ICML

2022–2026 LIVE

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Machine Learning

2025 · 3,330 papers

このEditionに反映済みのmain full research papersのみ掲載しています。著者リンクは日本の大学への著者別所属根拠がある場合に限ります。

2025 · ICML
PhantomWiki: On-Demand Datasets for Reasoning and Retrieval Evaluation
Albert Gong, Kamilė Stankevičiūtė, Chao Wan, Anmol Kabra, Raphael Thesmar, Johann Lee, Julius Klenke, Carla P Gomes, Kilian Q Weinberger
Machine Learning
日本大学: 関与なし（対象大学）
2025 · ICML
Phase and Amplitude-aware Prompting for Enhancing Adversarial Robustness
Yibo Xu, Dawei Zhou, Decheng Liu, Nannan Wang
Machine Learning
日本大学: 関与なし（対象大学）
2025 · ICML
Phase transitions for the existence of unregularized M-estimators in single index models
Takuya Koriyama, Pierre C Bellec
Machine Learning
日本大学: 関与なし（対象大学）
2025 · ICML
Physics Aware Neural Networks for Unsupervised Binding Energy Prediction
Ke Liu, Hao Chen, Chunhua Shen
Machine Learning
日本大学: 関与なし（対象大学）
2025 · ICML
Physics-Informed DeepONets for drift-diffusion on metric graphs: simulation and parameter identification
Jan Blechschmidt, Tom-Christian Riemer, Max Winkler, Martin Stoll, Jan-Frederik Pietschmann
Machine Learning
日本大学: 関与なし（対象大学）
2025 · ICML
Physics-Informed Generative Modeling of Wireless Channels
Benedikt Böck, Andreas Oeldemann, Timo Mayer, Francesco Rossetto, Wolfgang Utschick
Machine Learning
日本大学: 関与なし（対象大学）
2025 · ICML
Physics-Informed Weakly Supervised Learning For Interatomic Potentials
Makoto Takamoto, Viktor Zaverkin, Mathias Niepert
Machine Learning
日本大学: 関与なし（対象大学）
2025 · ICML
Physics-informed Temporal Alignment for Auto-regressive PDE Foundation Models
Congcong Zhu, Xiaoyan Xu, Jiayue Han, Jingrun Chen
Machine Learning
日本大学: 関与なし（対象大学）
2025 · ICML
PiD: Generalized AI-Generated Images Detection with Pixelwise Decomposition Residuals
Xinghe Fu, Zhiyuan Yan, Zheng Yang, Taiping Yao, Yandan Zhao, Shouhong Ding, Xi Li
Machine Learning
日本大学: 関与なし（対象大学）
2025 · ICML
PieClam: A Universal Graph Autoencoder Based on Overlapping Inclusive and Exclusive Communities
Daniel Zilberg, Ron Levie
Machine Learning
日本大学: 関与なし（対象大学）
2025 · ICML
Piloting Structure-Based Drug Design via Modality-Specific Optimal Schedule
Keyue Qiu, Yuxuan Song, Zhehuan Fan, Peidong Liu, Zhe Zhang, Mingyue Zheng, Hao Zhou, Wei-Ying Ma
Machine Learning
日本大学: 関与なし（対象大学）
2025 · ICML
PipeOffload: Improving Scalability of Pipeline Parallelism with Memory Optimization
Xinyi Wan, Penghui Qi, Guangxing Huang, Min Lin, Jialin Li
Machine Learning
日本大学: 関与なし（対象大学）
2025 · ICML
Pivoting Factorization: A Compact Meta Low-Rank Representation of Sparsity for Efficient Inference in Large Language Models
Jialin Zhao, Yingtao Zhang, Carlo Vittorio Cannistraci
Machine Learning
日本大学: 関与なし（対象大学）
2025 · ICML
Pixel-level Certified Explanations via Randomized Smoothing
Alaa Anani, Tobias Lorenz, Mario Fritz, Bernt Schiele
Machine Learning
日本大学: 関与なし（対象大学）
2025 · ICML
Pixel2Feature Attack (P2FA): Rethinking the Perturbed Space to Enhance Adversarial Transferability
Renpu Liu, Hao Wu, Jiawei Zhang, Xin Cheng, Xiangyang Luo, Bin Ma, Jinwei Wang
Machine Learning
日本大学: 関与なし（対象大学）
2025 · ICML
