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
Preference-Modulated Structural Attention for Multi-Objective Combinatorial Optimization
Rongsheng Jia, Jun Zhang, Yifan Zhang, Jian Cheng
Machine Learning
日本大学: 関与なし（対象大学）
2026 · ICML
Preference-based Antibody Expression Ranking: Scaling with Large-scale Weak Supervision
Josh Sun, Morteza Babaie, Wenyang hou, Mark Crowley, David Young
Machine Learning
日本大学: 関与なし（対象大学）
2026 · ICML
Prefix-Cache-Aware Data Reordering for LLM-Augmented Database Analytics
Yingze Li, dong wang, Yiming Guo, Yao Chen, Hongzhi Wang, Bingsheng He
Machine Learning
日本大学: 関与なし（対象大学）
2026 · ICML
Prescriptive Scaling Reveals the Evolution of Language Model Capabilities
Hanlin Zhang, Jikai Jin, Vasilis Syrgkanis, Sham Kakade
Machine Learning
日本大学: 関与なし（対象大学）
2026 · ICML
Preserve-Then-Quantize: Balancing Rank Budgets for Quantization Error Reconstruction in LLMs
Yoonjun Cho, Dongjae Jeon, Soeun Kim, Moongyu Jeon, Albert No
Machine Learning
日本大学: 関与なし（対象大学）
2026 · ICML
Preserving Plasticity in Continual Learning via Dynamical Isometry
Andries Rosseau, Robert Müller, Ann Nowe
Machine Learning
日本大学: 関与なし（対象大学）
2026 · ICML
Pressure Reveals Character: Behavioural Alignment Evaluation at Depth
Nora Petrova, John Burden
Machine Learning
日本大学: 関与なし（対象大学）
2026 · ICML
PretrainZero: Reinforcement Active Learning on Pretraining Data
Xingrun Xing, Zhiyuan Fan, Jie Lou, Guoqi Li, Jiajun Zhang, Debing Zhang
Machine Learning
日本大学: 関与なし（対象大学）
2026 · ICML
Pretrained Vision-Language-Action Models are Surprisingly Resistant to Forgetting in Continual Learning
Huihan Liu, Changyeon Kim, Bo Liu, Minghuan Liu, Yuke Zhu
Machine Learning
日本大学: 関与なし（対象大学）
2026 · ICML
Primal-Spectral Generative Modeling: Fast Analytical Generation via Pseudoinverse Lévy Inversion
Zhiyuan Ouyang, Simei Huang, Zuokai Wen, Xiangyun Zhang, Junchi Yan
Machine Learning
日本大学: 関与なし（対象大学）
2026 · ICML
Principle-Evolvable Scientific Discovery via Uncertainty Minimization
Yingming Pu, Tao LIN, Hongyu Chen
Machine Learning
日本大学: 関与なし（対象大学）
2026 · ICML
Principled Confidence Estimation for Deep Computed Tomography
Matteo Gätzner, Johannes Kirschner
Machine Learning
日本大学: 関与なし（対象大学）
2026 · ICML
Principled RL for Flow Matching Emerges from the Chunk-level Policy Optimization
Yifu Luo, Haoyuan Sun, Xinhao Hu, Penghui Du, Keyu Fan, Bo Li, SiNan Du, Xu Wan, Zhiyu Chen, Bo Xia, Yongzhe Chang, Kai Wu, Kun Gai, Tiantian Zhang, Xueqian Wang
Machine Learning
日本大学: 関与なし（対象大学）
2026 · ICML
Principled SVD-based Delta Compression via Quantization Error Minimization
Boya Xiong, Shuo Wang, Weifeng Ge, Guanhua CHEN, Yun Chen
Machine Learning
日本大学: 関与なし（対象大学）
2026 · ICML
Principled Synthetic Data Enables the First Scaling Laws for LLMs in Recommendation
Benyu Zhang, Qiang Zhang, Jianpeng Cheng, Hong-You Chen, Qifei wang, Wei Sun, Shen Li, Jia Li, Jiahao Wu, Xiangjun Fan, Hong Yan
