ICLR 2025

3,703 papers

Doubly robust identification of treatment effects from multiple environments

Piersilvio De Bartolomeis, Julia Kostin, Javier Abad, Yixin Wang, Fanny Yang

Revisiting Random Walks for Learning on Graphs

Jinwoo Kim, Olga Zaghen, Ayhan Suleymanzade, Youngmin Ryou, Seunghoon Hong

Modeling Unseen Environments with Language-guided Composable Causal Components in Reinforcement Learning

Xinyue Wang, Biwei Huang

Generalizable Motion Planning via Operator Learning

Sharath Matada, Luke Bhan, Yuanyuan Shi, Nikolay Atanasov

Revisiting Source-Free Domain Adaptation: a New Perspective via Uncertainty Control

Gezheng Xu, Hui GUO, Li Yi, Charles Ling, Boyu Wang

NetFormer: An interpretable model for recovering dynamical connectivity in neuronal population dynamics

Ziyu Lu, Wuwei Zhang, Trung Le, Hao Wang, Uygar Sümbül

Block Verification Accelerates Speculative Decoding

Ziteng Sun, Uri Mendlovic, Yaniv Leviathan, Asaf Aharoni, Jae Hun Ro

Efficient Diversity-Preserving Diffusion Alignment via Gradient-Informed GFlowNets

Zhen Liu, Tim Z. Xiao, Weiyang Liu, Yoshua Bengio, Dinghuai Zhang

Kernel-based Optimally Weighted Conformal Time-Series Prediction

Jonghyeok Lee, Chen Xu, Yao Xie

BAMDP Shaping: a Unified Framework for Intrinsic Motivation and Reward Shaping

Aly Lidayan, Michael D Dennis, Stuart Russell

Fine-Tuning Discrete Diffusion Models via Reward Optimization with Applications to DNA and Protein Design

Chenyu Wang, Masatoshi Uehara, Yichun He, Amy Wang, Avantika Lal

R^2-Guard: Robust Reasoning Enabled LLM Guardrail via Knowledge-Enhanced Logical Reasoning

Mintong Kang, Bo Li

EC-DIT: Scaling Diffusion Transformers with Adaptive Expert-Choice Routing

Haotian Sun, Tao Lei, Bowen Zhang, Yanghao Li, Haoshuo Huang

Self-Improving Robust Preference Optimization

Eugene Choi, Arash Ahmadian, Matthieu Geist, Olivier Pietquin, Mohammad Gheshlaghi azar

Improved Diffusion-based Generative Model with Better Adversarial Robustness

Zekun Wang, Mingyang Yi, Shuchen Xue, Zhenguo Li, Ming Liu

PWM: Policy Learning with Multi-Task World Models

Ignat Georgiev, Varun Giridhar, Nicklas Hansen, Animesh Garg

The Semantic Hub Hypothesis: Language Models Share Semantic Representations Across Languages and Modalities

Zhaofeng Wu, Xinyan Velocity Yu, Dani Yogatama, Jiasen Lu, Yoon Kim

AssembleFlow: Rigid Flow Matching with Inertial Frames for Molecular Assembly

Hongyu Guo, Yoshua Bengio, Shengchao Liu

Self-MoE: Towards Compositional Large Language Models with Self-Specialized Experts

Junmo Kang, Leonid Karlinsky, Hongyin Luo, Zhen Wang, Jacob A Hansen

Looking Inward: Language Models Can Learn About Themselves by Introspection

Felix Jedidja Binder, James Chua, Tomek Korbak, Henry Sleight, John Hughes

AVHBench: A Cross-Modal Hallucination Benchmark for Audio-Visual Large Language Models

Kim Sung-Bin, Oh Hyun-Bin, JungMok Lee, Arda Senocak, Joon Son Chung

Confidence Elicitation: A New Attack Vector for Large Language Models

Brian Formento, Chuan-Sheng Foo, See-Kiong Ng

MetaMetrics: Calibrating Metrics for Generation Tasks Using Human Preferences

Genta Indra Winata, David Anugraha, Lucky Susanto, Garry Kuwanto, Derry Tanti Wijaya

Contrastive Learning from Synthetic Audio Doppelgängers

Manuel Cherep, Nikhil Singh

Multiple Heads are Better than One: Mixture of Modality Knowledge Experts for Entity Representation Learning

Yichi Zhang, Zhuo Chen, Lingbing Guo, Yajing Xu, Binbin Hu

Weighted Multi-Prompt Learning with Description-free Large Language Model Distillation

Sua Lee, Kyubum Shin, Jung Ho Park

When do GFlowNets learn the right distribution?

