Conferences · eligible papers

ICML

2021–2025 確定版

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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。

  1. 2025 · ICML

    AxBench: Steering LLMs? Even Simple Baselines Outperform Sparse Autoencoders

    Zhengxuan Wu, Aryaman Arora, Atticus Geiger, Zheng Wang, Jing Huang, Dan Jurafsky, Christopher D Manning, Christopher Potts

    Machine Learning

    日本大学: 関与なし(対象大学)

  2. 2025 · ICML

    B-score: Detecting biases in large language models using response history

    An Vo, Mohammad Reza Taesiri, Daeyoung Kim, Anh Totti Nguyen

    Machine Learning

    日本大学: 関与なし(対象大学)

  3. 2025 · ICML

    BAME: Block-Aware Mask Evolution for Efficient N:M Sparse Training

    Chenyi Yang, Wenjie Nie, Yuxin Zhang, Yuhang Wu, Xiawu Zheng, Guannan Jiang, Rongrong Ji

    Machine Learning

    日本大学: 関与なし(対象大学)

  4. 2025 · ICML

    BARK: A Fully Bayesian Tree Kernel for Black-box Optimization

    Toby Boyne, Jose Pablo Folch, Robert Matthew Lee, Behrang Shafei, Ruth Misener

    Machine Learning

    日本大学: 関与なし(対象大学)

  5. 2025 · ICML

    BARNN: A Bayesian Autoregressive and Recurrent Neural Network

    Dario Coscia, Max Welling, Nicola Demo, Gianluigi Rozza

    Machine Learning

    日本大学: 関与なし(対象大学)

  6. 2025 · ICML

    BAnG: Bidirectional Anchored Generation for Conditional RNA Design

    Roman Klypa, Alberto Bietti, Sergei Grudinin

    Machine Learning

    日本大学: 関与なし(対象大学)

  7. 2025 · ICML

    BCE vs. CE in Deep Feature Learning

    Qiufu Li, Huibin Xiao, Linlin Shen

    Machine Learning

    日本大学: 関与なし(対象大学)

  8. 2025 · ICML

    BDC-CLIP: Brownian Distance Covariance for Adapting CLIP to Action Recognition

    Fei Long, Xiaoou Li, Jiaming Lv, Haoyuan Yang, Xianjun Cheng, Peihua Li

    Machine Learning

    日本大学: 関与なし(対象大学)

  9. 2025 · ICML

    BECAME: Bayesian Continual Learning with Adaptive Model Merging

    Mei Li, Yuxiang Lu, Qinyan Dai, Suizhi Huang, Yue Ding, Hongtao Lu

    Machine Learning

    日本大学: 関与なし(対象大学)

  10. 2025 · ICML

    BEST-Route: Adaptive LLM Routing with Test-Time Optimal Compute

    Dujian Ding, Ankur Mallick, Shaokun Zhang, Chi Wang, Daniel Madrigal, Mirian Del Carmen Hipolito Garcia, Menglin Xia, Laks V. S. Lakshmanan, Qingyun Wu, Victor Rühle

    Machine Learning

    日本大学: 関与なし(対象大学)

  11. 2025 · ICML

    BILBO: BILevel Bayesian Optimization

    Ruth Wan Theng Chew, Quoc Phong Nguyen, Bryan Kian Hsiang Low

    Machine Learning

    日本大学: 関与なし(対象大学)

  12. 2025 · ICML

    BOOD: Boundary-based Out-Of-Distribution Data Generation

    Qilin Liao, Shuo Yang, Bo Zhao, Ping Luo, Hengshuang Zhao

    Machine Learning

    日本大学: 関与なし(対象大学)

  13. 2025 · ICML

    BOPO: Neural Combinatorial Optimization via Best-anchored and Objective-guided Preference Optimization

    Zijun Liao, Jinbiao Chen, Debing Wang, Zizhen Zhang, Jiahai Wang

    Machine Learning

    日本大学: 関与なし(対象大学)

  14. 2025 · ICML

    BRIDGE: Bootstrapping Text to Control Time-Series Generation via Multi-Agent Iterative Optimization and Diffusion Modeling

    Hao Li, Yu-Hao Huang, Chang Xu, Viktor Schlegel, Renhe Jiang, Riza Batista-Navarro, Goran Nenadic, Jiang Bian

