ICLR 2025

3,703 papers

Stabilized Neural Prediction of Potential Outcomes in Continuous Time

Konstantin Hess, Stefan Feuerriegel

PhyloLM: Inferring the Phylogeny of Large Language Models and Predicting their Performances in Benchmarks

Nicolas Yax, Pierre-yves Oudeyer, Stefano Palminteri

Attention with Markov: A Curious Case of Single-layer Transformers

Ashok Vardhan Makkuva, Marco Bondaschi, Adway Girish, Alliot Nagle, Martin Jaggi

Privacy-Aware Lifelong Learning

Ozan Özdenizci, Elmar Rueckert, Robert Legenstein

BioDiscoveryAgent: An AI Agent for Designing Genetic Perturbation Experiments

Yusuf H Roohani, Andrew H. Lee, Qian Huang, Jian Vora, Zachary Steinhart

Self-Evolving Multi-Agent Collaboration Networks for Software Development

Yue Hu, Yuzhu Cai, Yaxin Du, Xinyu Zhu, Xiangrui Liu

AutoBencher: Towards Declarative Benchmark Construction

Xiang Lisa Li, Farzaan Kaiyom, Evan Zheran Liu, Yifan Mai, Percy Liang

Glauber Generative Model: Discrete Diffusion Models via Binary Classification

Harshit Varma, Dheeraj Mysore Nagaraj, Karthikeyan Shanmugam

Adaptive Methods through the Lens of SDEs: Theoretical Insights on the Role of Noise

Enea Monzio Compagnoni, Tianlin Liu, Rustem Islamov, Frank Norbert Proske, Antonio Orvieto

Surgical, Cheap, and Flexible: Mitigating False Refusal in Language Models via Single Vector Ablation

Xinpeng Wang, Chengzhi Hu, Paul Röttger, Barbara Plank

WebRL: Training LLM Web Agents via Self-Evolving Online Curriculum Reinforcement Learning

Zehan Qi, Xiao Liu, Iat Long Iong, Hanyu Lai, Xueqiao Sun

Temporal Heterogeneous Graph Generation with Privacy, Utility, and Efficiency

Xinyu He, Dongqi Fu, Hanghang Tong, Ross Maciejewski, Jingrui He

The impact of allocation strategies in subset learning on the expressive power of neural networks

Ofir Schlisselberg, Ran Darshan

Polyrating: A Cost-Effective and Bias-Aware Rating System for LLM Evaluation

Jasper Dekoninck, Maximilian Baader, Martin Vechev

Bayesian WeakS-to-Strong from Text Classification to Generation

Ziyun Cui, Ziyang Zhang, Guangzhi Sun, Wen Wu, Chao Zhang

Can Watermarked LLMs be Identified by Users via Crafted Prompts?

Aiwei Liu, Sheng Guan, Yiming Liu, Leyi Pan, Yifei Zhang

TC-MoE: Augmenting Mixture of Experts with Ternary Expert Choice

Shen Yan, Xingyan Bin, Sijun Zhang, Yisen Wang, Zhouchen Lin

KooNPro: A Variance-Aware Koopman Probabilistic Model Enhanced by Neural Process for Time Series Forecasting

Ronghua Zheng, Hanru Bai, Weiyang Ding

What is Wrong with Perplexity for Long-context Language Modeling?

Lizhe Fang, Yifei Wang, Zhaoyang Liu, Chenheng Zhang, Stefanie Jegelka

Automated Filtering of Human Feedback Data for Aligning Text-to-Image Diffusion Models

YongJin Yang, Sihyeon Kim, Hojung Jung, Sangmin Bae, SangMook Kim

Generalizing Weisfeiler-Lehman Kernels to Subgraphs

Dongkwan Kim, Alice Oh

On Quantizing Neural Representation for Variable-Rate Video Coding

Junqi Shi, Zhujia Chen, Hanfei Li, Qi Zhao, Ming Lu

You Only Sample Once: Taming One-Step Text-to-Image Synthesis by Self-Cooperative Diffusion GANs

