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Machine Learning

2025 · 3,330 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。

2025 · ICML
Puzzle: Distillation-Based NAS for Inference-Optimized LLMs
Akhiad Bercovich, Tomer Ronen, Talor Abramovich, Nir Ailon, Nave Assaf, Mohammed Dabbah, Ido Galil, Amnon Geifman, Yonatan Geifman, Izhak Golan, Netanel Haber, Ehud Dov Karpas, Roi Koren, Itay Levy, Pavlo Molchanov, Shahar Mor, Zach Moshe, Najeeb Nabwani, Omri Puny, Ran Rubin, Itamar Schen, Ido Shahaf, Oren Tropp, Omer Ullman Argov, Ran Zilberstein, Ran El-Yaniv
Machine Learning
日本大学: 関与なし（対象大学）
2025 · ICML
PyTDC: A multimodal machine learning training, evaluation, and inference platform for biomedical foundation models
Alejandro Velez-Arce, Marinka Zitnik
Machine Learning
日本大学: 関与なし（対象大学）
2025 · ICML
Q-Supervised Contrastive Representation: A State Decoupling Framework for Safe Offline Reinforcement Learning
Zhihe Yang, Yunjian Xu, Yang Zhang
Machine Learning
日本大学: 関与なし（対象大学）
2025 · ICML
Q-VDiT: Towards Accurate Quantization and Distillation of Video-Generation Diffusion Transformers
Weilun Feng, Chuanguang Yang, Haotong Qin, Xiangqi Li, Yu Wang, Zhulin An, Libo Huang, Boyu Diao, Zixiang Zhao, Yongjun Xu, Michele Magno
Machine Learning
日本大学: 関与なし（対象大学）
2025 · ICML
QEM-Bench: Benchmarking Learning-based Quantum Error Mitigation and QEMFormer as a Multi-ranged Context Learning Baseline
Tianyi Bao, Ruizhe Zhong, Xinyu Ye, Yehui Tang, Junchi Yan
Machine Learning
日本大学: 関与なし（対象大学）
2025 · ICML
QLASS: Boosting Language Agent Inference via Q-Guided Stepwise Search
Zongyu Lin, Yao Tang, Xingcheng Yao, Da Yin, Ziniu Hu, Yizhou Sun, Kai-Wei Chang
Machine Learning
日本大学: 関与なし（対象大学）
2025 · ICML
QMamba: On First Exploration of Vision Mamba for Image Quality Assessment
Fengbin Guan, Xin Li, Zihao Yu, Yiting Lu, Zhibo Chen
Machine Learning
日本大学: 関与なし（対象大学）
2025 · ICML
QPRL : Learning Optimal Policies with Quasi-Potential Functions for Asymmetric Traversal
Jumman Hossain, Nirmalya Roy
Machine Learning
日本大学: 関与なし（対象大学）
2025 · ICML
QT-DoG: Quantization-Aware Training for Domain Generalization
Saqib Javed, Hieu Le, Mathieu Salzmann
Machine Learning
日本大学: 関与なし（対象大学）
2025 · ICML
QUTE: Quantifying Uncertainty in TinyML models with Early-exit-assisted ensembles for model-monitoring
Nikhil Pratap Ghanathe, Steven J E Wilton
Machine Learning
日本大学: 関与なし（対象大学）
2025 · ICML
QoS-Efficient Serving of Multiple Mixture-of-Expert LLMs Using Partial Runtime Reconfiguration
Hamidreza Imani, Jiaxin Peng, Peiman Mohseni, Abdolah Amirany, Tarek El-Ghazawi
Machine Learning
日本大学: 関与なし（対象大学）
2025 · ICML
QuEST: Stable Training of LLMs with 1-Bit Weights and Activations
Andrei Panferov, Jiale Chen, Soroush Tabesh, Mahdi Nikdan, Dan Alistarh
Machine Learning
日本大学: 関与なし（対象大学）
2025 · ICML
QuEst: Enhancing Estimates of Quantile-Based Distributional Measures Using Model Predictions
Zhun Deng, Thomas P Zollo, Benjamin Eyre, Amogh Inamdar, David Madras, Richard Zemel
