ICLR 2025

3,703 papers

Provably Accurate Shapley Value Estimation via Leverage Score Sampling

Christopher Musco, R. Teal Witter

Decomposition Polyhedra of Piecewise Linear Functions

Marie-Charlotte Brandenburg, Moritz Leo Grillo, Christoph Hertrich

Scalable Discrete Diffusion Samplers: Combinatorial Optimization and Statistical Physics

Sebastian Sanokowski, Wilhelm Franz Berghammer, Haoyu Peter Wang, Martin Ennemoser, Sepp Hochreiter

What Matters When Repurposing Diffusion Models for General Dense Perception Tasks?

Guangkai Xu, Yongtao Ge, Mingyu Liu, Chengxiang Fan, Kangyang Xie

Scalable Decentralized Learning with Teleportation

Yuki Takezawa, Sebastian U Stich

MiniPLM: Knowledge Distillation for Pre-training Language Models

Yuxian Gu, Hao Zhou, Fandong Meng, Jie Zhou, Minlie Huang

On the Role of Attention Heads in Large Language Model Safety

Zhenhong Zhou, Haiyang Yu, Xinghua Zhang, Rongwu Xu, Fei Huang

Watch Less, Do More: Implicit Skill Discovery for Video-Conditioned Policy

Jiangxing Wang, Zongqing Lu

EMOS: Embodiment-aware Heterogeneous Multi-robot Operating System with LLM Agents

Junting Chen, Checheng Yu, Xunzhe Zhou, Tianqi Xu, Yao Mu

MeshMask: Physics-Based Simulations with Masked Graph Neural Networks

Paul Garnier, Vincent Lannelongue, Jonathan Viquerat, Elie Hachem

DeepLTL: Learning to Efficiently Satisfy Complex LTL Specifications for Multi-Task RL

Mathias Jackermeier, Alessandro Abate

On Disentangled Training for Nonlinear Transform in Learned Image Compression

Han Li, Shaohui Li, Wenrui Dai, Maida Cao, Nuowen Kan

SelKD: Selective Knowledge Distillation via Optimal Transport Perspective

Liangliang Shi, Zhengyan Shi, Junchi Yan

Stochastic variance-reduced Gaussian variational inference on the Bures-Wasserstein manifold

Hoang Phuc Hau Luu, Hanlin Yu, Bernardo Williams, Marcelo Hartmann, Arto Klami

HELM: Hierarchical Encoding for mRNA Language Modeling

Mehdi Yazdani-Jahromi, Mangal Prakash, Tommaso Mansi, Artem Moskalev, Rui Liao

Exploring a Principled Framework for Deep Subspace Clustering

Xianghan Meng, Zhiyuan Huang, Wei He, Xianbiao Qi, Rong Xiao

Beyond Interpretability: The Gains of Feature Monosemanticity on Model Robustness

Qi Zhang, Yifei Wang, Jingyi Cui, Xiang Pan, Qi Lei

Topograph: An Efficient Graph-Based Framework for Strictly Topology Preserving Image Segmentation

Laurin Lux, Alexander H Berger, Alexander Weers, Nico Stucki, Daniel Rueckert

Diffusion Models are Evolutionary Algorithms

Yanbo Zhang, Benedikt Hartl, Hananel Hazan, Michael Levin

Glad: A Streaming Scene Generator for Autonomous Driving

Bin Xie, Yingfei Liu, Tiancai Wang, Jiale Cao, Xiangyu Zhang

Chain-of-Thought Provably Enables Learning the (Otherwise) Unlearnable

Chenxiao Yang, Zhiyuan Li, David Wipf

Discrete Distribution Networks

Lei Yang

Scaling FP8 training to trillion-token LLMs

Maxim Fishman, Brian Chmiel, Ron Banner, Daniel Soudry

AlphaEdit: Null-Space Constrained Knowledge Editing for Language Models

Junfeng Fang, Houcheng Jiang, Kun Wang, Yunshan Ma, Jie Shi

Exploiting Distribution Constraints for Scalable and Efficient Image Retrieval

Mohammad Omama, Po-han Li, Sandeep P. Chinchali

Flavors of Margin: Implicit Bias of Steepest Descent in Homogeneous Neural Networks

Nikolaos Tsilivis, Gal Vardi, Julia Kempe

On the Modeling Capabilities of Large Language Models for Sequential Decision Making

