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
Training-Free Hashing-Based Attention via Binary Principal Components
Daohai Yu, Zhanpeng Zeng, Keyu Chen, Wenhao Li, Zhifeng Shen, Luxi Lin, Ruizhi Qiao, Xing Sun, Rongrong Ji
Machine Learning
日本大学: 関与なし（対象大学）
2026 · ICML
Training-Free Multimodal Large Language Model Orchestration
Tianyu Xie, Yuexiao Ma, Yuhang Wu, Wang Chen, Jiayi Ji, Tat-Seng Chua, Xiawu Zheng, Rongrong Ji
Machine Learning
日本大学: 関与なし（対象大学）
2026 · ICML
Training-Free Rate-Distortion-Perception Traversal With Diffusion
Yuhan Wang, Suzhi Bi, Angela Yingjun Zhang
Machine Learning
日本大学: 関与なし（対象大学）
2026 · ICML
Training-Free Vector Quantization via Gaussian VAEs
Tongda Xu, Wendi Zheng, Jiajun He, Jose Miguel Hernandez-Lobato, Yan Wang, Ya-Qin Zhang, Jie Tang
Machine Learning
日本大学: 関与なし（対象大学）
2026 · ICML
Training-Trajectory-Aware Token Selection
Zhanming Shen, Jiaqi Hu, Zeyu Qin, Hao Chen, Wentao Ye, Zenan Huang, Yihong Zhuang, Guoshan Lu, Junlin Zhou, Junbo Zhao
Machine Learning
日本大学: 関与なし（対象大学）
2026 · ICML
Training–Inference Consistent Segmented Execution for Long-Context LLMs
Xianpeng Shang, Jiang Li, Zehua Duo, Qianyi Cai, Xiangdong Su
Machine Learning
日本大学: 関与なし（対象大学）
2026 · ICML
Trajectory Consistency for One-Step Generation on Euler Mean Flows
Zhiqi Li, Yuchen Sun, Duowen Chen, Jinjin He, Bo Zhu
Machine Learning
日本大学: 関与なし（対象大学）
2026 · ICML
Trajectory Seriation via Spectral Tangent Alignment and Global Embedding
Zhixin Zhou, Navin Souda, Arash Amini
Machine Learning
日本大学: 関与なし（対象大学）
2026 · ICML
Trajectory Stitching for Solving Inverse Problems with Flow-Based Models
Alexander Denker, Zeljko Kereta, Carola-Bibiane Schönlieb, Moshe Eliasof
Machine Learning
日本大学: 関与なし（対象大学）
2026 · ICML
Trajectory-Aware Certified Decentralized Unlearning via SGD Stability
Hengliang Wu, Jiale Yang, Shuzhen Chen, Di Wang, Dongxiao Yu, Youming Tao
Machine Learning
日本大学: 関与なし（対象大学）
2026 · ICML
Trajectory-Aware Heuristic Learning for Combinatorial Search
Mustafa Seddiqi, Marta Kersten-Oertel, Tiberiu Popa
Machine Learning
日本大学: 関与なし（対象大学）
2026 · ICML
Trajectory-Aware Spiking DiTs Conversion via Membrane Potential Error-Feedback
Haoran Fang, Tianxing Man, Xingchen Li, Wanli Shi, Jinjie Fang, Bin Gu
Machine Learning
日本大学: 関与なし（対象大学）
2026 · ICML
Trajectory-Level Data Augmentation for Offline Reinforcement Learning
Tobias Schmähling, Matthias Burkhardt, Tobias Windisch
Machine Learning
日本大学: 関与なし（対象大学）
2026 · ICML
Trajectory-Level Speculative Decoding for Diffusion Language Models
Tianxiang Pan, Baitao Gong, Mo Guang, Hongwei Yong, Tianpeng Jiang, Yaqian Li, Zheng Cao, Kaiwen Long
Machine Learning
日本大学: 関与なし（対象大学）
2026 · ICML
Trajectory-Stabilized Inference for Diffusion-Based Video Inpainting
Zhanhe Zhang, Jiahua Li, Xu Yang, Kun Wei, Cheng Deng
Machine Learning
日本大学: 関与なし（対象大学）
2026 · ICML
TranX-Adapter: Bridging Artifacts and Semantics within MLLMs for Robust AI-generated Image Detection