Plan-and-Act: Improving Planning of Agents for Long-Horizon Tasks
Lutfi Eren Erdogan, Nicholas Lee, Sehoon Kim, Suhong Moon, Hiroki Furuta, Gopala Anumanchipalli, Kurt Keutzer, Amir Gholami
Machine Learning
日本大学: 関与なし（対象大学）
2025 · ICML
Plausible Token Amplification for Improving Accuracy of Differentially Private In-Context Learning Based on Implicit Bayesian Inference
Yusuke Yamasaki, Kenta Niwa, Daiki Chijiwa, Takumi Fukami, Takayuki Miura
Machine Learning
日本大学: 関与なし（対象大学）
2025 · ICML
PlaySlot: Learning Inverse Latent Dynamics for Controllable Object-Centric Video Prediction and Planning
Angel Villar-Corrales, Sven Behnke
Machine Learning
日本大学: 関与なし（対象大学）
2025 · ICML
Playmate: Flexible Control of Portrait Animation via 3D-Implicit Space Guided Diffusion
Xingpei Ma, Jiaran Cai, Yuansheng Guan, Shenneng Huang, Qiang Zhang, Shunsi Zhang
Machine Learning
日本大学: 関与なし（対象大学）
2025 · ICML
Point Cloud Dataset Distillation
Deyu Bo, Xinchao Wang
Machine Learning
日本大学: 関与なし（対象大学）
2025 · ICML
Point-Level Topological Representation Learning on Point Clouds
Vincent Peter Grande, Michael T Schaub
Machine Learning
日本大学: 関与なし（対象大学）
2025 · ICML
Pointwise Information Measures as Confidence Estimators in Deep Neural Networks: A Comparative Study
Shelvia Wongso, Rohan Ghosh, Mehul Motani
Machine Learning
日本大学: 関与なし（対象大学）
2025 · ICML
PoisonBench: Assessing Language Model Vulnerability to Poisoned Preference Data
Tingchen Fu, Mrinank Sharma, Philip Torr, Shay B Cohen, David Krueger, Fazl Barez
Machine Learning
日本大学: 関与なし（対象大学）
2025 · ICML
PoisonedEye: Knowledge Poisoning Attack on Retrieval-Augmented Generation based Large Vision-Language Models
Chenyang Zhang, Xiaoyu Zhang, Jian Lou, Kai Wu, Zilong Wang, Xiaofeng Chen
Machine Learning
日本大学: 関与なし（対象大学）
2025 · ICML
PokéChamp: an Expert-level Minimax Language Agent
Seth Karten, Andy Luu Nguyen, Chi Jin
Machine Learning
日本大学: 関与なし（対象大学）
2025 · ICML
Policy Design for Two-sided Platforms with Participation Dynamics
Haruka Kiyohara, Fan Yao, Sarah Dean
Machine Learning
日本大学: 関与なし（対象大学）
2025 · ICML
Policy Filtration for RLHF to Mitigate Noise in Reward Models
Chuheng Zhang, Wei Shen, Li Zhao, Xuyun Zhang, Xiaolong Xu, Wanchun Dou, Jiang Bian
Machine Learning
日本大学: 関与なし（対象大学）
2025 · ICML
Policy Gradient with Tree Expansion
Gal Dalal, Assaf Hallak, Gugan Thoppe, Shie Mannor, Gal Chechik
Machine Learning
日本大学: 関与なし（対象大学）
2025 · ICML
Policy Guided Tree Search for Enhanced LLM Reasoning
Yang Li
Machine Learning
日本大学: 関与なし（対象大学）
2025 · ICML
Policy Optimization for CMDPs with Bandit Feedback: Learning Stochastic and Adversarial Constraints
Francesco Emanuele Stradi, Anna Lunghi, Matteo Castiglioni, Alberto Marchesi, Nicola Gatti
Machine Learning
日本大学: 関与なし（対象大学）
2025 · ICML
Policy Regularization on Globally Accessible States in Cross-Dynamics Reinforcement Learning
Zhenghai Xue, Lang Feng, Jiacheng Xu, Kang Kang, Xiang Wen, Bo An, Shuicheng Yan
Machine Learning
日本大学: 関与なし（対象大学）
2025 · ICML
Policy-Regret Minimization in Markov Games with Function Approximation
Thanh Nguyen-Tang, Raman Arora
Machine Learning
日本大学: 関与なし（対象大学）
2025 · ICML
Policy-labeled Preference Learning: Is Preference Enough for RLHF?