Yihong Luo, Xiaolong Chen, Xinghua Qu, Tianyang Hu, Jing Tang

FlashMask: Efficient and Rich Mask Extension of FlashAttention

Guoxia Wang, Jinle Zeng, Xiyuan Xiao, Siming Wu, Jiabin Yang

Proteina: Scaling Flow-based Protein Structure Generative Models

Tomas Geffner, Kieran Didi, Zuobai Zhang, Danny Reidenbach, Zhonglin Cao

Rethinking Invariance in In-context Learning

Lizhe Fang, Yifei Wang, Khashayar Gatmiry, Lei Fang, Yisen Wang

Progressive Compositionality in Text-to-Image Generative Models

Xu Han, Linghao Jin, Xiaofeng Liu, Paul Pu Liang

Graph-based Document Structure Analysis

Yufan Chen, Ruiping Liu, Junwei Zheng, Di Wen, Kunyu Peng

Neural networks on Symmetric Spaces of Noncompact Type

Xuan Son Nguyen, Shuo Yang, Aymeric Histace

Uni$^2$Det: Unified and Universal Framework for Prompt-Guided Multi-dataset 3D Detection

Yubin Wang, Zhikang Zou, Xiaoqing Ye, Xiao Tan, Errui Ding

Bio-xLSTM: Generative modeling, representation and in-context learning of biological and chemical sequences

Niklas Schmidinger, Lisa Schneckenreiter, Philipp Seidl, Johannes Schimunek, Pieter-Jan Hoedt

Efficient and Robust Neural Combinatorial Optimization via Wasserstein-Based Coresets

Xu Wang, Fuyou Miao, Wenjie Liu, Yan Xiong

Neuroplastic Expansion in Deep Reinforcement Learning

Jiashun Liu, Johan Samir Obando Ceron, Aaron Courville, Ling Pan

InCoDe: Interpretable Compressed Descriptions For Image Generation

Armand Comas, Aditya Chattopadhyay, Feliu Formosa, Changyu Liu, Octavia Camps

RevisEval: Improving LLM-as-a-Judge via Response-Adapted References

Qiyuan Zhang, Yufei Wang, Tiezheng Yu, Yuxin Jiang, Chuhan Wu

RelCon: Relative Contrastive Learning for a Motion Foundation Model for Wearable Data

Maxwell A Xu, Jaya Narain, Gregory Darnell, Haraldur T Hallgrimsson, Hyewon Jeong

Hybrid Regularization Improves Diffusion-based Inverse Problem Solving

Hongkun Dou, Zeyu Li, Jinyang Du, Lijun Yang, Wen Yao

Towards Explaining the Power of Constant-depth Graph Neural Networks for Structured Linear Programming

Qian Li, Minghui Ouyang, Tian Ding, Yuyi Wang, Qingjiang Shi

The KoLMogorov Test: Compression by Code Generation

Ori Yoran, Kunhao Zheng, Fabian Gloeckle, Jonas Gehring, Gabriel Synnaeve

GraphBridge: Towards Arbitrary Transfer Learning in GNNs

Li Ju, Xingyi Yang, Qi Li, Xinchao Wang

Monet: Mixture of Monosemantic Experts for Transformers

Jungwoo Park, Ahn Young Jin, Kee-eung Kim, Jaewoo Kang

SCBench: A KV Cache-Centric Analysis of Long-Context Methods

Yucheng Li, Huiqiang Jiang, Qianhui Wu, Xufang Luo, Surin Ahn

Lightweight Neural App Control

Filippos Christianos, Georgios Papoudakis, Thomas Coste, Jianye Hao, Jun Wang

Learning LLM-as-a-Judge for Preference Alignment

Ziyi Ye, Xiangsheng Li, Qiuchi Li, Qingyao Ai, Yujia Zhou

Accelerating 3D Molecule Generation via Jointly Geometric Optimal Transport

Haokai Hong, Wanyu Lin, KC Tan

Measuring And Improving Persuasiveness Of Large Language Models

Somesh Kumar Singh, Yaman Kumar Singla, Harini S I, Balaji Krishnamurthy

Improved Sampling Algorithms for Lévy-Itô Diffusion Models

Vadim Popov, Assel Yermekova, Tasnima Sadekova, Artem Khrapov, Mikhail Sergeevich Kudinov

LiFT: Learning to Fine-Tune via Bayesian Parameter Efficient Meta Fine-Tuning

Minyoung Kim, Timothy Hospedales

Reinforcement Learning from Imperfect Corrective Actions and Proxy Rewards

Zhaohui Jiang, Xuening Feng, Paul Weng, Yifei Zhu, Yan Song

CAX: Cellular Automata Accelerated in JAX

Maxence Faldor, Antoine Cully

LongMemEval: Benchmarking Chat Assistants on Long-Term Interactive Memory

Di Wu, Hongwei Wang, Wenhao Yu, Yuwei Zhang, Kai-Wei Chang

Atomas: Hierarchical Adaptive Alignment on Molecule-Text for Unified Molecule Understanding and Generation

