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
Latent Reasoning VLA: Latent Thinking and Prediction for Vision-Language-Action Models
Shuanghao Bai, Jing Lyu, Wanqi Zhou, Zhe Li, Dakai Wang, Lei Xing, Xiaoguang Zhao, Pengwei Wang, Zhongyuan Wang, Cheng Chi, Badong Chen, Shanghang Zhang
Machine Learning
日本大学: 関与なし（対象大学）
2026 · ICML
Latent Reasoning in TRMs is Secretly a Policy Improvement Operator
Arip Asadulaev, Rayan Banerjee, Fakhri Karray, Martin Takac
Machine Learning
日本大学: 関与なし（対象大学）
2026 · ICML
Latent Representation Alignment for Offline Goal-Conditioned Reinforcement Learning
Hyungkyu Kang, Byeongchan Kim, Min-hwan Oh
Machine Learning
日本大学: 関与なし（対象大学）
2026 · ICML
Latent Space Robust Optimization of Neural Processes with Aligned Stratified Order-Statistic Loss Reduction
Qi Tao, Jiarong Wen, Jing Yang, Guanlin Wu, Zhang Kaiyu, Yiqin Lv, Wumei Du, Xingxing Liang, Qi Wang
Machine Learning
日本大学: 関与なし（対象大学）
2026 · ICML
Latent Spherical Flow Policy for Reinforcement Learning with Combinatorial Actions
Lingkai Kong, Anagha Satish, Hezi Jiang, Akseli Kangaslahti, Andrew Ma, Wenbo Chen, Mingxiao Song, Lily Xu, Milind Tambe
Machine Learning
日本大学: 関与なし（対象大学）
2026 · ICML
Latent Thoughts Tuning: Bridging Context and Reasoning with Fused Information in Latent Tokens
Weihao Liu, Dehai Min, Lu Cheng
Machine Learning
日本大学: 関与なし（対象大学）
2026 · ICML
Latent-Guided Cooperative Energy-Based Models
Cong Geng, Xue Han, Ye Yuan, Qiang Hu, Xin Huang, Ruiqiao Bai, JUNLAN FENG
Machine Learning
日本大学: 関与なし（対象大学）
2026 · ICML
LatentChem: From Textual CoT to Latent Thinking in Chemical Reasoning
Xinwu Ye, Yicheng Mao, Yuxuan Liao, Jia Zhang, Yimeng (Yoyo) Liu, Hao Li, Fang Wu, Zhiwei Li, Zehong Wang, Zhiyuan Liu, Zhenfei Yin, Li Yuan, Phil Torr, Huan Sun, xiangxiang Zeng, Mengdi Wang, Le Cong, Shenghua Gao, Robert Tang
Machine Learning
日本大学: 関与なし（対象大学）
2026 · ICML
LatentLens: Revealing Highly Interpretable Visual Tokens in LLMs
Benno Krojer, Perampalli Shravan Nayak, Oscar Mañas, Vaibhav Adlakha, Desmond Elliott, Siva Reddy, Marius Mosbach
Machine Learning
日本大学: 関与なし（対象大学）
2026 · ICML
Lavida-R1: Advancing Reasoning for Unified Multimodal Diffusion Language Models
Shufan Li, Yuchen Zhu, Kangning Liu, Zhe Lin, Yongxin Chen, Molei Tao, Aditya Grover, Jiuxiang Gu, Jason Kuen
Machine Learning
日本大学: 関与なし（対象大学）
2026 · ICML
Layer-Centric Factors of Variation Disentanglement for Task- and Model-Agnostic Generalization
Hee-Jun Jung, Jongmin Park, Minwoo Kang, Hoyong Kim, Kangil Kim
Machine Learning
日本大学: 関与なし（対象大学）
2026 · ICML
Layer-wise Gradient Disentanglement: Decoupling Semantics and Preferences in Direct Preference Optimization
Mengyang Li, Shuang Liu, Zhong Zhang
Machine Learning
日本大学: 関与なし（対象大学）
2026 · ICML
LayerT2V: A Unified Multi-Layer Video Generation Framework
Guangzhao Li, Kangrui Cen, Baixuan Zhao, Yi Xin, Siqi Luo, Guangtao Zhai, Lei Zhang, Xiaohong Liu