Taehyun Cho, Seokhun Ju, Seungyub Han, Dohyeong Kim, Kyungjae Lee, Jungwoo Lee
Machine Learning
日本大学: 関与なし（対象大学）
2025 · ICML
Poly2Vec: Polymorphic Fourier-Based Encoding of Geospatial Objects for GeoAI Applications
Maria Despoina Siampou, Jialiang Li, John Krumm, Cyrus Shahabi, Hua Lu
Machine Learning
日本大学: 関与なし（対象大学）
2025 · ICML
PolyConf: Unlocking Polymer Conformation Generation through Hierarchical Generative Models
Fanmeng Wang, Wentao Guo, Qi Ou, Hongshuai Wang, Haitao Lin, Hongteng Xu, Zhifeng Gao
Machine Learning
日本大学: 関与なし（対象大学）
2025 · ICML
Polynomial Time Learning Augmented Algorithms for NP-hard Permutation Problems
Evripidis Bampis, Bruno Escoffier, Dimitris Fotakis, Panagiotis Patsilinakos, Michalis Xefteris
Machine Learning
日本大学: 関与なし（対象大学）
2025 · ICML
Polynomial-Delay MAG Listing with Novel Locally Complete Orientation Rules
Tian-Zuo Wang, Wen-Bo Du, Zhi-Hua Zhou
Machine Learning
日本大学: 関与なし（対象大学）
2025 · ICML
Polynomial-Time Approximability of Constrained Reinforcement Learning
Jeremy Mcmahan
Machine Learning
日本大学: 関与なし（対象大学）
2025 · ICML
Portable Reward Tuning: Towards Reusable Fine-Tuning across Different Pretrained Models
Daiki Chijiwa, Taku Hasegawa, Kyosuke Nishida, Kuniko Saito, Susumu Takeuchi
Machine Learning
日本大学: 関与なし（対象大学）
2025 · ICML
Position: A Theory of Deep Learning Must Include Compositional Sparsity
David A. Danhofer, Davide D’Ascenzo, Rafael Dubach, Tomaso A Poggio
Machine Learning
日本大学: 関与なし（対象大学）
2025 · ICML
Position: AI Agents Need Authenticated Delegation
Tobin South, Samuele Marro, Thomas Hardjono, Robert Mahari, Cedric Deslandes Whitney, Alan Chan, Alex Pentland
Machine Learning
日本大学: 関与なし（対象大学）
2025 · ICML
Position: AI Competitions Provide the Gold Standard for Empirical Rigor in GenAI Evaluation
D. Sculley, William Cukierski, Phil Culliton, Sohier Dane, Maggie M Demkin, Ryan Holbrook, Addison Howard, Paul T Mooney, Walter Reade, Meg Risdal, Nate Keating
Machine Learning
日本大学: 関与なし（対象大学）
2025 · ICML
Position: AI Evaluation Should Learn from How We Test Humans
Yan Zhuang, Qi Liu, Zachary Pardos, Patrick C. Kyllonen, Jiyun Zu, Zhenya Huang, Shijin Wang, Enhong Chen
Machine Learning
日本大学: 関与なし（対象大学）
2025 · ICML
Position: AI Safety Must Embrace an Antifragile Perspective
Ming Jin, Hyunin Lee
Machine Learning
日本大学: 関与なし（対象大学）
2025 · ICML
Position: AI Safety should prioritize the Future of Work
Sanchaita Hazra, Bodhisattwa Prasad Majumder, Tuhin Chakrabarty
Machine Learning
日本大学: 関与なし（対象大学）
2025 · ICML
Position: AI Scaling: From Up to Down and Out
Yunke Wang, Yanxi Li, Chang Xu
Machine Learning
日本大学: 関与なし（対象大学）
2025 · ICML
Position: AI Should Not Be An Imitation Game: Centaur Evaluations
Andreas Haupt, Erik Brynjolfsson