Machine Learning
日本大学: 関与なし（対象大学）
2025 · ICML
QuRe: Query-Relevant Retrieval through Hard Negative Sampling in Composed Image Retrieval
Jaehyun Kwak, Ramahdani Muhammad Izaaz Inhar, Se-Young Yun, Sung-Ju Lee
Machine Learning
日本大学: 関与なし（対象大学）
2025 · ICML
Quadratic Upper Bound for Boosting Robustness
Euijin You, Hyang-Won Lee
Machine Learning
日本大学: 関与なし（対象大学）
2025 · ICML
Quadruple Attention in Many-body Systems for Accurate Molecular Property Predictions
Jiahua Rao, Dahao Xu, Wentao Wei, Yicong Chen, Mingjun Yang, Yuedong Yang
Machine Learning
日本大学: 関与なし（対象大学）
2025 · ICML
Quamba2: A Robust and Scalable Post-training Quantization Framework for Selective State Space Models
Hung-Yueh Chiang, Chi-Chih Chang, Natalia Frumkin, Kai-Chiang Wu, Mohamed S. Abdelfattah, Diana Marculescu
Machine Learning
日本大学: 関与なし（対象大学）
2025 · ICML
QuanONet: Quantum Neural Operator with Application to Differential Equation
Ruocheng Wang, Zhuo Xia, Ge Yan, Junchi Yan
Machine Learning
日本大学: 関与なし（対象大学）
2025 · ICML
QuantSpec: Self-Speculative Decoding with Hierarchical Quantized KV Cache
Rishabh Tiwari, Haocheng Xi, Aditya Tomar, Coleman Richard Charles Hooper, Sehoon Kim, Maxwell Horton, Mahyar Najibi, Michael W. Mahoney, Kurt Keutzer, Amir Gholami
Machine Learning
日本大学: 関与なし（対象大学）
2025 · ICML
Quantifying Memory Utilization with Effective State-Size
Rom Parnichkun, Neehal Tumma, Armin W Thomas, Alessandro Moro, Qi An, Taiji Suzuki, Atsushi Yamashita, Michael Poli, Stefano Massaroli
Machine Learning
日本大学: 中央大学 / 東京大学
2025 · ICML
Quantifying Prediction Consistency Under Fine-tuning Multiplicity in Tabular LLMs
Faisal Hamman, Pasan Dissanayake, Saumitra Mishra, Freddy Lecue, Sanghamitra Dutta
Machine Learning
日本大学: 関与なし（対象大学）
2025 · ICML
Quantifying Treatment Effects: Estimating Risk Ratios via Observational Studies
Ahmed Boughdiri, Julie Josse, Erwan Scornet
Machine Learning
日本大学: 関与なし（対象大学）
2025 · ICML
Quantum Algorithms for Finite-horizon Markov Decision Processes
Bin Luo, Yuwen Huang, Jonathan Allcock, Xiaojun Lin, Shengyu Zhang, John C.S. Lui
Machine Learning
日本大学: 関与なし（対象大学）
2025 · ICML
Quantum Optimization via Gradient-Based Hamiltonian Descent
Jiaqi Leng, Bin Shi
Machine Learning
日本大学: 関与なし（対象大学）
2025 · ICML
Quantum Speedup for Hypergraph Sparsification
Chenghua Liu, Minbo Gao, Zhengfeng Ji, Mingsheng Ying
Machine Learning
日本大学: 関与なし（対象大学）
2025 · ICML
Quantum Speedups in Regret Analysis of Infinite Horizon Average-Reward Markov Decision Processes
Bhargav Ganguly, Yang Xu, Vaneet Aggarwal
Machine Learning
日本大学: 関与なし（対象大学）
2025 · ICML
R*: Efficient Reward Design via Reward Structure Evolution and Parameter Alignment Optimization with Large Language Models
Pengyi Li, Jianye Hao, Hongyao Tang, Yifu Yuan, Jinbin Qiao, Zibin Dong, Yan Zheng
Machine Learning
日本大学: 関与なし（対象大学）
2025 · ICML
R.I.P.: Better Models by Survival of the Fittest Prompts
