ICML 2025

3,330 papers

Position: AI Evaluation Should Learn from How We Test Humans

Yan Zhuang, Qi Liu, Zachary Pardos, Patrick C. Kyllonen, Jiyun Zu

Position: Language model developers should report train-test overlap

Andy K Zhang, Kevin Klyman, Yifan Mai, Yoav Levine, Yian Zhang

Position: Trustworthy AI Agents Require the Integration of Large Language Models and Formal Methods

Yedi Zhang, Yufan Cai, Xinyue Zuo, Xiaokun Luan, Kailong Wang

Position: Editing Large Language Models Poses Serious Safety Risks

Paul Youssef, Zhixue Zhao, Daniel Braun, Jörg Schlötterer, Christin Seifert

Position: Challenges and Future Directions of Data-Centric AI Alignment

Min-Hsuan Yeh, Jeffrey Wang, Xuefeng Du, Seongheon Park, Leitian Tao

Position: The Artificial Intelligence and Machine Learning Community Should Adopt a More Transparent and Regulated Peer Review Process

Jing Yang

Position: Formal Mathematical Reasoning—A New Frontier in AI

Kaiyu Yang, Gabriel Poesia, Jingxuan He, Wenda Li, Kristin E. Lauter

Position: LLMs Need a Bayesian Meta-Reasoning Framework for More Robust and Generalizable Reasoning

Hanqi Yan, Linhai Zhang, Jiazheng Li, Zhenyi Shen, Yulan He

Position: Retrieval-augmented systems can be dangerous medical communicators

Lionel Wong, Ayman Ali, Raymond M Xiong, Zejiang Shen, Yoon Kim

Position: Deep Learning is Not So Mysterious or Different

Andrew Gordon Wilson

Position: Human Baselines in Model Evaluations Need Rigor and Transparency (With Recommendations & Reporting Checklist)

Kevin Wei, Patricia Paskov, Sunishchal Dev, Michael J Byun, Anka Reuel

Position: AI Scaling: From Up to Down and Out

Yunke Wang, Yanxi Li, Chang Xu

Position: Evaluating Generative AI Systems Is a Social Science Measurement Challenge

Hanna Wallach, Meera Desai, A. Feder Cooper, Angelina Wang, Chad Atalla

Position: AI Agents Need Authenticated Delegation

Tobin South, Samuele Marro, Thomas Hardjono, Robert Mahari, Cedric Deslandes Whitney

Position: Contextual Integrity is Inadequately Applied to Language Models

Yan Shvartzshnaider, Vasisht Duddu

Position: Societal Impacts Research Requires Benchmarks for Creative Composition Tasks

Judy Hanwen Shen

Position: AI Competitions Provide the Gold Standard for Empirical Rigor in GenAI Evaluation

D. Sculley, William Cukierski, Phil Culliton, Sohier Dane, Maggie M Demkin

Position: When Incentives Backfire, Data Stops Being Human

Sebastin Santy, Prasanta Bhattacharya, Manoel Horta Ribeiro, Kelsey R Allen, Sewoong Oh

Position: Graph Matching Systems Deserve Better Benchmarks

Indradyumna Roy, Saswat Meher, Eeshaan Jain, Soumen Chakrabarti, Abir De

Position: Theory of Mind Benchmarks are Broken for Large Language Models

Matthew Riemer, Zahra Ashktorab, Djallel Bouneffouf, Payel Das, Miao Liu

Position: An Empirically Grounded Identifiability Theory Will Accelerate Self Supervised Learning Research

Patrik Reizinger, Randall Balestriero, David Klindt, Wieland Brendel

Position: AI’s growing due process problem

Sunayana Rane

Position: Principles of Animal Cognition to Improve LLM Evaluations

Sunayana Rane, Cyrus F. Kirkman, Graham Todd, Amanda Royka, Ryan M.C. Law

Position: All Current Generative Fidelity and Diversity Metrics are Flawed

Ossi Räisä, Boris van Breugel, Mihaela van der Schaar

Position: Causal Machine Learning Requires Rigorous Synthetic Experiments for Broader Adoption

Audrey Poinsot, Panayiotis Panayiotou, Alessandro Leite, Nicolas Chesneau, Ozgur Simsek

Position: Explainable AI Cannot Advance Without Better User Studies

Matej Pičulin, Bernarda Petek, Irena Ograjenšek, Erik Strumbelj

Position: Iterative Online-Offline Joint Optimization is Needed to Manage Complex LLM Copyright Risks

Yanzhou Pan, Jiayi Chen, Jiamin Chen, Zhaozhuo Xu, Denghui Zhang

Position: Democratic AI is Possible. The Democracy Levels Framework Shows How It Might Work.

