ICML

2021–2025 確定版

著者一覧 · 国際会議 · 大学ランキング

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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
Fleet of Agents: Coordinated Problem Solving with Large Language Models
Lars Henning Klein, Nearchos Potamitis, Roland Aydin, Robert West, Caglar Gulcehre, Akhil Arora
Machine Learning
日本大学: 関与なし（対象大学）
2025 · ICML
Flex3D: Feed-Forward 3D Generation with Flexible Reconstruction Model and Input View Curation
Junlin Han, Jianyuan Wang, Andrea Vedaldi, Philip Torr, Filippos Kokkinos
Machine Learning
日本大学: 関与なし（対象大学）
2025 · ICML
FlexControl: Computation-Aware Conditional Control with Differentiable Router for Text-to-Image Generation
Zheng Fang, Lichuan Xiang, Xu Cai, Kaicheng Zhou, Hongkai Wen
Machine Learning
日本大学: 関与なし（対象大学）
2025 · ICML
FlexTok: Resampling Images into 1D Token Sequences of Flexible Length
Roman Bachmann, Jesse Allardice, David Mizrahi, Enrico Fini, Oğuzhan Fatih Kar, Elmira Amirloo, Alaaeldin El-Nouby, Amir Zamir, Afshin Dehghan
Machine Learning
日本大学: 関与なし（対象大学）
2025 · ICML
FlexiClip: Locality-Preserving Free-Form Character Animation
Anant Khandelwal
Machine Learning
日本大学: 関与なし（対象大学）
2025 · ICML
FlexiReID: Adaptive Mixture of Expert for Multi-Modal Person Re-Identification
Zhen Sun, Lei Tan, Yunhang Shen, Chengmao Cai, Xing Sun, Pingyang Dai, Liujuan Cao, Rongrong Ji
Machine Learning
日本大学: 関与なし（対象大学）
2025 · ICML
Flexibility-conditioned protein structure design with flow matching
Vsevolod Viliuga, Leif Seute, Nicolas Wolf, Simon Wagner, Arne Elofsson, Jan Stühmer, Frauke Gräter
Machine Learning
日本大学: 関与なし（対象大学）
2025 · ICML
Flexible Tails for Normalizing Flows
Tennessee Hickling, Dennis Prangle
Machine Learning
日本大学: 関与なし（対象大学）
2025 · ICML
Flexible and Efficient Grammar-Constrained Decoding
Kanghee Park, Timothy Zhou, Loris D’Antoni
Machine Learning
日本大学: 関与なし（対象大学）
2025 · ICML
Flexible, Efficient, and Stable Adversarial Attacks on Machine Unlearning
Zihan Zhou, Yang Zhou, Zijie Zhang, Lingjuan Lyu, Da Yan, Ruoming Jin, Dejing Dou
Machine Learning
日本大学: 関与なし（対象大学）
2025 · ICML
FlipAttack: Jailbreak LLMs via Flipping
Yue Liu, Xiaoxin He, Miao Xiong, Jinlan Fu, Shumin Deng, Yingwei Ma, Jiaheng Zhang, Bryan Hooi
Machine Learning
日本大学: 関与なし（対象大学）
2025 · ICML
FloE: On-the-Fly MoE Inference on Memory-constrained GPU
Yuxin Zhou, Zheng Li, Jun Zhang, Jue Wang, Yiping Wang, Zhongle Xie, Ke Chen, Lidan Shou
Machine Learning
日本大学: 関与なし（対象大学）
2025 · ICML
Floating-Point Neural Networks Can Represent Almost All Floating-Point Functions
Geonho Hwang, Yeachan Park, Wonyeol Lee, Sejun Park
Machine Learning
日本大学: 関与なし（対象大学）
2025 · ICML
Flopping for FLOPs: Leveraging Equivariance for Computational Efficiency
Georg Bökman, David Nordström, Fredrik Kahl
Machine Learning
日本大学: 関与なし（対象大学）
2025 · ICML
Flow Matching for Denoised Social Recommendation
Yinxuan Huang, Ke Liang, Zhuofan Dong, Xiaodong Qu, Wang Tianxiang, Yue Han, Jingao Xu, Bin Zhou, Ye Wang
