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
MixFP4: Enhancing NVFP4 with Adaptive FP4/INT4 Block RepresentationsJiaxiang Zou, Yonghao Chen, Ruilong WU, Xinyu Chen
Machine Learning
日本大学: 関与なし(対象大学)
2026 · ICML
MixReasoning: Switching Modes to ThinkHaiquan Lu, Gongfan Fang, Xinyin Ma, Qi Li, Xinchao Wang
Machine Learning
日本大学: 関与なし(対象大学)
2026 · ICML
Mixing Configurations for Downstream PredictionJuntang Wang, Hao Wu, Yihan Wang, Dongmian Zou, Shixin Xu
Machine Learning
日本大学: 関与なし(対象大学)
2026 · ICML
Mixing Expertise with Confidence: A Mixture of Experts Framework for Robust Multi-Modal Continual LearningMd Abdullah Al Forhad, Yuansheng Zhu Zhu., Abhinab Acharya, Xumin Liu, Qi Yu, Weishi Shi
Machine Learning
日本大学: 関与なし(対象大学)
2026 · ICML
Mixture Prototype Flow Matching for Open-Set Supervised Anomaly DetectionFuyun Wang, Yuanzhi Wang, Xu Guo, Sujia Huang, Tong Zhang, Dan Wang, Hui Yan, Xin Liu, Zhen Cui
Machine Learning
日本大学: 関与なし(対象大学)
2026 · ICML
Mixture of Concept Bottleneck ExpertsFrancesco De Santis, Gabriele Ciravegna, Giovanni De Felice, Arianna Casanova, Francesco Giannini, Michelangelo Diligenti, Mateo Espinosa Zarlenga, Pietro Barbiero, Johannes Schneider, Danilo Giordano
Machine Learning
日本大学: 関与なし(対象大学)
2026 · ICML
Mixture of Distributions Matters: Dynamic Sparse Attention for Efficient Video Diffusion TransformersYuxi Liu, Yipeng Hu, Zekun Zhang, Kunze Jiang, Kun Yuan
Machine Learning
日本大学: 関与なし(対象大学)
2026 · ICML
Mixture of Horizons in Action ChunkingDong Jing, Gang Wang, Jiaqi Liu, Weiliang Tang, Zelong Sun, Yunchao Yao, Zhenyu Wei, Yunhui Liu, Zhiwu Lu, Mingyu Ding
Machine Learning
日本大学: 関与なし(対象大学)
2026 · ICML
Mixtures Closest To A Given Measure: A Semidefinite Programming ApproachSrećko Ðurašinović, Jean B Lasserre, Victor Magron
Machine Learning
日本大学: 関与なし(対象大学)
2026 · ICML
Mixtures of geodesic factor analyzers on Riemannian homogeneous spacesHengchao Chen, Yuanyao Tan, Chao Huang, Hongtu Zhu, Qiang Sun
Machine Learning
日本大学: 関与なし(対象大学)
2026 · ICML
MoCL: Metabolic Optimization for Curvature-Aware Continual LearningJiajun Lai, Qi Liu, Shijie Li, Huaiguang Jiang
Machine Learning
日本大学: 関与なし(対象大学)
2026 · ICML
MoCo-EA: Exploiting Adversarial Mode Connectivity for Efficient Evolutionary AttacksHyo Seo Kim, Gang Luo, Can Chen, Binghui Wang, Yue Duan, Ren Wang
Machine Learning
日本大学: 関与なし(対象大学)
2026 · ICML
MoDA: Modulation Adapter for Fine-Grained Visual Understanding in Instructional MLLMsWayner Barrios, Andrés Villa, Juan Leon Alcazar, SouYoung Jin, Bernard Ghanem
Machine Learning
日本大学: 関与なし(対象大学)
2026 · ICML
MoLF: Mixture-of-Latent-Flow for Pan-Cancer Spatial Gene Expression Prediction from HistologySusu Hu, Stefanie Speidel
Machine Learning
日本大学: 関与なし(対象大学)
2026 · ICML
MoLoRA: Composable Specialization via Per-Token Adapter RoutingShrey Shah, Justin Wagle