Machine Learning
日本大学: 関与なし（対象大学）
2026 · ICML
LazyAttention: Efficient Retrieval-Augmented Generation with Deferred Positional Encoding
Haocheng Xia, Mihir Pamnani, Hanxi Fang, Supawit Chockchowwat, Yongjoo Park
Machine Learning
日本大学: 関与なし（対象大学）
2026 · ICML
Leaderboard Incentives: Model Rankings under Strategic Post-Training
Yatong Chen, Guanhua Zhang, Moritz Hardt
Machine Learning
日本大学: 関与なし（対象大学）
2026 · ICML
Leak@$k$: Unlearning Does Not Make LLMs Forget Under Probabilistic Decoding
Hadi Reisizadeh, Jiajun Ruan, Yiwei Chen, Soumyadeep Pal, Sijia Liu, Mingyi Hong
Machine Learning
日本大学: 関与なし（対象大学）
2026 · ICML
LeakGFN: Robust Molecular Generation in Generative Flow Networks via Flow Decomposition
Hwanhee Kim, Seungyeon Choi, Sanghyun Park
Machine Learning
日本大学: 関与なし（対象大学）
2026 · ICML
Learn from A Rationalist: Distilling Intermediate Interpretable Rationales
Jiayi Dai, Randy Goebel
Machine Learning
日本大学: 関与なし（対象大学）
2026 · ICML
Learn from Your Mistakes: Tree-like Self-Play for Secure Code LLMs
Wenqi Chen, Ziyan Zhang, Bin Wang, Lin Liu, Hengheng Zhang, Zhengsu Chen
Machine Learning
日本大学: 関与なし（対象大学）
2026 · ICML
Learn to Merge: Meta-Learning for Adaptive Multi-Task Model Merging
Jun Chen, Qin Zhang, Weizhi Zhang, Xiao Luo, Philip Yu, Ziyue Qiao
Machine Learning
日本大学: 関与なし（対象大学）
2026 · ICML
Learn to Think: Improving Multimodal Reasoning through Vision-Aware Self-Improvement Training
Qihuang Zhong, Liang Ding, Wenjie Xuan, Juhua Liu, Bo Du, Dacheng Tao
Machine Learning
日本大学: 関与なし（対象大学）
2026 · ICML
Learn to change the world: Multi-level reinforcement learning with model-changing actions
Ziqing Lu, Babak Hassibi, Lifeng Lai, Weiyu Xu
Machine Learning
日本大学: 関与なし（対象大学）
2026 · ICML
Learn-to-learn on Arbitrary Textual Conditioning: A Hypernetwork-Driven Meta-gated LLM
Luo Ji, Qi Qin, Ningyuan Xi, Teng Chen, Qingqing Gu, Hongyan Li
Machine Learning
日本大学: 関与なし（対象大学）
2026 · ICML
Learnability-Driven Knowledge Assimilation for Class-Incremental Semantic Segmentation
Xinyue Zhang, Xu Zou, Wanjia Luo, Yanjie Wang, Jiahuan Zhou, Sheng Zhong, Luxin Yan
Machine Learning
日本大学: 関与なし（対象大学）
2026 · ICML
Learnability-Informed Fine-Tuning of Diffusion Language Models
Shubham Parashar, Atharv Chagi, Jacob Helwig, Lakshmi Madhavarapu, Sushil Vemuri, James Caverlee, Dileep Kalathil, Shuiwang Ji
Machine Learning
日本大学: 関与なし（対象大学）
2026 · ICML
Learnable Kernel Density Estimation for Graphs and Its Application to Graph-Level Anomaly Detection
Xudong Wang, Ziheng Sun, Chris Ding, Jicong Fan
Machine Learning
日本大学: 関与なし（対象大学）
2026 · ICML
LearniBridge: Learnable Calibration of Feature Caching for Diffusion Models Acceleration
Xuyue Huang, Zhe Chen, Wang Shen, Xiao-Ping Zhang
Machine Learning
日本大学: 関与なし（対象大学）
2026 · ICML
Learning $U$-Statistics with Active Inference