Wenbin Wang, Yuge Huang, Jianqing Xu, Yue Yu, Jiangtao Yan, Shouhong Ding, Pan Zhou, Yong Luo
Machine Learning
日本大学: 関与なし（対象大学）
2026 · ICML
TransLight: Image-Guided Customized Lighting Control with Generative Decoupling
Zongming Li, Lianghui Zhu, Haocheng Shen, Longjin Ran, Wenyu Liu, Xinggang Wang
Machine Learning
日本大学: 関与なし（対象大学）
2026 · ICML
TransNormal: Dense Visual Semantics for Diffusion-based Transparent Object Normal Estimation
Mingwei Li, Hehe Fan, Yi Yang
Machine Learning
日本大学: 関与なし（対象大学）
2026 · ICML
Transfer Learning in High-dimensional Ising Models
Joonho Kim, Seyoung Park
Machine Learning
日本大学: 関与なし（対象大学）
2026 · ICML
Transfer Learning in Nonparametric Regression with Deep ReLU Networks
Junpeng Ren, Carlos Misael Madrid Padilla, Yanzhen Chen, OSCAR HERNAN MADRID PADILLA
Machine Learning
日本大学: 関与なし（対象大学）
2026 · ICML
Transferable Reinforcement Learning via Probabilistic Latent Embeddings and Dynamic Policy Adaptation for Sim-to-Real Deployment
Gengyue Han, Yiheng Feng
Machine Learning
日本大学: 関与なし（対象大学）
2026 · ICML
Transform Trained Transformer for Accelerating Native 4K Video Generation
Jiangning Zhang, Junwei Zhu, Teng Hu, Yabiao Wang, Donghao Luo, Weijian Cao, Zhenye Gan, Xiaobin Hu, Zhucun Xue, Xiangtai Li, Chengjie Wang, Yong Liu
Machine Learning
日本大学: 関与なし（対象大学）
2026 · ICML
Transformed Latent Variable Multi-Output Gaussian Processes
Xiaoyu Jiang, Xinxing Shi, Sokratia Georgaka, Magnus Rattray, Mauricio Álvarez
Machine Learning
日本大学: 関与なし（対象大学）
2026 · ICML
Transformer Circuits Can Realize Clustering Algorithms
Kenneth Clarkson, Lior Horesh, Takuya Ito, Charlotte Park, Parikshit Ram
Machine Learning
日本大学: 関与なし（対象大学）
2026 · ICML
Transformers Can Learn Posterior Predictive Distributions In-Context
Gyeonghun Kang, Changwoo Lee, Xiang Cheng
Machine Learning
日本大学: 関与なし（対象大学）
2026 · ICML
Transformers Efficiently Perform In-Context Logistic Regression via Normalized Gradient Descent
Chenyang Zhang, Yuan Cao
Machine Learning
日本大学: 関与なし（対象大学）
2026 · ICML
Transformers Learn the Optimal DDPM Denoiser for Multi-Token GMMs
Hongkang Li, Hancheng Min, Rene Vidal
Machine Learning
日本大学: 関与なし（対象大学）
2026 · ICML
Transformers Provably Learn Algorithmic Solutions for Graph Connectivity, But Only with the Right Data
Qilin Ye, Deqing Fu, Robin Jia, Vatsal Sharan
Machine Learning
日本大学: 関与なし（対象大学）
2026 · ICML
Transformers learn factored representations
Adam Shai, Loren Amdahl-Culleton, Casper Christensen, Henry R Bigelow, Fernando Rosas, Alexander Boyd, Eric Alt, Kyle Ray, Paul Riechers
Machine Learning
日本大学: 関与なし（対象大学）
2026 · ICML
Transformers with RL or SFT Provably Learn Sparse Boolean Functions, But Differently
Bochen Lyu, Yiyang Jia, Xiaohao Cai, Zhanxing Zhu
Machine Learning
日本大学: 関与なし（対象大学）
2026 · ICML
Transforming Weather Data from Pixel to Latent Space
Sijie Zhao, Feng Liu, Xueliang Zhang, Hao Chen, Tao Han, JUNCHAO GONG, Ran Tao, Pengfeng Xiao, Xinyu Gu, LEI BAI