    Machine Learning

    日本大学: 東京大学

  15. 2025 · ICML

    BRiTE: Bootstrapping Reinforced Thinking Process to Enhance Language Model Reasoning

    Han Zhong, Yutong Yin, Shenao Zhang, Xiaojun Xu, Yuanxin Liu, Yifei Zuo, Zhihan Liu, Boyi Liu, Sirui Zheng, Hongyi Guo, Liwei Wang, Mingyi Hong, Zhaoran Wang

    Machine Learning

    日本大学: 関与なし(対象大学)

  16. 2025 · ICML

    BSLoRA: Enhancing the Parameter Efficiency of LoRA with Intra-Layer and Inter-Layer Sharing

    Yuhua Zhou, Ruifeng Li, Changhai Zhou, Fei Yang, Aimin Pan

    Machine Learning

    日本大学: 関与なし(対象大学)

  17. 2025 · ICML

    BSO: Binary Spiking Online Optimization Algorithm

    Yu Liang, Yu Yang, Wenjie Wei, Ammar Belatreche, Shuai Wang, Malu Zhang, Yang Yang

    Machine Learning

    日本大学: 関与なし(対象大学)

  18. 2025 · ICML

    BSemiFL: Semi-supervised Federated Learning via a Bayesian Approach

    Haozhao Wang, Shengyu Wang, Jiaming Li, Hao Ren, Xingshuo Han, Wenchao Xu, Shangwei Guo, Tianwei Zhang, Ruixuan Li

    Machine Learning

    日本大学: 関与なし(対象大学)

  19. 2025 · ICML

    BaWA: Automatic Optimizing Pruning Metric for Large Language Models with Balanced Weight and Activation

    Lian Liu, Xiandong Zhao, Guanchen Li, Dong Li, Mengdi Wang, Yinhe Han, Xiaowei Li, Ying Wang

    Machine Learning

    日本大学: 関与なし(対象大学)

  20. 2025 · ICML

    BackSlash: Rate Constrained Optimized Training of Large Language Models

    Jun Wu, Jiangtao Wen, Yuxing Han

    Machine Learning

    日本大学: 関与なし(対象大学)

  21. 2025 · ICML

    Backdoor Attacks in Token Selection of Attention Mechanism

    Yunjuan Wang, Raman Arora

    Machine Learning

    日本大学: 関与なし(対象大学)

  22. 2025 · ICML

    BalancEdit: Dynamically Balancing the Generality-Locality Trade-off in Multi-modal Model Editing

    Dongliang Guo, Mengxuan Hu, Zihan Guan, Thomas Hartvigsen, Sheng Li

    Machine Learning

    日本大学: 関与なし(対象大学)

  23. 2025 · ICML

    Balanced Learning for Domain Adaptive Semantic Segmentation

    Wangkai Li, Rui Sun, Bohao Liao, Zhaoyang Li, Tianzhu Zhang

    Machine Learning

    日本大学: 関与なし(対象大学)

  24. 2025 · ICML

    Balancing Efficiency and Expressiveness: Subgraph GNNs with Walk-Based Centrality

    Joshua Southern, Yam Eitan, Guy Bar-Shalom, Michael M. Bronstein, Haggai Maron, Fabrizio Frasca

    Machine Learning

    日本大学: 関与なし(対象大学)

  25. 2025 · ICML

    Balancing Interference and Correlation in Spatial Experimental Designs: A Causal Graph Cut Approach

    Jin Zhu, Jingyi Li, Hongyi Zhou, Yinan Lin, Zhenhua Lin, Chengchun Shi

    Machine Learning

    日本大学: 関与なし(対象大学)

  26. 2025 · ICML

    Balancing Model Efficiency and Performance: Adaptive Pruner for Long-tailed Data

    Zhe Zhao, Haibin Wen, Pengkun Wang, Shuang Wang, Zhenkun Wang, Qingfu Zhang, Yang Wang

    Machine Learning

    日本大学: 関与なし(対象大学)

  27. 2025 · ICML

    Balancing Preservation and Modification: A Region and Semantic Aware Metric for Instruction-Based Image Editing

    Zhuoying Li, Zhu Xu, Yuxin Peng, Yang Liu

    Machine Learning

    日本大学: 関与なし(対象大学)

