ICML

2022–2026 LIVE

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Machine Learning

2026 · 6,341 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。

2026 · ICML
Enhancing Train-Free Infinite-Frame Generation for Consistent Long Videos
xiaokun Feng, Jiashu Zhu, Meiqi Wu, Chubin Chen, Fangyuan Mao, Haiyang Guo, Jiahong Wu, Xiangxiang Chu, Kaiqi Huang
Machine Learning
日本大学: 関与なし（対象大学）
2026 · ICML
EnsembleVLA: Ensemble Learning for Vision-Language Action Models
Mingchen Song, Xiang Deng, Jie Wei, Dongmei Jiang, Liqiang Nie, Weili Guan
Machine Learning
日本大学: 関与なし（対象大学）
2026 · ICML
Ensembling Sparse Autoencoders
Soham Gadgil, Chris Lin, Su-In Lee
Machine Learning
日本大学: 関与なし（対象大学）
2026 · ICML
EntRAG: Entity-Centric Retrieval-Augmented Generation for Knowledge-based Visual Question Answering
Yiheng Hu, Xiaoyang Wang, Qing Liu, Sherry Xu, Qian Fu, Wenjie Zhang
Machine Learning
日本大学: 関与なし（対象大学）
2026 · ICML
Entangled No More: Multi-Domain Decoupling for Robust Dynamic Graph Neural Networks
Youda Mo, Chaobo He, Junwei Cheng, Peng Mei, Quanlong Guan
Machine Learning
日本大学: 関与なし（対象大学）
2026 · ICML
EnterpriseOps-Gym: Environments and Evaluations for Stateful Agentic Planning and Tool Use in Enterprise Settings
Shiva Malay, Perampalli Shravan Nayak, Sagar Davasam, Srinivas Sunkara, Sai Rajeswar Mudumba
Machine Learning
日本大学: 関与なし（対象大学）
2026 · ICML
EntroKV: Entropy-Guided Dynamic Budget Allocation for KV-Cache Compression
Wenhao Gao, Haoran Cao, Yueyan Li, YongGao Xiao, Caixia Yuan, Xiaojie Wang
Machine Learning
日本大学: 関与なし（対象大学）
2026 · ICML
Entropic Mirror Monte Carlo
Anas CHERRADI, Yazid Janati, Alain Oliviero Durmus, Sylvain Le Corff, Yohan Petetin, Julien Stoehr
Machine Learning
日本大学: 関与なし（対象大学）
2026 · ICML
Entropy-Aware Dynamic KV Cache Sparsification for Autoregressive Image Generation and Editing
Tong Tong, LING XING, Linjie Li, Rui Yan, Zhengyuan Yang, Lijuan Wang, Alex Jinpeng Wang
Machine Learning
日本大学: 関与なし（対象大学）
2026 · ICML
Entropy-Aware On-Policy Distillation of Language Models
Woogyeol Jin, Taywon Min, Yongjin Yang, Dennis Wei, Yi Zhou, Swanand Kadhe, Nathalie Baracaldo, Kimin Lee
Machine Learning
日本大学: 関与なし（対象大学）
2026 · ICML
Entropy-aware Span-Constrained Optimal Transport for Robust Cross-Tokenizer Knowledge Distillation
Zhi-Ping Liu, Simiao Li, Wei Li, Hanting Chen, Jie Hu, Hua-Lei Yin, Xinghao Chen
Machine Learning
日本大学: 関与なし（対象大学）
2026 · ICML
Entropy-informed Decoding: Adaptive Information-Driven Branching
Benjamin Patrick Evans, Sumitra Ganesh, Leo Ardon
Machine Learning
日本大学: 関与なし（対象大学）
2026 · ICML
Envisioning Beyond the Few: Disentangled Semantics and Primitives for Few-Shot Atypical Layout-to-Image Generation
Nan Bao, Yifan Zhao, Wenzhuang Wang, Jia Li
Machine Learning
日本大学: 関与なし（対象大学）
2026 · ICML
Envy-Free Allocation of Indivisible Goods via Noisy Queries