Machine Learning
日本大学: 関与なし（対象大学）
2026 · ICML
Transitive Representation Learning Enhances Histopathology Annotation
Moritz Schaefer, Zoe Piran, Nils Philipp Walter, Animesh Awasthi, Christoph Bock, Jure Leskovec, Zinaida Good
Machine Learning
日本大学: 関与なし（対象大学）
2026 · ICML
Transitivity Meets Cyclicity: Explicit Preference Decomposition for Dynamic Large Language Model Alignment
Yucong Huang, Xiucheng Li, Kaiqi Zhao, Jing Li
Machine Learning
日本大学: 関与なし（対象大学）
2026 · ICML
Translation Heads: Disentangling meaning from language in LLM-based machine translation
Théo Lasnier, Armel Randy Zebaze, Djamé Seddah, Rachel Bawden, Benoît Sagot
Machine Learning
日本大学: 関与なし（対象大学）
2026 · ICML
Transolver-3: Scaling Up Transformer Solvers to Industrial-Scale Geometries
Hang Zhou, Haixu Wu, Haonan Shangguan, Yuezhou Ma, Huikun Weng, Jianmin Wang, Mingsheng Long
Machine Learning
日本大学: 関与なし（対象大学）
2026 · ICML
Transport Clustering: Solving Low-Rank Optimal Transport via Clustering
Henri Schmidt, Peter Halmos, Benjamin Raphael
Machine Learning
日本大学: 関与なし（対象大学）
2026 · ICML
Transport and Merge: Cross-Architecture Merging for Large Language Models
Chenhang Cui, Binyun Yang, Fei Shen, Yuxin Chen, Jingnan Zheng, Xiang Wang, An Zhang, Tat-Seng Chua
Machine Learning
日本大学: 関与なし（対象大学）
2026 · ICML
Transport or Discard: Robust Unbalanced Optimal Transport for Cross-Domain Policy Adaptation
Wenyu Chen, Yujia Zhang, Wei Guo, Linli Ma, Yanbo Wang, Pinle Qin, Jianchao Zeng
Machine Learning
日本大学: 関与なし（対象大学）
2026 · ICML
Transporting Task Vectors across Different Architectures without Training
Filippo Rinaldi, Aniello Panariello, Giacomo Salici, Angelo Porrello, Simone Calderara
Machine Learning
日本大学: 関与なし（対象大学）
2026 · ICML
Treatment Responder Classification with Abstention
Haoxiang Wang, Haoxuan Li, Ziyan Wang, Zhiheng Zhang, Aoqi Zuo, Erdun Gao, Kun Zhang, Mingming Gong
Machine Learning
日本大学: 関与なし（対象大学）
2026 · ICML
Tree-Structured Orthonormal Decomposition of the Aitchison Simplex
Daisuke Yamada, Qijun Zhang, Travis Pence, Barbara Bendlin, Federico Rey, Vikas Singh
Machine Learning
日本大学: 関与なし（対象大学）
2026 · ICML
TreeCUA: Efficiently Scaling GUI Automation with Tree-Structured Verifiable Evolution
Deyang Jiang, Jing Huang, Xuanle Zhao, Lei Chen, Liming Zheng, Fanfan Liu, Haibo Qiu, Peng Shi, Zhixiong Zeng
Machine Learning
日本大学: 関与なし（対象大学）
2026 · ICML
TreePO: Enhancing Policy Efficacy and Inference Efficiency with Tree Modeling
Yizhi Li, Qingshui Gu, Zhoufutu Wen, Ziniu Li, Ruibin Yuan, Tianshun Xing, Shuyue Guo, Tuney Zheng, 周欣, Xingwei Qu, Wangchunshu Zhou, Zheng Zhang, Wei Shen, Wei Xue, Qian Liu, Chenghua Lin, Jian Yang, Ge Zhang, Wenhao Huang
Machine Learning
日本大学: 関与なし（対象大学）
2026 · ICML
Trees to Flows and Back: Unifying Decision Trees and Diffusion Models
Sai Niranjan Ramachandran, Suvrit Sra
Machine Learning
日本大学: 関与なし（対象大学）
2026 · ICML
Tri-Scale Neural ODEs for Continuous Multi-Omics Disease Modeling