Machine Learning
日本大学: 関与なし（対象大学）
2026 · ICML
Principled Zero-shot Ranking Agents with Tournament Graphs
Sheshansh Agrawal, Thien Nguyen, Douwe Kiela
Machine Learning
日本大学: 関与なし（対象大学）
2026 · ICML
Prior Diffusiveness and Regret in the Linear-Gaussian Bandit
Yifan Zhu, John Duchi, Benjamin Van Roy
Machine Learning
日本大学: 関与なし（対象大学）
2026 · ICML
Prioritize the Process, Not Just the Outcome: Rewarding Latent Thought Trajectories Improves Reasoning in Looped Language Models
Jonathan Williams, Olga Russakovsky, Esin Tureci
Machine Learning
日本大学: 関与なし（対象大学）
2026 · ICML
Prioritized Model Experience Replay
Muxi Tao, jiangtao wen, Yuxing Han
Machine Learning
日本大学: 関与なし（対象大学）
2026 · ICML
Priority-Aware Shapley Value
Kiljae Lee, Ziqi Liu, Weijing Tang, Yuan Zhang
Machine Learning
日本大学: 関与なし（対象大学）
2026 · ICML
Prism-MoE: Efficient Dense-to-MoE Conversion for Visual Autoregressive Generation
Ying Li, Zefang Wang, Zhaode Wang, Zhiwen Chen, chengfei lv, Huan Wang
Machine Learning
日本大学: 関与なし（対象大学）
2026 · ICML
Prism: Spectral-Aware Block-Sparse Attention
Xinghao Wang, Pengyu Wang, Xiaoran Liu, Fangxu Liu, Jason Chu, Kai Song, Xipeng Qiu
Machine Learning
日本大学: 関与なし（対象大学）
2026 · ICML
PrivAct: Internalizing Contextual Privacy Preservation via Multi-Agent Preference Training
Yuhan Cheng, Hancheng Ye, Hai Li, Jingwei Sun, Yiran Chen
Machine Learning
日本大学: 関与なし（対象大学）
2026 · ICML
PrivCode++: Latent-Conditioned Differentially Private Code Generation for Comprehensive Guarantees
Zheng Liu, Chen GONG, Terry Yue Zhuo, Zhou Yang, Kecen Li, Wenlong Meng, Xinwen Hou, Yu Liu, Xiaochen Li
Machine Learning
日本大学: 関与なし（対象大学）
2026 · ICML
PrivGate: Steering Contextual Integrity in LLMs via Latent Space Geometry
Runshan Hu, Yukun Dong, Yingying Huangfu, Ruohan Zhao, Yi Xie, Tieyan Li
Machine Learning
日本大学: 関与なし（対象大学）
2026 · ICML
Privacy Amplification in Differentially Private Zeroth-Order Optimization with Hidden States
Eli Chien, Wei-Ning Chen, Pan Li
Machine Learning
日本大学: 関与なし（対象大学）
2026 · ICML
Privacy-Aware Data Integration for Enhanced Quantile Inference under Heterogeneity
Leheng Cai, Qirui Hu, Shuyuan Wu
Machine Learning
日本大学: 関与なし（対象大学）
2026 · ICML
Privacy-Aware Video Anomaly Detection through Orthogonal Subspace Projection
Lei Wang, Wenxiang Diao, Andrew Busch, Jun Zhou, Yongsheng Gao
Machine Learning
日本大学: 関与なし（対象大学）
2026 · ICML
Privasis: Synthesizing the Largest "Public" Private Dataset from Scratch
Hyunwoo Kim, Niloofar Mireshghallah, Michael Duan, Rui Xin, Stella Li, Jaehun Jung, David Acuna, Qi Pang, Hanshen Xiao, Edward Suh, Sewoong Oh, Yulia Tsvetkov, Pang Wei Koh, Yejin Choi
Machine Learning
日本大学: 関与なし（対象大学）
2026 · ICML
Private Learning with Public Feature Conditioning
Shuli Jiang, Walid Krichene, Nicolas Mayoraz
Machine Learning
日本大学: 関与なし（対象大学）
2026 · ICML