Machine Learning
日本大学: 関与なし（対象大学）
2025 · ICML
Flow Matching for Few-Trial Neural Adaptation with Stable Latent Dynamics
Puli Wang, Yu Qi, Yueming Wang, Gang Pan
Machine Learning
日本大学: 関与なし（対象大学）
2025 · ICML
Flow Q-Learning
Seohong Park, Qiyang Li, Sergey Levine
Machine Learning
日本大学: 関与なし（対象大学）
2025 · ICML
Flow of Reasoning: Training LLMs for Divergent Reasoning with Minimal Examples
Fangxu Yu, Lai Jiang, Haoqiang Kang, Shibo Hao, Lianhui Qin
Machine Learning
日本大学: 関与なし（対象大学）
2025 · ICML
Flow-based Domain Randomization for Learning and Sequencing Robotic Skills
Aidan Curtis, Eric Li, Michael Noseworthy, Nishad Gothoskar, Sachin Chitta, Hui Li, Leslie Pack Kaelbling, Nicole E Carey
Machine Learning
日本大学: 関与なし（対象大学）
2025 · ICML
Flow-field inference from neural data using deep recurrent networks
Timothy Doyeon Kim, Thomas Zhihao Luo, Tankut Can, Kamesh Krishnamurthy, Jonathan W. Pillow, Carlos D Brody
Machine Learning
日本大学: 関与なし（対象大学）
2025 · ICML
Flow-of-Options: Diversified and Improved LLM Reasoning by Thinking Through Options
Lakshmi Nair, Ian Trase, J. Mark Kim
Machine Learning
日本大学: 関与なし（対象大学）
2025 · ICML
FlowAR: Scale-wise Autoregressive Image Generation Meets Flow Matching
Sucheng Ren, Qihang Yu, Ju He, Xiaohui Shen, Alan Yuille, Liang-Chieh Chen
Machine Learning
日本大学: 関与なし（対象大学）
2025 · ICML
FlowDrag: 3D-aware Drag-based Image Editing with Mesh-guided Deformation Vector Flow Fields
Gwanhyeong Koo, Sunjae Yoon, Younghwan Lee, Ji Woo Hong, Chang D. Yoo
Machine Learning
日本大学: 関与なし（対象大学）
2025 · ICML
Flowing Datasets with Wasserstein over Wasserstein Gradient Flows
Clément Bonet, Christophe Vauthier, Anna Korba
Machine Learning
日本大学: 関与なし（対象大学）
2025 · ICML
Fluctuations of the largest eigenvalues of transformed spiked Wigner matrices
Aro Lee, Ji Oon Lee
Machine Learning
日本大学: 関与なし（対象大学）
2025 · ICML
Focal-SAM: Focal Sharpness-Aware Minimization for Long-Tailed Classification
Sicong Li, Qianqian Xu, Zhiyong Yang, Zitai Wang, Linchao Zhang, Xiaochun Cao, Qingming Huang
Machine Learning
日本大学: 関与なし（対象大学）
2025 · ICML
Focus On This, Not That! Steering LLMs with Adaptive Feature Specification
Tom A. Lamb, Adam Davies, Alasdair Paren, Philip Torr, Francesco Pinto
Machine Learning
日本大学: 関与なし（対象大学）
2025 · ICML
Forest-of-Thought: Scaling Test-Time Compute for Enhancing LLM Reasoning
Zhenni Bi, Kai Han, Chuanjian Liu, Yehui Tang, Yunhe Wang
Machine Learning
日本大学: 関与なし（対象大学）
2025 · ICML
Foundation Model Insights and a Multi-Model Approach for Superior Fine-Grained One-shot Subset Selection
Zhijing Wan, Zhixiang Wang, Zheng Wang, Xin Xu, Shin’Ichi Satoh
Machine Learning
日本大学: 関与なし（対象大学）
2025 · ICML
Foundation Molecular Grammar: Multi-Modal Foundation Models Induce Interpretable Molecular Graph Languages
Michael Sun, Weize Yuan, Gang Liu, Wojciech Matusik, Jie Chen
Machine Learning
日本大学: 関与なし（対象大学）
2025 · ICML
Fourier Position Embedding: Enhancing Attention’s Periodic Extension for Length Generalization
