ICLR 2025

3,703 papers

JPEG Inspired Deep Learning

Ahmed H. Salamah, Kaixiang Zheng, Yiwen Liu, En-Hui Yang

CHASE-SQL: Multi-Path Reasoning and Preference Optimized Candidate Selection in Text-to-SQL

Mohammadreza Pourreza, Hailong Li, Ruoxi Sun, Yeounoh Chung, Shayan Talaei

Captured by Captions: On Memorization and its Mitigation in CLIP Models

Wenhao Wang, Adam Dziedzic, Grace C. Kim, Michael Backes, Franziska Boenisch

Sensitivity-Constrained Fourier Neural Operators for Forward and Inverse Problems in Parametric Differential Equations

Abdolmehdi Behroozi, Chaopeng Shen, Daniel Kifer

PaPaGei: Open Foundation Models for Optical Physiological Signals

Arvind Pillai, Dimitris Spathis, Fahim Kawsar, Mohammad Malekzadeh

One Model Transfer to All: On Robust Jailbreak Prompts Generation against LLMs

Linbao Li, Yannan Liu, Daojing He, Yu Li

E(3)-equivariant models cannot learn chirality: Field-based molecular generation

Alexandru Dumitrescu, Dani Korpela, Markus Heinonen, Yogesh Verma, Valerii Iakovlev

Unlocking State-Tracking in Linear RNNs Through Negative Eigenvalues

Riccardo Grazzi, Julien Siems, Arber Zela, Jörg K.H. Franke, Frank Hutter

As Simple as Fine-tuning: LLM Alignment via Bidirectional Negative Feedback Loss

Xin Mao, Huimin Xu, Feng-Lin Li, Ziqi Jin, Wang Chen

Linear Partial Gromov-Wasserstein Embedding

Yikun Bai, Abihith Kothapalli, Hengrong Du, Rocio Diaz Martin, Soheil Kolouri

Scalable Mechanistic Neural Networks

Jiale Chen, Dingling Yao, Adeel Pervez, Dan Alistarh, Francesco Locatello

Bridging Context Gaps: Leveraging Coreference Resolution for Long Contextual Understanding

Yanming Liu, Xinyue Peng, Jiannan Cao, Shi Bo, Yanxin Shen

Cross-Entropy Is All You Need To Invert the Data Generating Process

Patrik Reizinger, Alice Bizeul, Attila Juhos, Julia E Vogt, Randall Balestriero

General Scene Adaptation for Vision-and-Language Navigation

Haodong Hong, Yanyuan Qiao, Sen Wang, Jiajun Liu, Qi Wu

Language Models Need Inductive Biases to Count Inductively

Yingshan Chang, Yonatan Bisk

Everything, Everywhere, All at Once: Is Mechanistic Interpretability Identifiable?

Maxime Méloux, Silviu Maniu, François Portet, Maxime Peyrard

Promptriever: Instruction-Trained Retrievers Can Be Prompted Like Language Models

Orion Weller, Benjamin Van Durme, Dawn Lawrie, Ashwin Paranjape, Yuhao Zhang

Regret-Optimal List Replicable Bandit Learning: Matching Upper and Lower Bounds

Michael Chen, A. Pavan, N. V. Vinodchandran, Ruosong Wang, Lin Yang

Intrinsic Dimension Correlation: uncovering nonlinear connections in multimodal representations

Lorenzo Basile, Santiago Acevedo, Luca Bortolussi, Fabio Anselmi, Alex Rodriguez

Conformal Prediction Sets Can Cause Disparate Impact

Jesse C. Cresswell, Bhargava Kumar, Yi Sui, Mouloud Belbahri

Can Video LLMs Refuse to Answer? Alignment for Answerability in Video Large Language Models

Eunseop Yoon, Hee Suk Yoon, Mark A. Hasegawa-Johnson, Chang D. Yoo

The Foundations of Tokenization: Statistical and Computational Concerns

Juan Luis Gastaldi, John Terilla, Luca Malagutti, Brian DuSell, Tim Vieira

KaSA: Knowledge-Aware Singular-Value Adaptation of Large Language Models

Fan Wang, Juyong Jiang, Chansung Park, Sunghun Kim, Jing Tang

Towards Scalable Topological Regularizers

Wong Hiu Tung, Darrick Lee, Hong Yan

Physics-informed Temporal Difference Metric Learning for Robot Motion Planning

Ruiqi Ni, Zherong Pan, Ahmed H Qureshi

The OMG dataset: An Open MetaGenomic corpus for mixed-modality genomic language modeling