Xiaoning Wang, Huo Yuyang, Liuhua Peng, Changliang Zou
Machine Learning
日本大学: 関与なし（対象大学）
2026 · ICML
Learning 3D-Gaussian Simulators from RGB Videos
Mikel Zhobro, Andreas René Geist, Georg Martius
Machine Learning
日本大学: 関与なし（対象大学）
2026 · ICML
Learning Adaptive Perturbation-Conditioned Contexts for Robust Transcriptional Response Prediction
Yinhua Piao, Hyomin Kim, SEONGHWAN KIM, Yunhak Oh, Junhyeok Jeon, Sangyeon Hwang, Jaechang Lim, Woo Youn Kim, Chanyoung Park, Sungsoo Ahn
Machine Learning
日本大学: 関与なし（対象大学）
2026 · ICML
Learning Adaptive Topology with FiLM-Guided Distillation for Tertiary Structure-Based RNA Design
Zixun Zhang, Yuncheng Jiang, Yuzhe Zhou, Jiayou Zheng, Shuguang Cui, Zhen Li
Machine Learning
日本大学: 関与なし（対象大学）
2026 · ICML
Learning Anisotropic Value Geometry with Finsler Reinforcement Learning
Jumman Hossain, Nirmalya Roy
Machine Learning
日本大学: 関与なし（対象大学）
2026 · ICML
Learning Attribute–Affordance Hierarchies in Hyperbolic Space for Open-Vocabulary 3D Object Affordance Grounding
Yuxuan Wang, Tong Li, Yihang Zhu, Guangtao Lyu, Yukuan Min, Chenghao Xu, Jiexi Yan, Xu Yang, Cheng Deng
Machine Learning
日本大学: 関与なし（対象大学）
2026 · ICML
Learning Biophysical Models of Large-Scale Multineuronal Data To Enable Precise Neurostimulation
Amrith Lotlikar, Ian Tanoh, Praful Vasireddy, Andrew Lanpouthakoun, Michael A Sommeling, Ramandeep Vilkhu, A.J. Phillips, Alexander Sher, Alan Litke, Scott Linderman, EJ Chichilnisky, Subhasish Mitra
Machine Learning
日本大学: 関与なし（対象大学）
2026 · ICML
Learning Cardiac Latent Representations in Vectorcardiogram Space
Bosong Huang, Panzhen Zhao, Zengxiang Li, Patricia Lee, Wei Jin, Alan Liew, Ming Jin, Shirui Pan
Machine Learning
日本大学: 関与なし（対象大学）
2026 · ICML
Learning Coherent Representations: A Topological Approach to Interpretability
Sigurd Gaukstad, Melvin Vaupel, Valdemar Kargård Olsen, Erik Hermansen, Benjamin Dunn
Machine Learning
日本大学: 関与なし（対象大学）
2026 · ICML
Learning Compressed Shape-Aware Molecular Representations for Virtual Screening
Robin Winter, Julian Cremer, Djork-Arné Clevert
Machine Learning
日本大学: 関与なし（対象大学）
2026 · ICML
Learning Context-Conditioned Predicate Semantics via Prototype Feedback
NamGyu Jung, Chang Choi
Machine Learning
日本大学: 関与なし（対象大学）
2026 · ICML
Learning Coupled Continuous-Time Latent Dynamics from Irregular Events
Jiankai Zuo, Yang Zhang, Yu Zhang, Jiarui Liang, YAYING ZHANG
Machine Learning
日本大学: 関与なし（対象大学）
2026 · ICML
Learning Credal Ensembles via Distributionally Robust Optimization
Kaizheng Wang, Ghifari Adam Faza, Fabio Cuzzolin, Siu Lun Chau, David Moens, Hans Hallez
Machine Learning
日本大学: 関与なし（対象大学）
2026 · ICML
Learning Decentralized LLM Collaboration with Multi-Agent Actor Critic
Shuo Liu, Tianle Chen, Ryan Amiri, Christopher Amato
Machine Learning
日本大学: 関与なし（対象大学）
2026 · ICML
Learning Discrete Diffusion on Graphs via Free-Energy Gradient Flows