Tiago Silva, Rodrigo Barreto Alves, Eliezer de Souza da Silva, Amauri H Souza, Vikas Garg

UniWav: Towards Unified Pre-training for Speech Representation Learning and Generation

Alexander H. Liu, Sang-gil Lee, Chao-Han Huck Yang, Yuan Gong, Yu-Chiang Frank Wang

Investigating the Pre-Training Dynamics of In-Context Learning: Task Recognition vs. Task Learning

Xiaolei Wang, Xinyu Tang, Junyi Li, Xin Zhao, Ji-Rong Wen

Accelerated Over-Relaxation Heavy-Ball Method: Achieving Global Accelerated Convergence with Broad Generalization

Jingrong Wei, Long Chen

Advancing Graph Generation through Beta Diffusion

Xinyang Liu, Yilin He, Bo Chen, Mingyuan Zhou

Revisit Large-Scale Image-Caption Data in Pre-training Multimodal Foundation Models

Zhengfeng Lai, Vasileios Saveris, Chen Chen, Hong-You Chen, Haotian Zhang

Learning-Augmented Search Data Structures

Chunkai Fu, Brandon G. Nguyen, Jung Hoon Seo, Ryan S. Zesch, Samson Zhou

Examining Alignment of Large Language Models through Representative Heuristics: the case of political stereotypes

Sullam Jeoung, Yubin Ge, Haohan Wang, Jana Diesner

Learning How Hard to Think: Input-Adaptive Allocation of LM Computation

Mehul Damani, Idan Shenfeld, Andi Peng, Andreea Bobu, Jacob Andreas

Hotspot-Driven Peptide Design via Multi-Fragment Autoregressive Extension

Jiahan Li, Tong Chen, Shitong Luo, Chaoran Cheng, Jiaqi Guan

ReNovo: Retrieval-Based \emph{De Novo} Mass Spectrometry Peptide Sequencing

Shaorong Chen, Jun Xia, Jingbo Zhou, Lecheng Zhang, Zhangyang Gao

T-Stitch: Accelerating Sampling in Pre-Trained Diffusion Models with Trajectory Stitching

Zizheng Pan, Bohan Zhuang, De-An Huang, Weili Nie, Zhiding Yu

The Directionality of Optimization Trajectories in Neural Networks

Sidak Pal Singh, Bobby He, Thomas Hofmann, Bernhard Schölkopf

DeeperForward: Enhanced Forward-Forward Training for Deeper and Better Performance

Liang Sun, Yang Zhang, Weizhao He, Jiajun Wen, Linlin Shen

Generalizing Reasoning Problems to Longer Lengths

Changnan Xiao, Bing Liu

Control-oriented Clustering of Visual Latent Representation

Han Qi, Haocheng Yin, Heng Yang

Pedestrian Motion Reconstruction: A Large-scale Benchmark via Mixed Reality Rendering with Multiple Perspectives and Modalities

Yichen Wang, Yiyi Zhang, Xinhao Hu, Li Niu, Jianfu Zhang

Advancing LLM Reasoning Generalists with Preference Trees

Lifan Yuan, Ganqu Cui, Hanbin Wang, Ning Ding, Xingyao Wang

Prediction Risk and Estimation Risk of the Ridgeless Least Squares Estimator under General Assumptions on Regression Errors

Sungyoon Lee, Sokbae Lee

Test-time Adaptation for Regression by Subspace Alignment

Kazuki Adachi, Shin'ya Yamaguchi, Atsutoshi Kumagai, Tomoki Hamagami

OptiBench Meets ReSocratic: Measure and Improve LLMs for Optimization Modeling

Zhicheng Yang, Yiwei Wang, Yinya Huang, Zhijiang Guo, Wei Shi

Leveraging Variable Sparsity to Refine Pareto Stationarity in Multi-Objective Optimization

Zeou Hu, Yaoliang Yu

Towards Neural Scaling Laws for Time Series Foundation Models

Qingren Yao, Chao-Han Huck Yang, Renhe Jiang, Yuxuan Liang, Ming Jin

Shedding Light on Time Series Classification using Interpretability Gated Networks

Yunshi Wen, Tengfei Ma, Ronny Luss, Debarun Bhattacharjya, Achille Fokoue

Prevalence of Negative Transfer in Continual Reinforcement Learning: Analyses and a Simple Baseline