Private and Stable Test-time Adaptation with Differential Privacy
Zefeng Li, Qiaoyue Tang, Mathias Lécuyer, Evan Shelhamer
Machine Learning
日本大学: 関与なし（対象大学）
2026 · ICML
Privately Fine-Tuned LLMs Preserve Temporal Dynamics in Tabular Data
Lucas Rosenblatt, Peihan Liu, Ryan McKenna, Natalia Ponomareva
Machine Learning
日本大学: 関与なし（対象大学）
2026 · ICML
Privileged Information Distillation for Language Models
Emiliano Penaloza, Dheeraj Vattikonda, Nicolas Gontier, Alexandre Lacoste, Laurent Charlin, Massimo Caccia
Machine Learning
日本大学: 関与なし（対象大学）
2026 · ICML
ProAct: A Benchmark and Multimodal Framework for Structure-Aware Proactive Response
Xiaomeng ZHU, Fengming ZHU, Weijie Zhou, Ye Tian, Zhenlin Hu, Yufei Huang, Yuchun Guo, Xinyu Wu, Zhengyou Zhang, Fangzhen Lin, Xuantang Xiong
Machine Learning
日本大学: 関与なし（対象大学）
2026 · ICML
ProConMV: Provenance-Enabled Conceptual Framework for Interpretable Multi-View Diabetic Retinopathy Diagnosis
Xiaoling Luo, Shuo Yang, Qihao Xu, Jiansong Zhang, Zhuoqin Yang, Zhihui Lai, Linlin Shen, Chengliang Liu
Machine Learning
日本大学: 関与なし（対象大学）
2026 · ICML
ProEval: Proactive Failure Discovery and Efficient Performance Estimation for Generative AI Evaluation
Yizheng Huang, Wenjun Zeng, Aditi Kumaresan, Zi Wang
Machine Learning
日本大学: 関与なし（対象大学）
2026 · ICML
ProMeCD: Unifying Long-Tailed and Noisy Label Learning via White-Box Control
Yu Zhu
Machine Learning
日本大学: 関与なし（対象大学）
2026 · ICML
ProMiSE: Protein Multi-State Evaluation Benchmark in Biological Contexts
Bonjae Ku, Seeun Kim, Yubeen Kim, Hahnbeom Park, Chaok Seok
Machine Learning
日本大学: 関与なし（対象大学）
2026 · ICML
ProOPF: Benchmarking and Improving LLMs for Professional-Grade Power Systems Optimization Modeling
Chao Shen, Zihan Guo, Xu Wan, Zhenghao Yang, Yifan Zhang, Wenqi Huang, Jie Song, Zongyan Zhang, Mingyang Sun
Machine Learning
日本大学: 関与なし（対象大学）
2026 · ICML
ProRL: Effective Reinforcement Learning for Proactive Recommendation via Rectified Policy Gradient Estimation
Hongru Hou, Tiehua Mei, Denghui Geng, Jinhui Huang, Ao Xu, Hengrui Chen, Jiaqing Liang, Deqing Yang
Machine Learning
日本大学: 関与なし（対象大学）
2026 · ICML
ProSAR: Prototype-Guided Semantic Augmentation and Refinement for Time Series Contrastive Learning
Caiyi Yang, Chenglin Li, Hao Zhang, Weijia Lu, ZHIFEI YANG, Wenrui Dai, xiaodong Zhang, Xiaofeng Ma, Can Zhang, Junni Zou, Hongkai Xiong
Machine Learning
日本大学: 関与なし（対象大学）
2026 · ICML
Proact-VL: A Proactive VideoLLM for Real-Time AI Companions
Weicai Yan, Yuhong Dai, Qi Ran, Haodong Li, Wang Lin, Tao Jin, Xing Xie, Hao Liao, Jianxun Lian
Machine Learning
日本大学: 関与なし（対象大学）
2026 · ICML
Proactive Defense Benchmark against Deepfake Generation
Joonhyuk Baek, Wonjune Seo, Jae-yun Kim, Saerom Park, Hoki Kim
Machine Learning
日本大学: 関与なし（対象大学）
2026 · ICML
ProactiveLLM: Learning Active Interaction for Streaming Large Language Models