Shohaib Shaffiey, Massimiliano Pierobon
Machine Learning
日本大学: 関与なし（対象大学）
2026 · ICML
TriAttention: Efficient Long Reasoning with Trigonometric KV Compression
Weian Mao, Xi Lin, Wei Huang, Yuxin Xie, Tianfu Fu, Bohan Zhuang, Song Han, Yukang Chen
Machine Learning
日本大学: 関与なし（対象大学）
2026 · ICML
TriForces: Augmenting Atomistic GNNs for Transferable Representations
Ali Ramlaoui, Alexandre Duval, Hannah Bull, Victor Schmidt, Hugues Talbot, Fragkiskos Malliaros, Joseph Musielewicz
Machine Learning
日本大学: 関与なし（対象大学）
2026 · ICML
Triadic Dynamics Aware Diffusion Posterior Sampling for Inverse Problems: Optimizing Guidance and Stochasticity Schedules
Junseo Bang, Dong Ju Mun, Hoigi Seo, Seongmin Hong, Se Young Chun
Machine Learning
日本大学: 関与なし（対象大学）
2026 · ICML
Trifuse: Enhancing Attention-Based GUI Grounding via Multimodal Fusion
Longhui Ma, Di Zhao, Siwei Wang, Zhao Lv, Miao Wang
Machine Learning
日本大学: 関与なし（対象大学）
2026 · ICML
TritonGym: A Benchmark for Agentic LLM Workflows in Triton GPU Code Generation
Yue Guan, Yichen Lin, Xu Zhao, Jianzhu Yao, Xinwei Qiang, zhongkai yu, Pramod Viswanath, Yufei Ding, Adnan Aziz
Machine Learning
日本大学: 関与なし（対象大学）
2026 · ICML
Trojan-Speak: Bypassing Constitutional Classifiers with No Jailbreak Tax via Adversarial Finetuning
Bilgehan Sel, Xuanli He, Alwin Peng, Ming Jin, Jerry Wei
Machine Learning
日本大学: 関与なし（対象大学）
2026 · ICML
Trust Functions: Near Lossless Weak-to-Strong Generalization by Learning to Trust the Weak Teacher
Arda Uzunoglu, Alvin Zhang, Daniel Khashabi
Machine Learning
日本大学: 関与なし（対象大学）
2026 · ICML
Trust It or Not: Evidential Uncertainty for Feed-Forward 3D Reconstruction with Trust3R
Zihao Zhu, Wenyuan Zhao, Nuo Chen, Chao Tian, Zhiwen Fan
Machine Learning
日本大学: 関与なし（対象大学）
2026 · ICML
Trust Region Inverse Reinforcement Learning: Explicit Dual Ascent using Local Policy Updates
Anish Abhijit Diwan, Davide Tateo, Christopher Mower, Haitham Bou Ammar, Jan Peters, Oleg Arenz
Machine Learning
日本大学: 関与なし（対象大学）
2026 · ICML
Trust Region Masking for Long-Horizon LLM Reinforcement Learning
Yingru Li, Jiacai Liu, Jiawei Xu, Yuxuan Tong, Ziniu Li, Baoxiang Wang
Machine Learning
日本大学: 関与なし（対象大学）
2026 · ICML
Trust-Region Diffusion Policies for Massively Parallel On-Policy RL
Huy Le, Onur Celik, Denis Blessing, Tai Hoang, Claas Voelcker, Axel Brunnbauer, Felix Richter, Michael Volpp, Gerhard Neumann
Machine Learning
日本大学: 関与なし（対象大学）
2026 · ICML
Trustworthy Federated Label Distribution Learning under Annotation Quality Disparity
Junxiang Wu, Zhiqiang Kou, Hongwei Zeng, Wenke Huang, Biao Liu, Hanlin Gu, Yuheng Jia, Di Jiang, Yang Liu, Xin Geng
Machine Learning
日本大学: 関与なし（対象大学）
2026 · ICML
TrustworthyQENN: A Quantum Evidential Neural Network Based on Complex-Valued Contrastive Learning for Uncertainty Pattern Classification
Xiaolong Chen, Fuyuan Xiao, Xiaohong Zhang, Zehong Cao, Chin-teng Lin
Machine Learning
日本大学: 関与なし（対象大学）
2026 · ICML