  28. 2025 · ICML

    Balancing the Scales: A Theoretical and Algorithmic Framework for Learning from Imbalanced Data

    Corinna Cortes, Anqi Mao, Mehryar Mohri, Yutao Zhong

    Machine Learning

    日本大学: 関与なし(対象大学)

  29. 2025 · ICML

    BanditSpec: Adaptive Speculative Decoding via Bandit Algorithms

    Yunlong Hou, Fengzhuo Zhang, Cunxiao Du, Xuan Zhang, Jiachun Pan, Tianyu Pang, Chao Du, Vincent Tan, Zhuoran Yang

    Machine Learning

    日本大学: 関与なし(対象大学)

  30. 2025 · ICML

    Banyan: Improved Representation Learning with Explicit Structure

    Mattia Opper, Siddharth N

    Machine Learning

    日本大学: 関与なし(対象大学)

  31. 2025 · ICML

    Batch List-Decodable Linear Regression via Higher Moments

    Ilias Diakonikolas, Daniel Kane, Sushrut Karmalkar, Sihan Liu, Thanasis Pittas

    Machine Learning

    日本大学: 関与なし(対象大学)

  32. 2025 · ICML

    BaxBench: Can LLMs Generate Correct and Secure Backends?

    Mark Vero, Niels Mündler, Victor Chibotaru, Veselin Raychev, Maximilian Baader, Nikola Jovanović, Jingxuan He, Martin Vechev

    Machine Learning

    日本大学: 関与なし(対象大学)

  33. 2025 · ICML

    Bayesian Active Learning for Bivariate Causal Discovery

    Yuxuan Wang, Mingzhou Liu, Xinwei Sun, Wei Wang, Yizhou Wang

    Machine Learning

    日本大学: 関与なし(対象大学)

  34. 2025 · ICML

    Bayesian Basis Function Approximation for Scalable Gaussian Process Priors in Deep Generative Models

    Mehmet Yiğit Balık, Maksim Sinelnikov, Priscilla Ong, Harri Lähdesmäki

    Machine Learning

    日本大学: 関与なし(対象大学)

  35. 2025 · ICML

    Bayesian Inference for Correlated Human Experts and Classifiers

    Markelle Kelly, Alex James Boyd, Sam Showalter, Mark Steyvers, Padhraic Smyth

    Machine Learning

    日本大学: 関与なし(対象大学)

  36. 2025 · ICML

    Bayesian Neural Scaling Law Extrapolation with Prior-Data Fitted Networks

    Dongwoo Lee, Dong Bok Lee, Steven Adriaensen, Juho Lee, Sung Ju Hwang, Frank Hutter, Seon Joo Kim, Hae Beom Lee

    Machine Learning

    日本大学: 関与なし(対象大学)

  37. 2025 · ICML

    Bayesian Optimization from Human Feedback: Near-Optimal Regret Bounds

    Aya Kayal, Sattar Vakili, Laura Toni, Da-Shan Shiu, Alberto Bernacchia

    Machine Learning

    日本大学: 関与なし(対象大学)

  38. 2025 · ICML

    Bayesian Weight Enhancement with Steady-State Adaptation for Test-time Adaptation in Dynamic Environments

    Jae-Hong Lee

    Machine Learning

    日本大学: 関与なし(対象大学)

  39. 2025 · ICML

    Be Confident: Uncovering Overfitting in MLLM Multi-Task Tuning

    Wenke Huang, Jian Liang, Guancheng Wan, Didi Zhu, He Li, Jiawei Shao, Mang Ye, Bo Du, Dacheng Tao

    Machine Learning

    日本大学: 関与なし(対象大学)

  40. 2025 · ICML

    Be a Goldfish: Forgetting Bad Conditioning in Sparse Linear Regression via Variational Autoencoders

    Kuheli Pratihar, Debdeep Mukhopadhyay

    Machine Learning

    日本大学: 関与なし(対象大学)

  41. 2025 · ICML

    Behavior-Regularized Diffusion Policy Optimization for Offline Reinforcement Learning

    Chen-Xiao Gao, Chenyang Wu, Mingjun Cao, Chenjun Xiao, Yang Yu, Zongzhang Zhang

    Machine Learning

    日本大学: 関与なし(対象大学)