Ermo Hua, Che Jiang, Xingtai Lv, Kaiyan Zhang, Youbang Sun, Yuchen Fan, Xuekai Zhu, Biqing Qi, Ning Ding, Bowen Zhou
Machine Learning
日本大学: 関与なし（対象大学）
2025 · ICML
FourierMamba: Fourier Learning Integration with State Space Models for Image Deraining
Dong Li, Yidi Liu, Xueyang Fu, Jie Huang, Senyan Xu, Qi Zhu, Zheng-Jun Zha
Machine Learning
日本大学: 関与なし（対象大学）
2025 · ICML
Fragments to Facts: Partial-Information Fragment Inference from LLMs
Lucas Rosenblatt, Bin Han, Robert Wolfe, Bill Howe
Machine Learning
日本大学: 関与なし（対象大学）
2025 · ICML
FrameBridge: Improving Image-to-Video Generation with Bridge Models
Yuji Wang, Zehua Chen, Chen Xiaoyu, Yixiang Wei, Jun Zhu, Jianfei Chen
Machine Learning
日本大学: 関与なし（対象大学）
2025 · ICML
Fraud-Proof Revenue Division on Subscription Platforms
Abheek Ghosh, Tzeh Yuan Neoh, Nicholas Teh, Giannis Tyrovolas
Machine Learning
日本大学: 関与なし（対象大学）
2025 · ICML
Free Process Rewards without Process Labels
Lifan Yuan, Wendi Li, Huayu Chen, Ganqu Cui, Ning Ding, Kaiyan Zhang, Bowen Zhou, Zhiyuan Liu, Hao Peng
Machine Learning
日本大学: 関与なし（対象大学）
2025 · ICML
FreeMesh: Boosting Mesh Generation with Coordinates Merging
Jian Liu, Haohan Weng, Biwen Lei, Xianghui Yang, Zibo Zhao, Zhuo Chen, Song Guo, Tao Han, Chunchao Guo
Machine Learning
日本大学: 関与なし（対象大学）
2025 · ICML
Freeze-Omni: A Smart and Low Latency Speech-to-speech Dialogue Model with Frozen LLM
Xiong Wang, Yangze Li, Chaoyou Fu, Yike Zhang, Yunhang Shen, Lei Xie, Ke Li, Xing Sun, Long Ma
Machine Learning
日本大学: 関与なし（対象大学）
2025 · ICML
From Black Boxes to Transparent Minds: Evaluating and Enhancing the Theory of Mind in Multimodal Large Language Models
Xinyang Li, Siqi Liu, Bochao Zou, Jiansheng Chen, Huimin Ma
Machine Learning
日本大学: 関与なし（対象大学）
2025 · ICML
From Complex to Atomic: Enhancing Augmented Generation via Knowledge-Aware Dual Rewriting and Reasoning
Jinyu Wang, Jingjing Fu, Rui Wang, Lei Song, Jiang Bian
Machine Learning
日本大学: 関与なし（対象大学）
2025 · ICML
From Crowdsourced Data to High-quality Benchmarks: Arena-Hard and Benchbuilder Pipeline
Tianle Li, Wei-Lin Chiang, Evan Frick, Lisa Dunlap, Tianhao Wu, Banghua Zhu, Joseph E. Gonzalez, Ion Stoica
Machine Learning
日本大学: 関与なし（対象大学）
2025 · ICML
From Debate to Equilibrium: Belief-Driven Multi-Agent LLM Reasoning via Bayesian Nash Equilibrium
Xie Yi, Zhanke Zhou, Chentao Cao, Qiyu Niu, Tongliang Liu, Bo Han
Machine Learning
日本大学: 関与なし（対象大学）
2025 · ICML
From Feature Interaction to Feature Generation: A Generative Paradigm of CTR Prediction Models
Mingjia Yin, Junwei Pan, Hao Wang, Ximei Wang, Shangyu Zhang, Jie Jiang, Defu Lian, Enhong Chen
Machine Learning
日本大学: 関与なし（対象大学）
2025 · ICML
From Individual Experience to Collective Evidence: A Reporting-Based Framework for Identifying Systemic Harms
Jessica Dai, Paula Gradu, Inioluwa Deborah Raji, Benjamin Recht
Machine Learning
日本大学: 関与なし（対象大学）
2025 · ICML
From Jack of All Trades to Master of One: Specializing LLM-based Autoraters to a Test Set