Machine Learning
日本大学: 関与なし(対象大学)
2026 · ICML
MoRGen: Mixture-of-Resolutions Generative Forecasting for Irregularly Sampled Medical Time-Series DataNassim Oufattole, Matthew McDermott, Collin Stultz
Machine Learning
日本大学: 関与なし(対象大学)
2026 · ICML
MoSA: Motion-constrained Stress Adaptation for Mitigating Real-to-Sim Gap in Continuum Dynamics via Learning Residual AnisotropyJiaxu Wang, Junhao He, Jingkai SUN, Yi Gu, Yunyang Mo, Jiahang Cao, Qiang Zhang, Renjing Xu
Machine Learning
日本大学: 関与なし(対象大学)
2026 · ICML
MoSE: Mixture of Slimmable Experts for Efficient and Adaptive Language ModelsNurbek Tastan, Stefanos Laskaridis, Karthik Nandakumar, Samuel Horváth
Machine Learning
日本大学: 関与なし(対象大学)
2026 · ICML
MoSSP: A Momentum-Based Single-Loop Stochastic Penalty Method for Nonconvex Constrained DC-regularized OptimizationLuxuan Li, Chunfeng Cui, Xiao Wang
Machine Learning
日本大学: 関与なし(対象大学)
2026 · ICML
MoST: Mixing Speech and Text with Modality-Aware Mixture of ExpertsYuxuan Lou, Kai Yang, Yang You
Machine Learning
日本大学: 関与なし(対象大学)
2026 · ICML
MoVie: Multimodal Video Compression with Text GuidanceJiaqi Hu, Haoji Hu, Heming Sun, Lianrui Mu
Machine Learning
日本大学: 横浜国立大学
2026 · ICML
MobileFusion: Mobile-Friendly Infrared and Visible Image Fusion via Structural Re-parameterizationYufa Duan, Jialing Huang, Yingying Wang, Weimin Cai, Xinghao Ding, Xiaotong Tu
Machine Learning
日本大学: 関与なし(対象大学)
2026 · ICML
Mobility-Embedded POIs: Learning What A Place Is and How It Is Used from Human MovementMaria Despoina Siampou, Shushman Choudhury, Shang-Ling Hsu, Neha Arora, Cyrus Shahabi
Machine Learning
日本大学: 関与なし(対象大学)
2026 · ICML
Modality-Decoupled Online Recursive EditingSiyuan Li, Youyuan Zhang, Fangming Liu, Jing Li
Machine Learning
日本大学: 関与なし(対象大学)
2026 · ICML
Mode Seeking meets Mean Seeking for Fast Long Video GenerationShengqu Cai, Weili Nie, Chao Liu, Julius Berner, Lvmin Zhang, Nanye Ma, Hansheng Chen, Maneesh Agrawala, Leonidas Guibas, Gordon Wetzstein, Arash Vahdat
Machine Learning
日本大学: 関与なし(対象大学)
2026 · ICML
Model Fusion via RetrofittingPhoomraphee Luenam, Andreas Spanopoulos, Amit Sant, Sotiris Anagnostidis, Thomas Hofmann, Sidak Pal Singh
Machine Learning
日本大学: 関与なし(対象大学)
2026 · ICML
Model Merging Scaling Laws in Large Language ModelsYuanyi Wang, Yanggan Gu, Yiming Zhang, Qi ZHOU, Zhaoyi Yan, Congkai Xie, Xinyao Wang, Jianbo Yuan, Hongxia Yang
Machine Learning
日本大学: 関与なし(対象大学)
2026 · ICML
Model Monotonicity in Autobidding Auctions: When Do Better Predictions Lead to Better Outcomes?Ashwinkumar Badanidiyuru
Machine Learning
日本大学: 関与なし(対象大学)
2026 · ICML
Model-Based Diffusion Sampling for Predictive Control in Offline Decision MakingHaldun Balim, Na Li, Yilun Du
Machine Learning
日本大学: 関与なし(対象大学)
2026 · ICML