  42. 2025 · ICML

    Behavior-agnostic Task Inference for Robust Offline In-context Reinforcement Learning

    Long Ma, Fangwei Zhong, Yizhou Wang

    Machine Learning

    日本大学: 関与なし(対象大学)

  43. 2025 · ICML

    Behavioral Exploration: Learning to Explore via In-Context Adaptation

    Andrew Wagenmaker, Zhiyuan Zhou, Sergey Levine

    Machine Learning

    日本大学: 関与なし(対象大学)

  44. 2025 · ICML

    Bellman Unbiasedness: Toward Provably Efficient Distributional Reinforcement Learning with General Value Function Approximation

    Taehyun Cho, Seungyub Han, Seokhun Ju, Dohyeong Kim, Kyungjae Lee, Jungwoo Lee

    Machine Learning

    日本大学: 関与なし(対象大学)

  45. 2025 · ICML

    Benchmarking Abstract and Reasoning Abilities Through A Theoretical Perspective

    Qingchuan Ma, Yuhang Wu, Xiawu Zheng, Rongrong Ji

    Machine Learning

    日本大学: 関与なし(対象大学)

  46. 2025 · ICML

    Benchmarking Quantum Reinforcement Learning

    Nico Meyer, Christian Ufrecht, George Yammine, Georgios Kontes, Christopher Mutschler, Daniel Scherer

    Machine Learning

    日本大学: 関与なし(対象大学)

  47. 2025 · ICML

    Benefits of Early Stopping in Gradient Descent for Overparameterized Logistic Regression

    Jingfeng Wu, Peter Bartlett, Matus Telgarsky, Bin Yu

    Machine Learning

    日本大学: 関与なし(対象大学)

  48. 2025 · ICML

    Benign Overfitting in Token Selection of Attention Mechanism

    Keitaro Sakamoto, Issei Sato

    Machine Learning

    日本大学: 東京大学

  49. 2025 · ICML

    Benign Samples Matter! Fine-tuning On Outlier Benign Samples Severely Breaks Safety

    Zihan Guan, Mengxuan Hu, Ronghang Zhu, Sheng Li, Anil Vullikanti

    Machine Learning

    日本大学: 関与なし(対象大学)

  50. 2025 · ICML

    Best Subset Selection: Optimal Pursuit for Feature Selection and Elimination

    Zhihan Zhu, Yanhao Zhang, Yong Xia

    Machine Learning

    日本大学: 関与なし(対象大学)

  51. 2025 · ICML

    Best of Both Worlds: Advantages of Hybrid Graph Sequence Models

    Ali Behrouz, Ali Parviz, Mahdi Karami, Clayton Sanford, Bryan Perozzi, Vahab Mirrokni

    Machine Learning

    日本大学: 関与なし(対象大学)

  52. 2025 · ICML

    Best of Both Worlds: Regret Minimization versus Minimax Play

    Adrian Müller, Jon Schneider, Stratis Skoulakis, Luca Viano, Volkan Cevher

    Machine Learning

    日本大学: 関与なし(対象大学)

  53. 2025 · ICML

    Better to Teach than to Give: Domain Generalized Semantic Segmentation via Agent Queries with Diffusion Model Guidance

    Fan Li, Xuan Wang, Min Qi, Zhaoxiang Zhang, Yuelei Xu

    Machine Learning

    日本大学: 関与なし(対象大学)

  54. 2025 · ICML

    Beyond Atoms: Enhancing Molecular Pretrained Representations with 3D Space Modeling

    Shuqi Lu, Xiaohong Ji, Bohang Zhang, Lin Yao, Siyuan Liu, Zhifeng Gao, Linfeng Zhang, Guolin Ke

    Machine Learning

    日本大学: 関与なし(対象大学)

  55. 2025 · ICML

    Beyond Bradley-Terry Models: A General Preference Model for Language Model Alignment

    Yifan Zhang, Ge Zhang, Yue Wu, Kangping Xu, Quanquan Gu

    Machine Learning

    日本大学: 関与なし(対象大学)

  56. 2025 · ICML

    Beyond CVaR: Leveraging Static Spectral Risk Measures for Enhanced Decision-Making in Distributional Reinforcement Learning

    Mehrdad Moghimi, Hyejin Ku

    Machine Learning

    日本大学: 関与なし(対象大学)