Martin Klissarov, R Devon Hjelm, Alexander T Toshev, Bogdan Mazoure

Differentiable Rule Induction from Raw Sequence Inputs

Kun Gao, Katsumi Inoue, Yongzhi Cao, Hanpin Wang, Yang Feng

Diffusion Models as Cartoonists: The Curious Case of High Density Regions

Rafal Karczewski, Markus Heinonen, Vikas Garg

Scaling In-the-Wild Training for Diffusion-based Illumination Harmonization and Editing by Imposing Consistent Light Transport

Lvmin Zhang, Anyi Rao, Maneesh Agrawala

From Pixels to Tokens: Byte-Pair Encoding on Quantized Visual Modalities

Wanpeng Zhang, Zilong Xie, Yicheng Feng, Yijiang Li, Xingrun Xing

PAD: Personalized Alignment of LLMs at Decoding-time

Ruizhe Chen, Xiaotian Zhang, Meng Luo, Wenhao Chai, Zuozhu Liu

Null Counterfactual Factor Interactions for Goal-Conditioned Reinforcement Learning

Caleb Chuck, Fan Feng, Carl Qi, Chang Shi, Siddhant Agarwal

Visual Haystacks: A Vision-Centric Needle-In-A-Haystack Benchmark

Tsung-Han Wu, Giscard Biamby, Jerome Quenum, Ritwik Gupta, Joseph E. Gonzalez

Learning Generalizable Skills from Offline Multi-Task Data for Multi-Agent Cooperation

Sicong Liu, Yang Shu, Chenjuan Guo, Bin Yang

Optimal Protocols for Continual Learning via Statistical Physics and Control Theory

Francesco Mori, Stefano Sarao Mannelli, Francesca Mignacco

SPARTUN3D: Situated Spatial Understanding of 3D World in Large Language Model

Yue Zhang, Zhiyang Xu, Ying Shen, Parisa Kordjamshidi, Lifu Huang

Needle Threading: Can LLMs Follow Threads Through Near-Million-Scale Haystacks?

Jonathan Roberts, Kai Han, Samuel Albanie

Advantage Alignment Algorithms

Juan Agustin Duque, Milad Aghajohari, Tim Cooijmans, razvan ciuca, Tianyu Zhang

Fengbo: a Clifford Neural Operator pipeline for 3D PDEs in Computational Fluid Dynamics

Alberto Pepe, Mattia Montanari, Joan Lasenby

Multi-Field Adaptive Retrieval

Millicent Li, Tongfei Chen, Benjamin Van Durme, Patrick Xia

Error-quantified Conformal Inference for Time Series

Junxi Wu, Dongjian Hu, Yajie Bao, Shu-Tao Xia, Changliang Zou

Towards General-Purpose Model-Free Reinforcement Learning

Scott Fujimoto, Pierluca D'Oro, Amy Zhang, Yuandong Tian, Michael Rabbat

Higher-Order Graphon Neural Networks: Approximation and Cut Distance

Daniel Herbst, Stefanie Jegelka

COAT: Compressing Optimizer states and Activations for Memory-Efficient FP8 Training

Haocheng Xi, Han Cai, Ligeng Zhu, Yao Lu, Kurt Keutzer

Towards Understanding the Robustness of Diffusion-Based Purification: A Stochastic Perspective

Yiming Liu, Kezhao Liu, Yao Xiao, Ziyi Dong, Xiaogang Xu

Generative Verifiers: Reward Modeling as Next-Token Prediction

Lunjun Zhang, Arian Hosseini, Hritik Bansal, Mehran Kazemi, Aviral Kumar

CertainlyUncertain: A Benchmark and Metric for Multimodal Epistemic and Aleatoric Awareness

Khyathi Chandu, Linjie Li, Anas Awadalla, Ximing Lu, Jae Sung Park

Can LLMs Generate Novel Research Ideas? A Large-Scale Human Study with 100+ NLP Researchers

Chenglei Si, Diyi Yang, Tatsunori Hashimoto

Improving Generalization and Robustness in SNNs Through Signed Rate Encoding and Sparse Encoding Attacks

Bhaskar Mukhoty, Hilal AlQuabeh, Bin Gu

Distributed Speculative Inference (DSI): Speculation Parallelism for Provably Faster Lossless Language Model Inference

Nadav Timor, Jonathan Mamou, Daniel Korat, Moshe Berchansky, Oren Pereg

Smaller, Weaker, Yet Better: Training LLM Reasoners via Compute-Optimal Sampling

Hritik Bansal, Arian Hosseini, Rishabh Agarwal, Vinh Q. Tran, Mehran Kazemi

3DGS-Drag: Dragging Gaussians for Intuitive Point-Based 3D Editing

Jiahua Dong, Yu-Xiong Wang

Non-myopic Generation of Language Models for Reasoning and Planning

Chang Ma, Haiteng Zhao, Junlei Zhang, Junxian He, Lingpeng Kong

A3D: Does Diffusion Dream about 3D Alignment?