Dario Rancati, Jan Maas, Francesco Locatello
Machine Learning
日本大学: 関与なし（対象大学）
2026 · ICML
Learning Discriminative and Generalizable Anomaly Detector for Dynamic Graph with Limited Supervision
Yuxing Tian, Yiyan Qi, Fengran Mo, Weixu Zhang, Jian Guo, Jian-Yun Nie
Machine Learning
日本大学: 関与なし（対象大学）
2026 · ICML
Learning Disentangled Multi-Agent World Model for Decentralized Control
Di Xue, Jing Jiang, Shaowei Zhang, Wenhao Guo, lei yuan, Zongzhang Zhang, Yang Yu
Machine Learning
日本大学: 関与なし（対象大学）
2026 · ICML
Learning Dynamic Stability Landscapes in Synchronization Networks
Christian Nauck, Junyou Zhu, Michael Lindner, Frank Hellmann
Machine Learning
日本大学: 関与なし（対象大学）
2026 · ICML
Learning Dynamics of Zeroth-Order Optimization: A Kernel Perspective
Zhe Li, Bicheng Ying, Zidong Liu, Haibo Yang
Machine Learning
日本大学: 関与なし（対象大学）
2026 · ICML
Learning Efficient Guardrails for Compliance
Xiaofei Wen, Wenjie Mo, Yanan Xie, Peng Qi, Muhao Chen
Machine Learning
日本大学: 関与なし（対象大学）
2026 · ICML
Learning Fingerprints for Medical Time Series with Redundancy-Constrained Information Maximization
Huayu Li, ZhengXiao He, Xiwen Chen, Jingjing Wang, Siyuan Tian, Jinghao Wen, Ao Li
Machine Learning
日本大学: 関与なし（対象大学）
2026 · ICML
Learning Flexible Generalization in Video Quality Assessment by Bringing Device and Viewing Condition Distributions
Nickolay Safonov, Dmitriy Vatolin
Machine Learning
日本大学: 関与なし（対象大学）
2026 · ICML
Learning GUI Grounding with Spatial Reasoning from Visual Feedback
Yu Zhao, Wei-Ning Chen, Huseyin Inan, Samuel Kessler, Lu Wang, Lukas Wutschitz, Fangkai Yang, Chaoyun Zhang, Pasquale Minervini, Saravanakumar Rajmohan, Robert A Sim
Machine Learning
日本大学: 関与なし（対象大学）
2026 · ICML
Learning Gaussian Graphical Models from a Glauber Trajectory Without Mixing
Eric Shen, Tony Wu, Mahbod Majid, Ankur Moitra
Machine Learning
日本大学: 関与なし（対象大学）
2026 · ICML
Learning Gaussian Mixture-distributed Prototypes for 3D Scene Graph Generation from RGB-D Sequences
Rongxing Ding, Hongyu Qu, Xinguang Xiang, Pengpeng Li, Xiangbo Shu
Machine Learning
日本大学: 関与なし（対象大学）
2026 · ICML
Learning General Causal Structures with Hidden Dynamic Process for Climate Analysis
Minghao Fu, Biwei Huang, Zijian Li, Yujia Zheng, Ignavier Ng, Guangyi Chen, Yingyao Hu, Kun Zhang
Machine Learning
日本大学: 関与なし（対象大学）
2026 · ICML
Learning Generalizable Skill Policy with Data-Efficient Unsupervised RL
Jongchan Park, Seungjun Oh, Seungho Baek, Yusung Kim
Machine Learning
日本大学: 関与なし（対象大学）
2026 · ICML
Learning Generalized Label Distributions
Haitao Wu, Weiwei Li, Kun Yue, Xiuyi Jia
Machine Learning
日本大学: 関与なし（対象大学）
2026 · ICML
Learning Generalized Trackers with Elastic Token Budgets
Yinchao Ma, Jianpeng Yang, Yuyang Tang, Jie Xiao, Dengqing Yang, Tianzhu Zhang
Machine Learning
日本大学: 関与なし（対象大学）
2026 · ICML
Learning Global Representation from Queries for Vectorized HD Map Construction