Yikun Zhang, Geyan Ye, Chaohao Yuan, Bo Han, Long-Kai Huang

Benchmarking Predictive Coding Networks -- Made Simple

Luca Pinchetti, Chang Qi, Oleh Lokshyn, Cornelius Emde, Amine M'Charrak

Teaching Human Behavior Improves Content Understanding Abilities Of VLMs

Somesh Kumar Singh, Harini S I, Yaman Kumar Singla, Changyou Chen, Rajiv Ratn Shah

VLAS: Vision-Language-Action Model with Speech Instructions for Customized Robot Manipulation

Wei Zhao, Pengxiang Ding, Zhang Min, Zhefei Gong, Shuanghao Bai

Convergence of Score-Based Discrete Diffusion Models: A Discrete-Time Analysis

Zikun Zhang, Zixiang Chen, Quanquan Gu

Measuring And Improving Engagement of Text-to-Image Generation Models

Varun Khurana, Yaman Kumar Singla, Jayakumar Subramanian, Changyou Chen, Rajiv Ratn Shah

Data Unlearning in Diffusion Models

Silas Alberti, Kenan Hasanaliyev, Manav Shah, Stefano Ermon

CryoGEN: Generative Energy-based Models for Cryogenic Electron Tomography Reconstruction

Yunfei Teng, Yuxuan Ren, Kai Chen, Xi Chen, Zhaoming Chen

Reasoning Elicitation in Language Models via Counterfactual Feedback

Alihan Hüyük, Xinnuo Xu, Jacqueline R. M. A. Maasch, Aditya V. Nori, Javier Gonzalez

Pareto Low-Rank Adapters: Efficient Multi-Task Learning with Preferences

Nikolaos Dimitriadis, Pascal Frossard, Francois Fleuret

A Theoretical Perspective: How to Prevent Model Collapse in Self-consuming Training Loops

Shi Fu, Yingjie Wang, Yuzhu Chen, Xinmei Tian, Dacheng Tao

Simple ReFlow: Improved Techniques for Fast Flow Models

Beomsu Kim, Yu-Guan Hsieh, Michal Klein, Marco Cuturi, Jong Chul Ye

CARTS: Advancing Neural Theorem Proving with Diversified Tactic Calibration and Bias-Resistant Tree Search

Xiao-wen Yang, Zhi Zhou, Haiming Wang, Aoxue Li, Wen-Da Wei

A Riemannian Framework for Learning Reduced-order Lagrangian Dynamics

Katharina Friedl, Noémie Jaquier, Jens Lundell, Tamim Asfour, Danica Kragic

CheapNet: Cross-attention on Hierarchical representations for Efficient protein-ligand binding Affinity Prediction

Hyukjun Lim, Sun Kim, Sangseon Lee

Divergence-enhanced Knowledge-guided Context Optimization for Visual-Language Prompt Tuning

Yilun Li, Miaomiao Cheng, Xu Han, Wei Song

Disentangled Representation Learning with the Gromov-Monge Gap

Théo Uscidda, Luca Eyring, Karsten Roth, Fabian J Theis, Zeynep Akata

Coreset Spectral Clustering

Ben Jourdan, Gregory Schwartzman, Peter Macgregor, He Sun

Multimodal Quantitative Language for Generative Recommendation

Jianyang Zhai, Zi-Feng Mai, Chang-Dong Wang, Feidiao Yang, Xiawu Zheng

Density estimation with LLMs: a geometric investigation of in-context learning trajectories

Toni J.b. Liu, Nicolas Boulle, Raphaël Sarfati, Christopher Earls

Weak-to-Strong Preference Optimization: Stealing Reward from Weak Aligned Model

Wenhong Zhu, Zhiwei He, Xiaofeng Wang, Pengfei Liu, Rui Wang

Neural Context Flows for Meta-Learning of Dynamical Systems

Roussel Desmond Nzoyem, David A.W. Barton, Tom Deakin

Does Safety Training of LLMs Generalize to Semantically Related Natural Prompts?