Model-Dowser: Data-Free Importance Probing to Mitigate Catastrophic Forgetting in Multimodal Large Language ModelsHyeontaek Hwang, DINH SON NGUYEN, Daeyoung Kim
Machine Learning
日本大学: 関与なし(対象大学)
2026 · ICML
Model-Free Robust Average-Reward Reinforcement Learning with Sample Complexity AnalysisZachary Roch, George Atia, Yue Wang
Machine Learning
日本大学: 関与なし(対象大学)
2026 · ICML
Model-Preserving Adaptive RoundingAlbert Tseng, Zhaofeng Sun, Chris De Sa
Machine Learning
日本大学: 関与なし(対象大学)
2026 · ICML
Modeling Attributional Style at Scale: A Dataset and Analysis for Psychological Attribution Assessment and ReframingQiang Zhou, Hanzhen Zhu, Pan Wang, Rui Tu, Huaizhi Qu, Zhuoran Wang, Xin Hu, Lei Li, Tianlong Chen, Jingtong Hu
Machine Learning
日本大学: 関与なし(対象大学)
2026 · ICML
Modeling Covariate Transition for Efficient Estimation of Longitudinal Treatment Effects in Randomized ExperimentsNaoki Chihara, Tatsushi Oka, Yasuko Matsubara, Yasushi Sakurai, Shota Yasui
Machine Learning
日本大学: 慶應義塾大学 / 大阪大学
2026 · ICML
Modeling Hierarchical Thinking in Large Reasoning ModelsG M Shahariar, Erfan Shayegani, Ali Nazari, Nael Abu-Ghazaleh
Machine Learning
日本大学: 関与なし(対象大学)
2026 · ICML
Modeling Long-Tail Relations in the Operating Room via In-Context Multimodal LearningBoqiang Xu, Wei Zhang, Ding Ma, Jian Liang, Zhenan Sun, Zhen Lei
Machine Learning
日本大学: 名古屋大学
2026 · ICML
Modeling Spectral Energy Shifts in Spatio-Temporal Graph Anomaly DetectionYilin Liu, Hongchao Zhang, Ahmad Taha, Taylor T Johnson, Meiyi Ma
Machine Learning
日本大学: 関与なし(対象大学)
2026 · ICML
Modeling Temporal scRNA-seq Data with Latent Gaussian Process and Optimal TransportMehmet Yigit Balik, Harri Lähdesmäki
Machine Learning
日本大学: 関与なし(対象大学)
2026 · ICML
Modelling Attention with Aitchison Geometry: Token Distinguishability and Temperature ScalingSam Hilton-Jones, Timothy Norman, Zhanxing Zhu
Machine Learning
日本大学: 関与なし(対象大学)
2026 · ICML
Models Under SCOPE: Scalable and Controllable Routing via Pre-hoc ReasoningQi Cao, Shuhao Zhang, Ruizhe Zhou, Ruiyi Zhang, Peijia Qin, Pengtao Xie
Machine Learning
日本大学: 関与なし(対象大学)
2026 · ICML
ModernVBERT: Towards Smaller Visual Document RetrieversPaul Teiletche, Quentin Macé, Max Conti, António Loison, Gautier Viaud, Pierre Colombo, Manuel Faysse
Machine Learning
日本大学: 関与なし(対象大学)
2026 · ICML
Modular Pretraining Enables Access ControlEthan Roland, Murat Cubuktepe, Erick Martinez, Stijn Servaes, Keenan Pepper, Michael Vaiana, Diogo de Lucena, Judd Rosenblatt, Addie Foote, Cem Anil, Alex Cloud
Machine Learning
日本大学: 関与なし(対象大学)
2026 · ICML
MolAlign3D: Enhancing Fixed-Dimensional E(3)-Equivariant Latent Space for High-Fidelity 3D Molecular Reconstruction and EditingZitao Chen, Jiatong Ji, Yinjun Jia, Wei-Ying Ma, Yanyan Lan
Machine Learning
日本大学: 関与なし(対象大学)
2026 · ICML
Moment Matching Q-LearningYiyan Edgar, Sifei Liu, Weitong Zhang
Machine Learning
日本大学: 関与なし(対象大学)