TruthRL: Incentivizing Truthful LLMs via Reinforcement Learning
Zhepei Wei, Xiao Yang, Kai Sun, Jiaqi Wang, Rulin Shao, Jingxiang Chen, Mohammad Kachuee, Teja Gollapudi, Yiwei Liao, Nicolas SCHEFFER, Rakesh Wanga, Anuj Kumar, Yu Meng, Scott Yih, Xin Dong
Machine Learning
日本大学: 関与なし（対象大学）
2026 · ICML
Truthfulness Does Not Scale Like Reasoning: Why Polling Fails as a Proxy Verifier
Yegor Denisov-Blanch, Joshua Kazdan, Jessica Chudnovsky, Rylan Schaeffer, Sheng Guan, Soji Adeshina, Sanmi Koyejo
Machine Learning
日本大学: 関与なし（対象大学）
2026 · ICML
TsLLM: Augmenting LLMs for General Time Series Understanding and Prediction
Felix Parker, Nimeesha Chan, Chi Zhang, Kimia Ghobadi
Machine Learning
日本大学: 関与なし（対象大学）
2026 · ICML
Tucker Attention: A generalization of approximate attention mechanisms
Timon Klein, Jonas Kusch, Sebastian Sager, Stefan Schnake, Steffen Schotthöfer
Machine Learning
日本大学: 関与なし（対象大学）
2026 · ICML
TuneAhead: Predicting Fine-tuning Performance Before Training Begins
Yuxiang Luo, Haonan Long, Chen Wang, Qiqi Duan, Xiaotian Lin, Yanwei XU, Yuyu Luo, Weikai Yang, Nan Tang
Machine Learning
日本大学: 関与なし（対象大学）
2026 · ICML
Tuning the Implicit Regularizer of Masked Diffusion Language Models: Enhancing Generalization via Insights from $k$-Parity
Jianhao Huang, Baharan Mirzasoleiman
Machine Learning
日本大学: 関与なし（対象大学）
2026 · ICML
Tuning-Free One-Class Discriminant Learning for Tabular Anomaly Detection
Xuan-Ha Nguyen, Vu Duong, VanHoi Nguyen, Kim-Hung Le, Nhien-An Le-Khac
Machine Learning
日本大学: 関与なし（対象大学）
2026 · ICML
Turbo Connection: Reasoning as Information Flow from Higher to Lower Layers
Mohan Tang, Sidi Lu
Machine Learning
日本大学: 関与なし（対象大学）
2026 · ICML
Turbo4DGen: Ultra-Fast Acceleration for 4D Generation
Yuanbin Man, Ying Huang, Zhile Ren, Miao Yin
Machine Learning
日本大学: 関与なし（対象大学）
2026 · ICML
TurboGS: Accelerating 3D Gaussian Splatting via Error-Guided Sparse Pixel Sampling and Optimization
Zheng Dong, Daifei Qiu, Pinxuan Dai, Ke Xu, Jiamin Xu, Lili He, Rynson W Lau, Weiwei Xu
Machine Learning
日本大学: 関与なし（対象大学）
2026 · ICML
Turning Adaptation into Assets: Cross-Domain Bridging for Online Vision-Language Navigation
Zixuan Hu, Xuantuo Huang, Yancheng Li, Yichun Hu, Shengyong Xu, LINGYU DUAN
Machine Learning
日本大学: 関与なし（対象大学）
2026 · ICML
Turning Back Without Forgetting: Selective Backward Refinement for Parameter-Efficient Continual Learning
Anushka Tiwari, Kaiyi Ji
Machine Learning
日本大学: 関与なし（対象大学）
2026 · ICML
Turning Bias into Bugs: Bandit-Guided Style Manipulation Attacks on LLM Judges
XIANGLIN YANG, Bryan Hooi, Gelei Deng, Tianwei Zhang, Jin Song Dong
Machine Learning
日本大学: 関与なし（対象大学）
2026 · ICML
Turning Drift into Constraint: Robust Reasoning Alignment in Non-Stationary Multi-Stream Environments
Xiaoyu Yang, En Yu, Wei Duan, Jie Lu
Machine Learning
日本大学: 関与なし（対象大学）
2026 · ICML
Turning Stale Gradients into Stable Gradients: Coherent Coordinate Descent with Implicit Landscape Smoothing for Lightweight Zeroth-Order Optimization