Machine Learning
日本大学: 関与なし（対象大学）
2025 · ICML
Position: AI’s growing due process problem
Sunayana Rane
Machine Learning
日本大学: 関与なし（対象大学）
2025 · ICML
Position: Algebra Unveils Deep Learning - An Invitation to Neuroalgebraic Geometry
Giovanni Luca Marchetti, Vahid Shahverdi, Stefano Mereta, Matthew Trager, Kathlén Kohn
Machine Learning
日本大学: 関与なし（対象大学）
2025 · ICML
Position: All Current Generative Fidelity and Diversity Metrics are Flawed
Ossi Räisä, Boris Van Breugel, Mihaela Van Der Schaar
Machine Learning
日本大学: 関与なし（対象大学）
2025 · ICML
Position: An Empirically Grounded Identifiability Theory Will Accelerate Self Supervised Learning Research
Patrik Reizinger, Randall Balestriero, David Klindt, Wieland Brendel
Machine Learning
日本大学: 関与なし（対象大学）
2025 · ICML
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
Machine Learning
日本大学: 関与なし（対象大学）
2025 · ICML
Position: Build Agent Advocates, Not Platform Agents
Sayash Kapoor, Noam Kolt, Seth Lazar
Machine Learning
日本大学: 関与なし（対象大学）
2025 · ICML
Position: Causal Machine Learning Requires Rigorous Synthetic Experiments for Broader Adoption
Audrey Poinsot, Panayiotis Panayiotou, Alessandro Leite, Nicolas Chesneau, Özgür Şimşek, Marc Schoenauer
Machine Learning
日本大学: 関与なし（対象大学）
2025 · ICML
Position: Certified Robustness Does Not (Yet) Imply Model Security
Andrew Craig Cullen, Paul Montague, Sarah Monazam Erfani, Benjamin I. P. Rubinstein
Machine Learning
日本大学: 関与なし（対象大学）
2025 · ICML
Position: Challenges and Future Directions of Data-Centric AI Alignment
Min-Hsuan Yeh, Jeffrey Wang, Xuefeng Du, Seongheon Park, Leitian Tao, Shawn Im, Yixuan Li
Machine Learning
日本大学: 関与なし（対象大学）
2025 · ICML
Position: Constants are Critical in Regret Bounds for Reinforcement Learning
Simone Drago, Marco Mussi, Alberto Maria Metelli
Machine Learning
日本大学: 関与なし（対象大学）
2025 · ICML
Position: Contextual Integrity is Inadequately Applied to Language Models
Yan Shvartzshnaider, Vasisht Duddu
Machine Learning
日本大学: 関与なし（対象大学）
2025 · ICML
Position: Current Model Licensing Practices are Dragging Us into a Quagmire of Legal Noncompliance
Moming Duan, Mingzhe Du, Rui Zhao, Mengying Wang, Yinghui Wu, Nigel Shadbolt, Bingsheng He
Machine Learning
日本大学: 関与なし（対象大学）
2025 · ICML
Position: Deep Learning is Not So Mysterious or Different
Andrew Gordon Wilson
Machine Learning
日本大学: 関与なし（対象大学）
2025 · ICML
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, Flynn Devine, Andrew Konya, Smitha Milli, Manon Revel, Kevin Feng, Amy X Zhang, Bilva Chandra, Michiel A. Bakker, Atoosa Kasirzadeh
Machine Learning
日本大学: 関与なし（対象大学）
2025 · ICML
Position: Don’t Use the CLT in LLM Evals With Fewer Than a Few Hundred Datapoints
Sam Bowyer, Laurence Aitchison, Desi R. Ivanova