Junlong Tong, Yao Zhang, Anhao Zhao, Yingqi Fan, Yunpu Ma, Xiaoyu Shen
Machine Learning
日本大学: 関与なし（対象大学）
2026 · ICML
ProbMoE: Differentiable Probabilistic Routing for Mixture-of-Experts
Heng Zhao, Zilei Shao, Guy Van den Broeck, Zhe Zeng
Machine Learning
日本大学: 関与なし（対象大学）
2026 · ICML
Probabilistic Bisection Algorithm Provably Achieves Exponential Convergence
Ganghua Wang, Yuwei Cheng, Haifeng Xu
Machine Learning
日本大学: 関与なし（対象大学）
2026 · ICML
Probabilistic Modeling of Latent Agentic Substructures in Deep Neural Networks
Su Hyeong Lee, Risi Kondor, Richard Ngo
Machine Learning
日本大学: 関与なし（対象大学）
2026 · ICML
Probabilistic Performance Guarantees for Multi-Task Reinforcement Learning
Yannik Schnitzer, Mathias Jackermeier, Alessandro Abate, David Parker
Machine Learning
日本大学: 関与なし（対象大学）
2026 · ICML
Probabilistic Retrofitting of Learned Simulators
Cristiana Diaconu, Miles Cranmer, Richard E Turner, Tanya Marwah, Payel Mukhopadhyay
Machine Learning
日本大学: 関与なし（対象大学）
2026 · ICML
Probabilistic Robustness Certificates against Adversarial Attacks
Sara Taheri, Majid Zamani
Machine Learning
日本大学: 関与なし（対象大学）
2026 · ICML
Probabilistic Salient Object Ranking
Rongjin Guo, Guan Huankang, Rynson W Lau
Machine Learning
日本大学: 関与なし（対象大学）
2026 · ICML
Probabilistically-routed Bayesian Additive Spanning Trees for Learning on Constrained Domains
Abhisek Chakraborty, Abhishek Mandal, Anirban Chakraborty
Machine Learning
日本大学: 関与なし（対象大学）
2026 · ICML
Probability of Matching for Batch Multi-Objective Bayesian Optimization
Mingqian Li, Sina Zadeh, Raymundo Arroyave, Xiaoning Qian
Machine Learning
日本大学: 関与なし（対象大学）
2026 · ICML
Probability-Entropy Calibration: An Elastic Indicator for Adaptive Fine-tuning
Wenhao Yu, Shaohang Wei, Jiahong Liu, Yifan Li, Minda Hu, Aiwei Liu, Hao Zhang, Irwin King
Machine Learning
日本大学: 関与なし（対象大学）
2026 · ICML
Probably Approximately Correct Labels
Emmanuel J Candes, Andrew Ilyas, Tijana Zrnic
Machine Learning
日本大学: 関与なし（対象大学）
2026 · ICML
ProbeLLM: Automating Principled Diagnosis of LLM Failures
Yue Huang, Zhengzhe Jiang, Yuchen Ma, Yu Jiang, Xiangqi Wang, Yujun Zhou, Yuexing Hao, kehan guo, Pin-Yu Chen, Marzyeh Ghassemi, Stefan Feuerriegel, Xiangliang Zhang
Machine Learning
日本大学: 関与なし（対象大学）
2026 · ICML
Probing Cross-modal Information Hubs in Audio-Visual LLMs
Jihoo Jung, Chaeyoung Jung, Ji-Hoon Kim, Joon Son Chung
Machine Learning
日本大学: 関与なし（対象大学）
2026 · ICML
Probing How Scalable Table Data Enhances General Long-Context Reasoning
Huaibing Xie, Guoliang Zhao, Yang Liu, Shihan Dou, Siming Huang, Yanling Xiao, Shaolei Wang, Yiting Liu, Cheng Zhang, Shaofan Liu, PlutoZhou
Machine Learning
日本大学: 関与なし（対象大学）
2026 · ICML
Probing RLVR Training Instability through the Lens of Objective-Level Hacking
Yiming Dong, Kun Fu, Haoyu Li, Xinyuan Zhu, Yurou Liu, Lijing Shao, Jieping Ye, Zheng Wang
Machine Learning