Shoumeng Qiu, Xinrun Li, Yang Long, Xiangyang Xue, Varun Ojha, Jian Pu
Machine Learning
日本大学: 関与なし（対象大学）
2026 · ICML
Learning Graph Foundation Models on Riemannian Graph-of-Graphs
Haokun Liu, Zezhong Ding, Xike Xie
Machine Learning
日本大学: 関与なし（対象大学）
2026 · ICML
Learning Hamiltonian Dynamics at Scale: A Differential-Geometric Approach
Katharina Friedl, Noémie Jaquier, Mika Liao, Danica Kragic
Machine Learning
日本大学: 関与なし（対象大学）
2026 · ICML
Learning Hamiltonian Flow Maps: Mean Flow Consistency for Large-Timestep Molecular Dynamics
Winfried Ripken, Michael Plainer, Gregor Lied, Thorben Frank, Oliver Unke, Stefan Chmiela, Frank Noe, Klaus-robert Mueller
Machine Learning
日本大学: 関与なし（対象大学）
2026 · ICML
Learning High-Dimensional Parity Functions with Product Networks using Gradient Descent
Guillaume Larue, Louis-Adrien Dufrène, Quentin Lampin, Hadi Ghauch, Ghaya Rekaya-Ben Othman
Machine Learning
日本大学: 関与なし（対象大学）
2026 · ICML
Learning High-Frequency Continuous Action Chunks in Latent Space
Kunyun Wang, Yuhang Zheng, Yupeng Zheng, Jieru Zhao, Wenchao Ding
Machine Learning
日本大学: 関与なし（対象大学）
2026 · ICML
Learning Human-Robot Collaboration via Heterogeneous-Agent Lyapunov Policy Optimization
Hao Zhang, Yaru Niu, Yikai Wang, Ding Zhao, Eric Tseng
Machine Learning
日本大学: 関与なし（対象大学）
2026 · ICML
Learning Interpretable Options by Identifying Reward Diffusion Bottlenecks in Reinforcement Learning
Yiming Fei, Ziming Wang, Rui Yan, Huajin Tang
Machine Learning
日本大学: 関与なし（対象大学）
2026 · ICML
Learning Junta Distributions, Quantum Junta States, and QAC$^0$ Circuits
Jinge Bao, Francisco Escudero Gutiérrez
Machine Learning
日本大学: 関与なし（対象大学）
2026 · ICML
Learning Latent Action World Models in the Wild
Quentin Garrido, Tushar Nagarajan, Basile Terver, Nicolas Ballas, Yann LeCun, Michael Rabbat
Machine Learning
日本大学: 関与なし（対象大学）
2026 · ICML
Learning Locally, Revising Globally: Global Reviser for Federated Learning with Noisy Labels
Yuxin Tian, Mouxing Yang, Yuhao Zhou, Jian Wang, Qing Ye, Tongliang Liu, Gang Niu, Jiancheng Lv
Machine Learning
日本大学: 関与なし（対象大学）
2026 · ICML
Learning Long Range Spatio-Temporal Representations over Continuous Time Dynamic Graphs with State Space Models
Ayushman Raghuvanshi, Thummaluru Siddartha Reddy, Sundeep Prabhakar Chepuri, Mahesh Chandran
Machine Learning
日本大学: 関与なし（対象大学）
2026 · ICML
Learning Manifold Data with Flow Matching
Sophia Pi, Mingcheng Lu, Maojiang Su, Weimin Wu, Jerry Yao-Chieh Hu, Han Liu
Machine Learning
日本大学: 関与なし（対象大学）
2026 · ICML
Learning Manifold and Itô Dynamics with Branched Neural Rough Differential Equations
Luke Thompson, Dai Shi, Lequan Lin, Junbin Gao, Andi Han
Machine Learning
日本大学: 関与なし（対象大学）
2026 · ICML
Learning Molecular Semantic Invariant Representation with Prototype Constraint
Zhiqiang Li, Jianqing Liang, Zhiqiang Wang, Xizhao Luo, Jiye Liang