Zihan Li, Yan Hao Ling, Jonathan Scarlett, Warut Suksompong
Machine Learning
日本大学: 関与なし（対象大学）
2026 · ICML
EpiCache: Episodic KV Cache Management for Long-Term Conversation on Resource-Constrained Environments
Minsoo Kim, Arnav Kundu, Han-Byul Kim, Richa Dixit, Minsik Cho
Machine Learning
日本大学: 関与なし（対象大学）
2026 · ICML
EpiCoCo: De Novo Epitope Generation via MHC-Context Co-Modeling and Contrastive Affinity Guidance
Haoyang Luan, Gufeng Yu, Letian Chen, Zhenran Xiao, Yueshan Huang, Junkun Guo, Yang Yang
Machine Learning
日本大学: 関与なし（対象大学）
2026 · ICML
EpiTwin: Spatiotemporal Graph Transformers for Epileptic sEEG Signal Reconstruction
Jingbo Yang, Yunfeng Zhao, Chao Qiu, Yulin Sun, Xiuyun Liu, Xiaofei Wang
Machine Learning
日本大学: 関与なし（対象大学）
2026 · ICML
Episodic Memory-Guided Controllable Experience Synthesis for Reinforcement Learning
Xiao Ma, Tian Li, Wu-Jun Li
Machine Learning
日本大学: 関与なし（対象大学）
2026 · ICML
Epistemic Gain, Aleatoric Cost: Uncertainty Decomposition in Multi-Agent Debate for Math Reasoning
Dan Qiao, Binbin Chen, Fengyu Cai, Jianlong Chen, Wenhao Li, Fuxin Jiang, Zuzhi Chen, Hongyuan Zha, Tieying Zhang, Baoxiang Wang
Machine Learning
日本大学: 関与なし（対象大学）
2026 · ICML
Epistemic Uncertainty Quantification for Pre-trained VLMs via Riemannian Flow Matching
Li Ju, Mayank Nautiyal, Andreas Hellander, Ekta Vats, Prashant Singh
Machine Learning
日本大学: 関与なし（対象大学）
2026 · ICML
EqGINO: Equivariant Geometry-Informed Fourier Neural Operators for 3D PDEs
Sungwon Kim, Juho Song, Seungmin Shin, Guimok Cho, Sangkook Kim, Chanyoung Park
Machine Learning
日本大学: 関与なし（対象大学）
2026 · ICML
Equalized Generative Treatment: Matching f-divergences for Fairness in Generative Models
Alexandre Verine, Rafael Pinot, Florian Le Bronnec
Machine Learning
日本大学: 関与なし（対象大学）
2026 · ICML
EquiCAD: A Geometric Equivariant Neural Network for 3D Shape Classiﬁcation
Yonghao Su, Yantao Gan, Junfeng Long, Caiyang Yu, Wenhao Zheng, Jiancheng Lv, Xianggen Liu
Machine Learning
日本大学: 関与なし（対象大学）
2026 · ICML
Equilibrium Pricing in Oligopolistic Data Markets
Bhaskar Ray Chaudhury, Jugal Garg, Eklavya Sharma, Jiaxin Song
Machine Learning
日本大学: 関与なし（対象大学）
2026 · ICML
Equilibrium Propagation for Non-Conservative Systems
Antonino Emanuele Scurria, Dimitri Vanden Abeele, Bortolo Matteo Mognetti, Serge Massar
Machine Learning
日本大学: 関与なし（対象大学）
2026 · ICML
Equilibrium Reasoners: Learning Attractors Enables Scalable Reasoning
Benhao Huang, Zhengyang Geng, Zico Kolter
Machine Learning
日本大学: 関与なし（対象大学）
2026 · ICML
Equivalence of Context and Parameter Updates in Modern Transformer Blocks
Adrian Goldwaser, Michael Munn, Xavi Gonzalvo, Benoit Dherin
Machine Learning
日本大学: 関与なし（対象大学）
2026 · ICML
Equivariant Covariance Tensors: Guaranteed SPD Uncertainty for Tensor-Valued Geometric Learning
Ruihan Liu, Yu Ji, Jianbo Yu, Shifu Yan, Qingchao Jiang
Machine Learning
