embeddings

Jacob Mitchell Springer, Suhas Kotha, Daniel Fried, Graham Neubig, Aditi Raghunathan

Spherical Tree-Sliced Wasserstein Distance

Hoang V. Tran, Thanh Chu, Minh-Khoi Nguyen-Nhat, Huyen Trang Pham, Tam Le

Mini-batch Coresets for Memory-efficient Language Model Training on Data Mixtures

Dang Nguyen, Wenhan Yang, Rathul Anand, Yu Yang, Baharan Mirzasoleiman

Understanding Optimization in Deep Learning with Central Flows

Jeremy Cohen, Alex Damian, Ameet Talwalkar, J Zico Kolter, Jason D. Lee

Learning mirror maps in policy mirror descent

Carlo Alfano, Sebastian Rene Towers, Silvia Sapora, Chris Lu, Patrick Rebeschini

DistRL: An Asynchronous Distributed Reinforcement Learning Framework for On-Device Control Agent

Taiyi Wang, zhihao wu, Jianheng Liu, Jianye Hao, Jun Wang

TimeInf: Time Series Data Contribution via Influence Functions

Yizi Zhang, Jingyan Shen, Xiaoxue Xiong, Yongchan Kwon

Advancing Out-of-Distribution Detection via Local Neuroplasticity

Alessandro Canevaro, Julian Schmidt, Mohammad Sajad Marvi, Hang Yu, Georg Martius

When LLMs Play the Telephone Game: Cultural Attractors as Conceptual Tools to Evaluate LLMs in Multi-turn Settings

Jérémy Perez, Grgur Kovač, Corentin Léger, Cédric Colas, Gaia Molinaro

Hierarchical Uncertainty Estimation for Learning-based Registration in Neuroimaging

Xiaoling Hu, Karthik Gopinath, Peirong Liu, Malte Hoffmann, Koen Van Leemput

GPUDrive: Data-driven, multi-agent driving simulation at 1 million FPS

Saman Kazemkhani, Aarav Pandya, Daphne Cornelisse, Brennan Shacklett, Eugene Vinitsky

InstantPortrait: One-Step Portrait Editing via Diffusion Multi-Objective Distillation

Zhixin Lai, Keqiang Sun, Fu-Yun Wang, Dhritiman Sagar, Erli Ding

GTR: Improving Large 3D Reconstruction Models through Geometry and Texture Refinement

Peiye Zhuang, Songfang Han, Chaoyang Wang, Aliaksandr Siarohin, Jiaxu Zou

Approximation algorithms for combinatorial optimization with predictions

Antonios Antoniadis, Marek Elias, Adam Polak, Moritz Venzin

AgentHarm: A Benchmark for Measuring Harmfulness of LLM Agents

Maksym Andriushchenko, Alexandra Souly, Mateusz Dziemian, Derek Duenas, Maxwell Lin

MotherNet: Fast Training and Inference via Hyper-Network Transformers

Andreas C Mueller, Carlo A Curino, Raghu Ramakrishnan

Swing-by Dynamics in Concept Learning and Compositional Generalization

Yongyi Yang, Core Francisco Park, Ekdeep Singh Lubana, Maya Okawa, Wei Hu

Revealing the 3D Cosmic Web through Gravitationally Constrained Neural Fields

Brandon Zhao, Aviad Levis, Liam Connor, Pratul P. Srinivasan, Katherine Bouman

Fair Submodular Cover

Wenjing Chen, Shuo Xing, Samson Zhou, Victoria G. Crawford

Generalized Consistency Trajectory Models for Image Manipulation

Beomsu Kim, Jaemin Kim, Jeongsol Kim, Jong Chul Ye

Demystifying Topological Message-Passing with Relational Structures: A Case Study on Oversquashing in Simplicial Message-Passing