Aviv Ovadya, Kyle Redman, Luke Thorburn, Quan Ze Chen, Oliver Smith

Position: Solve Layerwise Linear Models First to Understand Neural Dynamical Phenomena (Neural Collapse, Emergence, Lazy/Rich Regime, and Grokking)

Yoonsoo Nam, Seok Hyeong Lee, Clémentine Carla Juliette Dominé, Yeachan Park, Charles London

Position: The Right to AI

Rashid Mushkani, Hugo Berard, Allison Cohen, Shin Koseki

Position: The Future of Bayesian Prediction Is Prior-Fitted

Samuel Müller, Arik Reuter, Noah Hollmann, David Rügamer, Frank Hutter

Position: Rethinking LLM Bias Probing Using Lessons from the Social Sciences

Kirsten Morehouse, Siddharth Swaroop, Weiwei Pan

Position: Probabilistic Modelling is Sufficient for Causal Inference

Bruno Kacper Mlodozeniec, David Krueger, Richard E Turner

Position: Scaling LLM Agents Requires Asymptotic Analysis with LLM Primitives

Elliot Meyerson, Xin Qiu

Position: Lifetime tuning is incompatible with continual reinforcement learning

Golnaz Mesbahi, Parham Mohammad Panahi, Olya Mastikhina, Steven Tang, Martha White

Position: Machine Learning Models Have a Supply Chain Problem

Sarah Meiklejohn, Hayden Blauzvern, Mihai Maruseac, Spencer Schrock, Laurent Simon

Position: Algebra Unveils Deep Learning - An Invitation to Neuroalgebraic Geometry

Giovanni Luca Marchetti, Vahid Shahverdi, Stefano Mereta, Matthew Trager, Kathlén Kohn

Position: In-House Evaluation Is Not Enough. Towards Robust Third-Party Evaluation and Flaw Disclosure for General-Purpose AI

Shayne Longpre, Kevin Klyman, Ruth Elisabeth Appel, Sayash Kapoor, Rishi Bommasani

Position: Truly Self-Improving Agents Require Intrinsic Metacognitive Learning

Tennison Liu, Mihaela van der Schaar

Position: Supervised Classifiers Answer the Wrong Questions for OOD Detection

Yucen Lily Li, Daohan Lu, Polina Kirichenko, Shikai Qiu, Tim G. J. Rudner

Position: Humanity Faces Existential Risk from Gradual Disempowerment

Jan Kulveit, Raymond Douglas, Nora Ammann, Deger Turan, David Krueger

Position: Uncertainty Quantification Needs Reassessment for Large Language Model Agents

Michael Kirchhof, Gjergji Kasneci, Enkelejda Kasneci

Position: You Can’t Manufacture a NeRF

Ma Kimmel, Mueed Ur Rehman, Yonatan Bisk, Gary K. Fedder

Position: The AI Conference Peer Review Crisis Demands Author Feedback and Reviewer Rewards

Jaeho Kim, Yunseok Lee, Seulki Lee

Position: Build Agent Advocates, Not Platform Agents

Sayash Kapoor, Noam Kolt, Seth Lazar

Position: The Most Expensive Part of an LLM *should* be its Training Data

Nikhil Kandpal, Colin Raffel

Position: AI Safety Must Embrace an Antifragile Perspective

Ming Jin, Hyunin Lee

Position: Not All Explanations for Deep Learning Phenomena Are Equally Valuable

Alan Jeffares, Mihaela van der Schaar

Position: We Can’t Understand AI Using our Existing Vocabulary

John Hewitt, Robert Geirhos, Been Kim

Position: AI Safety should prioritize the Future of Work

Sanchaita Hazra, Bodhisattwa Prasad Majumder, Tuhin Chakrabarty

Position: AI Should Not Be An Imitation Game: Centaur Evaluations

Andreas Haupt, Erik Brynjolfsson

Position: We Need Responsible, Application-Driven (RAD) AI Research

Sarah Hartman, Cheng Soon Ong, Julia Powles, Petra Kuhnert

Position: General Intelligence Requires Reward-based Pretraining

Seungwook Han, Jyothish Pari, Samuel J. Gershman, Pulkit Agrawal

Position: Spectral GNNs Rely Less on Graph Fourier Basis than Conceived

Yuhe Guo, Huayi Tang, Jiahong Ma, Hongteng Xu, Zhewei Wei

Position: Future Research and Challenges Remain Towards AI for Software Engineering