日本大学: 関与なし（対象大学）
2026 · ICML
Equivariant Latent Alignment via Flow Matching under Group Symmetries
Sunghyun Kim, Jaehoon Hahm, Jeongwoo Shin, Joonseok Lee
Machine Learning
日本大学: 関与なし（対象大学）
2026 · ICML
Equivariant Neural Networks for General Linear Symmetries on Lie Algebras
Chankyo Kim, Sicheng Zhao, Minghan Zhu, Tzu-Yuan Lin, Maani Ghaffari
Machine Learning
日本大学: 関与なし（対象大学）
2026 · ICML
Erased but Not Forgotten: How Backdoors Compromise Concept Erasure
Tobias Braun, Jonas Henry Grebe, Patrick Mohr Gordillo, Marcus Rohrbach, Anna Rohrbach
Machine Learning
日本大学: 関与なし（対象大学）
2026 · ICML
Error Amplification Limits ANN-to-SNN Conversion in Continuous Control
Zijie Xu, Zihan Huang, Yiting Dong, Kang Chen, Wenxuan Liu, Zhaofei Yu
Machine Learning
日本大学: 関与なし（対象大学）
2026 · ICML
Error Analysis of Discrete Flow with Generator Matching
Zhengyan Wan, Yidong Ouyang, Qiang Yao, Liyan Xie, Fang Fang, Hongyuan Zha, Guang Cheng
Machine Learning
日本大学: 関与なし（対象大学）
2026 · ICML
Error Propagation Mechanisms and Compensation Strategies for Quantized Diffusion Models
Songwei Liu, Chao Zeng, Chenqian Yan, Xurui Peng, WANG, Fangmin Chen, Xing Mei
Machine Learning
日本大学: 関与なし（対象大学）
2026 · ICML
Error Propagation in Dynamic Programming: From Stochastic Control to American Option Pricing
Andrea Della Vecchia, Damir Filipovic
Machine Learning
日本大学: 関与なし（対象大学）
2026 · ICML
Error-Driven Graph Augmentation for Mesh-Based PDE Surrogates
Xuan Minh Vuong Nguyen, Nissrine Akkari, Fabien Casenave, Jonathan Viquerat, Elie Hachem
Machine Learning
日本大学: 関与なし（対象大学）
2026 · ICML
Escaping Mode Collapse in LLM Generation via Geometric Regulation
Xin Du, Kumiko Tanaka-Ishii
Machine Learning
日本大学: 早稲田大学
2026 · ICML
Escaping Whack-a-Mole: Optimizing Documentation as Repo-Specific Playbooks for Coding Agents
Yutong Cheng, Haifeng Chen, Wenchao Yu, Xujiang Zhao, Peng Gao, Wei Cheng
Machine Learning
日本大学: 関与なし（対象大学）
2026 · ICML
Escaping the Diversity Trap in Robotic Manipulation via Anchor-Centric Adaptation
Yanzhe Chen, Kevin Yuchen, Qi Lv, Lin Yiqi, Zechen Bai, Chen GAO, Mike Zheng Shou
Machine Learning
日本大学: 関与なし（対象大学）
2026 · ICML
Escaping the Likelihood Trap: Geometric Diversity Optimization for Long-Form Image Captioning
Qingmei Tang, Shuai Hao, Rong Fu, Zirui Mo, Xiang Liu, Jiaxuan Lu, Wenyu Wang
Machine Learning
日本大学: 関与なし（対象大学）
2026 · ICML
Escaping the Mode: Multi-Answer Reinforcement Learning in LMs
Isha Puri, Mehul Damani, Idan Shenfeld, Marzyeh Ghassemi, Jacob Andreas, Yoon Kim
Machine Learning
日本大学: 関与なし（対象大学）
2026 · ICML
Escaping the Subspace Trap: The Role of Optimizer Geometry in Model Width Expansion
Jiabei Chen, Haoyu Wang, Yang Yu, Yao Xu, Liangdong Wang, Guang Liu, Shizhu He, Jun Zhao, Kang Liu
Machine Learning
日本大学: 関与なし（対象大学）
2026 · ICML
Escaping the Verifier: Learning to Reason via Demonstrations
Locke Cai, Max Ryabinin, Ivan Provilkov