日本大学: 関与なし（対象大学）
2026 · ICML
Probing the Geometry of Diffusion Models with the String Method
Elio Moreau, Florentin Coeurdoux, Grégoire Ferré, Eric Vanden-Eijnden
Machine Learning
日本大学: 関与なし（対象大学）
2026 · ICML
Probing the Inductive Bias of Neural Networks through Learning Random Cellular Automata
Jan Disselhoff, Michael Wand
Machine Learning
日本大学: 関与なし（対象大学）
2026 · ICML
Probing the Knowledge Boundary: An Interactive Agentic Framework for Deep Knowledge Extraction
Yuheng Yang, Siqi Zhu, Tao Feng, Ge Liu, Jiaxuan You
Machine Learning
日本大学: 関与なし（対象大学）
2026 · ICML
Problem Distributions as Tasks: Repurposing Meta Learning for Generative Combinatorial Optimization towards Multi-task Pretraining and Adaptation
Wenzheng Pan, Jiale Ma, Nuoyan Chen, Yang Li, Junchi Yan
Machine Learning
日本大学: 関与なし（対象大学）
2026 · ICML
ProcMEM: Learning Reusable Procedural Memory from Experience via Non-Parametric PPO for LLM Agents
QIRUI MI, Zhijian Ma, Mengyue Yang, Yisen Wang, Haoxuan Li, Haifeng Zhang, Jun Wang
Machine Learning
日本大学: 関与なし（対象大学）
2026 · ICML
Procedural Generation Of Algorithm Discovery Tasks in Machine Learning
Alexander D. Goldie, Zilin Wang, Adrian Hayler, Deepak Nathani, Edan Toledo, Ken Thampiratwong, Aleksandra Kalisz, Michael Beukman, Alistair Letcher, Shashank Reddy Chirra, Clarisse Wibault, Theo Wolf, Charles O'Neill, Uljad Berdica, Nicholas Roberts, Saeed Rahmani, Roberta Raileanu, Shimon Whiteson, Jakob Foerster
Machine Learning
日本大学: 関与なし（対象大学）
2026 · ICML
Procedural Pretraining: Warming Up Language Models with Abstract Data
Liangze Jiang, Zachary Shinnick, Anton Hengel, Hemanth Saratchandran, Damien Teney
Machine Learning
日本大学: 関与なし（対象大学）
2026 · ICML
Process Reward Agents for Steering Knowledge-Intensive Reasoning
Jiwoong Sohn, Tomasz Sternal, Kenneth Styppa, Torsten Hoefler, Michael Moor
Machine Learning
日本大学: 関与なし（対象大学）
2026 · ICML
Profiling the Irrational Agent: Cognitive Modeling of LLM Behaviors in Sequential Jailbreaks
Xikang Yang, Biyu Zhou, Xuehai Tang, Jizhong Han, Songlin Hu
Machine Learning
日本大学: 関与なし（対象大学）
2026 · ICML
Progressive Cramming: Reliable Token Compression and What It Reveals
Dmitrii Tarasov, Timofei Lashukov, Elizaveta Goncharova, Andrey Kuznetsov
Machine Learning
日本大学: 関与なし（対象大学）
2026 · ICML
Progressive Graph Structure Adjustment for Homophily Shift Adaptation
Hongwei Wen, Can Zhang, Haoyu He, Hanyuan Hang, Minglong Lei
Machine Learning
日本大学: 関与なし（対象大学）
2026 · ICML
ProjQ: Project-and-Quantize for Adapter-Aware LLM Compression
Wenya Yu, Chao Zhang, Li Wang, Samson Lasaulce, Merouane DEBBAH
Machine Learning
日本大学: 関与なし（対象大学）
2026 · ICML
Projection-Free Algorithms for Minimax Problems
Khanh-Hung Giang-Tran, Soroosh Shafiee, Nam Ho-Nguyen
Machine Learning
日本大学: 関与なし（対象大学）
2026 · ICML
Prompt Injection as Role Confusion
Charles Ye, Jasmine Cui, Dylan Hadfield-Menell