Diaaeldin Taha, James Chapman, Marzieh Eidi, Karel Devriendt, Guido Montúfar

From Tokens to Lattices: Emergent Lattice Structures in Language Models

Bo Xiong, Steffen Staab

Eliminating Position Bias of Language Models: A Mechanistic Approach

Ziqi Wang, Hanlin Zhang, Xiner Li, Kuan-Hao Huang, Chi Han

Towards a Unified and Verified Understanding of Group-Operation Networks

Wilson Wu, Louis Jaburi, jacob drori, Jason Gross

Closed-Form Merging of Parameter-Efficient Modules for Federated Continual Learning

Riccardo Salami, Pietro Buzzega, Matteo Mosconi, Jacopo Bonato, Luigi Sabetta

Beyond Linear Approximations: A Novel Pruning Approach for Attention Matrix

Yingyu Liang, Jiangxuan Long, Zhenmei Shi, Zhao Song, Yufa Zhou

Convex Formulations for Training Two-Layer ReLU Neural Networks

Karthik Prakhya, Tolga Birdal, Alp Yurtsever

Federated Granger Causality Learning For Interdependent Clients With State Space Representation

Ayush Mohanty, Nazal Mohamed, Paritosh Ramanan, Nagi Gebraeel

Comparing Targeting Strategies for Maximizing Social Welfare with Limited Resources

Vibhhu Sharma, Bryan Wilder

How Does Critical Batch Size Scale in Pre-training?

Hanlin Zhang, Depen Morwani, Nikhil Vyas, Jingfeng Wu, Difan Zou

Transformers Handle Endogeneity in In-Context Linear Regression

Haodong Liang, Krishna Balasubramanian, Lifeng LAI

Generalization v.s. Memorization: Tracing Language Models’ Capabilities Back to Pretraining Data

Xinyi Wang, Antonis Antoniades, Yanai Elazar, Alfonso Amayuelas, Alon Albalak

Rethinking Reward Modeling in Preference-based Large Language Model Alignment

Hao Sun, Yunyi Shen, Jean-Francois Ton

Frequency-Guided Masking for Enhanced Vision Self-Supervised Learning

Amin Karimi Monsefi, Mengxi Zhou, Nastaran Karimi Monsefi, Ser-Nam Lim, Wei-Lun Chao

PADRe: A Unifying Polynomial Attention Drop-in Replacement for Efficient Vision Transformer

Pierre-David Letourneau, Manish Kumar Singh, Hsin-Pai Cheng, Shizhong Han, Yunxiao Shi

Expressivity of Neural Networks with Random Weights and Learned Biases

Ezekiel Williams, Alexandre Payeur, Avery Hee-Woon Ryoo, Thomas Jiralerspong, Matthew G Perich

Bilinear MLPs enable weight-based mechanistic interpretability

Michael T Pearce, Thomas Dooms, Alice Rigg, Jose Oramas, Lee Sharkey

Differentially Private Federated Learning with Time-Adaptive Privacy Spending

Shahrzad Kiani, Nupur Kulkarni, Adam Dziedzic, Stark Draper, Franziska Boenisch

Language-Image Models with 3D Understanding

Jang Hyun Cho, Boris Ivanovic, Yulong Cao, Edward Schmerling, Yue Wang

DataGen: Unified Synthetic Dataset Generation via Large Language Models

Yue Huang, Siyuan Wu, Chujie Gao, Dongping Chen, Qihui Zhang

Learning a Fast Mixing Exogenous Block MDP using a Single Trajectory

Alexander Levine, Peter Stone, Amy Zhang

The Hyperfitting Phenomenon: Sharpening and Stabilizing LLMs for Open-Ended Text Generation

Fredrik Carlsson, Fangyu Liu, Daniel Ward, Murathan Kurfali, Joakim Nivre

Breaking the Reclustering Barrier in Centroid-based Deep Clustering

Lukas Miklautz, Timo Klein, Kevin Sidak, Collin Leiber, Thomas Lang

SoundCTM: Unifying Score-based and Consistency Models for Full-band Text-to-Sound Generation