Machine Learning
日本大学: 関与なし（対象大学）
2026 · ICML
Esoteric Language Models: A Family of Any-Order Diffusion LLMs
Subham Sekhar Sahoo, Zhihan Yang, Yash Akhauri, Johnna Liu, Deepansha Singh, Zhoujun Cheng, Zhengzhong Liu, Eric Xing, John Thickstun, Arash Vahdat
Machine Learning
日本大学: 関与なし（対象大学）
2026 · ICML
Estimating Continuous Treatment Effects with Two-Stage Kernel Ridge Regression
Seok-Jin Kim, Kaizheng Wang
Machine Learning
日本大学: 関与なし（対象大学）
2026 · ICML
Estimating Correlation Clustering Cost in Node-Arrival Stream
Kaiwen Liu, Seba Daniela Villalobos, Qin Zhang
Machine Learning
日本大学: 関与なし（対象大学）
2026 · ICML
Estimating Tail Risks in Language Model Output Distributions
Rico Angell, Raghav Singhal, Zachary Horvitz, Zhou Yu, Rajesh Ranganath, Kathleen McKeown, He He
Machine Learning
日本大学: 関与なし（対象大学）
2026 · ICML
Estimating the Empowerment of Language Model Agents
Jinyeop Song, Jeff Gore, Max Kleiman-Weiner
Machine Learning
日本大学: 関与なし（対象大学）
2026 · ICML
Estimation of Treatment Effects Under Nonstationarity via the Truncated Policy Gradient Estimator
Ramesh Johari, Tianyi Peng, Wenqian Xing
Machine Learning
日本大学: 関与なし（対象大学）
2026 · ICML
Euclean: Automated Geometry Problem Formalization with Unified Verification in Lean
Linbin Tang, Jingyan You, Zilin Kang, Hanzhang Liu, Sophia Zhang, Zenan Li, Chenrui Cao, Liangcheng Song, Jiaao Wu, Xian Zhang, Fan Yang
Machine Learning
日本大学: 関与なし（対象大学）
2026 · ICML
Euler–Poincaré Neural Dynamics: A Geometric-Mechanics Framework for Scientific Simulation
Sungwoo Park, Jongwon Lee, Jiwoong Kim
Machine Learning
日本大学: 関与なし（対象大学）
2026 · ICML
EvReflection: Event-Driven Micro-Dynamics for Reflection Removal
Jiaxiao Wang, Dachun Kai, Huyue Zhu, Quanquan Hu, Zhenyang Xu, Xiaoyan Sun
Machine Learning
日本大学: 関与なし（対象大学）
2026 · ICML
Evaluating AI Grading on Real-World Handwritten College Mathematics: A Large-Scale Study Toward a Benchmark
Zhiqi Yu, Xingping Liu, Haobin Mao, Mingshuo Liu, Long Chen, Jack Xin, Yifeng Yu
Machine Learning
日本大学: 関与なし（対象大学）
2026 · ICML
Evaluating Bivariate Causal Statements Based on Mutual Compatibility
Erik Jahn, Dominik Janzing
Machine Learning
日本大学: 関与なし（対象大学）
2026 · ICML
Evaluating Contextual Illegality: AI Compliance in Corporate Law Scenarios
Hilal Aka, Joe Kwon, Noam Kolt
Machine Learning
日本大学: 関与なし（対象大学）
2026 · ICML
Evaluating LLM Uncertainty in Long-Form Generation Using Deterministic Ground Truth
Ido Amit, Ido Galil, Ran El-Yaniv
Machine Learning
日本大学: 関与なし（対象大学）
2026 · ICML
Evaluating LLMs When They Do Not Know the Answer: Statistical Evaluation of Mathematical Reasoning via Comparative Signals
Zihan Dong, Zhixian Zhang, Yang Zhou, Can Jin, Ruijia Wu, Linjun Zhang
Machine Learning
日本大学: 関与なし（対象大学）
2026 · ICML
Evaluating Language Models in Realistic Conversational Contexts
Ilija Subasic, Andrew Rabinovich, Zhao Chen