Machine Learning
日本大学: 関与なし（対象大学）
2026 · ICML
Learning More from Less: Unlocking Internal Representations for Benchmark Compression
Yueqi Zhang, Jin Hu, Shaoxiong Feng, Peiwen Yuan, Xinglin Wang, Yiwei Li, Jiayi Shi, Chuyi Tan, Ji Zhang, Boyuan Pan, Yao Hu, Kan Li
Machine Learning
日本大学: 関与なし（対象大学）
2026 · ICML
Learning Multi-Agent Coordination via Sheaf-ADMM
Jeffrey Seely, Bartłomiej Cupiał, Llion Jones
Machine Learning
日本大学: 関与なし（対象大学）
2026 · ICML
Learning Multi-Scale Hypergraph for High-Order Brain Connectivity Analysis
Jaeyoon Sim, Soojin Hwang, Seunghun Baek, Guorong Wu, Won Hwa Kim
Machine Learning
日本大学: 関与なし（対象大学）
2026 · ICML
Learning Multi-Timescale Abstractions for Hierarchical Combinatorial Planning
Vivienne Huiling Wang, Tinghuai Wang, Joni Pajarinen
Machine Learning
日本大学: 関与なし（対象大学）
2026 · ICML
Learning Normalized Energy Models for Linear Inverse Problems
Nicolas M Zilberstein, Santiago Segarra, Eero Simoncelli, Florentin Guth
Machine Learning
日本大学: 関与なし（対象大学）
2026 · ICML
Learning Partial Concept Classes and Universal Rates Under Massart Noise
Ariel Avital, Klim Efremenko, Steve Hanneke
Machine Learning
日本大学: 関与なし（対象大学）
2026 · ICML
Learning Permutation Distributions via Reflected Diffusion on Ranks
Sizhuang He, Yangtian Zhang, Shiyang Zhang, David van Dijk
Machine Learning
日本大学: 関与なし（対象大学）
2026 · ICML
Learning Permutation from Structure Without Supervision
Ran Eisenberg, Ofir Lindenbaum
Machine Learning
日本大学: 関与なし（対象大学）
2026 · ICML
Learning Permutation-invariant Macroscopic Dynamics
Zhichao Han, Mengyi Chen, Qianxiao Li
Machine Learning
日本大学: 関与なし（対象大学）
2026 · ICML
Learning Protein Structure-Function Relationships through Knowledge-guided Representation Decomposition
Mingqing Wang, Zhiwei Nie, ATHANASIOS VASILAKOS, Yonghong He, Zhixiang Ren
Machine Learning
日本大学: 関与なし（対象大学）
2026 · ICML
Learning Query-Aware Budget-Tier Routing for Runtime Agent Memory
Haozhen Zhang, Haodong Yue, Tao Feng, Quanyu Long, Jianzhu Bao, Bowen Jin, Weizhi Zhang, Xiao Li, Jiaxuan You, Chengwei Qin, Wenya Wang
Machine Learning
日本大学: 関与なし（対象大学）
2026 · ICML
Learning Randomized Reductions
Ferhat Erata, Orr Paradise, Thanos Typaldos, Timos Antonopoulos, ThanhVu Nguyen, Shafi Goldwasser, Ruzica Piskac
Machine Learning
日本大学: 関与なし（対象大学）
2026 · ICML
Learning Rate Annealing Improves Tuning Robustness in Stochastic Optimization
Amit Attia, Tomer Koren
Machine Learning
日本大学: 関与なし（対象大学）
2026 · ICML
Learning Rate Scaling across LoRA Ranks and Transfer to Full Finetuning
Nan Chen, Soledad Villar, Soufiane Hayou
Machine Learning
日本大学: 関与なし（対象大学）
2026 · ICML
Learning Reward–Cost Balance in Safe RL via Score-Based World Models
Yuetian Wang, Dianxi Shi, Yuanze Wang, Huanhuan Yang, Shiming Song, Chunping Qiu
Machine Learning
日本大学: 関与なし（対象大学）
2026 · ICML
Learning Rewrite-Invariant Reasoning with Targeted Alternation Training