Machine Learning
日本大学: 関与なし（対象大学）
2025 · ICML
Position: Editing Large Language Models Poses Serious Safety Risks
Paul Youssef, Zhixue Zhao, Daniel Braun, Jörg Schlötterer, Christin Seifert
Machine Learning
日本大学: 関与なし（対象大学）
2025 · ICML
Position: Enough of Scaling LLMs! Lets Focus on Downscaling
Yash Goel, Ayan Sengupta, Tanmoy Chakraborty
Machine Learning
日本大学: 関与なし（対象大学）
2025 · ICML
Position: Evaluating Generative AI Systems Is a Social Science Measurement Challenge
Hanna Wallach, Meera Desai, A. Feder Cooper, Angelina Wang, Chad Atalla, Solon Barocas, Su Lin Blodgett, Alexandra Chouldechova, Emily Corvi, P. Alex Dow, Jean Garcia-Gathright, Alexandra Olteanu, Nicholas J Pangakis, Stefanie Reed, Emily Sheng, Dan Vann, Jennifer Wortman Vaughan, Matthew Vogel, Hannah Washington, Abigail Z. Jacobs
Machine Learning
日本大学: 関与なし（対象大学）
2025 · ICML
Position: Explainable AI Cannot Advance Without Better User Studies
Matej Pičulin, Bernarda Petek, Irena Ograjenšek, Erik Strumbelj
Machine Learning
日本大学: 関与なし（対象大学）
2025 · ICML
Position: Formal Mathematical Reasoning—A New Frontier in AI
Kaiyu Yang, Gabriel Poesia, Jingxuan He, Wenda Li, Kristin E. Lauter, Swarat Chaudhuri, Dawn Song
Machine Learning
日本大学: 関与なし（対象大学）
2025 · ICML
Position: Future Research and Challenges Remain Towards AI for Software Engineering
Alex Gu, Naman Jain, Wen-Ding Li, Manish Shetty, Kevin Ellis, Koushik Sen, Armando Solar-Lezama
Machine Learning
日本大学: 関与なし（対象大学）
2025 · ICML
Position: General Intelligence Requires Reward-based Pretraining
Seungwook Han, Jyothish Pari, Samuel J. Gershman, Pulkit Agrawal
Machine Learning
日本大学: 関与なし（対象大学）
2025 · ICML
Position: Generative AI Regulation Can Learn from Social Media Regulation
Ruth Elisabeth Appel
Machine Learning
日本大学: 関与なし（対象大学）
2025 · ICML
Position: Graph Learning Will Lose Relevance Due To Poor Benchmarks
Maya Bechler-Speicher, Ben Finkelshtein, Fabrizio Frasca, Luis Müller, Jan Tönshoff, Antoine Siraudin, Viktor Zaverkin, Michael M. Bronstein, Mathias Niepert, Bryan Perozzi, Mikhail Galkin, Christopher Morris
Machine Learning
日本大学: 関与なし（対象大学）
2025 · ICML
Position: Graph Matching Systems Deserve Better Benchmarks
Indradyumna Roy, Saswat Meher, Eeshaan Jain, Soumen Chakrabarti, Abir De
Machine Learning
日本大学: 関与なし（対象大学）
2025 · ICML
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, Xavier Roberts-Gaal, Rachel Calcott, Evie Coxon, Chinmay Deshpande
Machine Learning
日本大学: 関与なし（対象大学）
2025 · ICML
Position: Humanity Faces Existential Risk from Gradual Disempowerment
Jan Kulveit, Raymond Douglas, Nora Ammann, Deger Turan, David Krueger, David Duvenaud
Machine Learning
日本大学: 関与なし（対象大学）
2025 · ICML