Ping Yu, Weizhe Yuan, Olga Golovneva, Tianhao Wu, Sainbayar Sukhbaatar, Jason E Weston, Jing Xu
Machine Learning
日本大学: 関与なし（対象大学）
2025 · ICML
R2-T2: Re-Routing in Test-Time for Multimodal Mixture-of-Experts
Zhongyang Li, Ziyue Li, Tianyi Zhou
Machine Learning
日本大学: 関与なし（対象大学）
2025 · ICML
R3DM: Enabling Role Discovery and Diversity Through Dynamics Models in Multi-agent Reinforcement Learning
Harsh Goel, Mohammad Omama, Behdad Chalaki, Vaishnav Tadiparthi, Ehsan Moradi Pari, Sandeep P. Chinchali
Machine Learning
日本大学: 関与なし（対象大学）
2025 · ICML
RAGGED: Towards Informed Design of Scalable and Stable RAG Systems
Jennifer Hsia, Afreen Shaikh, Zora Zhiruo Wang, Graham Neubig
Machine Learning
日本大学: 関与なし（対象大学）
2025 · ICML
RAPID: Long-Context Inference with Retrieval-Augmented Speculative Decoding
Guanzheng Chen, Qilong Feng, Jinjie Ni, Xin Li, Michael Qizhe Shieh
Machine Learning
日本大学: 関与なし（対象大学）
2025 · ICML
RATE: Causal Explainability of Reward Models with Imperfect Counterfactuals
David Reber, Sean M Richardson, Todd Nief, Cristina Garbacea, Victor Veitch
Machine Learning
日本大学: 関与なし（対象大学）
2025 · ICML
RBench: Graduate-level Multi-disciplinary Benchmarks for LLM & MLLM Complex Reasoning Evaluation
Meng-Hao Guo, Jiajun Xu, Yi Zhang, Jiaxi Song, Haoyang Peng, Yi-Xuan Deng, Xinzhi Dong, Kiyohiro Nakayama, Zhengyang Geng, Chen Wang, Bolin Ni, Guo-Wei Yang, Yongming Rao, Houwen Peng, Han Hu, Gordon Wetzstein, Shi-Min Hu
Machine Learning
日本大学: 関与なし（対象大学）
2025 · ICML
RE-Bench: Evaluating Frontier AI R&D Capabilities of Language Model Agents against Human Experts
Hjalmar Wijk, Tao Roa Lin, Joel Becker, Sami Jawhar, Neev Parikh, Thomas Broadley, Lawrence Chan, Michael Chen, Joshua M Clymer, Jai Dhyani, Elena Ericheva, Katharyn Garcia, Brian Goodrich, Nikola Jurkovic, Megan Kinniment, Aron Lajko, Seraphina Nix, Lucas Jun Koba Sato, William Saunders, Maksym Taran, Ben West, Elizabeth Barnes
Machine Learning
日本大学: 関与なし（対象大学）
2025 · ICML
RE-IMAGINE: Symbolic Benchmark Synthesis for Reasoning Evaluation
Xinnuo Xu, Rachel Lawrence, Kshitij Dubey, Atharva Pandey, Risa Ueno, Fabian Falck, Aditya V. Nori, Rahul Sharma, Amit Sharma, Javier Gonzalez
Machine Learning
日本大学: 関与なし（対象大学）
2025 · ICML
REG: Rectified Gradient Guidance for Conditional Diffusion Models
Zhengqi Gao, Kaiwen Zha, Tianyuan Zhang, Zihui Xue, Duane S Boning
Machine Learning
日本大学: 関与なし（対象大学）
2025 · ICML
REINFORCE Adversarial Attacks on Large Language Models: An Adaptive, Distributional, and Semantic Objective
Simon Geisler, Tom Wollschläger, M. H. I. Abdalla, Vincent Cohen-Addad, Johannes Gasteiger, Stephan Günnemann
Machine Learning
日本大学: 関与なし（対象大学）
2025 · ICML
RIFLEx: A Free Lunch for Length Extrapolation in Video Diffusion Transformers
Min Zhao, Guande He, Yixiao Chen, Hongzhou Zhu, Chongxuan Li, Jun Zhu
Machine Learning
日本大学: 関与なし（対象大学）
2025 · ICML
RISE: Radius of Influence based Subgraph Extraction for 3D Molecular Graph Explanation
Jingxiang Qu, Wenhan Gao, Jiaxing Zhang, Xufeng Liu, Hua Wei, Haibin Ling, Yi Liu