Mara Finkelstein, Daniel Deutsch, Parker Riley, Juraj Juraska, Geza Kovacs, Markus Freitag
Machine Learning
日本大学: 関与なし（対象大学）
2025 · ICML
From Kernels to Features: A Multi-Scale Adaptive Theory of Feature Learning
Noa Rubin, Kirsten Fischer, Javed Lindner, Inbar Seroussi, Zohar Ringel, Michael Krämer, Moritz Helias
Machine Learning
日本大学: 関与なし（対象大学）
2025 · ICML
From Language Models over Tokens to Language Models over Characters
Tim Vieira, Benjamin Lebrun, Mario Giulianelli, Juan Luis Gastaldi, Brian Dusell, John Terilla, Timothy J. O’Donnell, Ryan Cotterell
Machine Learning
日本大学: 関与なし（対象大学）
2025 · ICML
From Local Details to Global Context: Advancing Vision-Language Models with Attention-Based Selection
Lincan Cai, Jingxuan Kang, Shuang Li, Wenxuan Ma, Binhui Xie, Zhida Qin, Jian Liang
Machine Learning
日本大学: 関与なし（対象大学）
2025 · ICML
From Logits to Hierarchies: Hierarchical Clustering made Simple
Emanuele Palumbo, Moritz Vandenhirtz, Alain Ryser, Imant Daunhawer, Julia E Vogt
Machine Learning
日本大学: 関与なし（対象大学）
2025 · ICML
From Low Rank Gradient Subspace Stabilization to Low-Rank Weights: Observations, Theories, and Applications
Ajay Kumar Jaiswal, Yifan Wang, Lu Yin, Shiwei Liu, Runjin Chen, Jiawei Zhao, Ananth Grama, Yuandong Tian, Zhangyang Wang
Machine Learning
日本大学: 関与なし（対象大学）
2025 · ICML
From Mechanistic Interpretability to Mechanistic Biology: Training, Evaluating, and Interpreting Sparse Autoencoders on Protein Language Models
Etowah Adams, Liam Bai, Minji Lee, Yiyang Yu, Mohammed Alquraishi
Machine Learning
日本大学: 関与なし（対象大学）
2025 · ICML
From Passive to Active Reasoning: Can Large Language Models Ask the Right Questions under Incomplete Information?
Zhanke Zhou, Xiao Feng, Zhaocheng Zhu, Jiangchao Yao, Sanmi Koyejo, Bo Han
Machine Learning
日本大学: 関与なし（対象大学）
2025 · ICML
From Pixels to Perception: Interpretable Predictions via Instance-wise Grouped Feature Selection
Moritz Vandenhirtz, Julia E Vogt
Machine Learning
日本大学: 関与なし（対象大学）
2025 · ICML
From RAG to Memory: Non-Parametric Continual Learning for Large Language Models
Bernal Jiménez Gutiérrez, Yiheng Shu, Weijian Qi, Sizhe Zhou, Yu Su
Machine Learning
日本大学: 関与なし（対象大学）
2025 · ICML
From Spectrum-free towards Baseline-view-free: Double-track Proximity Driven Multi-view Clustering
Shengju Yu, Zhibin Dong, Siwei Wang, Suyuan Liu, Ke Liang, Xinwang Liu, Yue Liu, Yi Zhang
Machine Learning
日本大学: 関与なし（対象大学）
2025 · ICML
From Theory to Practice: Rethinking Green and Martin Kernels for Unleashing Graph Transformers
Yoon Hyeok Lee, Jaemin Park, Taejin Paik, Doyun Kim, Bosun Hwang
Machine Learning
日本大学: 関与なし（対象大学）
2025 · ICML
From Thousands to Billions: 3D Visual Language Grounding via Render-Supervised Distillation from 2D VLMs
Ang Cao, Sergio Arnaud, Oleksandr Maksymets, Jianing Yang, Ayush Jain, Ada Martin, Vincent-Pierre Berges, Paul Mcvay, Ruslan Partsey, Aravind Rajeswaran, Franziska Meier, Justin Johnson, Jeong Joon Park, Alexander Sax