Savva Victorovich Ignatyev, Nina Konovalova, Daniil Selikhanovych, Oleg Voynov, Nikolay Patakin

Unlearn and Burn: Adversarial Machine Unlearning Requests Destroy Model Accuracy

Yangsibo Huang, Daogao Liu, Lynn Chua, Badih Ghazi, Pritish Kamath

MMAU: A Massive Multi-Task Audio Understanding and Reasoning Benchmark

S Sakshi, Utkarsh Tyagi, Sonal Kumar, Ashish Seth, Ramaneswaran Selvakumar

Linear Transformer Topological Masking with Graph Random Features

Isaac Reid, Kumar Avinava Dubey, Deepali Jain, William F Whitney, Amr Ahmed

Variance-Reducing Couplings for Random Features

Isaac Reid, Stratis Markou, Krzysztof Marcin Choromanski, Richard E. Turner, Adrian Weller

Privacy Auditing of Large Language Models

Ashwinee Panda, Xinyu Tang, Christopher A. Choquette-Choo, Milad Nasr, Prateek Mittal

Rethinking Fair Representation Learning for Performance-Sensitive Tasks

Charles Jones, Fabio De Sousa Ribeiro, Mélanie Roschewitz, Daniel C. Castro, Ben Glocker

Contextualizing biological perturbation experiments through language

Menghua Wu, Russell Littman, Jacob Levine, Lin Qiu, Tommaso Biancalani

cryoSPHERE: Single-Particle HEterogeneous REconstruction from cryo EM

Gabriel Ducrocq, Lukas Grunewald, Sebastian Westenhoff, Fredrik Lindsten

DON’T STOP ME NOW: EMBEDDING BASED SCHEDULING FOR LLMS

Rana Shahout, Eran Malach, Chunwei Liu, Weifan Jiang, Minlan Yu

EIA: ENVIRONMENTAL INJECTION ATTACK ON GENERALIST WEB AGENTS FOR PRIVACY LEAKAGE

Zeyi Liao, Lingbo Mo, Chejian Xu, Mintong Kang, Jiawei Zhang

Multimodality Helps Few-shot 3D Point Cloud Semantic Segmentation

Zhaochong An, Guolei Sun, Yun Liu, Runjia Li, Min Wu

Instructional Segment Embedding: Improving LLM Safety with Instruction Hierarchy

Tong Wu, Shujian Zhang, Kaiqiang Song, Silei Xu, Sanqiang Zhao

Enhancing Language Model Agents using Diversity of Thoughts

Vijay Lingam, Behrooz Omidvar Tehrani, Sujay Sanghavi, Gaurav Gupta, Sayan Ghosh

SelectFormer in Data Markets: Privacy-Preserving and Efficient Data Selection for Transformers with Multi-Party Computation

Xu Ouyang, Felix Xiaozhu Lin, Yangfeng Ji

Not All Language Model Features Are One-Dimensionally Linear

Joshua Engels, Eric J Michaud, Isaac Liao, Wes Gurnee, Max Tegmark

Subtask-Aware Visual Reward Learning from Segmented Demonstrations

Changyeon Kim, Minho Heo, Doohyun Lee, Honglak Lee, Jinwoo Shin

Sort-free Gaussian Splatting via Weighted Sum Rendering

Qiqi Hou, Randall Rauwendaal, Zifeng Li, Hoang Le, Farzad Farhadzadeh

PIN: Prolate Spheroidal Wave Function-based Implicit Neural Representations

Dhananjaya Jayasundara, Heng Zhao, Demetrio Labate, Vishal M. Patel

Logical Consistency of Large Language Models in Fact-Checking

Bishwamittra Ghosh, Sarah Hasan, Naheed Anjum Arafat, Arijit Khan

Learning Transformer-based World Models with Contrastive Predictive Coding

Maxime Burchi, Radu Timofte

DistillHGNN: A Knowledge Distillation Approach for High-Speed Hypergraph Neural Networks

Saman Forouzandeh, Parham Moradi DW, Mahdi Jalili

TopoDiffusionNet: A Topology-aware Diffusion Model

Saumya Gupta, Dimitris Samaras, Chao Chen

Do LLMs estimate uncertainty well in instruction-following?