Hongjoon Ahn, Jinu Hyeon, Youngmin Oh, Bosun Hwang, Taesup Moon

MAGE: Model-Level Graph Neural Networks Explanations via Motif-based Graph Generation

Zhaoning Yu, Hongyang Gao

Budgeted Online Continual Learning by Adaptive Layer Freezing and Frequency-based Sampling

Minhyuk Seo, Hyunseo Koh, Jonghyun Choi

CodeMMLU: A Multi-Task Benchmark for Assessing Code Understanding & Reasoning Capabilities of CodeLLMs

Dung Manh Nguyen, Thang Chau Phan, Nam Le Hai, Tien-Thong Doan, Nam V. Nguyen

Expected Sliced Transport Plans

Xinran Liu, Rocio Diaz Martin, Yikun Bai, Ashkan Shahbazi, Matthew Thorpe

Magpie: Alignment Data Synthesis from Scratch by Prompting Aligned LLMs with Nothing

Zhangchen Xu, Fengqing Jiang, Luyao Niu, Yuntian Deng, Radha Poovendran

Do LLMs Recognize Your Preferences? Evaluating Personalized Preference Following in LLMs

Siyan Zhao, Mingyi Hong, Yang Liu, Devamanyu Hazarika, Kaixiang Lin

OMG: Opacity Matters in Material Modeling with Gaussian Splatting

Silong Yong, Venkata Nagarjun Pudureddiyur Manivannan, Bernhard Kerbl, Zifu Wan, Simon Stepputtis

Skill Expansion and Composition in Parameter Space

Tenglong Liu, Jianxiong Li, Yinan Zheng, Haoyi Niu, Yixing Lan

Decision Information Meets Large Language Models: The Future of Explainable Operations Research

Yansen Zhang, Qingcan Kang, Wing Yin Yu, HaileiGong, Xiaojin Fu

Enhancing Uncertainty Estimation and Interpretability with Bayesian Non-negative Decision Layer

Xinyue Hu, Zhibin Duan, Bo Chen, Mingyuan Zhou

HOPE for a Robust Parameterization of Long-memory State Space Models

Annan Yu, Michael W. Mahoney, N. Benjamin Erichson

Sequential Controlled Langevin Diffusions

Junhua Chen, Lorenz Richter, Julius Berner, Denis Blessing, Gerhard Neumann

ACE: All-round Creator and Editor Following Instructions via Diffusion Transformer

Zhen Han, Zeyinzi Jiang, Yulin Pan, Jingfeng ZHANG, Chaojie Mao

Feedback Favors the Generalization of Neural ODEs

Jindou Jia, Zihan Yang, Meng Wang, Kexin Guo, Jianfei Yang

Mix-CPT: A Domain Adaptation Framework via Decoupling Knowledge Learning and Format Alignment

Jinhao Jiang, Junyi Li, Xin Zhao, Yang Song, Tao Zhang

An Effective Manifold-based Optimization Method for Distributionally Robust Classification

Jiawei Huang, Hu Ding

Diverse Policies Recovering via Pointwise Mutual Information Weighted Imitation Learning

Hanlin Yang, Jian Yao, Weiming Liu, Qing Wang, Hanmin Qin

Second-Order Fine-Tuning without Pain for LLMs: A Hessian Informed Zeroth-Order Optimizer

Yanjun Zhao, Sizhe Dang, Haishan Ye, Guang Dai, Yi Qian

Visually Consistent Hierarchical Image Classification

Seulki Park, Youren Zhang, Stella X. Yu, Sara Beery, Jonathan Huang

Stochastic Semi-Gradient Descent for Learning Mean Field Games with Population-Aware Function Approximation

Chenyu Zhang, Xu Chen, Xuan Di

Learning vector fields of differential equations on manifolds with geometrically constrained operator-valued kernels

Daning Huang, Hanyang He, John Harlim, Yan Li

System 1.x: Learning to Balance Fast and Slow Planning with Language Models

Swarnadeep Saha, Archiki Prasad, Justin Chen, Peter Hase, Elias Stengel-Eskin

Once-for-All: Controllable Generative Image Compression with Dynamic Granularity Adaptation

Anqi Li, Feng Li, Yuxi Liu, Runmin Cong, Yao Zhao

MuseGNN: Forming Scalable, Convergent GNN Layers that Minimize a Sampling-Based Energy