2026 · ICML
Momentum Further Constrains Sharpness at the Edge of Stochastic StabilityArseniy Andreyev, Advikar Ananthkumar, Marc Walden, Tomaso A Poggio, Pierfrancesco Beneventano
Machine Learning
日本大学: 関与なし(対象大学)
2026 · ICML
Monitorability as a Free Gift: How RLVR Spontaneously Aligns ReasoningZidi Xiong, Shan Chen, Himabindu Lakkaraju
Machine Learning
日本大学: 関与なし(対象大学)
2026 · ICML
Monitoring MonitorabilityMelody Guan, Miles Wang, Micah Carroll, Zehao Dou, Annie Wei, Marcus Williams, Benjamin Arnav, Joost Huizinga, Ian Kivlichan, Amelia Glaese, Jakub Pachocki, Bowen Baker
Machine Learning
日本大学: 関与なし(対象大学)
2026 · ICML
MonoScale: Scaling Multi-Agent System with Monotonic ImprovementShuai Shao, Yixiang Liu, Bingwei Lu, Weinan Zhang
Machine Learning
日本大学: 関与なし(対象大学)
2026 · ICML
Monotonic Variational Gaussian Process for Efficient Data CollectionDonghyun Lee, Young Myoung Ko
Machine Learning
日本大学: 関与なし(対象大学)
2026 · ICML
More Capable, Less Cooperative? When LLMs Fail at Zero-Cost CollaborationAdvait Yadav, Sidney Black, Oliver Sourbut
Machine Learning
日本大学: 関与なし(対象大学)
2026 · ICML
More Edits, More Stable: Understanding the Lifelong Normalization in Sequential Model EditingXin Ma, Wei Chen, Qi Liu, Derong Xu, Zhi Zheng, Tong Xu, Enhong Chen
Machine Learning
日本大学: 関与なし(対象大学)
2026 · ICML
More Sail than Ballast: Addressing Harmful Knowledge Leakage in the Expansive Reasoning Space of LRMsQibing Ren, Xinhao Song, Ke Fan, Lijun Li, Zhanpeng Zhou, Gongshen Liu, Junchi Yan, Lizhuang Ma, Jing Shao
Machine Learning
日本大学: 関与なし(対象大学)
2026 · ICML
Mosaic: Runtime-Efficient Multi-Agent Embodied PlanningKunjal Panchal, Saayan Mitra, Sunav Choudhary, Victor Bursztyn, Somdeb Sarkhel, Hui Guan
Machine Learning
日本大学: 関与なし(対象大学)
2026 · ICML
Mosaic: Unlocking Over 30$\times$ Context Length for Diffusion LLMs Inference via Global Memory Planning and Dynamic Peak TamingLiang Zheng, Bowen Shi, Yitao Hu, Jiawei Zhang, Ruofan Li, Guotao Yang, Zhixin Zhao, Zhengchao Wang, Sheng Chen, Wenxin Li, Dezhi Ran, Tao Xie, Keqiu Li
Machine Learning
日本大学: 関与なし(対象大学)
2026 · ICML
MoshiRAG: Asynchronous Knowledge Retrieval for Full-Duplex Speech Language ModelsChung-Ming Chien, Manu Orsini, Eugene Kharitonov, Neil Zeghidour, Karen Livescu, Alexandre Défossez
Machine Learning
日本大学: 関与なし(対象大学)
2026 · ICML
MotiMotion: Motion-Controlled Video Generation with Visual ReasoningHsin-Ying Lee, Hanwen Jiang, Yiqun Mei, Jing Shi, Ming-Hsuan Yang, Zhixin Shu
Machine Learning
日本大学: 関与なし(対象大学)
2026 · ICML
Motion Attribution for Video GenerationXindi Wu, Despoina Paschalidou, Jun Gao, Antonio Torralba, Laura Leal-Taixé, Olga Russakovsky, Sanja Fidler, Jonathan Lorraine
Machine Learning
日本大学: 関与なし(対象大学)
2026 · ICML
Motion Dynamics Learning for Few-Shot Embodied AdaptationSibo He, Weiying Xie, Daixun Li, Junhao Zhong, Jiayun Tian, Yunke Wang, Leyuan Fang, Gang He, Yunsong Li