Koichi Saito, Dongjun Kim, Takashi Shibuya, Chieh-Hsin Lai, Zhi Zhong

Doubly Optimal Policy Evaluation for Reinforcement Learning

Shuze Liu, Claire Chen, Shangtong Zhang

Graph Transformers Dream of Electric Flow

Xiang Cheng, Lawrence Carin, Suvrit Sra

Online Clustering with Nearly Optimal Consistency

T-H. Hubert Chan, Shaofeng H.-C. Jiang, Tianyi Wu, Mengshi Zhao

MuirBench: A Comprehensive Benchmark for Robust Multi-image Understanding

Fei Wang, Xingyu Fu, James Y. Huang, Zekun Li, Qin Liu

Progressive distillation induces an implicit curriculum

Abhishek Panigrahi, Bingbin Liu, Sadhika Malladi, Andrej Risteski, Surbhi Goel

Better than Your Teacher: LLM Agents that learn from Privileged AI Feedback

Sanjiban Choudhury, Paloma Sodhi

AgentTrek: Agent Trajectory Synthesis via Guiding Replay with Web Tutorials

Yiheng Xu, Dunjie Lu, Zhennan Shen, Junli Wang, Zekun Wang

Efficient stagewise pretraining via progressive subnetworks

Abhishek Panigrahi, Nikunj Saunshi, Kaifeng Lyu, Sobhan Miryoosefi, Sashank J. Reddi

Test of Time: A Benchmark for Evaluating LLMs on Temporal Reasoning

Bahare Fatemi, Mehran Kazemi, Anton Tsitsulin, Karishma Malkan, Jinyeong Yim

Towards hyperparameter-free optimization with differential privacy

Ruixuan Liu, Zhiqi Bu

LLaRA: Supercharging Robot Learning Data for Vision-Language Policy

Xiang Li, Cristina Mata, Jongwoo Park, Kumara Kahatapitiya, Yoo Sung Jang

Graph Neural Networks Can (Often) Count Substructures

Paolo Pellizzoni, Till Hendrik Schulz, Karsten Borgwardt

MAVIS: Mathematical Visual Instruction Tuning with an Automatic Data Engine

Renrui Zhang, Xinyu Wei, Dongzhi Jiang, Ziyu Guo, Yichi Zhang

Beyond FVD: An Enhanced Evaluation Metrics for Video Generation Distribution Quality

Ge Ya Luo, Gian Mario Favero, ZhiHao Luo, Alexia Jolicoeur-Martineau, Christopher Pal

NeurFlow: Interpreting Neural Networks through Neuron Groups and Functional Interactions

Tue Minh Cao, Nhat Hoang-Xuan, Hieu Pham, Phi Le Nguyen, My T. Thai

Unlocking Guidance for Discrete State-Space Diffusion and Flow Models

Hunter Nisonoff, Junhao Xiong, Stephan Allenspach, Jennifer Listgarten

GenARM: Reward Guided Generation with Autoregressive Reward Model for Test-Time Alignment

Yuancheng Xu, Udari Madhushani Sehwag, Alec Koppel, Sicheng Zhu, Bang An

On the Price of Differential Privacy for Hierarchical Clustering

Chengyuan Deng, Jie Gao, Jalaj Upadhyay, Chen Wang, Samson Zhou

RepoGraph: Enhancing AI Software Engineering with Repository-level Code Graph

Siru Ouyang, Wenhao Yu, Kaixin Ma, Zilin Xiao, Zhihan Zhang

Asynchronous RLHF: Faster and More Efficient Off-Policy RL for Language Models

Michael Noukhovitch, Shengyi Huang, Sophie Xhonneux, Arian Hosseini, Rishabh Agarwal

MGDA Converges under Generalized Smoothness, Provably

Qi Zhang, Peiyao Xiao, Shaofeng Zou, Kaiyi Ji

MetaOOD: Automatic Selection of OOD Detection Models

Yuehan Qin, Yichi Zhang, Yi Nian, Xueying Ding, Yue Zhao

PolyNet: Learning Diverse Solution Strategies for Neural Combinatorial Optimization