Haitian Jiang, Renjie Liu, zengfeng Huang, Yichuan Wang, Xiao Yan

Reward Dimension Reduction for Scalable Multi-Objective Reinforcement Learning

Giseung Park, Youngchul Sung

On Large Language Model Continual Unlearning

Chongyang Gao, Lixu Wang, Kaize Ding, Chenkai Weng, Xiao Wang

An Empirical Analysis of Uncertainty in Large Language Model Evaluations

Qiujie Xie, Qingqiu Li, Zhuohao Yu, Yuejie Zhang, Yue Zhang

A Robust Method to Discover Causal or Anticausal Relation

Yu Yao, Yang Zhou, Bo Han, Mingming Gong, Kun Zhang

Graph Neural Preconditioners for Iterative Solutions of Sparse Linear Systems

Jie Chen

The "Law'' of the Unconscious Contrastive Learner: Probabilistic Alignment of Unpaired Modalities

Yongwei Che, Benjamin Eysenbach

On Evaluating the Durability of Safeguards for Open-Weight LLMs

Xiangyu Qi, Boyi Wei, Nicholas Carlini, Yangsibo Huang, Tinghao Xie

Hypothetical Minds: Scaffolding Theory of Mind for Multi-Agent Tasks with Large Language Models

Logan Cross, Violet Xiang, Agam Bhatia, Daniel LK Yamins, Nick Haber

h4rm3l: A Language for Composable Jailbreak Attack Synthesis

Moussa Koulako Bala Doumbouya, Ananjan Nandi, Gabriel Poesia, Davide Ghilardi, Anna Goldie

Pacmann: Efficient Private Approximate Nearest Neighbor Search

Mingxun Zhou, Elaine Shi, Giulia Fanti

The Crystal Ball Hypothesis in diffusion models: Anticipating object positions from initial noise

Yuanhao Ban, Ruochen Wang, Tianyi Zhou, Boqing Gong, Cho-jui Hsieh

MTU-Bench: A Multi-granularity Tool-Use Benchmark for Large Language Models

Pei Wang, Yanan Wu, Noah Wang, Jiaheng Liu, Xiaoshuai Song

Reflexive Guidance: Improving OoDD in Vision-Language Models via Self-Guided Image-Adaptive Concept Generation

Jihyo Kim, Seulbi Lee, Sangheum Hwang

Progress or Regress? Self-Improvement Reversal in Post-training

Ting Wu, Xuefeng Li, Pengfei Liu

CREIMBO: Cross-Regional Ensemble Interactions in Multi-view Brain Observations

Noga Mudrik, Ryan Ly, Oliver Ruebel, Adam Shabti Charles

DARE the Extreme: Revisiting Delta-Parameter Pruning For Fine-Tuned Models

Wenlong Deng, Yize Zhao, Vala Vakilian, Minghui Chen, Xiaoxiao Li

DUALFormer: Dual Graph Transformer

Jiaming Zhuo, Yuwei Liu, Yintong Lu, Ziyi Ma, Kun Fu

Proving Olympiad Inequalities by Synergizing LLMs and Symbolic Reasoning

Zenan Li, Zhaoyu Li, Wen Tang, Xian Zhang, Yuan Yao

Automatic Curriculum Expert Iteration for Reliable LLM Reasoning

Zirui Zhao, Hanze Dong, Amrita Saha, Caiming Xiong, Doyen Sahoo

Human Simulacra: Benchmarking the Personification of Large Language Models

Qiujie Xie, Qiming Feng, Tianqi Zhang, Qingqiu Li, Linyi Yang

SimXRD-4M: Big Simulated X-ray Diffraction Data and Crystal Symmetry Classification Benchmark

Bin Cao, Yang Liu, Zinan Zheng, Ruifeng Tan, Jia Li

Accurate and Scalable Graph Neural Networks via Message Invariance

Zhihao Shi, Jie Wang, Zhiwei Zhuang, Xize Liang, Bin Li

Data-centric Prediction Explanation via Kernelized Stein Discrepancy

Mahtab Sarvmaili, Hassan Sajjad, Ga Wu

DreamBench++: A Human-Aligned Benchmark for Personalized Image Generation

Yuang Peng, Yuxin Cui, Haomiao Tang, Zekun Qi, Runpei Dong

When Prompt Engineering Meets Software Engineering: CNL-P as Natural and Robust "APIs'' for Human-AI Interaction

Zhenchang Xing, Yang Liu, Zhuo Cheng, Qing Huang, Dehai Zhao