Machine Learning
日本大学: 関与なし(対象大学)
2026 · ICML
Motion Planning in Compressed Representation SpacesLukas Lao Beyer, Sertac Karaman
Machine Learning
日本大学: 関与なし(対象大学)
2026 · ICML
Motion-Aware Caching for Efficient Autoregressive Video GenerationJing Xu, Yuexiao Ma, Xuzhe Zheng, WANG, Shiwei Liu, Chenqian Yan, Xiawu Zheng, Rongrong Ji, Fei Chao, Songwei Liu
Machine Learning
日本大学: 関与なし(対象大学)
2026 · ICML
Motion-Residual Conflict-Aware Time Reversal for Generative InbetweeningZhenbang zhang, Zihui Cui, Haythem El-Messiry, Renmin Han, Zhiqiang Xu
Machine Learning
日本大学: 関与なし(対象大学)
2026 · ICML
MotionGRPO: Overcoming Low Intra-Group Diversity in GRPO-Based Egocentric Motion RecoveryNanjie Yao, Junlong Ren, Wenhao Shen, Hao Wang
Machine Learning
日本大学: 関与なし(対象大学)
2026 · ICML
MotionMAR: Multi-scale Auto-Regressive Human Motion Reconstruction from Sparse ObservationsYuhua Luo, Junsheng Zhang, Mengyin Liu, Xincheng Lin, Ming Yan, Zhudi Chen, Chenglu Wen, Lan Xu, Siqi Shen, Cheng Wang
Machine Learning
日本大学: 関与なし(対象大学)
2026 · ICML
Move-Then-Operate: Behavioral Phasing for Human-Like Robotic ManipulationHaoming Xu, Lei Lei, Jie Gu, Chu Tang, Jingmin Chen, Rui-Qi Wang
Machine Learning
日本大学: 関与なし(対象大学)
2026 · ICML
Moving Out: Physically-grounded Human-AI CollaborationXuhui Kang, Sung-Wook Lee, Haolin Liu, Yuyan Wang, Yen-Ling Kuo
Machine Learning
日本大学: 関与なし(対象大学)
2026 · ICML
MuCO: Generative Peptide Cyclization Empowered by Multi-stage Conformation OptimizationYitian Wang, Zhao Yang, Angxiao Yue, Wentao Guo, Yaning Cui, Hongteng Xu
Machine Learning
日本大学: 関与なし(対象大学)
2026 · ICML
MuLoCo: Muon is a Practical Inner Optimizer for DiLoCoBenjamin Thérien, Xiaolong Huang, Aaron Defazio, Irina Rish, Eugene Belilovsky
Machine Learning
日本大学: 関与なし(対象大学)
2026 · ICML
MulFCoder: Framework-conditioned Multi-agent for MLLM-based Multi-framework Front-end Code GenerationJie Wu, Haoran Ma, Shisong Tang, Yulin Xu, Xiaoyu Kang, Jiechao Gao
Machine Learning
日本大学: 関与なし(対象大学)
2026 · ICML
Multi-Adapter Representation Interventions via Energy CalibrationManjiang Yu, Hongji Li, Junwei Chen, Xue Li, Priyanka Singh, YANG CAO, Lijie Hu
Machine Learning
日本大学: 東京科学大学
2026 · ICML
Multi-Agent Reinforcement Learning with Submodular RewardWenjing Chen, Chengyuan Qian, Shuo Xing, Yi Zhou, Victoria Crawford
Machine Learning
日本大学: 関与なし(対象大学)
2026 · ICML
Multi-Agent Teams Hold Experts BackAneesh Pappu, Batu El, Hancheng Cao, Carmelo di Nolfo, Yanchao Sun, Meng Cao, James Zou
Machine Learning
日本大学: 関与なし(対象大学)
2026 · ICML
Multi-Distribution Robust Conformal PredictionYUQI YANG, Ying Jin
Machine Learning
日本大学: 関与なし(対象大学)
2026 · ICML
Multi-Head Attention as a Source of Catastrophic Forgetting in MoE TransformersAnrui Chen, Ruijun Huang, Xin Zhang, Fang DONG(董方), Hengjie Cao, Zhendong Huang, Yifeng Yang, Mengyi Chen, Jixian Zhou, Mingzhi Dong, Yujiang Wang, Jinlong Hou, Qin Lv, Robert Dick, Yuan Cheng, Tun Lu, Fan Yang, Li Shang