Chen Liang, Xiatao Sun, Qian Wang, Daniel Rakita
Machine Learning
日本大学: 関与なし（対象大学）
2026 · ICML
Tvcache: A Tool-Value Cache for Post-Training LLM Agents
Abhishek Vijaya Kumar, Bhaskar Kataria, Byungsoo Oh, Emaad Manzoor, Rachee Singh
Machine Learning
日本大学: 関与なし（対象大学）
2026 · ICML
Twice Sequential Monte Carlo for Tree Search
Yaniv Oren, Joery de Vries, Pascal Van der Vaart, Matthijs T. J. Spaan, Wendelin Boehmer
Machine Learning
日本大学: 関与なし（対象大学）
2026 · ICML
TwinQuant: Learnable Subspace Decomposition for 4-Bit LLM Quantization
Haodong WANG, Junjie Liu, Zicong Hong, Qianli Liu, Jian Lin, Song Guo, Xu Chen
Machine Learning
日本大学: 関与なし（対象大学）
2026 · ICML
TwinWeaver: An LLM-Based Foundation Model Framework for Pan-Cancer Digital Twins
Nikita Makarov, Maria Bordukova, Lena von Voithenberg, Estrella Pivel-Villanueva, Sabrina Mielke, Jonathan Wickes, Hanchen Wang, Mingyu Ma, Keunwoo Choi, Kyunghyun Cho, Stephen Ra, Raul Rodriguez-Esteban, Fabian Schmich, Michael Menden
Machine Learning
日本大学: 関与なし（対象大学）
2026 · ICML
Twins: Learn to Predict Unified Representations with Focal Loss
Kaixiong Gong, Xin Cai, Bin Lin, Hao Wang, Yunlong Lin, Mingzhe Zheng, Bohao Li, Jian-Wei Zhang, Miles Yang, Zhao Zhong, Liefeng Bo, Xiangyu Yue
Machine Learning
日本大学: 関与なし（対象大学）
2026 · ICML
Two Calm Ends and the Wild Middle: A Geometric Picture of Memorization in Diffusion Models
Nick Dodson, Xinyu Gao, Qingsong Wang, Yusu Wang, Zhengchao Wan
Machine Learning
日本大学: 関与なし（対象大学）
2026 · ICML
Two Modalities Are Better Than One: Efficient Adversarial Purification via Multimodal Diffusion Models
Mingyuan Bai, Wei Huang, Tenghui Li, Andong Wang, Chao Li, Cesar F Caiafa, Junbin Gao, Qibin Zhao
Machine Learning
日本大学: 関与なし（対象大学）
2026 · ICML
Two-Layer Linear Auto-Regressive Models Estimate Latent States
Yahya Sattar, Sunmook Choi, Leo Maynard-Zhang, Yassir Jedra, Maryam Fazel, Sarah Dean
Machine Learning
日本大学: 関与なし（対象大学）
2026 · ICML
Two-Parameter Flows for Learning Population Dynamics of Physical Systems
Paul Schwerdtner, Tobias Blickhan, Benjamin Peherstorfer
Machine Learning
日本大学: 関与なし（対象大学）
2026 · ICML
Two-Stage Unit Tying for Simplifying Differentiable Logic Gate Networks
Seungheon Lee, Jeongmin Sun, Jaeyong Chung
Machine Learning
日本大学: 関与なし（対象大学）
2026 · ICML
Two-dimensional quantization for geometry-aware audio coding
Tal Shuster, Eliya Nachmani
Machine Learning
日本大学: 関与なし（対象大学）
2026 · ICML
U$^3$CF: Unbiased, Unconfounding, and Unified Causal Framework for Multi-Target Domain Adaptation
Wenxu Wang, Yeqiang Liu, Rui Zhou, Jing Wang, Zhenbo Li, Wenbo Gong
Machine Learning
日本大学: 関与なし（対象大学）
2026 · ICML
U-Cast: A Surprisingly Simple and Efficient Frontier Probabilistic AI Weather Forecaster
Salva Ruhling Cachay, Duncan Watson-Parris, Rose Yu
Machine Learning
日本大学: 関与なし（対象大学）
2026 · ICML
UAV$^2$: A Unified and Adaptive Scheduling Framework for UAV Autopilot System with Reinforcement Learning