André Hottung, Mridul Mahajan, Kevin Tierney

MMWorld: Towards Multi-discipline Multi-faceted World Model Evaluation in Videos

Xuehai He, Weixi Feng, Kaizhi Zheng, Yujie Lu, Wanrong Zhu

On the Convergence of No-Regret Dynamics in Information Retrieval Games with Proportional Ranking Functions

Omer Madmon, Idan Pipano, Itamar Reinman, Moshe Tennenholtz

Scalable Bayesian Learning with posteriors

Samuel Duffield, Kaelan Donatella, Johnathan Chiu, Phoebe Klett, Daniel Simpson

Navigating the Digital World as Humans Do: Universal Visual Grounding for GUI Agents

Boyu Gou, Ruohan Wang, Boyuan Zheng, Yanan Xie, Cheng Chang

Linear Combination of Saved Checkpoints Makes Consistency and Diffusion Models Better

Enshu Liu, Junyi Zhu, Zinan Lin, Xuefei Ning, Shuaiqi Wang

TetSphere Splatting: Representing High-Quality Geometry with Lagrangian Volumetric Meshes

Minghao Guo, Bohan Wang, Kaiming He, Wojciech Matusik

Multi-Robot Motion Planning with Diffusion Models

Yorai Shaoul, Itamar Mishani, Shivam Vats, Jiaoyang Li, Maxim Likhachev

Learning from Imperfect Human Feedback: A Tale from Corruption-Robust Dueling

Yuwei Cheng, Fan Yao, Xuefeng Liu, Haifeng Xu

Grokking at the Edge of Numerical Stability

Lucas Prieto, Melih Barsbey, Pedro A. M. Mediano, Tolga Birdal

Is Large-scale Pretraining the Secret to Good Domain Generalization?

Piotr Teterwak, Kuniaki Saito, Theodoros Tsiligkaridis, Bryan A. Plummer, Kate Saenko

NextBestPath: Efficient 3D Mapping of Unseen Environments

Shiyao Li, Antoine Guedon, Clémentin Boittiaux, Shizhe Chen, Vincent Lepetit

Improved Algorithms for Kernel Matrix-Vector Multiplication Under Sparsity Assumptions

Piotr Indyk, Michael Kapralov, Kshiteej Sheth, Tal Wagner

Balancing Act: Diversity and Consistency in Large Language Model Ensembles

Ahmed Abdulaal, Chen Jin, Nina Montana-Brown, Aryo Pradipta Gema, Daniel C. Castro

Transformers Can Learn Temporal Difference Methods for In-Context Reinforcement Learning

Jiuqi Wang, Ethan Blaser, Hadi Daneshmand, Shangtong Zhang

SBSC: Step-by-Step Coding for Improving Mathematical Olympiad Performance

Kunal Singh, Ankan Biswas, Sayandeep Bhowmick, Pradeep Moturi, Siva Kishore Gollapalli

Bridging the Gap Between f-divergences and Bayes Hilbert Spaces

Linus Lach, Alexander Willi Fottner, Yarema Okhrin

Learning Graph Quantized Tokenizers

Limei Wang, Kaveh Hassani, Si Zhang, Dongqi Fu, Baichuan Yuan

GPS: A Probabilistic Distributional Similarity with Gumbel Priors for Set-to-Set Matching

Ziming Zhang, Fangzhou Lin, Haotian Liu, Jose Morales, Haichong Zhang

AnoLLM: Large Language Models for Tabular Anomaly Detection

Che-Ping Tsai, Ganyu Teng, Phillip Wallis, Wei Ding

Bayesian Regularization of Latent Representation

Chukwudi Paul Obite, Zhi Chang, Keyan Wu, Shiwei Lan

Conformalized Interactive Imitation Learning: Handling Expert Shift and Intermittent Feedback

Michelle D Zhao, Henny Admoni, Reid Simmons, Aaditya Ramdas, Andrea Bajcsy

LLM-wrapper: Black-Box Semantic-Aware Adaptation of Vision-Language Models for Referring Expression Comprehension

Amaia Cardiel, Eloi Zablocki, Elias Ramzi, Oriane Siméoni, Matthieu Cord