Machine Learning
日本大学: 関与なし(対象大学)
2026 · ICML
Multi-Head LatentMoE and Head Parallel: Communication-Efficient and Deterministic MoE ParallelismChenwei Cui, Rockwell Jackson, Benjamin Joseph Herrera, Ana Tarano, Hannah Kerner
Machine Learning
日本大学: 関与なし(対象大学)
2026 · ICML
Multi-Integration of Labels Across Categories for Component Identification in Multi-trial Time SeriesNoga Mudrik, Yuxi Chen, Gal Mishne, Adam Charles
Machine Learning
日本大学: 関与なし(対象大学)
2026 · ICML
Multi-Label Learning with Contrastive Cluster Self-Supervision for 3D Hierarchical Semantic SegmentationShuyu Cao, Chongshou Li, Jie Xu, Tianrui Li, Na Zhao
Machine Learning
日本大学: 関与なし(対象大学)
2026 · ICML
Multi-Label Test-Time Adaptation with Bayesian Conditional PriorsQiru Li, Ao Zhou, Zhiwei Jiang, Zifeng Cheng, Cong Wang, Yafeng Yin, Qing Gu
Machine Learning
日本大学: 関与なし(対象大学)
2026 · ICML
Multi-Level Strategic Classification: Incentivizing Improvement through Promotion and Relegation DynamicsZiyuan Huang, Lina Alkarmi, Mingyan Liu
Machine Learning
日本大学: 関与なし(対象大学)
2026 · ICML
Multi-Objective Bayesian Optimization via Adaptive $\varepsilon$-Constraint DecompositionYaohong Yang, Sammie Katt, Samuel Kaski
Machine Learning
日本大学: 関与なし(対象大学)
2026 · ICML
Multi-Objective Learning for Diffusion Models: A Statistical Theory under Semi-Supervised LearningZiheng Cheng, Yixiao Huang, Hanlin Zhu, Haoran Geng, Somayeh Sojoudi, Jitendra Malik, Pieter Abbeel, Xin Guo
Machine Learning
日本大学: 関与なし(対象大学)
2026 · ICML
Multi-Objective Preference Optimization: Improving Human Alignment of Generative ModelsAkhil Agnihotri, Rahul Jain, Deepak Ramachandran, Zheng Wen
Machine Learning
日本大学: 関与なし(対象大学)
2026 · ICML
Multi-Objective Protein Design via Memory-Aware Test-Time Scaling in Diffusion ModelsMing Yang, Xin Zheng, Yi Li, YIZHEN ZHENG, Huan Yee Koh, Yanqing Guo, Xiaofeng Cao, Shirui Pan
Machine Learning
日本大学: 関与なし(対象大学)
2026 · ICML
Multi-Round Human–AI Collaboration with User-Specified RequirementsSima Noorani, Shayan Kiyani, Hamed Hassani, George Pappas
Machine Learning
日本大学: 関与なし(対象大学)
2026 · ICML
Multi-Scale Wavelet Transformers for Operator Learning of Dynamical SystemsXuesong Wang, Michael Groom, Rafael Oliveira, He Zhao, Terence O'kane, Edwin V. Bonilla
Machine Learning
日本大学: 関与なし(対象大学)
2026 · ICML
Multi-Task Bayesian In-Context LearningQingyang Zhu, Eric Oermann, Kyunghyun Cho
Machine Learning
日本大学: 関与なし(対象大学)
2026 · ICML
Multi-Task GRPO: Reliable LLM Reasoning Across TasksShyam Sundhar Ramesh, Xiaotong Ji, Matthieu Zimmer, Sangwoong Yoon, Zhiyong Wang, Haitham Bou Ammar, Aurelien Lucchi, Ilija Bogunovic
Machine Learning
日本大学: 関与なし(対象大学)
2026 · ICML