Andre Cornman, Jacob West-Roberts, Antonio Pedro Camargo, Simon Roux, Martin Beracochea

Associative memory and dead neurons

Vladimir Fanaskov, Ivan Oseledets

What should a neuron aim for? Designing local objective functions based on information theory

Andreas Christian Schneider, Valentin Neuhaus, David Alexander Ehrlich, Abdullah Makkeh, Alexander S Ecker

Universal generalization guarantees for Wasserstein distributionally robust models

Tam Le, Jérôme Malick

HASARD: A Benchmark for Vision-Based Safe Reinforcement Learning in Embodied Agents

Tristan Tomilin, Meng Fang, Mykola Pechenizkiy

Separation Power of Equivariant Neural Networks

Marco Pacini, Xiaowen Dong, Bruno Lepri, Gabriele Santin

Interpretable Causal Representation Learning for Biological Data in the Pathway Space

Jesus de la Fuente Cedeño, Robert Lehmann, Carlos Ruiz-Arenas, Jan Voges, Irene Marín-Goñi

Feature-Based Online Bilateral Trade

Solenne Gaucher, Martino Bernasconi, Matteo Castiglioni, Andrea Celli, Vianney Perchet

MathGAP: Out-of-Distribution Evaluation on Problems with Arbitrarily Complex Proofs

Andreas Opedal, Haruki Shirakami, Bernhard Schölkopf, Abulhair Saparov, Mrinmaya Sachan

HR-Extreme: A High-Resolution Dataset for Extreme Weather Forecasting

Nian Ran, Peng Xiao, Yue Wang, Wesley Shi, Jianxin Lin

Video In-context Learning: Autoregressive Transformers are Zero-Shot Video Imitators

Wentao Zhang, Junliang Guo, Tianyu He, Li Zhao, Linli Xu

Going Beyond Static: Understanding Shifts with Time-Series Attribution

Jiashuo Liu, Nabeel Seedat, Peng Cui, Mihaela van der Schaar

Gramian Multimodal Representation Learning and Alignment

Giordano Cicchetti, Eleonora Grassucci, Luigi Sigillo, Danilo Comminiello

ILLUSION: Unveiling Truth with a Comprehensive Multi-Modal, Multi-Lingual Deepfake Dataset

Kartik Thakral, Rishabh Ranjan, Akanksha Singh, Akshat Jain, Mayank Vatsa

An Exploration with Entropy Constrained 3D Gaussians for 2D Video Compression

Xiang Liu, Bin Chen, Zimo Liu, Yaowei Wang, Shu-Tao Xia

S4M: S4 for multivariate time series forecasting with Missing values

Peng Jing, Meiqi Yang, Qiong Zhang, Xiaoxiao Li

Flow: Modularized Agentic Workflow Automation

Boye Niu, Yiliao Song, Kai Lian, Yifan Shen, Yu Yao

Instant Policy: In-Context Imitation Learning via Graph Diffusion

Vitalis Vosylius, Edward Johns

Mitigating Parameter Interference in Model Merging via Sharpness-Aware Fine-Tuning

Yeoreum Lee, Jinwook Jung, Sungyong Baik

Unveiling the Magic of Code Reasoning through Hypothesis Decomposition and Amendment

Yuze Zhao, Tianyun Ji, Wenjun Feng, Zhenya Huang, Qi Liu

Second Order Bounds for Contextual Bandits with Function Approximation

Aldo Pacchiano

Fictitious Synthetic Data Can Improve LLM Factuality via Prerequisite Learning

Yujian Liu, Shiyu Chang, Tommi Jaakkola, Yang Zhang

Provence: efficient and robust context pruning for retrieval-augmented generation

Nadezhda Chirkova, Thibault Formal, Vassilina Nikoulina, Stéphane Clinchant

Test-time Adaptation for Cross-modal Retrieval with Query Shift

Haobin Li, Peng Hu, Qianjun Zhang, Xi Peng, XitingLiu

Action abstractions for amortized sampling

Oussama Boussif, Lena Nehale Ezzine, Joseph D Viviano, Michał Koziarski, Moksh Jain