  57. 2025 · ICML

    Beyond Communication Overhead: A Multilevel Monte Carlo Approach for Mitigating Compression Bias in Distributed Learning

    Ze’Ev Zukerman, Bassel Hamoud, Kfir Yehuda Levy

    Machine Learning

    日本大学: 関与なし(対象大学)

  58. 2025 · ICML

    Beyond Confidence: Exploiting Homogeneous Pattern for Semi-Supervised Semantic Segmentation

    Rui Sun, Huayu Mai, Wangkai Li, Yujia Chen, Naisong Luo, Yuan Wang, Tianzhu Zhang

    Machine Learning

    日本大学: 関与なし(対象大学)

  59. 2025 · ICML

    Beyond Cropped Regions: New Benchmark and Corresponding Baseline for Chinese Scene Text Retrieval in Diverse Layouts

    Gengluo Li, Huawen Shen, Yu Zhou

    Machine Learning

    日本大学: 関与なし(対象大学)

  60. 2025 · ICML

    Beyond Entropy: Region Confidence Proxy for Wild Test-Time Adaptation

    Zixuan Hu, Yichun Hu, Xiaotong Li, Shixiang Tang, Lingyu Duan

    Machine Learning

    日本大学: 関与なし(対象大学)

  61. 2025 · ICML

    Beyond Induction Heads: In-Context Meta Learning Induces Multi-Phase Circuit Emergence

    Gouki Minegishi, Hiroki Furuta, Shohei Taniguchi, Yusuke Iwasawa, Yutaka Matsuo

    Machine Learning

    日本大学: 東京大学

  62. 2025 · ICML

    Beyond Log-Concavity and Score Regularity: Improved Convergence Bounds for Score-Based Generative Models in W2-distance

    Marta Gentiloni Silveri, Antonio Ocello

    Machine Learning

    日本大学: 関与なし(対象大学)

  63. 2025 · ICML

    Beyond Low-rank Decomposition: A Shortcut Approach for Efficient On-Device Learning

    Le-Trung Nguyen, Aël Quélennec, Van-Tam Nguyen, Enzo Tartaglione

    Machine Learning

    日本大学: 関与なし(対象大学)

  64. 2025 · ICML

    Beyond Matryoshka: Revisiting Sparse Coding for Adaptive Representation

    Tiansheng Wen, Yifei Wang, Zequn Zeng, Zhong Peng, Yudi Su, Xinyang Liu, Bo Chen, Hongwei Liu, Stefanie Jegelka, Chenyu You

    Machine Learning

    日本大学: 関与なし(対象大学)

  65. 2025 · ICML

    Beyond Message Passing: Neural Graph Pattern Machine

    Zehong Wang, Zheyuan Zhang, Tianyi Ma, Nitesh V Chawla, Chuxu Zhang, Yanfang Ye

    Machine Learning

    日本大学: 関与なし(対象大学)

  66. 2025 · ICML

    Beyond Minimax Rates in Group Distributionally Robust Optimization via a Novel Notion of Sparsity

    Quan M. Nguyen, Nishant A Mehta, Cristóbal A Guzmán

    Machine Learning

    日本大学: 関与なし(対象大学)

  67. 2025 · ICML

    Beyond One-Hot Labels: Semantic Mixing for Model Calibration

    Haoyang Luo, Linwei Tao, Minjing Dong, Chang Xu

    Machine Learning

    日本大学: 関与なし(対象大学)

  68. 2025 · ICML

    Beyond Self-Interest: How Group Strategies Reshape Content Creation in Recommendation Platforms?

    Yaolong Yu, Fan Yao, Sinno Jialin Pan

    Machine Learning

    日本大学: 関与なし(対象大学)

  69. 2025 · ICML

    Beyond Self-Repellent Kernels: History-Driven Target Towards Efficient Nonlinear MCMC on General Graphs

    Jie Hu, Yi-Ting Ma, Do Young Eun

    Machine Learning

    日本大学: 関与なし(対象大学)

  70. 2025 · ICML

    Beyond Sensor Data: Foundation Models of Behavioral Data from Wearables Improve Health Predictions

    Eray Erturk, Fahad Kamran, Salar Abbaspourazad, Sean Jewell, Harsh Sharma, Yujie Li, Sinead Williamson, Nicholas J Foti, Joseph Futoma