Machine Learning
日本大学: 関与なし（対象大学）
2026 · ICML
Evaluating Newtonian Mechanics in Video Generative Models with Real Physical Systems
Antonios Tragoudaras, Chenyu Zhang, Daniil Cherniavskii, Antonis Vozikis, Thijmen Nijdam, Derck Prinzhorn, Márk Bodrácska, Nicu Sebe, Andrii Zadaianchuk, Efstratios Gavves
Machine Learning
日本大学: 関与なし（対象大学）
2026 · ICML
Evaluating Object-Centric Models beyond Object Discovery
Krishnakant Singh, Simone Schaub-Meyer, Stefan Roth
Machine Learning
日本大学: 関与なし（対象大学）
2026 · ICML
Evaluating Parameter Efficient Methods for RLVR
Qingyu Yin, Yulun Wu, Zhennan Shen, Sunbowen Li, Zhilin Wang, Yanshu Li, Chak Tou Leong, Jiale Kang, Jinjin Gu
Machine Learning
日本大学: 関与なし（対象大学）
2026 · ICML
Evaluating Relational Reasoning in LLMs with REL
Lukas Fesser, Yasha Ektefaie, Ada Fang, Sham Kakade, Marinka Zitnik
Machine Learning
日本大学: 関与なし（対象大学）
2026 · ICML
Evaluating Robustness of Reasoning Models on Parameterized Logical Problems
Naïm Es-sebbani, Esteban Marquer, Yakoub Salhi, Zied Bouraoui
Machine Learning
日本大学: 関与なし（対象大学）
2026 · ICML
Evaluating Sample Utility for Efficient Data Selection by Mimicking Model Weights
Tzu-Heng Huang, Manjot Bilkhu, John Cooper, Frederic Sala, Javier Movellan
Machine Learning
日本大学: 関与なし（対象大学）
2026 · ICML
Evaluating and Explaining Prompt Sensitivity of LLMs Using Interactions
Ruiyang Qin, Qingzhuo Wang, Tian Wang, Zhihua Wei, Wen Shen
Machine Learning
日本大学: 関与なし（対象大学）
2026 · ICML
Evaluating and Rewarding LALMs for Expressive Role-Play TTS via Mean Continuation Log-Probability
Yong Ren, Jingbei Li, Haiyang Sun, Yujie Chen, Cheng Yi, Yechang Huang, Hao Gu, Ye Bai, Xuerui Yang
Machine Learning
日本大学: 関与なし（対象大学）
2026 · ICML
Evaluating and Steering Modality Preferences in Multi-modal LLMs
Yu Zhang, Jinlong Ma, Yongshuai Hou, Xuefeng Bai, Kehai Chen, Yang Xiang, Jun Yu, Min zhang
Machine Learning
日本大学: 関与なし（対象大学）
2026 · ICML
Evaluating the Representation Space of Diffusion Models via Self-Supervised Principles
Xiao Li, Yixuan Jia, Zekai Zhang, Xiang Li, Lianghe Shi, Jinxin Zhou, Zhihui Zhu, Liyue Shen, Qing Qu
Machine Learning
日本大学: 関与なし（対象大学）
2026 · ICML
Even Faster Kernel Matrix Linear Algebra via Density Estimation
Rikhav Shah, Sandeep Silwal, Haike Xu
Machine Learning
日本大学: 関与なし（対象大学）
2026 · ICML
Event2Vec: Processing neuromorphic events directly by representations in vector space
Wei Fang, Priyadarshini Panda
Machine Learning
日本大学: 関与なし（対象大学）
2026 · ICML
Every Step Counts: Decoding Trajectories as Authorship Fingerprints of dLLMs
Qi Li, Runpeng Yu, Haiquan Lu, Xinchao Wang
Machine Learning
日本大学: 関与なし（対象大学）
2026 · ICML
Evidential Copula Concept Embedding Models
Yanjie Qiu, Xiaodong Yue, Xuhui Fan, Yufei Chen, Jie Shi, Wei Liu
Machine Learning
日本大学: 関与なし（対象大学）
2026 · ICML
Evidential Reasoning Advances Interpretable Real-World Disease Screening