Machine Learning
日本大学: 関与なし（対象大学）
2025 · ICML
RLEF: Grounding Code LLMs in Execution Feedback with Reinforcement Learning
Jonas Gehring, Kunhao Zheng, Jade Copet, Vegard Mella, Taco Cohen, Gabriel Synnaeve
Machine Learning
日本大学: 関与なし（対象大学）
2025 · ICML
RLTHF: Targeted Human Feedback for LLM Alignment
Yifei Xu, Tusher Chakraborty, Emre Kiciman, Bibek Aryal, Srinagesh Sharma, Songwu Lu, Ranveer Chandra
Machine Learning
日本大学: 関与なし（対象大学）
2025 · ICML
ROME is Forged in Adversity: Robust Distilled Datasets via Information Bottleneck
Zheng Zhou, Wenquan Feng, Qiaosheng Zhang, Shuchang Lyu, Qi Zhao, Guangliang Cheng
Machine Learning
日本大学: 関与なし（対象大学）
2025 · ICML
ROPO: Robust Preference Optimization for Large Language Models
Xize Liang, Chao Chen, Shuang Qiu, Jie Wang, Yue Wu, Zhihang Fu, Hanzhu Chen, Feng Wu, Jieping Ye
Machine Learning
日本大学: 関与なし（対象大学）
2025 · ICML
ROS: A GNN-based Relax-Optimize-and-Sample Framework for Max-$k$-Cut Problems
Yeqing Qiu, Ye Xue, Akang Wang, Yiheng Wang, Qingjiang Shi, Zhi-Quan Luo
Machine Learning
日本大学: 関与なし（対象大学）
2025 · ICML
RULEBREAKERS: Challenging LLMs at the Crossroads between Formal Logic and Human-like Reasoning
Jason Chan, Robert J. Gaizauskas, Zhixue Zhao
Machine Learning
日本大学: 関与なし（対象大学）
2025 · ICML
RUN: Reversible Unfolding Network for Concealed Object Segmentation
Chunming He, Rihan Zhang, Fengyang Xiao, Chengyu Fang, Longxiang Tang, Yulun Zhang, Linghe Kong, Deng-Ping Fan, Kai Li, Sina Farsiu
Machine Learning
日本大学: 関与なし（対象大学）
2025 · ICML
RWKVQuant: Quantizing the RWKV Family with Proxy Guided Hybrid of Scalar and Vector Quantization
Chen Xu, Yuxuan Yue, Zukang Xu, Xing Hu, Jiangyong Yu, Zhixuan Chen, Sifan Zhou, Zhihang Yuan, Dawei Yang
Machine Learning
日本大学: 関与なし（対象大学）
2025 · ICML
RZ-NAS: Enhancing LLM-guided Neural Architecture Search via Reflective Zero-Cost Strategy
Zipeng Ji, Guanghui Zhu, Chunfeng Yuan, Yihua Huang
Machine Learning
日本大学: 関与なし（対象大学）
2025 · ICML
Radio: Rate–Distortion Optimization for Large Language Model Compression
Sean I. Young
Machine Learning
日本大学: 関与なし（対象大学）
2025 · ICML
Raising the Bar: Investigating the Values of Large Language Models via Generative Evolving Testing
Han Jiang, Xiaoyuan Yi, Zhihua Wei, Ziang Xiao, Shu Wang, Xing Xie
Machine Learning
日本大学: 関与なし（対象大学）
2025 · ICML
Random Feature Representation Boosting
Nikita Zozoulenko, Thomas Cass, Lukas Gonon
Machine Learning
日本大学: 関与なし（対象大学）
2025 · ICML
Random Policy Evaluation Uncovers Policies of Generative Flow Networks
Haoran He, Emmanuel Bengio, Qingpeng Cai, Ling Pan
Machine Learning
日本大学: 関与なし（対象大学）
2025 · ICML
Random Registers for Cross-Domain Few-Shot Learning
Shuai Yi, Yixiong Zou, Yuhua Li, Ruixuan Li
Machine Learning
日本大学: 関与なし（対象大学）
2025 · ICML
Randomized Dimensionality Reduction for Euclidean Maximization and Diversity Measures
Jie Gao, Rajesh Jayaram, Benedikt Kolbe, Shay Sapir, Chris Schwiegelshohn, Sandeep Silwal, Erik Waingarten