    Machine Learning

    日本大学: 関与なし(対象大学)

  71. 2025 · ICML

    Beyond Task-Specific Reasoning: A Unified Conditional Generative Framework for Abstract Visual Reasoning

    Fan Shi, Bin Li, Xiangyang Xue

    Machine Learning

    日本大学: 関与なし(対象大学)

  72. 2025 · ICML

    Beyond The Rainbow: High Performance Deep Reinforcement Learning on a Desktop PC

    Tyler Clark, Mark Towers, Christine Evers, Jonathon Hare

    Machine Learning

    日本大学: 関与なし(対象大学)

  73. 2025 · ICML

    Beyond Topological Self-Explainable GNNs: A Formal Explainability Perspective

    Steve Azzolin, Sagar Malhotra, Andrea Passerini, Stefano Teso

    Machine Learning

    日本大学: 関与なし(対象大学)

  74. 2025 · ICML

    Beyond Zero Initialization: Investigating the Impact of Non-Zero Initialization on LoRA Fine-Tuning Dynamics

    Shiwei Li, Xiandi Luo, Xing Tang, Haozhao Wang, Hao Chen, Weihong Luo, Yuhua Li, Xiuqiang He, Ruixuan Li

    Machine Learning

    日本大学: 関与なし(対象大学)

  75. 2025 · ICML

    Beyond the Permutation Symmetry of Transformers: The Role of Rotation for Model Fusion

    Binchi Zhang, Zaiyi Zheng, Zhengzhang Chen, Jundong Li

    Machine Learning

    日本大学: 関与なし(対象大学)

  76. 2025 · ICML

    Bi-perspective Splitting Defense: Achieving Clean-Seed-Free Backdoor Security

    Yangyang Shen, Xiao Tan, Dian Shen, Meng Wang, Beilun Wang

    Machine Learning

    日本大学: 関与なし(対象大学)

  77. 2025 · ICML

    BiAssemble: Learning Collaborative Affordance for Bimanual Geometric Assembly

    Yan Shen, Ruihai Wu, Yubin Ke, Xinyuan Song, Zeyi Li, Xiaoqi Li, Hongwei Fan, Haoran Lu, Hao Dong

    Machine Learning

    日本大学: 関与なし(対象大学)

  78. 2025 · ICML

    BiMaCoSR: Binary One-Step Diffusion Model Leveraging Flexible Matrix Compression for Real Super-Resolution

    Kai Liu, Kaicheng Yang, Zheng Chen, Zhiteng Li, Yong Guo, Wenbo Li, Linghe Kong, Yulun Zhang

    Machine Learning

    日本大学: 関与なし(対象大学)

  79. 2025 · ICML

    BiMark: Unbiased Multilayer Watermarking for Large Language Models

    Xiaoyan Feng, He Zhang, Yanjun Zhang, Leo Yu Zhang, Shirui Pan

    Machine Learning

    日本大学: 関与なし(対象大学)

  80. 2025 · ICML

    Bifurcate then Alienate: Incomplete Multi-view Clustering via Coupled Distribution Learning with Linear Overhead

    Shengju Yu, Yiu-Ming Cheung, Siwei Wang, Xinwang Liu, En Zhu

    Machine Learning

    日本大学: 関与なし(対象大学)

  81. 2025 · ICML

    Binary Hypothesis Testing for Softmax Models and Leverage Score Models

    Yuzhou Gu, Zhao Song, Junze Yin

    Machine Learning

    日本大学: 関与なし(対象大学)

  82. 2025 · ICML

    BinauralFlow: A Causal and Streamable Approach for High-Quality Binaural Speech Synthesis with Flow Matching Models

    Susan Liang, Dejan Markovic, Israel D. Gebru, Steven Krenn, Todd Keebler, Jacob Sandakly, Frank Yu, Samuel Hassel, Chenliang Xu, Alexander Richard

    Machine Learning

    日本大学: 関与なし(対象大学)

  83. 2025 · ICML

    Bipartite Ranking From Multiple Labels: On Loss Versus Label Aggregation

    Michal Lukasik, Lin Chen, Harikrishna Narasimhan, Aditya Krishna Menon, Wittawat Jitkrittum, Felix X. Yu, Sashank J. Reddi, Gang Fu, Mohammadhossein Bateni, Sanjiv Kumar