Chenyu Lian, Hong-Yu Zhou, Jing Qin
Machine Learning
日本大学: 関与なし（対象大学）
2026 · ICML
EvoC2F: Compiling Tool Orchestration for Efficient and Evolvable LLM Agents
Lei Wei, Qi Liu, Ruiyang Huang, Xiao Peng, TT, Lanbo Lin, Chenhao Jiang, Yuanwu Xu, Tianyuan Yang, Jiayao Liu, Li Cai, Yuying Li, Bin Wang
Machine Learning
日本大学: 関与なし（対象大学）
2026 · ICML
EvoCF: Multi-Agent Collaboration via Agentic Memory-Driven Evolutionary Counterfactual Planning
Haotian Chi, Zeyu Feng, Xingrui Yu, Linbo Luo, Yew Soon ONG, Ivor Tsang, Hechang Chen, Yi Chang, Haiyan Yin
Machine Learning
日本大学: 関与なし（対象大学）
2026 · ICML
EvoClaw: Evaluating AI Agents on Continuous Software Evolution
Gangda Deng, Zhaoling Chen, Zhongming Yu, Haoyang Fan, Yuhong Liu, Yuxin Yang, Dhruv Parikh, Rajgopal Kannan, Le Cong, Mengdi Wang, Qian Zhang, Viktor Prasanna, Robert Tang, Xingyao Wang
Machine Learning
日本大学: 関与なし（対象大学）
2026 · ICML
EvoEGF-Mol: Evolving Exponential Geodesic Flow for Structure-based Drug Design
Yaowei Jin, Junjie Wang, Cheng Cao, Penglei Wang, Duo An, Qian Shi
Machine Learning
日本大学: 関与なし（対象大学）
2026 · ICML
EvoGM: Learning to Merge LLMs via Evolutionary Generative Optimization
Tao Jiang, Xinmeng Yu, Chenhao Yi, Yiling Wu, Yan Li, Ran Cheng, Dongmei Jiang, Jianguo Zhang
Machine Learning
日本大学: 関与なし（対象大学）
2026 · ICML
EvoMAS: Evolutionary Generation of Multi-Agent Systems
Yuntong Hu, Yuting Zhang, Matthew Trager, Yi Zhang, Shuo Yang, Wei Xia, Stefano Soatto
Machine Learning
日本大学: 関与なし（対象大学）
2026 · ICML
EvoMAS: Heuristics in the Loop—Evolving Smarter Agentic Workflows
Yangbo Wei, Zhen Huang, Ronghao Xu, Hong Wang, WEI W XING
Machine Learning
日本大学: 関与なし（対象大学）
2026 · ICML
Evolution Strategies at Scale: LLM Fine-Tuning Beyond Reinforcement Learning
Xin Qiu, Yulu Gan, Conor Hayes, Qiyao Liang, Yinggan XU, Roberto Dailey, Elliot Meyerson, Babak Hodjat, Risto Miikkulainen
Machine Learning
日本大学: 関与なし（対象大学）
2026 · ICML
Evolution Strategies at the Hyperscale
Bidipta Sarkar, Mattie Fellows, Juan Duque, Alistair Letcher, Antonio León Villares, Anya Sims, Clarisse Wibault, Dmitry Samsonov, Dylan Cope, Jarek Liesen, Kang Li, Lukas Seier, Theo Wolf, Uljad Berdica, Valentin Mohl, Alexander D. Goldie, Aaron Courville, Karin Sevegnani, Shimon Whiteson, Jakob Foerster
Machine Learning
日本大学: 関与なし（対象大学）
2026 · ICML
Evolution of Benchmark: Black-Box Optimization Benchmark Design through Large Language Model
Chen Wang, Sijie Ma, Zeyuan Ma, Yue-Jiao Gong
Machine Learning
日本大学: 関与なし（対象大学）
2026 · ICML
Evolutionary Multi-View Classification with Label Noise via Gradient and Feature Dual-Perception
Shuai Li, Xinyan Liang, Yuhua Qian, Li Lv
Machine Learning
日本大学: 関与なし（対象大学）
2026 · ICML
Evolving Interdependent Operators with Large Language Models for Multi-Objective Combinatorial Optimization
Junhao Qiu, Xin Chen, LiangGE, Liyong Lin, Zhichao Lu, Qingfu Zhang
Machine Learning