Machine Learning
日本大学: 関与なし（対象大学）
2025 · ICML
From Token to Rhythm: A Multi-Scale Approach for ECG-Language Pretraining
Fuying Wang, Jiacheng Xu, Lequan Yu
Machine Learning
日本大学: 関与なし（対象大学）
2025 · ICML
From Uncertain to Safe: Conformal Adaptation of Diffusion Models for Safe PDE Control
Peiyan Hu, Xiaowei Qian, Wenhao Deng, Rui Wang, Haodong Feng, Ruiqi Feng, Tao Zhang, Long Wei, Yue Wang, Zhi-Ming Ma, Tailin Wu
Machine Learning
日本大学: 関与なし（対象大学）
2025 · ICML
From Weight-Based to State-Based Fine-Tuning: Further Memory Reduction on LoRA with Parallel Control
Chi Zhang, Ren Lianhai, Jingpu Cheng, Qianxiao Li
Machine Learning
日本大学: 関与なし（対象大学）
2025 · ICML
Fully Dynamic Embedding into $\ell_p$ Spaces
Kiarash Banihashem, Xiang Chen, Mohammadtaghi Hajiaghayi, Sungchul Kim, Kanak Mahadik, Ryan A. Rossi, Tong Yu
Machine Learning
日本大学: 関与なし（対象大学）
2025 · ICML
Fully Dynamic Euclidean Bi-Chromatic Matching in Sublinear Update Time
Gramoz Goranci, Peter Kiss, Neel Patel, Martin P. Seybold, Eva Szilagyi, Da Wei Zheng
Machine Learning
日本大学: 関与なし（対象大学）
2025 · ICML
Fully Heteroscedastic Count Regression with Deep Double Poisson Networks
Spencer Young, Porter Jenkins, Longchao Da, Jeff Dotson, Hua Wei
Machine Learning
日本大学: 関与なし（対象大学）
2025 · ICML
FunBO: Discovering Acquisition Functions for Bayesian Optimization with FunSearch
Virginia Aglietti, Ira Ktena, Jessica Schrouff, Eleni Sgouritsa, Francisco Ruiz, Alan Malek, Alexis Bellot, Silvia Chiappa
Machine Learning
日本大学: 関与なし（対象大学）
2025 · ICML
Function Encoders: A Principled Approach to Transfer Learning in Hilbert Spaces
Tyler Ingebrand, Adam Thorpe, Ufuk Topcu
Machine Learning
日本大学: 関与なし（対象大学）
2025 · ICML
Function-Space Learning Rates
Edward Milsom, Ben Anson, Laurence Aitchison
Machine Learning
日本大学: 関与なし（対象大学）
2025 · ICML
Function-to-Style Guidance of LLMs for Code Translation
Longhui Zhang, Bin Wang, Jiahao Wang, Xiaofeng Zhao, Min Zhang, Hao Yang, Meishan Zhang, Yu Li, Jing Li, Jun Yu, Min Zhang
Machine Learning
日本大学: 関与なし（対象大学）
2025 · ICML
Functional Alignment Can Mislead: Examining Model Stitching
Damian Smith, Harvey Mannering, Antonia Marcu
Machine Learning
日本大学: 関与なし（対象大学）
2025 · ICML
Fundamental Bias in Inverting Random Sampling Matrices with Application to Sub-sampled Newton
Chengmei Niu, Zhenyu Liao, Zenan Ling, Michael W. Mahoney
Machine Learning
日本大学: 関与なし（対象大学）
2025 · ICML
Fundamental Limits of Visual Autoregressive Transformers: Universal Approximation Abilities
Yifang Chen, Xiaoyu Li, Yingyu Liang, Zhenmei Shi, Zhao Song
Machine Learning
日本大学: 関与なし（対象大学）
2025 · ICML
Fundamental limits of learning in sequence multi-index models and deep attention networks: high-dimensional asymptotics and sharp thresholds
Emanuele Troiani, Hugo Cui, Yatin Dandi, Florent Krzakala, Lenka Zdeborova
Machine Learning
日本大学: 関与なし（対象大学）
2025 · ICML
FuseUNet: A Multi-Scale Feature Fusion Method for U-like Networks
Quansong He, Xiangde Min, Kaishen Wang, Tao He