Juyeon Heo, Miao Xiong, Christina Heinze-Deml, Jaya Narain

Let Me Grok for You: Accelerating Grokking via Embedding Transfer from a Weaker Model

Zhiwei Xu, Zhiyu Ni, Yixin Wang, Wei Hu

Data Distillation for extrapolative protein design through exact preference optimization

Mostafa Karimi, Sharmi Banerjee, Tommi Jaakkola, Bella Dubrov, Shang Shang

Towards Out-of-Modal Generalization without Instance-level Modal Correspondence

Zhuo Huang, Gang Niu, Bo Han, Masashi Sugiyama, Tongliang Liu

Causal Discovery via Bayesian Optimization

Bao Duong, Sunil Gupta, Thin Nguyen

Point-SAM: Promptable 3D Segmentation Model for Point Clouds

Yuchen Zhou, Jiayuan Gu, Tung Yen Chiang, Fanbo Xiang, Hao Su

CBMA: Improving Conformal Prediction through Bayesian Model Averaging

Pankaj Bhagwat, Linglong Kong, Bei Jiang

Spectro-Riemannian Graph Neural Networks

Karish Grover, Haiyang Yu, Xiang Song, Qi Zhu, Han Xie

TIS-DPO: Token-level Importance Sampling for Direct Preference Optimization With Estimated Weights

Aiwei Liu, Haoping Bai, Zhiyun Lu, Yanchao Sun, Xiang Kong

Learning Diverse Attacks on Large Language Models for Robust Red-Teaming and Safety Tuning

Seanie Lee, Minsu Kim, Lynn Cherif, David Dobre, Juho Lee

Efficient Training of Neural Stochastic Differential Equations by Matching Finite Dimensional Distributions

Jianxin Zhang, Josh Viktorov, Doosan Jung, Emily Pitler

RefactorBench: Evaluating Stateful Reasoning in Language Agents Through Code

Dhruv Gautam, Spandan Garg, Jinu Jang, Neel Sundaresan, Roshanak Zilouchian Moghaddam

Cross-Modal Safety Mechanism Transfer in Large Vision-Language Models

Shicheng Xu, Liang Pang, Yunchang Zhu, Huawei Shen, Xueqi Cheng

PostEdit: Posterior Sampling for Efficient Zero-Shot Image Editing

Feng Tian, Yixuan Li, Yichao Yan, Shanyan Guan, Yanhao Ge

Isometric Regularization for Manifolds of Functional Data

Hyeongjun Heo, Seonghun Oh, Jae Yong Lee, Young Min Kim, Yonghyeon LEE

KAA: Kolmogorov-Arnold Attention for Enhancing Attentive Graph Neural Networks

Taoran Fang, Tianhong Gao, Chunping Wang, YihaoShang, Wei Chow

Natural Language Inference Improves Compositionality in Vision-Language Models

Paola Cascante-Bonilla, Yu Hou, Yang Trista Cao, Hal Daume III, Rachel Rudinger

Rethinking Self-Distillation: Label Averaging and Enhanced Soft Label Refinement with Partial Labels

Hyeonsu Jeong, Hye Won Chung

Fine-Tuning Attention Modules Only: Enhancing Weight Disentanglement in Task Arithmetic

Ruochen Jin, Bojian Hou, Jiancong Xiao, Weijie J Su, Li Shen

Mask-DPO: Generalizable Fine-grained Factuality Alignment of LLMs

Yuzhe Gu, Wenwei Zhang, Chengqi Lyu, Dahua Lin, Kai Chen

DeepSeek-Prover-V1.5: Harnessing Proof Assistant Feedback for Reinforcement Learning and Monte-Carlo Tree Search

Huajian Xin, Z.Z. Ren, Junxiao Song, Zhihong Shao, Wanjia Zhao

TAID: Temporally Adaptive Interpolated Distillation for Efficient Knowledge Transfer in Language Models

Makoto Shing, Kou Misaki, Han Bao, Sho Yokoi, Takuya Akiba

Decoding Game: On Minimax Optimality of Heuristic Text Generation Strategies

Sijin Chen, Omar Hagrass, Jason Matthew Klusowski