Machine Learning
日本大学: 関与なし（対象大学）
2026 · ICML
Prompt Optimization with Minimal Unlabeled Input via Meta-Reasoning
Yuran Sun, Chuan Wu
Machine Learning
日本大学: 関与なし（対象大学）
2026 · ICML
Prompt Reinjection: Alleviating Prompt Forgetting in Multimodal Diffusion Transformers
Yuxuan Yao, Yuxuan Chen, Hui Li, Kaihui Cheng, Qipeng Guo, Yuwei Sun, Zilong Dong, Jingdong Wang, Siyu Zhu
Machine Learning
日本大学: 関与なし（対象大学）
2026 · ICML
Prompt Tuning for CLIP on the Pretrained Manifold
Xi Yang, Yuanrong Xu, Weigang Zhang, Guangming Lu, David Zhang, Jie Wen
Machine Learning
日本大学: 関与なし（対象大学）
2026 · ICML
PromptDyG: Test-Time Prompt Adaptation on Dynamic Graphs
Guoguo Ai, Chaoxi Niu, Hui Yan, Joey Tianyi Zhou, Yew Soon ONG, Guansong Pang
Machine Learning
日本大学: 関与なし（対象大学）
2026 · ICML
PromptPilot: Game-Theoretic Multi-Agent Prompt Optimization for Segment Anything
Guangze Shi, Yingjie Mi, Jia Shen, Feixue Shao, Jiarui Cao, Yexin Lai, Xueyu Liu, Rui Wang, Yongfei Wu, Mingqiang Wei
Machine Learning
日本大学: 関与なし（対象大学）
2026 · ICML
PromptRL: Prompt Matters in RL for Flow-Based Image Generation
Fu-Yun Wang, Han Zhang, Michaël Gharbi, Hongsheng Li, Taesung Park
Machine Learning
日本大学: 関与なし（対象大学）
2026 · ICML
ProphetKV: User-Query-Driven Selective Recomputation for Efficient KV Cache Reuse in Retrieval-Augmented Generation
Shihao Wang, Jiahao Chen, Yanqi Pan, Hao Huang, Yichen Hao, Xiangyu Zou, Wen Xia, Chongyang Qiu, Wentao Zhang, PengFei Wang
Machine Learning
日本大学: 関与なし（対象大学）
2026 · ICML
Propose, Solve, Verify: Self-Play Through Formal Verification
Alex Wilf, Pranjal Aggarwal, Bryan Parno, Daniel Fried, Louis-Philippe Morency, Paul Pu Liang, Sean Welleck
Machine Learning
日本大学: 関与なし（対象大学）
2026 · ICML
ProtDBench: A Unified Benchmark of Protein Binder Design and Evaluation
Cong Liu, Milong Ren, Jiaqi Guan, Chengyue Gong, Jinyuan Sun, Xinshi Chen, Wenzhi Xiao
Machine Learning
日本大学: 関与なし（対象大学）
2026 · ICML
Protein Autoregressive Modeling via Multiscale Structure Generation
Yanru Qu, Cheng-Yen Hsieh, Zaixiang Zheng, Ge Liu, Quanquan Gu
Machine Learning
日本大学: 関与なし（対象大学）
2026 · ICML
Protein Circuit Tracing via Cross-layer Transcoders
Darin Tsui, Kunal Talreja, Daniel Saeedi, Amirali Aghazadeh
Machine Learning
日本大学: 関与なし（対象大学）
2026 · ICML
Protein Design with Agent Rosetta: A Case Study for Specialized Scientific Agents
Jacopo Teneggi, SM Turzo, Tanya Marwah, Alberto Bietti, P. Douglas Renfrew, Vikram Mulligan, Siavash Golkar
Machine Learning
日本大学: 関与なし（対象大学）
2026 · ICML
Protein Fold Classification at Scale: Benchmarking and Pretraining
Dexiong Chen, Andrei Manolache, Mathias Niepert, Karsten Borgwardt
Machine Learning
日本大学: 関与なし（対象大学）
2026 · ICML
Protein Language Model Embeddings Improve Generalization of Implicit Transfer Operators
Panagiotis Antoniadis, Beatrice Pavesi, Simon Olsson, Ole Winther
Machine Learning
日本大学: 関与なし（対象大学）