Mousa Arraf, Ido Guy, Kira Radinsky
Machine Learning
日本大学: 関与なし（対象大学）
2026 · ICML
Learning Robust Multi-Agent Policies via Selective Adversarial Fault Induction
David H Mguni, Yaqi Sun, Haojun Chen, Wanrong Yang, Amir Darabi, Larry Orimoloye, Yaodong Yang
Machine Learning
日本大学: 関与なし（対象大学）
2026 · ICML
Learning Self-Correction in Vision–Language Models via Rollout Augmentation
Yi Ding, Ziliang Qiu, Bolian Li, Ruqi Zhang
Machine Learning
日本大学: 関与なし（対象大学）
2026 · ICML
Learning Self-Interpretation from Interpretability Artifacts: Training Lightweight Adapters on Vector-Label Pairs
Keenan Pepper, Alex McKenzie, Florin Pop, Stijn Servaes, Martin Leitgab, Michael Vaiana, Judd Rosenblatt, Michael Graziano, Diogo de Lucena
Machine Learning
日本大学: 関与なし（対象大学）
2026 · ICML
Learning Situated Awareness in the Real World
Chuhan Li, Rilyn Han, Joy Hsu, Yongyuan Liang, Rajiv Dhawan, Jiajun Wu, Ming-Hsuan Yang, Xin (Eric) Wang
Machine Learning
日本大学: 関与なし（対象大学）
2026 · ICML
Learning Sparse Visual Representations via Spatial-Semantic Factorization
Theodore Z. Zhao, Sid Kiblawi, Jianwei Yang, Naoto Usuyama, Reuben Tan, Noel Codella, Tristan Naumann, Hoifung Poon, Mu Wei
Machine Learning
日本大学: 関与なし（対象大学）
2026 · ICML
Learning Stochastic Bridges for Video Object Removal via Video-to-Video Translation
Zijie Lou, Xiangwei Feng, Jiaxin Wang, Jiangtao Yao, Fei Che, Tianbao Liu, WU CHENGJING, Xiaochao Qu, Luoqi Liu, Ting Liu
Machine Learning
日本大学: 関与なし（対象大学）
2026 · ICML
Learning Structured Reasoning via Tractable Trajectory Control
Po-Nien Kung, Zhen Yang, Jeffrey Luo, Cheng-Fu Yang, Haikang Deng, Zi-Yi Dou, Yinfei Yang, Nanyun Peng, Zhe Gan, Kai-Wei Chang
Machine Learning
日本大学: 関与なし（対象大学）
2026 · ICML
Learning Task-Sufficient World Models by Synergizing Agentic Exploration and Structured Modeling
Fan Feng, Yujia Zheng, Minghao Fu, Yongqiang Chen, Guangyi Chen, Kevin Murphy, Biwei Huang, Kun Zhang
Machine Learning
日本大学: 関与なし（対象大学）
2026 · ICML
Learning Taxonomic Trees with Hierarchical Representation Regularization for Large Multimodal Models
Hulingxiao He, Zhi Tan, Yuxin Peng
Machine Learning
日本大学: 関与なし（対象大学）
2026 · ICML
Learning Tight Rejection Boundaries without Negatives for Strict One-Class Audio Deepfake Detection
Yuze Zhao, Kuiyuan Zhang, Zhongyun Hua, Yushu Zhang, Qing Liao, Wei Jiang
Machine Learning
日本大学: 関与なし（対象大学）
2026 · ICML
Learning Transferable Interaction Primitives from Game Videos for Humanoid Locomotion
Xiangming Zhu, Huayu Deng, Haoran Zhao, Yiwei Hao, Yunbo Wang
Machine Learning
日本大学: 関与なし（対象大学）
2026 · ICML
Learning Treatment Allocations with Risk Control Under Partial Identifiability
Sofia Ek, Dave Zachariah
Machine Learning
日本大学: 関与なし（対象大学）
2026 · ICML
Learning Treatment Representations for Downstream Instrumental Variable Regression
Shiangyi Lin, Hui Lan, Vasilis Syrgkanis
Machine Learning
日本大学: 関与なし（対象大学）