    Machine Learning

    日本大学: 関与なし(対象大学)

  84. 2025 · ICML

    Bivariate Causal Discovery with Proxy Variables: Integral Solving and Beyond

    Yong Wu, Yanwei Fu, Shouyan Wang, Xinwei Sun

    Machine Learning

    日本大学: 関与なし(対象大学)

  85. 2025 · ICML

    Black-Box Adversarial Attacks on LLM-Based Code Completion

    Slobodan Jenko, Niels Mündler, Jingxuan He, Mark Vero, Martin Vechev

    Machine Learning

    日本大学: 関与なし(対象大学)

  86. 2025 · ICML

    Blink of an eye: a simple theory for feature localization in generative models

    Marvin Li, Aayush Karan, Sitan Chen

    Machine Learning

    日本大学: 関与なし(対象大学)

  87. 2025 · ICML

    BlockDialect: Block-wise Fine-grained Mixed Format Quantization for Energy-Efficient LLM Inference

    Wonsuk Jang, Thierry Tambe

    Machine Learning

    日本大学: 関与なし(対象大学)

  88. 2025 · ICML

    BoA: Attention-aware Post-training Quantization without Backpropagation

    Junhan Kim, Ho-Young Kim, Eulrang Cho, Chungman Lee, Joonyoung Kim, Yongkweon Jeon

    Machine Learning

    日本大学: 関与なし(対象大学)

  89. 2025 · ICML

    Bongard in Wonderland: Visual Puzzles that Still Make AI Go Mad?

    Antonia Wüst, Tim Tobiasch, Lukas Helff, Inga Ibs, Wolfgang Stammer, Devendra Singh Dhami, Constantin A. Rothkopf, Kristian Kersting

    Machine Learning

    日本大学: 関与なし(対象大学)

  90. 2025 · ICML

    Boost-and-Skip: A Simple Guidance-Free Diffusion for Minority Generation

    Soobin Um, Beomsu Kim, Jong Chul Ye

    Machine Learning

    日本大学: 関与なし(対象大学)

  91. 2025 · ICML

    Boosting Adversarial Robustness with CLAT: Criticality Leveraged Adversarial Training

    Bhavna Gopal, Huanrui Yang, Jingyang Zhang, Mark Horton, Yiran Chen

    Machine Learning

    日本大学: 関与なし(対象大学)

  92. 2025 · ICML

    Boosting Masked ECG-Text Auto-Encoders as Discriminative Learners

    Manh Pham Hung, Aaqib Saeed, Dong Ma

    Machine Learning

    日本大学: 関与なし(対象大学)

  93. 2025 · ICML

    Boosting Multi-Domain Fine-Tuning of Large Language Models through Evolving Interactions between Samples

    Xize Liang, Lin Yang, Jie Wang, Yiyang Lu, Runyu Wu, Hanzhu Chen, Jianye Hao

    Machine Learning

    日本大学: 関与なし(対象大学)

  94. 2025 · ICML

    Boosting Protein Graph Representations through Static-Dynamic Fusion

    Pengkang Guo, Bruno Correia, Pierre Vandergheynst, Daniel Probst

    Machine Learning

    日本大学: 関与なし(対象大学)

  95. 2025 · ICML

    Boosting Virtual Agent Learning and Reasoning: A Step-Wise, Multi-Dimensional, and Generalist Reward Model with Benchmark

    Bingchen Miao, Yang Wu, Minghe Gao, Qifan Yu, Wendong Bu, Wenqiao Zhang, Yunfei Li, Siliang Tang, Tat-Seng Chua, Juncheng Li

    Machine Learning

    日本大学: 関与なし(対象大学)

  96. 2025 · ICML

    Bootstrapping Self-Improvement of Language Model Programs for Zero-Shot Schema Matching

    Nabeel Seedat, Mihaela Van Der Schaar

    Machine Learning

    日本大学: 関与なし(対象大学)

  97. 2025 · ICML

    BounDr.E: Predicting Drug-likeness via Biomedical Knowledge Alignment and EM-like One-Class Boundary Optimization

    Dongmin Bang, Inyoung Sung, Yinhua Piao, Sangseon Lee, Sun Kim

    Machine Learning

    日本大学: 関与なし(対象大学)

  98. 2025 · ICML

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