Machine Learning
日本大学: 関与なし（対象大学）
2025 · ICML
Rank-One Modified Value Iteration
Arman Sharifi Kolarijani, Tolga Ok, Peyman Mohajerin Esfahani, Mohamad Amin Sharifi Kolarijani
Machine Learning
日本大学: 関与なし（対象大学）
2025 · ICML
Ranked Entropy Minimization for Continual Test-Time Adaptation
Jisu Han, Jaemin Na, Wonjun Hwang
Machine Learning
日本大学: 関与なし（対象大学）
2025 · ICML
Ranked from Within: Ranking Large Multimodal Models Without Labels
Weijie Tu, Weijian Deng, Dylan Campbell, Yu Yao, Jiyang Zheng, Tom Gedeon, Tongliang Liu
Machine Learning
日本大学: 関与なし（対象大学）
2025 · ICML
Ranking with Multiple Oracles: From Weak to Strong Stochastic Transitivity
Tao Jin, Yue Wu, Quanquan Gu, Farzad Farnoud
Machine Learning
日本大学: 関与なし（対象大学）
2025 · ICML
Rapid Overfitting of Multi-Pass SGD in Stochastic Convex Optimization
Shira Vansover-Hager, Tomer Koren, Roi Livni
Machine Learning
日本大学: 関与なし（対象大学）
2025 · ICML
Raptor: Scalable Train-Free Embeddings for 3D Medical Volumes Leveraging Pretrained 2D Foundation Models
Ulzee An, Moonseong Jeong, Simon Austin Lee, Aditya Gorla, Yuzhe Yang, Sriram Sankararaman
Machine Learning
日本大学: 関与なし（対象大学）
2025 · ICML
Re-ranking Reasoning Context with Tree Search Makes Large Vision-Language Models Stronger
Qi Yang, Chenghao Zhang, Lubin Fan, Kun Ding, Jieping Ye, Shiming Xiang
Machine Learning
日本大学: 関与なし（対象大学）
2025 · ICML
ReFocus: Visual Editing as a Chain of Thought for Structured Image Understanding
Xingyu Fu, Minqian Liu, Zhengyuan Yang, John Richard Corring, Yijuan Lu, Jianwei Yang, Dan Roth, Dinei Florencio, Cha Zhang
Machine Learning
日本大学: 関与なし（対象大学）
2025 · ICML
ReFrame: Layer Caching for Accelerated Inference in Real-Time Rendering
Lufei Liu, Tor M. Aamodt
Machine Learning
日本大学: 関与なし（対象大学）
2025 · ICML
RePaViT: Scalable Vision Transformer Acceleration via Structural Reparameterization on Feedforward Network Layers
Xuwei Xu, Yang Li, Yudong Chen, Jiajun Liu, Sen Wang
Machine Learning
日本大学: 関与なし（対象大学）
2025 · ICML
ReQFlow: Rectified Quaternion Flow for Efficient and High-Quality Protein Backbone Generation
Angxiao Yue, Zichong Wang, Hongteng Xu
Machine Learning
日本大学: 関与なし（対象大学）
2025 · ICML
ReVISE: Learning to Refine at Test-Time via Intrinsic Self-Verification
Hyunseok Lee, Seunghyuk Oh, Jaehyung Kim, Jinwoo Shin, Jihoon Tack
Machine Learning
日本大学: 関与なし（対象大学）
2025 · ICML
Reaction Graph: Towards Reaction-Level Modeling for Chemical Reactions with 3D Structures
Yingzhao Jian, Yue Zhang, Ying Wei, Hehe Fan, Yi Yang
Machine Learning
日本大学: 関与なし（対象大学）
2025 · ICML
RealRAG: Retrieval-augmented Realistic Image Generation via Self-reflective Contrastive Learning
Yuanhuiyi Lyu, Xu Zheng, Lutao Jiang, Yibo Yan, Xin Zou, Huiyu Zhou, Linfeng Zhang, Xuming Hu
Machine Learning
日本大学: 関与なし（対象大学）
2025 · ICML
Reasoning Limitations of Multimodal Large Language Models. A case study of Bongard Problems
Mikołaj Małkiński, Szymon Pawlonka, Jacek Mańdziuk
Machine Learning
日本大学: 関与なし（対象大学）
2025 · ICML