Injecting Universal Jailbreak Backdoors into LLMs in Minutes

Zhuowei Chen, Qiannan Zhang, Shichao Pei

OptionZero: Planning with Learned Options

Po-Wei Huang, Pei-Chiun Peng, Hung Guei, Ti-Rong Wu

Accelerating neural network training: An analysis of the AlgoPerf competition

Priya Kasimbeg, Frank Schneider, Runa Eschenhagen, Juhan Bae, Chandramouli Shama Sastry

CirT: Global Subseasonal-to-Seasonal Forecasting with Geometry-inspired Transformer

Yang Liu, Zinan Zheng, Jiashun Cheng, Fugee Tsung, Deli Zhao

MGCFNN: A Neural MultiGrid Solver with Novel Fourier Neural Network for High Wave Number Helmholtz Equations

Yan Xie, Minrui Lv, Chen-Song Zhang

ReCogLab: a framework testing relational reasoning & cognitive hypotheses on LLMs

Andrew Liu, Henry Prior, Gargi Balasubramaniam, Rivka Moroshko, Amir Zait

CViT: Continuous Vision Transformer for Operator Learning

Sifan Wang, Jacob H Seidman, Shyam Sankaran, Hanwen Wang, George J. Pappas

Combining Induction and Transduction for Abstract Reasoning

Wen-Ding Li, Keya Hu, Carter Larsen, Yuqing Wu, Simon Alford

Safety Representations for Safer Policy Learning

Kaustubh Mani, Vincent Mai, Charlie Gauthier, Annie S Chen, Samer B. Nashed

AndroidWorld: A Dynamic Benchmarking Environment for Autonomous Agents

Christopher Rawles, Sarah Clinckemaillie, Yifan Chang, Jonathan Waltz, Gabrielle Lau

How Learnable Grids Recover Fine Detail in Low Dimensions: A Neural Tangent Kernel Analysis of Multigrid Parametric Encodings

Samuel Audia, Soheil Feizi, Matthias Zwicker, Dinesh Manocha

AutoG: Towards automatic graph construction from tabular data

Zhikai Chen, Han Xie, Jian Zhang, Xiang Song, Jiliang Tang

Decoupling Angles and Strength in Low-rank Adaptation

Massimo Bini, Leander Girrbach, Zeynep Akata

Retri3D: 3D Neural Graphics Representation Retrieval

Yushi Guan, Daniel Kwan, Jean Sebastien Dandurand, Xi Yan, Ruofan Liang

Interaction Asymmetry: A General Principle for Learning Composable Abstractions

Jack Brady, Julius von Kügelgen, Sébastien Lachapelle, Simon Buchholz, Thomas Kipf

dEBORA: Efficient Bilevel Optimization-based low-Rank Adaptation

Emanuele Zangrando, Sara Venturini, Francesco Rinaldi, Francesco Tudisco

Deconstructing What Makes a Good Optimizer for Autoregressive Language Models

Rosie Zhao, Depen Morwani, David Brandfonbrener, Nikhil Vyas, Sham M. Kakade

Brain-inspired L_p-Convolution benefits large kernels and aligns better with visual cortex

Jea Kwon, Sungjun Lim, Kyungwoo Song, C. Justin Lee

Pangea: A Fully Open Multilingual Multimodal LLM for 39 Languages

Xiang Yue, Yueqi Song, Akari Asai, Seungone Kim, Jean de Dieu Nyandwi

Can LLMs Really Learn to Translate a Low-Resource Language from One Grammar Book?

Seth Aycock, David Stap, Di Wu, Christof Monz, Khalil Sima'an

Exponential Topology-enabled Scalable Communication in Multi-agent Reinforcement Learning

Xinran Li, Xiaolu Wang, Chenjia Bai, Jun Zhang

Aligning Visual Contrastive learning models via Preference Optimization

Amirabbas Afzali, Borna khodabandeh, Ali Rasekh, Mahyar JafariNodeh, Sepehr Kazemi Ranjbar

MANTRA: The Manifold Triangulations Assemblage

Rubén Ballester, Ernst Röell, Daniel Bin Schmid, Mathieu Alain, Sergio Escalera

EqNIO: Subequivariant Neural Inertial Odometry

Royina Karegoudra Jayanth, Yinshuang Xu, Ziyun Wang, Evangelos Chatzipantazis, Kostas Daniilidis

Weighted Point Set Embedding for Multimodal Contrastive Learning Toward Optimal Similarity Metric