Sravanti Addepalli, Yerram Varun, Arun Suggala, Karthikeyan Shanmugam, Prateek Jain

Curriculum-aware Training for Discriminating Molecular Property Prediction Models

Hansi Yang, Quanming Yao, James Kwok

COFlowNet: Conservative Constraints on Flows Enable High-Quality Candidate Generation

Yudong Zhang, Xuan Yu, Xu Wang, Zhaoyang Sun, Chen Zhang

NL-Eye: Abductive NLI For Images

Mor Ventura, Michael Toker, Nitay Calderon, Zorik Gekhman, Yonatan Bitton

Multi-objective antibody design with constrained preference optimization

Milong Ren, ZaiKai He, Haicang Zhang

Mini-Monkey: Alleviating the Semantic Sawtooth Effect for Lightweight MLLMs via Complementary Image Pyramid

Mingxin Huang, Yuliang Liu, dingkang liang, LianWen Jin, Xiang Bai

Foundation Models Secretly Understand Neural Network Weights: Enhancing Hypernetwork Architectures with Foundation Models

Jeffrey Gu, Serena Yeung-Levy

Lambda-Skip Connections: the architectural component that prevents Rank Collapse

Federico Arangath Joseph, Jerome Sieber, Melanie Zeilinger, Carmen Amo Alonso

Provably Reliable Conformal Prediction Sets in the Presence of Data Poisoning

Yan Scholten, Stephan Günnemann

SEBRA : Debiasing through Self-Guided Bias Ranking

Adarsh Kappiyath, ABHRA CHAUDHURI, Ajay Kumar Jaiswal, Ziquan Liu, Yunpeng Li

On Bits and Bandits: Quantifying the Regret-Information Trade-off

Itai Shufaro, Nadav Merlis, Nir Weinberger, Shie Mannor

TRENDy: Temporal Regression of Effective Nonlinear Dynamics

Matt Ricci, Guy Pelc, Zoe Piran, Noa Moriel, Mor Nitzan

SafeWatch: An Efficient Safety-Policy Following Video Guardrail Model with Transparent Explanations

Zhaorun Chen, Francesco Pinto, Minzhou Pan, Bo Li

Facilitating Multi-turn Function Calling for LLMs via Compositional Instruction Tuning

Mingyang Chen, sunhaoze, Tianpeng Li, Fan Yang, Hao Liang

MIRACLE 3D: Memory-efficient Integrated Robust Approach for Continual Learning on 3D Point Clouds via Shape Model Construction

Hossein Resani, Behrooz Nasihatkon

Tailoring Mixup to Data for Calibration

Quentin Bouniot, Pavlo Mozharovskyi, Florence d'Alché-Buc

ADAM Optimization with Adaptive Batch Selection

Gyu Yeol Kim, Min-hwan Oh

Signature Kernel Conditional Independence Tests in Causal Discovery for Stochastic Processes

Georg Manten, Cecilia Casolo, Emilio Ferrucci, Søren Wengel Mogensen, Cristopher Salvi

Semantics-Adaptive Activation Intervention for LLMs via Dynamic Steering Vectors

Weixuan Wang, Jingyuan Yang, Wei Peng

InstantSplamp: Fast and Generalizable Stenography Framework for Generative Gaussian Splatting

Chenxin Li, Hengyu Liu, Zhiwen Fan, Wuyang Li, Yifan liu

Integrating Protein Dynamics into Structure-Based Drug Design via Full-Atom Stochastic Flows

Xiangxin Zhou, Yi Xiao, Haowei Lin, Xinheng He, Jiaqi Guan

Generative Flows on Synthetic Pathway for Drug Design

Seonghwan Seo, Minsu Kim, Tony Shen, Martin Ester, Jinkyoo Park

Efficient Interpolation between Extragradient and Proximal Methods for Weak MVIs

Thomas Pethick, Ioannis Mavrothalassitis, Volkan Cevher

Semi-Supervised Vision-Centric 3D Occupancy World Model for Autonomous Driving

Xiang Li, Pengfei Li, Yupeng Zheng, Wei Sun, Yan Wang

Size-Generalizable RNA Structure Evaluation by Exploring Hierarchical Geometries

Zongzhao Li, Jiacheng Cen, Wenbing Huang, Taifeng Wang, Le Song

Multi-Task Corrupted Prediction for Learning Robust Audio-Visual Speech Representation

Sungnyun Kim, Sungwoo Cho, Sangmin Bae, Kangwook Jang, Se-Young Yun

Energy-based Backdoor Defense Against Federated Graph Learning

Guancheng Wan, Zitong Shi, Wenke Huang, Guibin Zhang, Dacheng Tao