Reasoning Through Execution: Unifying Process and Outcome Rewards for Code Generation
Zhuohao Yu, Weizheng Gu, Yidong Wang, Xingru Jiang, Zhengran Zeng, Jindong Wang, Wei Ye, Shikun Zhang
Machine Learning
日本大学: 東京科学大学
2025 · ICML
Reasoning-as-Logic-Units: Scaling Test-Time Reasoning in Large Language Models Through Logic Unit Alignment
Cheryl Li, Tianyuan Xu, Steven Y. Guo
Machine Learning
日本大学: 関与なし（対象大学）
2025 · ICML
Recommendations with Sparse Comparison Data: Provably Fast Convergence for Nonconvex Matrix Factorization
Suryanarayana Sankagiri, Jalal Etesami, Matthias Grossglauser
Machine Learning
日本大学: 関与なし（対象大学）
2025 · ICML
Reconstructing Cell Lineage Trees from Phenotypic Features with Metric Learning
Da Kuang, Guanwen Qiu, Junhyong Kim
Machine Learning
日本大学: 関与なし（対象大学）
2025 · ICML
Rectifying Conformity Scores for Better Conditional Coverage
Vincent Plassier, Alexander Fishkov, Victor Dheur, Mohsen Guizani, Souhaib Ben Taieb, Maxim Panov, Eric Moulines
Machine Learning
日本大学: 関与なし（対象大学）
2025 · ICML
Reducing Confounding Bias without Data Splitting for Causal Inference via Optimal Transport
Yuguang Yan, Zongyu Li, Haolin Yang, Zeqin Yang, Hao Zhou, Ruichu Cai, Zhifeng Hao
Machine Learning
日本大学: 関与なし（対象大学）
2025 · ICML
Reducing Tool Hallucination via Reliability Alignment
Hongshen Xu, Zichen Zhu, Lei Pan, Zihan Wang, Su Zhu, Da Ma, Ruisheng Cao, Lu Chen, Kai Yu
Machine Learning
日本大学: 関与なし（対象大学）
2025 · ICML
Reducing Variance of Stochastic Optimization for Approximating Nash Equilibria in Normal-Form Games
Linjian Meng, Wubing Chen, Wenbin Li, Tianpei Yang, Youzhi Zhang, Yang Gao
Machine Learning
日本大学: 関与なし（対象大学）
2025 · ICML
Redundancy Undermines the Trustworthiness of Self-Interpretable GNNs
Wenxin Tai, Ting Zhong, Goce Trajcevski, Fan Zhou
Machine Learning
日本大学: 関与なし（対象大学）
2025 · ICML
ReferSplat: Referring Segmentation in 3D Gaussian Splatting
Shuting He, Guangquan Jie, Changshuo Wang, Yun Zhou, Shuming Hu, Guanbin Li, Henghui Ding
Machine Learning
日本大学: 関与なし（対象大学）
2025 · ICML
Refined generalization analysis of the Deep Ritz Method and Physics-Informed Neural Networks
Xianliang Xu, Ye Li, Zhongyi Huang
Machine Learning
日本大学: 関与なし（対象大学）
2025 · ICML
Refining Adaptive Zeroth-Order Optimization at Ease
Yao Shu, Qixin Zhang, Kun He, Zhongxiang Dai
Machine Learning
日本大学: 関与なし（対象大学）
2025 · ICML
Reflect-then-Plan: Offline Model-Based Planning through a Doubly Bayesian Lens
Jihwan Jeong, Xiaoyu Wang, Jingmin Wang, Scott Sanner, Pascal Poupart
Machine Learning
日本大学: 関与なし（対象大学）
2025 · ICML
Reflection-Bench: Evaluating Epistemic Agency in Large Language Models
Lingyu Li, Yixu Wang, Haiquan Zhao, Shuqi Kong, Yan Teng, Chunbo Li, Yingchun Wang
Machine Learning
日本大学: 関与なし（対象大学）
2025 · ICML
Reflection-Window Decoding: Text Generation with Selective Refinement
Zeyu Tang, Zhenhao Chen, Xiangchen Song, Loka Li, Yunlong Deng, Yifan Shen, Guangyi Chen, Peter Spirtes, Kun Zhang
Machine Learning
日本大学: 関与なし（対象大学）