Toshimitsu Uesaka, Taiji Suzuki, Yuhta Takida, Chieh-Hsin Lai, Naoki Murata

Scaling Instruction-tuned LLMs to Million-token Contexts via Hierarchical Synthetic Data Generation

Linda He, Jue Wang, Maurice Weber, Shang Zhu, Ben Athiwaratkun

LoRA3D: Low-Rank Self-Calibration of 3D Geometric Foundation models

Ziqi Lu, Heng Yang, Danfei Xu, Boyi Li, Boris Ivanovic

Small-to-Large Generalization: Training Data Influences Models Consistently Across Scale

Alaa Khaddaj, Logan Engstrom, Aleksander Madry

Large Language Models Assume People are More Rational than We Really are

Ryan Liu, Jiayi Geng, Joshua Peterson, Ilia Sucholutsky, Thomas L. Griffiths

Can Transformers Do Enumerative Geometry?

Baran Hashemi, Roderic Guigo Corominas, Alessandro Giacchetto

Robustness Auditing for Linear Regression: To Singularity and Beyond

Ittai Rubinstein, Samuel B. Hopkins

MamKO: Mamba-based Koopman operator for modeling and predictive control

Zhaoyang Li, Minghao Han, Xunyuan Yin

Local Steps Speed Up Local GD for Heterogeneous Distributed Logistic Regression

Michael Crawshaw, Blake Woodworth, Mingrui Liu

Selective Unlearning via Representation Erasure Using Domain Adversarial Training

Nazanin Mohammadi Sepahvand, Eleni Triantafillou, Hugo Larochelle, Doina Precup, James J. Clark

LLMs Know More Than They Show: On the Intrinsic Representation of LLM Hallucinations

Hadas Orgad, Michael Toker, Zorik Gekhman, Roi Reichart, Idan Szpektor

Scaling up Masked Diffusion Models on Text

Shen Nie, Fengqi Zhu, Chao Du, Tianyu Pang, Qian Liu

Union-over-Intersections: Object Detection beyond Winner-Takes-All

Aritra Bhowmik, Pascal Mettes, Martin R. Oswald, Cees G. M. Snoek

AdvWave: Stealthy Adversarial Jailbreak Attack against Large Audio-Language Models

Mintong Kang, Chejian Xu, Bo Li

Efficient Multi-agent Offline Coordination via Diffusion-based Trajectory Stitching

Lei Yuan, Yuqi Bian, Lihe Li, Ziqian Zhang, Cong Guan

Mixture of Parrots: Experts improve memorization more than reasoning

Samy Jelassi, Clara Mohri, David Brandfonbrener, Alex Gu, Nikhil Vyas

Differentially Private Steering for Large Language Model Alignment

Anmol Goel, Yaxi Hu, Iryna Gurevych, Amartya Sanyal

Learning Geometric Reasoning Networks For Robot Task And Motion Planning

Smail Ait Bouhsain, Rachid Alami, Thierry Simeon

Scaling Transformers for Low-Bitrate High-Quality Speech Coding

Julian D Parker, Anton Smirnov, Jordi Pons, CJ Carr, Zack Zukowski

Kinetix: Investigating the Training of General Agents through Open-Ended Physics-Based Control Tasks

Michael Matthews, Michael Beukman, Chris Lu, Jakob Nicolaus Foerster

Complexity Lower Bounds of Adaptive Gradient Algorithms for Non-convex Stochastic Optimization under Relaxed Smoothness

Michael Crawshaw, Mingrui Liu

Better Instruction-Following Through Minimum Bayes Risk

Ian Wu, Patrick Fernandes, Amanda Bertsch, Seungone Kim, Sina Khoshfetrat Pakazad

Think while You Generate: Discrete Diffusion with Planned Denoising

Sulin Liu, Juno Nam, Andrew Campbell, Hannes Stärk, Yilun Xu

Offline RL in Regular Decision Processes: Sample Efficiency via Language Metrics

Ahana Deb, Roberto Cipollone, Anders Jonsson, Alessandro Ronca, Mohammad Sadegh Talebi

CONDA: Adaptive Concept Bottleneck for Foundation Models Under Distribution Shifts

Jihye Choi, Jayaram Raghuram, Yixuan Li, Somesh Jha

GraphRouter: A Graph-based Router for LLM Selections

Tao Feng, Yanzhen Shen, Jiaxuan You