2026 · ICML
Proteo-R1: Reasoning Foundation Models for De Novo Protein Design
Fang Wu, Weihao Xuan, Heli Qi, Hanqun CAO, Heng-Jui Chang, Zeqi Zhou, Li Erran Li, Haokai Zhao, Jian Ma, Zijian Ma, Yu-Chi Cheng, Kuan Pang, Robert Tang, Zehong Wang, Guanlue Li, Hanchen Wang, Kejun Ying, Pan Lu, Chiho Im, Seungju Han, Peng Xia, Tinson Xu, Yinxi Li, Deyao Zhu, Pheng Ann Heng, Naoto Yokoya, Masashi Sugiyama, Jure Leskovec, Yejin Choi
Machine Learning
日本大学: 東京大学 / 早稲田大学
2026 · ICML
Proteus: Lookup-Free Trellis-Coded Quantization by Lattice-Breaking Compute Codes for 2-Bit LLMs
Zhengwu Yang, Xunchao Li, Ke Cheng, Kunlong Liu, jianfengyang, HaoshuangWang, Kaipeng Deng, Qingqing Dang, Yanlin Sha, Yanjun Ma, Dianhai Yu
Machine Learning
日本大学: 関与なし（対象大学）
2026 · ICML
ProtoKV: Streaming Video Understanding under Delayed Query with Summary-State Memory
Ngoc Minh Le Tu, Jinyeong Lim, Dongsu Han
Machine Learning
日本大学: 関与なし（対象大学）
2026 · ICML
ProtoVAR: Efficient Dataset Distillation via Prototype-Guided Visual Autoregressive Modeling
Mingyu Wang, Wei Jiang
Machine Learning
日本大学: 関与なし（対象大学）
2026 · ICML
ProtocolBench: Which LLM MultiAgent Protocol to Choose?
Hongyi Du, Jiaqi Su, Jisen Li, Lijie Ding, Yingxuan Yang, Peixuan Han, Robert Tang, Kunlun Zhu, Jiaxuan You
Machine Learning
日本大学: 関与なし（対象大学）
2026 · ICML
Prototype Transformer: Towards Language Model Architectures Interpretable by Design
Yordan Yordanov, Matteo Forasassi, Bayar Menzat, Ruizhi Wang, Chang Qi, Markus Kaltenberger, Amine M'Charrak, Tommaso Salvatori, Thomas Lukasiewicz
Machine Learning
日本大学: 関与なし（対象大学）
2026 · ICML
Prototype-Based Test-Time Adaptation of Vision-Language Models
Zhaohong Huang, Yuxin Zhang, Wenjing Liu, Fei Chao, Rongrong Ji
Machine Learning
日本大学: 関与なし（対象大学）
2026 · ICML
Prototype-Grounded Concept Models for Verifiable Concept Alignment
Stefano Colamonaco, David Debot, Pietro Barbiero, Giuseppe Marra
Machine Learning
日本大学: 関与なし（対象大学）
2026 · ICML
Prototype-guided Bilateral Alignment Multimodal Federated Learning
Tianchi Liao, Lele Fu, Sheng Huang, Qing Hu, Hong-Ning Dai, Chuan Chen
Machine Learning
日本大学: 関与なし（対象大学）
2026 · ICML
Provable Accuracy Collapse of Embedding-Based Representations under Dimensionality Mismatch
Dionysis Arvanitakis, Vaggos Chatziafratis, Yiyuan Luo
Machine Learning
日本大学: 関与なし（対象大学）
2026 · ICML
Provable Benefits of RLVR over SFT for Reasoning Models: Learning to Backtrack Efficiently
Stanley Wei, Juno Kim
Machine Learning
日本大学: 関与なし（対象大学）
2026 · ICML
Provable Bounds for the Learnability of Sample-Compressible Families from Noisy Samples
Arefe Boushehrian, Amir Najafi
Machine Learning
日本大学: 関与なし（対象大学）
2026 · ICML
Provable Sample Efficiency of Curriculum Post-Training for Transformer Reasoning
Dake Bu, Wei Huang, Andi Han, Atsushi Nitanda, Hau-San Wong, Qingfu Zhang, Taiji Suzuki
Machine Learning
日本大学: 東京大学