Zeying Li, shuai zhao, Chaowen Wu, Boyang Li, Kai Huang
Machine Learning
日本大学: 関与なし（対象大学）
2026 · ICML
UB-SMoE: Universally Balanced Sparse Mixture-of-Experts for Resource-adaptive Federated Fine-tuning of Foundation Models
Van-Tuan Tran, Hong-Hanh Nguyen-Le, Marco Ruffini, Merim Dzaferagic
Machine Learning
日本大学: 関与なし（対象大学）
2026 · ICML
UCPO: Uncertainty-Aware Policy Optimization
Xianzhou Zeng, Jing Huang, Chunmei Xie, Gongrui Nan, Siye Chen, Mengyu Lu, Weiqi Xiong, Qixuan Zhou, Junhao Zhang, Qiang Zhu, Yadong Li, Xingzhong Xu
Machine Learning
日本大学: 関与なし（対象大学）
2026 · ICML
UDM-GRPO: Stable and Efficient Group Relative Policy Optimization for Uniform Discrete Diffusion Models
Jiaqi Wang, Haoge Deng, Ting Pan, Yang Liu, Chengyuan Wang, Fan Zhang, Yonggang Qi, Xinlong Wang
Machine Learning
日本大学: 関与なし（対象大学）
2026 · ICML
UFO: Chain-of-Evaluation for Omni-Condition Alignment in Multi-Modal Image Generation
Danning Zhang, Yijing Lin, Shuhan Zhuang, Mengqi Huang, Shaojin Wu, Shancheng Fang, Zhendong Mao
Machine Learning
日本大学: 関与なし（対象大学）
2026 · ICML
UGround: Towards Unified Visual Grounding with Unrolled Transformers
Rui Qian, Xin Yin, Chuanhang Deng, Zhiyuan Peng, Jian Xiong, Wei Zhai, Dejing Dou
Machine Learning
日本大学: 関与なし（対象大学）
2026 · ICML
UHR-BAT: Budget-Aware Token Compression Vision-Language model for Ultra-High-Resolution Remote Sensing
Yunkai Dang, Minxin Dai, Yuekun Yang, Zhangnanli, Wenbin Li, Feng Miao, Yang Gao
Machine Learning
日本大学: 関与なし（対象大学）
2026 · ICML
UI2Code^N: UI-to-Code Generation as Interactive Visual Optimization
ZHEN YANG, Wenyi Hong, Mingde Xu, Xinyue Fan, Weihan Wang, Jiale Cheng, Xiaotao Gu, Jie Tang
Machine Learning
日本大学: 関与なし（対象大学）
2026 · ICML
UMEM: Unified Memory Extraction and Management Framework for Generalizable Memory
Yongshi Ye, Hui Jiang, Feihu Jiang, Tian Lan, Yichao Du, Biao Fu, Xiaodong Shi, Qianghuai Jia, Longyue Wang, Weihua Luo
Machine Learning
日本大学: 関与なし（対象大学）
2026 · ICML
UOTIP: Unbalanced Optimal Transport Map for Unpaired Inverse Problems
Donggyu Lee, Taekyung Lee, Jaewoong Choi
Machine Learning
日本大学: 関与なし（対象大学）
2026 · ICML
URS: A Unified Neural Routing Solver for Cross-Problem Zero-Shot Generalization
Changliang Zhou, Canhong Yu, Shunyu Yao, Xi Lin, Zhenkun Wang, Yu Zhou, Qingfu Zhang
Machine Learning
日本大学: 関与なし（対象大学）
2026 · ICML
USE: A Unified Self-Ensembling Framework for Test-Time Prompt Tuning
Siru Jiang, Jian Liang, Ran He, Tieniu Tan
Machine Learning
日本大学: 関与なし（対象大学）
2026 · ICML
Ubiquity of Emergent Hebbian Dynamics in Regularized Learning
David Koplow, Tomaso A Poggio, Liu Ziyin
Machine Learning
日本大学: 関与なし（対象大学）
2026 · ICML
UltraHorizon: Benchmarking LLM-Agent Capabilities in Ultra Long-Horizon Scenarios
Haotian Luo, Huaisong Zhang, Xuelin Zhang, Haoyu Wang, Zeyu Qin, Wenjie Lu, Guozheng Ma, Haiying He, Yingsha Xie, Qiyang Zhou, Zixuan Hu, Hongze Mi, Yibo Wang, Naiqiang Tan, Hong Chen, Yi Fung, Chun Yuan, Li Shen
Machine Learning
日本大学: 関与なし（対象大学）