Alex Gu, Naman Jain, Wen-Ding Li, Manish Shetty, Kevin Ellis

Position: It Is Time We Test Neural Computation In Vitro

Frithjof Gressmann, Ashley Chen, Lily Hexuan Xie, Nancy Amato, Lawrence Rauchwerger

Position: Enough of Scaling LLMs! Lets Focus on Downscaling

Yash Goel, Ayan Sengupta, Tanmoy Chakraborty

Position: Political Neutrality in AI Is Impossible — But Here Is How to Approximate It

Jillian Fisher, Ruth Elisabeth Appel, Chan Young Park, Yujin Potter, Liwei Jiang

Position: We Need An Algorithmic Understanding of Generative AI

Oliver Eberle, Thomas Austin Mcgee, Hamza Giaffar, Taylor Whittington Webb, Ida Momennejad

Position: Current Model Licensing Practices are Dragging Us into a Quagmire of Legal Noncompliance

Moming Duan, Mingzhe Du, Rui Zhao, Mengying Wang, Yinghui Wu

Position: Constants are Critical in Regret Bounds for Reinforcement Learning

Simone Drago, Marco Mussi, Alberto Maria Metelli

Position: The Categorization of Race in ML is a Flawed Premise

Miriam Doh, Benedikt Höltgen, Piera Riccio, Nuria M Oliver

Position: A Theory of Deep Learning Must Include Compositional Sparsity

David A. Danhofer, Davide D’Ascenzo, Rafael Dubach, Tomaso A Poggio

Position: Certified Robustness Does Not (Yet) Imply Model Security

Andrew Craig Cullen, Paul Montague, Sarah Monazam Erfani, Benjamin I. P. Rubinstein

Position: Don’t Use the CLT in LLM Evals With Fewer Than a Few Hundred Datapoints

Sam Bowyer, Laurence Aitchison, Desi R. Ivanova

Position: Rethinking Explainable Machine Learning as Applied Statistics

Sebastian Bordt, Eric Raidl, Ulrike Von Luxburg

Position: Strong Consumer Protection is an Inalienable Defense for AI Safety in the United States

Serena Booth

Position: Stop treating ‘AGI’ as the north-star goal of AI research

Borhane Blili-Hamelin, Christopher Graziul, Leif Hancox-Li, Hananel Hazan, El-Mahdi El-Mhamdi

Position: Graph Learning Will Lose Relevance Due To Poor Benchmarks

Maya Bechler-Speicher, Ben Finkelshtein, Fabrizio Frasca, Luis Müller, Jan Tönshoff

Position: Beyond Assistance – Reimagining LLMs as Ethical and Adaptive Co-Creators in Mental Health Care

Abeer Badawi, Md Tahmid Rahman Laskar, Jimmy Huang, Shaina Raza, Elham Dolatabadi

Position: Generative AI Regulation Can Learn from Social Media Regulation

Ruth Elisabeth Appel

Position: LLM Social Simulations Are a Promising Research Method

Jacy Reese Anthis, Ryan Liu, Sean M Richardson, Austin C. Kozlowski, Bernard Koch

Position: Medical Large Language Model Benchmarks Should Prioritize Construct Validity

Ahmed Alaa, Thomas Hartvigsen, Niloufar Golchini, Shiladitya Dutta, Frances Dean

MedXpertQA: Benchmarking Expert-Level Medical Reasoning and Understanding

Yuxin Zuo, Shang Qu, Yifei Li, Zhang-Ren Chen, Xuekai Zhu

Beyond Communication Overhead: A Multilevel Monte Carlo Approach for Mitigating Compression Bias in Distributed Learning

Ze’Ev Zukerman, Bassel Hamoud, Kfir Yehuda Levy

Random Feature Representation Boosting

Nikita Zozoulenko, Thomas Cass, Lukas Gonon

Look Twice Before You Answer: Memory-Space Visual Retracing for Hallucination Mitigation in Multimodal Large Language Models