Multi-View Causal Discovery without Non-Gaussianity: Identifiability and AlgorithmsAmbroise Heurtebise, Lemir Omar Chehab, Pierre Ablin, Alexandre Gramfort, Aapo Hyvarinen
Machine Learning
日本大学: 関与なし(対象大学)
2026 · ICML
Multi-Way Representation AlignmentAkshit Achara, Tatiana Gaintseva, Matéo Mahaut, Pritish Chakraborty, Viktor Johansson, Melih Barsbey, Emanuele Rodolà, Donato Crisostomi
Machine Learning
日本大学: 関与なし(対象大学)
2026 · ICML
Multi-agent imitation learning with function approximation: linear Markov games and beyondLuca Viano, Till Freihaut, Emanuele Nevali, Volkan Cevher, Matthieu Geist, Giorgia Ramponi
Machine Learning
日本大学: 関与なし(対象大学)
2026 · ICML
Multi-marginal temporal Schrödinger Bridge Matching from unpaired dataThomas Gravier, Thomas Boyer, Auguste Genovesio
Machine Learning
日本大学: 関与なし(対象大学)
2026 · ICML
Multi-scale Explainer for Graph Neural NetworksLutong Wu, Shiying Cheng, Zhiqiang Wang, Jianqing Liang, Peng Song, Xizhao Luo, Jiye Liang
Machine Learning
日本大学: 関与なし(対象大学)
2026 · ICML
Multi-task Linear Regression without Eigenvalue Lower Bounds: Adaptivity, Robustness, and SafetySeok-Jin Kim
Machine Learning
日本大学: 関与なし(対象大学)
2026 · ICML
Multi-timescale Reinforcement Learning by Value ReconstructionZhan Su, Peixi Peng, Xinyu Hu, Cong Li, Yisen Zhao, Zhuojian Li, Yonghong Tian, Fanqi Shen
Machine Learning
日本大学: 関与なし(対象大学)
2026 · ICML
Multi-view Consistent Latent Action Learning for World Modeling and ControlShenghua Wan, Xiaohai Hu, Xunlan Zhou, lei yuan, Le Gan, De-Chuan Zhan
Machine Learning
日本大学: 関与なし(対象大学)
2026 · ICML
MultiBreak: A Scalable and Diverse Multi-turn Jailbreak Benchmark for Evaluating LLM SafetyJialin Song, Xiaodong Liu, Weiwei Yang, Wuyang Chen, Mingqian Feng, Xuekai Zhu, Jianfeng Gao
Machine Learning
日本大学: 関与なし(対象大学)
2026 · ICML
MultiHal: Multilingual Dataset for Knowledge-Graph Grounded Evaluation of LLM HallucinationsErnests Lavrinovics, Russa Biswas, Katja Hose, Johannes Bjerva
Machine Learning
日本大学: 関与なし(対象大学)
2026 · ICML
MultiLoReFT: Decoupling Shared and Modality-Specific Subspaces in Multimodal Learning via Low-Rank Representation Fine-TuningSana Tonekaboni, Viktoria Schuster, Caroline Uhler
Machine Learning
日本大学: 関与なし(対象大学)
2026 · ICML
MultiPriv: Benchmarking Individual-Level Privacy Reasoning in Vision-Language ModelsXiongtao Sun, HUI LI, Jiaming Zhang, Yujie Yang, Kaili Liu, Ruxin Feng, Wen Tan, Wei Yang Bryan Lim
Machine Learning
日本大学: 関与なし(対象大学)
2026 · ICML
Multicalibration Yields Better MatchingsRiccardo Colini Baldeschi, Simone Di Gregorio, Simone Fioravanti, Federico Fusco, Ido Guy, Daniel Haimovich, Stefano Leonardi, Fridolin Linder, Lorenzo Perini, Matteo Russo, Cem Sirin, Niek Tax
Machine Learning
日本大学: 関与なし(対象大学)
2026 · ICML
Multilingual Safety Alignment Via Sparse Weight EditingJiaming Liang, Zhaoxin Wang, Handing Wang
Machine Learning
日本大学: 関与なし(対象大学)