日本大学: 関与なし（対象大学）
2026 · ICML
Evolving Interpretable Constitutions for Multi-Agent Coordination
Ujwal Kumar, Alice Saito, Hershraj Niranjani, Rayan Yessou, Tan Phan Xuan
Machine Learning
日本大学: 芝浦工業大学 / 東京大学
2026 · ICML
Evolving Quantitative Reasoning through Self-Play in Digital Twin Markets
Tianmi Ma, Wenxin Huang, Jiawei Du, Lin Li, Xian Zhong, Joey Tianyi Zhou
Machine Learning
日本大学: 関与なし（対象大学）
2026 · ICML
ExCyTIn-Bench: Evaluating LLM agents on Cyber Threat Investigation
Yiran Wu, Mauricio Velazco, Andrew Zhao, Manuel Luján, Srisuma Movva, Yogesh Roy, Quang Nguyen, Roberto Rodriguez, Qingyun Wu, Michael Albada, Julia Kiseleva, Anand Mudgerikar
Machine Learning
日本大学: 関与なし（対象大学）
2026 · ICML
ExPLAIND: Unifying Model, Data, and Training Attribution to Study Model Behavior
Florian Eichin, Yupei Du, Philipp Mondorf, Maria Matveev, Barbara Plank, Michael Hedderich
Machine Learning
日本大学: 関与なし（対象大学）
2026 · ICML
ExVerus: Verus Proof Repair via Counterexample Reasoning
Jun Yang, Yuechun Sun, Yi Wu, Rodrigo Caridad, Yongwei Yuan, Jianan Yao, Shan Lu, Kexin Pei
Machine Learning
日本大学: 関与なし（対象大学）
2026 · ICML
Exact Functional ANOVA Decomposition for Categorical Inputs
Baptiste Ferrere, Nicolas Bousquet, Gamboa Fabrice, Jean-Michel Loubes, Joseph Muré
Machine Learning
日本大学: 関与なし（対象大学）
2026 · ICML
Exact Unlearning in Reinforcement Learning
Tang Thanh Nguyen, Raman Arora
Machine Learning
日本大学: 関与なし（対象大学）
2026 · ICML
Exact and Approximate Algorithms for Polytree Learning
Juha Harviainen, Frank Sommer, Manuel Sorge
Machine Learning
日本大学: 関与なし（対象大学）
2026 · ICML
Exactly Computing do-Shapley Values
R. Teal Witter, Álvaro Parafita, Tomas Garriga, Maximilian Muschalik, Fabian Fumagalli, Axel Brando, Lucas Rosenblatt
Machine Learning
日本大学: 関与なし（対象大学）
2026 · ICML
Excited Pfaffians: Generalized Neural Wave Functions Across Structure and State
Nicholas Gao, Till Grutschus, Frank Noe, Stephan Günnemann
Machine Learning
日本大学: 関与なし（対象大学）
2026 · ICML
Executable Agentic Memory for GUI Agent
Zerui Qin, Sheng Yue, Xingyuan Hua, Yongjian Fu, Ju Ren
Machine Learning
日本大学: 関与なし（対象大学）
2026 · ICML
ExpAlign: Expectation-Guided Vision–Language Alignment for Open-Vocabulary Grounding
Junyi Hu, Tian Bai, Fengyi Wu, Wenyan Li, Zhenming Peng, Yi ZHANG
Machine Learning
日本大学: 関与なし（対象大学）
2026 · ICML
ExpWeaver: LLM Agents Learn from Experience via Latent RAG
Tao Feng, Tianyang Luo, Jingjun Xu, Zhigang Hua, Yan Xie, Shuang Yang, Ge Liu, Jiaxuan You
Machine Learning
日本大学: 関与なし（対象大学）
2026 · ICML
Expand Neurons, Not Parameters
Linghao Kong, Inimai Subramanian, Yonadav Shavit, Micah Adler, Dan Alistarh, Nir Shavit
Machine Learning
日本大学: 関与なし（対象大学）
2026 · ICML
Expandable, Compressible, Mineable: Open-World Thermal Infrared Image Restoration
Pu Li, Huafeng Li, Yafei Zhang, Wen Wang, Neng Dong, Jie Wen
Machine Learning
日本大学: 関与なし（対象大学）