Machine Learning
日本大学: 関与なし（対象大学）
2025 · ICML
Fusing Reward and Dueling Feedback in Stochastic Bandits
Xuchuang Wang, Qirun Zeng, Jinhang Zuo, Xutong Liu, Mohammad Hajiesmaili, John C.S. Lui, Adam Wierman
Machine Learning
日本大学: 関与なし（対象大学）
2025 · ICML
G-Adaptivity: optimised graph-based mesh relocation for finite element methods
James Rowbottom, Georg Maierhofer, Teo Deveney, Eike Hermann Müller, Alberto Paganini, Katharina Schratz, Pietro Lio, Carola-Bibiane Schönlieb, Chris Budd
Machine Learning
日本大学: 関与なし（対象大学）
2025 · ICML
G-Designer: Architecting Multi-agent Communication Topologies via Graph Neural Networks
Guibin Zhang, Yanwei Yue, Xiangguo Sun, Guancheng Wan, Miao Yu, Junfeng Fang, Kun Wang, Tianlong Chen, Dawei Cheng
Machine Learning
日本大学: 関与なし（対象大学）
2025 · ICML
G-Sim: Generative Simulations with Large Language Models and Gradient-Free Calibration
Samuel Holt, Max Ruiz Luyten, Antonin Berthon, Mihaela Van Der Schaar
Machine Learning
日本大学: 関与なし（対象大学）
2025 · ICML
GANQ: GPU-Adaptive Non-Uniform Quantization for Large Language Models
Pengxiang Zhao, Xiaoming Yuan
Machine Learning
日本大学: 関与なし（対象大学）
2025 · ICML
GAPrompt: Geometry-Aware Point Cloud Prompt for 3D Vision Model
Zixiang Ai, Zichen Liu, Yuanhang Lei, Zhenyu Cui, Xu Zou, Jiahuan Zhou
Machine Learning
日本大学: 関与なし（対象大学）
2025 · ICML
GCAL: Adapting Graph Models to Evolving Domain Shifts
Ziyue Qiao, Qianyi Cai, Hao Dong, Jiawei Gu, Pengyang Wang, Meng Xiao, Xiao Luo, Hui Xiong
Machine Learning
日本大学: 関与なし（対象大学）
2025 · ICML
GEFA: A General Feature Attribution Framework Using Proxy Gradient Estimation
Yi Cai, Thibaud Ardoin, Gerhard Wunder
Machine Learning
日本大学: 関与なし（対象大学）
2025 · ICML
GHOST: Generalizable One-Shot Federated Graph Learning with Proxy-Based Topology Knowledge Retention
Jiaru Qian, Guancheng Wan, Wenke Huang, Guibin Zhang, Yuxin Wu, Bo Du, Mang Ye
Machine Learning
日本大学: 関与なし（対象大学）
2025 · ICML
GIVE: Structured Reasoning of Large Language Models with Knowledge Graph Inspired Veracity Extrapolation
Jiashu He, Mingyu Derek Ma, Jinxuan Fan, Dan Roth, Wei Wang, Alejandro Ribeiro
Machine Learning
日本大学: 関与なし（対象大学）
2025 · ICML
GLGENN: A Novel Parameter-Light Equivariant Neural Networks Architecture Based on Clifford Geometric Algebras
Ekaterina Filimoshina, Dmitry Shirokov
Machine Learning
日本大学: 関与なし（対象大学）
2025 · ICML
GMAIL: Generative Modality Alignment for generated Image Learning
Shentong Mo, Sukmin Yun
Machine Learning
日本大学: 関与なし（対象大学）
2025 · ICML
GPEN: Global Position Encoding Network for Enhanced Subgraph Representation Learning
Nannan Wu, Yuming Huang, Yiming Zhao, Jie Chen, Wenjun Wang
Machine Learning
日本大学: 関与なし（対象大学）
2025 · ICML
GPTAQ: Efficient Finetuning-Free Quantization for Asymmetric Calibration
Yuhang Li, Ruokai Yin, Donghyun Lee, Shiting Xiao, Priyadarshini Panda
Machine Learning
日本大学: 関与なし（対象大学）
2025 · ICML
GRADEO: Towards Human-Like Evaluation for Text-to-Video Generation via Multi-Step Reasoning