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, Michelle Sahar, Sean Mcgregor, Avijit Ghosh, Borhane Blili-Hamelin, Nathan Butters, Alondra Nelson, Dr. Amit Elazari, Andrew Sellars, Casey John Ellis, Dane Sherrets, Dawn Song, Harley Geiger, Ilona Cohen, Lauren Mcilvenny, Madhulika Srikumar, Mark M. Jaycox, Markus Anderljung, Nadine Farid Johnson, Nicholas Carlini, Nicolas Miailhe, Nik Marda, Peter Henderson, Rebecca S. Portnoff, Rebecca Weiss, Victoria Westerhoff, Yacine Jernite, Rumman Chowdhury, Percy Liang, Arvind Narayanan
Machine Learning
日本大学: 関与なし（対象大学）
2025 · ICML
Position: It Is Time We Test Neural Computation In Vitro
Frithjof Gressmann, Ashley Chen, Lily Hexuan Xie, Nancy Amato, Lawrence Rauchwerger
Machine Learning
日本大学: 関与なし（対象大学）
2025 · ICML
Position: Iterative Online-Offline Joint Optimization is Needed to Manage Complex LLM Copyright Risks
Yanzhou Pan, Jiayi Chen, Jiamin Chen, Zhaozhuo Xu, Denghui Zhang
Machine Learning
日本大学: 関与なし（対象大学）
2025 · ICML
Position: LLM Social Simulations Are a Promising Research Method
Jacy Reese Anthis, Ryan Liu, Sean M Richardson, Austin C. Kozlowski, Bernard Koch, Erik Brynjolfsson, James Evans, Michael S. Bernstein
Machine Learning
日本大学: 関与なし（対象大学）
2025 · ICML
Position: LLMs Need a Bayesian Meta-Reasoning Framework for More Robust and Generalizable Reasoning
Hanqi Yan, Linhai Zhang, Jiazheng Li, Zhenyi Shen, Yulan He
Machine Learning
日本大学: 関与なし（対象大学）
2025 · ICML
Position: Language model developers should report train-test overlap
Andy K Zhang, Kevin Klyman, Yifan Mai, Yoav Levine, Yian Zhang, Rishi Bommasani, Percy Liang
Machine Learning
日本大学: 関与なし（対象大学）
2025 · ICML
Position: Lifetime tuning is incompatible with continual reinforcement learning
Golnaz Mesbahi, Parham Mohammad Panahi, Olya Mastikhina, Steven Tang, Martha White, Adam White
Machine Learning
日本大学: 関与なし（対象大学）
2025 · ICML
Position: Machine Learning Models Have a Supply Chain Problem
Sarah Meiklejohn, Hayden Blauzvern, Mihai Maruseac, Spencer Schrock, Laurent Simon, Ilia Shumailov
Machine Learning
日本大学: 関与なし（対象大学）
2025 · ICML
Position: Medical Large Language Model Benchmarks Should Prioritize Construct Validity
Ahmed Alaa, Thomas Hartvigsen, Niloufar Golchini, Shiladitya Dutta, Frances Dean, Inioluwa Deborah Raji, Travis Zack
Machine Learning
日本大学: 関与なし（対象大学）
2025 · ICML
Position: Not All Explanations for Deep Learning Phenomena Are Equally Valuable
Alan Jeffares, Mihaela Van Der Schaar
Machine Learning
日本大学: 関与なし（対象大学）
2025 · ICML
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, Taylor Sorensen, Shangbin Feng, Yulia Tsvetkov, Margaret Roberts, Jennifer Pan, Dawn Song, Yejin Choi
Machine Learning
日本大学: 関与なし（対象大学）
2025 · ICML
Position: Principles of Animal Cognition to Improve LLM Evaluations