Xin Zou, Yizhou Wang, Yibo Yan, Yuanhuiyi Lyu, Kening Zheng

Contrastive Private Data Synthesis via Weighted Multi-PLM Fusion

Tianyuan Zou, Yang Liu, Peng Li, Yufei Xiong, Jianqing Zhang

HPS: Hard Preference Sampling for Human Preference Alignment

Xiandong Zou, Wanyu Lin, Yuchen Li, Pan Zhou

SpikeVideoFormer: An Efficient Spike-Driven Video Transformer with Hamming Attention and O(T) Complexity

Shihao Zou, Qingfeng Li, Wei Ji, Jingjing Li, Yongkui Yang

Analytical Lyapunov Function Discovery: An RL-based Generative Approach

Haohan Zou, Jie Feng, Hao Zhao, Yuanyuan Shi

EasyRef: Omni-Generalized Group Image Reference for Diffusion Models via Multimodal LLM

Zhuofan Zong, Dongzhi Jiang, Bingqi Ma, Guanglu Song, Hao Shao

Novelty Detection in Reinforcement Learning with World Models

Geigh Zollicoffer, Kenneth Eaton, Jonathan C Balloch, Julia Kim, Wei Zhou

FRUGAL: Memory-Efficient Optimization by Reducing State Overhead for Scalable Training

Philip Zmushko, Aleksandr Beznosikov, Martin Takac, Samuel Horváth

Decoupled SGDA for Games with Intermittent Strategy Communication

Ali Zindari, Parham Yazdkhasti, Anton Rodomanov, Tatjana Chavdarova, Sebastian U Stich

PieClam: A Universal Graph Autoencoder Based on Overlapping Inclusive and Exclusive Communities

Daniel Zilberg, Ron Levie

Commute Graph Neural Networks

Wei Zhuo, Han Yu, Guang Tan, Xiaoxiao Li

Agent-as-a-Judge: Evaluate Agents with Agents

Mingchen Zhuge, Changsheng Zhao, Dylan R. Ashley, Wenyi Wang, Dmitrii Khizbullin

Stealix: Model Stealing via Prompt Evolution

Zhixiong Zhuang, Hui-Po Wang, Maria-Irina Nicolae, Mario Fritz

Come Together, But Not Right Now: A Progressive Strategy to Boost Low-Rank Adaptation

Zhan Zhuang, Xiequn Wang, Wei Li, Yulong Zhang, Qiushi Huang

Mask-Enhanced Autoregressive Prediction: Pay Less Attention to Learn More

Xialie Zhuang, Zhikai Jia, Jianjin Li, Zhenyu Zhang, Li Shen

TimeStep Master: Asymmetrical Mixture of Timestep LoRA Experts for Versatile and Efficient Diffusion Models in Vision

Shaobin Zhuang, Yiwei Guo, Yanbo Ding, Kunchang Li, Xinyuan Chen

CSV-Occ: Fusing Multi-frame Alignment for Occupancy Prediction with Temporal Cross State Space Model and Central Voting Mechanism

Ziming Zhu, Yu Zhu, Jiahao Chen, Xiaofeng Ling, Huanlei Chen

AlphaQCM: Alpha Discovery in Finance with Distributional Reinforcement Learning

Zhoufan Zhu, Ke Zhu

SUICA: Learning Super-high Dimensional Sparse Implicit Neural Representations for Spatial Transcriptomics

Qingtian Zhu, Yumin Zheng, Yuling Sang, Yifan Zhan, Ziyan Zhu

Soft Reasoning: Navigating Solution Spaces in Large Language Models through Controlled Embedding Exploration

Qinglin Zhu, Runcong Zhao, Hanqi Yan, Yulan He, Yudong Chen

Best Subset Selection: Optimal Pursuit for Feature Selection and Elimination

Zhihan Zhu, Yanhao Zhang, Yong Xia

Measuring Diversity in Synthetic Datasets

Yuchang Zhu, Huizhe Zhang, Bingzhe Wu, Jintang Li, Zibin Zheng

An Optimistic Algorithm for online CMDPS with Anytime Adversarial Constraints

Jiahui Zhu, Kihyun Yu, Dabeen Lee, Xin Liu, Honghao Wei

Efficient LiDAR Reflectance Compression via Scanning Serialization

Jiahao Zhu, Kang You, Dandan Ding, Zhan Ma