Zhun Mou, Bin Xia, Zhengchao Huang, Wenming Yang, Jiaya Jia
Machine Learning
日本大学: 関与なし（対象大学）
2025 · ICML
GRAIL: Graph Edit Distance and Node Alignment using LLM-Generated Code
Samidha Verma, Arushi Goyal, Ananya Mathur, Ankit Anand, Sayan Ranu
Machine Learning
日本大学: 関与なし（対象大学）
2025 · ICML
GRAM: A Generative Foundation Reward Model for Reward Generalization
Chenglong Wang, Yang Gan, Yifu Huo, Yongyu Mu, Qiaozhi He, Murun Yang, Bei Li, Tong Xiao, Chunliang Zhang, Tongran Liu, Jingbo Zhu
Machine Learning
日本大学: 関与なし（対象大学）
2025 · ICML
GRU: Mitigating the Trade-off between Unlearning and Retention for LLMs
Yue Wang, Qizhou Wang, Feng Liu, Wei Huang, Yali Du, Xiaojiang Du, Bo Han
Machine Learning
日本大学: 関与なし（対象大学）
2025 · ICML
GS-Bias: Global-Spatial Bias Learner for Single-Image Test-Time Adaptation of Vision-Language Models
Zhaohong Huang, Yuxin Zhang, Jingjing Xie, Fei Chao, Rongrong Ji
Machine Learning
日本大学: 関与なし（対象大学）
2025 · ICML
GSM-$∞$: How Do your LLMs Behave over Infinitely Increasing Reasoning Complexity and Context Length?
Yang Zhou, Hongyi Liu, Zhuoming Chen, Yuandong Tian, Beidi Chen
Machine Learning
日本大学: 関与なし（対象大学）
2025 · ICML
GTR: A General, Multi-View, and Dynamic Framework for Trajectory Representation Learning
Xiangheng Wang, Ziquan Fang, Chenglong Huang, Danlei Hu, Lu Chen, Yunjun Gao
Machine Learning
日本大学: 関与なし（対象大学）
2025 · ICML
Galileo: Learning Global & Local Features of Many Remote Sensing Modalities
Gabriel Tseng, Anthony Fuller, Marlena Reil, Henry Herzog, Patrick Beukema, Favyen Bastani, James R Green, Evan Shelhamer, Hannah Kerner, David Rolnick
Machine Learning
日本大学: 関与なし（対象大学）
2025 · ICML
Gamma Distribution PCA-Enhanced Feature Learning for Angle-Robust SAR Target Recognition
Chong Zhang, Peng Zhang, Mengke Li
Machine Learning
日本大学: 関与なし（対象大学）
2025 · ICML
Gandalf the Red: Adaptive Security for LLMs
Niklas Pfister, Václav Volhejn, Manuel Knott, Santiago Arias, Julia Bazinska, Mykhailo Bichurin, Alan Y. Commike, Janet Darling, Peter Dienes, Matthew Fiedler, David Haber, Matthias Kraft, Marco Lancini, Max Mathys, Damian Pascual-Ortiz, Jakub Podolak, Adrià Romero-López, Kyriacos Shiarlis, Andreas Signer, Zsolt Terek, Athanasios Theocharis, Daniel Timbrell, Samuel Trautwein, Samuel Watts, Yun-Han Wu, Mateo Rojas-Carulla
Machine Learning
日本大学: 関与なし（対象大学）
2025 · ICML
Gap-Dependent Bounds for Federated $Q$-Learning
Haochen Zhang, Zhong Zheng, Lingzhou Xue
Machine Learning
日本大学: 関与なし（対象大学）
2025 · ICML
GaussMark: A Practical Approach for Structural Watermarking of Language Models
Adam Block, Alexander Rakhlin, Ayush Sekhari
Machine Learning
日本大学: 関与なし（対象大学）
2025 · ICML
GaussMarker: Robust Dual-Domain Watermark for Diffusion Models
Kecen Li, Zhicong Huang, Xinwen Hou, Cheng Hong
Machine Learning
日本大学: 関与なし（対象大学）
2025 · ICML
Gaussian Mixture Flow Matching Models
Hansheng Chen, Kai Zhang, Hao Tan, Zexiang Xu, Fujun Luan, Leonidas Guibas, Gordon Wetzstein, Sai Bi
Machine Learning
日本大学: 関与なし（対象大学）