Sunayana Rane, Cyrus F. Kirkman, Graham Todd, Amanda Royka, Ryan M.C. Law, Erica Cartmill, Jacob Gates Foster
Machine Learning
日本大学: 関与なし（対象大学）
2025 · ICML
Position: Probabilistic Modelling is Sufficient for Causal Inference
Bruno Kacper Mlodozeniec, David Krueger, Richard E Turner
Machine Learning
日本大学: 関与なし（対象大学）
2025 · ICML
Position: Rethinking Explainable Machine Learning as Applied Statistics
Sebastian Bordt, Eric Raidl, Ulrike Von Luxburg
Machine Learning
日本大学: 関与なし（対象大学）
2025 · ICML
Position: Rethinking LLM Bias Probing Using Lessons from the Social Sciences
Kirsten Morehouse, Siddharth Swaroop, Weiwei Pan
Machine Learning
日本大学: 関与なし（対象大学）
2025 · ICML
Position: Retrieval-augmented systems can be dangerous medical communicators
Lionel Wong, Ayman Ali, Raymond M Xiong, Zejiang Shen, Yoon Kim, Monica Agrawal
Machine Learning
日本大学: 関与なし（対象大学）
2025 · ICML
Position: Scaling LLM Agents Requires Asymptotic Analysis with LLM Primitives
Elliot Meyerson, Xin Qiu
Machine Learning
日本大学: 関与なし（対象大学）
2025 · ICML
Position: Societal Impacts Research Requires Benchmarks for Creative Composition Tasks
Judy Hanwen Shen
Machine Learning
日本大学: 関与なし（対象大学）
2025 · ICML
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, Wonyl Choi, Niclas Alexander Göring, Seungjai Lee
Machine Learning
日本大学: 関与なし（対象大学）
2025 · ICML
Position: Spectral GNNs Rely Less on Graph Fourier Basis than Conceived
Yuhe Guo, Huayi Tang, Jiahong Ma, Hongteng Xu, Zhewei Wei
Machine Learning
日本大学: 関与なし（対象大学）
2025 · ICML
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, Avijit Ghosh, Katherine A Heller, Jacob Metcalf, Fabricio Murai, Eryk Salvaggio, Andrew J Smart, Todd Snider, Mariame Tighanimine, Talia Ringer, Margaret Mitchell, Shiri Dori-Hacohen
Machine Learning
日本大学: 関与なし（対象大学）
2025 · ICML
Position: Strong Consumer Protection is an Inalienable Defense for AI Safety in the United States
Serena Booth
Machine Learning
日本大学: 関与なし（対象大学）
2025 · ICML
Position: Supervised Classifiers Answer the Wrong Questions for OOD Detection
Yucen Lily Li, Daohan Lu, Polina Kirichenko, Shikai Qiu, Tim G. J. Rudner, C. Bayan Bruss, Andrew Gordon Wilson
Machine Learning
日本大学: 関与なし（対象大学）
2025 · ICML
Position: The AI Conference Peer Review Crisis Demands Author Feedback and Reviewer Rewards
Jaeho Kim, Yunseok Lee, Seulki Lee
Machine Learning
日本大学: 関与なし（対象大学）
2025 · ICML
Position: The Artificial Intelligence and Machine Learning Community Should Adopt a More Transparent and Regulated Peer Review Process
Jing Yang
Machine Learning
日本大学: 関与なし（対象大学）
2025 · ICML
Position: The Categorization of Race in ML is a Flawed Premise
Miriam Doh, Benedikt Höltgen, Piera Riccio, Nuria M Oliver
Machine Learning
日本大学: 関与なし（対象大学）