2025 · ICML
Regress, Don’t Guess: A Regression-like Loss on Number Tokens for Language Models
Jonas Zausinger, Lars Pennig, Anamarija Kozina, Sean Sdahl, Julian Sikora, Adrian Dendorfer, Timofey Kuznetsov, Mohamad Hagog, Nina Wiedemann, Kacper Chlodny, Vincent Limbach, Anna Ketteler, Thorben Prein, Vishwa Mohan Singh, Michael Danziger, Jannis Born
Machine Learning
日本大学: 関与なし（対象大学）
2025 · ICML
Regression for the Mean: Auto-Evaluation and Inference with Few Labels through Post-hoc Regression
Benjamin Eyre, David Madras
Machine Learning
日本大学: 関与なし（対象大学）
2025 · ICML
Regret-Free Reinforcement Learning for Temporal Logic Specifications
R Majumdar, Mahmoud Salamati, Sadegh Soudjani
Machine Learning
日本大学: 関与なし（対象大学）
2025 · ICML
Regularized Langevin Dynamics for Combinatorial Optimization
Shengyu Feng, Yiming Yang
Machine Learning
日本大学: 関与なし（対象大学）
2025 · ICML
Reidentify: Context-Aware Identity Generation for Contextual Multi-Agent Reinforcement Learning
Zhiwei Xu, Kun Hu, Xin Xin, Weiliang Meng, Yiwei Shi, Hangyu Mao, Bin Zhang, Dapeng Li, Jiangjin Yin
Machine Learning
日本大学: 関与なし（対象大学）
2025 · ICML
ReinboT: Amplifying Robot Visual-Language Manipulation with Reinforcement Learning
Hongyin Zhang, Zifeng Zhuang, Han Zhao, Pengxiang Ding, Hongchao Lu, Donglin Wang
Machine Learning
日本大学: 関与なし（対象大学）
2025 · ICML
Reinforce LLM Reasoning through Multi-Agent Reflection
Yurun Yuan, Tengyang Xie
Machine Learning
日本大学: 関与なし（対象大学）
2025 · ICML
Reinforced Learning Explicit Circuit Representations for Quantum State Characterization from Local Measurements
Manwen Liao, Yan Zhu, Weitian Zhang, Yuxiang Yang
Machine Learning
日本大学: 関与なし（対象大学）
2025 · ICML
Reinforced Lifelong Editing for Language Models
Zherui Li, Houcheng Jiang, Hao Chen, Baolong Bi, Zhenhong Zhou, Fei Sun, Junfeng Fang, Xiang Wang
Machine Learning
日本大学: 関与なし（対象大学）
2025 · ICML
Reinforcement Learning Control of a Physical Robot Device for Assisted Human Walking without a Simulator
Junmin Zhong, Emiliano Quinones Yumbla, Seyed Yousef Soltanian, Ruofan Wu, Wenlong Zhang, Jennie Si
Machine Learning
日本大学: 関与なし（対象大学）
2025 · ICML
Reinforcement Learning for Quantum Control under Physical Constraints
Jan Ole Ernst, Aniket Chatterjee, Tim Franzmeyer, Axel Kuhn
Machine Learning
日本大学: 関与なし（対象大学）
2025 · ICML
Reinforcement Learning with Adaptive Reward Modeling for Expensive-to-Evaluate Systems
Hongyuan Su, Yu Zheng, Yuan Yuan, Yuming Lin, Depeng Jin, Yong Li
Machine Learning
日本大学: 関与なし（対象大学）
2025 · ICML
Reinforcement Learning with Random Time Horizons
Enric Ribera Borrell, Lorenz Richter, Christof Schuette
Machine Learning
日本大学: 関与なし（対象大学）
2025 · ICML
Reinforcement Learning with Segment Feedback
Yihan Du, Anna Winnicki, Gal Dalal, Shie Mannor, R. Srikant
Machine Learning
日本大学: 関与なし（対象大学）
2025 · ICML
Rejecting Hallucinated State Targets during Planning
Harry Zhao, Tristan Sylvain, Romain Laroche, Doina Precup, Yoshua Bengio
Machine Learning
日本大学: 関与なし（対象大学）