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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
Is Noise Conditioning Necessary for Denoising Generative Models?
Qiao Sun, Zhicheng Jiang, Hanhong Zhao, Kaiming He
Machine Learning
日本大学: 関与なし（対象大学）
2025 · ICML
Is Your Model Fairly Certain? Uncertainty-Aware Fairness Evaluation for LLMs
Yinong Oliver Wang, Nivedha Sivakumar, Falaah Arif Khan, Katherine Metcalf, Adam Golinski, Natalie Mackraz, Barry-John Theobald, Luca Zappella, Nicholas Apostoloff
Machine Learning
日本大学: 関与なし（対象大学）
2025 · ICML
Isolated Causal Effects of Natural Language
Victoria Lin, Louis-Philippe Morency, Eli Ben-Michael
Machine Learning
日本大学: 関与なし（対象大学）
2025 · ICML
Iterative Vectors: In-Context Gradient Steering without Backpropagation
Yiting Liu, Zhi-Hong Deng
Machine Learning
日本大学: 関与なし（対象大学）
2025 · ICML
It’s My Data Too: Private ML for Datasets with Multi-User Training Examples
Arun Ganesh, Ryan Mckenna, Hugh Brendan Mcmahan, Adam Smith, Fan Wu
Machine Learning
日本大学: 関与なし（対象大学）
2025 · ICML
Jacobian Sparse Autoencoders: Sparsify Computations, Not Just Activations
Lucy Farnik, Tim Lawson, Conor Houghton, Laurence Aitchison
Machine Learning
日本大学: 関与なし（対象大学）
2025 · ICML
Janus: Dual-Server Multi-Round Secure Aggregation with Verifiability for Federated Learning
Lang Pu, Jingjing Gu, Chao Lin, Xinyi Huang
Machine Learning
日本大学: 関与なし（対象大学）
2025 · ICML
Joint Learning of Energy-based Models and their Partition Function
Michael Eli Sander, Vincent Roulet, Tianlin Liu, Mathieu Blondel
Machine Learning
日本大学: 関与なし（対象大学）
2025 · ICML
Joint Localization and Activation Editing for Low-Resource Fine-Tuning
Wen Lai, Alexander Fraser, Ivan Titov
Machine Learning
日本大学: 関与なし（対象大学）
2025 · ICML
Joint Metric Space Embedding by Unbalanced Optimal Transport with Gromov–Wasserstein Marginal Penalization
Florian Beier, Moritz Piening, Robert Beinert, Gabriele Steidl
Machine Learning
日本大学: 関与なし（対象大学）
2025 · ICML
Joint MoE Scaling Laws: Mixture of Experts Can Be Memory Efficient
Jan Ludziejewski, Maciej Pióro, Jakub Krajewski, Maciej Stefaniak, Michał Krutul, Jan Małaśnicki, Marek Cygan, Piotr Sankowski, Kamil Adamczewski, Piotr Miłoś, Sebastian Jaszczur
Machine Learning
日本大学: 関与なし（対象大学）
2025 · ICML
Joker: Joint Optimization Framework for Lightweight Kernel Machines
Junhong Zhang, Zhihui Lai
Machine Learning
日本大学: 関与なし（対象大学）
2025 · ICML
Just Enough Shifts: Mitigating Over-Refusal in Aligned Language Models with Targeted Representation Fine-Tuning
Mahavir Dabas, Si Chen, Charles Fleming, Ming Jin, Ruoxi Jia
Machine Learning
日本大学: 関与なし（対象大学）
2025 · ICML
K$^2$IE: Kernel Method-based Kernel Intensity Estimators for Inhomogeneous Poisson Processes
Hideaki Kim, Tomoharu Iwata, Akinori Fujino
Machine Learning
日本大学: 関与なし（対象大学）
2025 · ICML
KABB: Knowledge-Aware Bayesian Bandits for Dynamic Expert Coordination in Multi-Agent Systems
Jusheng Zhang, Zimeng Huang, Yijia Fan, Ningyuan Liu, Mingyan Li, Zhuojie Yang, Jiawei Yao, Jian Wang, Keze Wang
Machine Learning
日本大学: 関与なし（対象大学）
2025 · ICML
KAN-AD: Time Series Anomaly Detection with Kolmogorov–Arnold Networks
Quan Zhou, Changhua Pei, Fei Sun, Han Jing, Zhengwei Gao, Haiming Zhang, Gaogang Xie, Dan Pei, Jianhui Li
Machine Learning
日本大学: 関与なし（対象大学）
2025 · ICML
KBQA-o1: Agentic Knowledge Base Question Answering with Monte Carlo Tree Search
Haoran Luo, Haihong E, Yikai Guo, Qika Lin, Xiaobao Wu, Xinyu Mu, Wenhao Liu, Meina Song, Yifan Zhu, Anh Tuan Luu
Machine Learning
日本大学: 関与なし（対象大学）
2025 · ICML
KEA: Keeping Exploration Alive by Proactively Coordinating Exploration Strategies
Shih-Min Yang, Martin Magnusson, Johannes A. Stork, Todor Stoyanov
Machine Learning
日本大学: 関与なし（対象大学）
2025 · ICML
KGMark: A Diffusion Watermark for Knowledge Graphs
Hongrui Peng, Haolang Lu, Yuanlong Yu, Weiye Fu, Kun Wang, Guoshun Nan
Machine Learning
日本大学: 関与なし（対象大学）
2025 · ICML
KIND: Knowledge Integration and Diversion for Training Decomposable Models
Yucheng Xie, Fu Feng, Ruixiao Shi, Jing Wang, Yong Rui, Xin Geng
Machine Learning
日本大学: 関与なし（対象大学）
2025 · ICML
KV Shifting Attention Enhances Language Modeling
Mingyu Xu, Bingning Wang, Weipeng Chen
Machine Learning
日本大学: 関与なし（対象大学）
2025 · ICML
KVTuner: Sensitivity-Aware Layer-Wise Mixed-Precision KV Cache Quantization for Efficient and Nearly Lossless LLM Inference
Xing Li, Zeyu Xing, Yiming Li, Linping Qu, Hui-Ling Zhen, Yiwu Yao, Wulong Liu, Sinno Jialin Pan, Mingxuan Yuan
Machine Learning
日本大学: 関与なし（対象大学）
2025 · ICML
Kandinsky Conformal Prediction: Beyond Class- and Covariate-Conditional Coverage
Konstantina Bairaktari, Jiayun Wu, Steven Wu
Machine Learning
日本大学: 関与なし（対象大学）
2025 · ICML
Kernel Quantile Embeddings and Associated Probability Metrics
Masha Naslidnyk, Siu Lun Chau, Francois-Xavier Briol, Krikamol Muandet
Machine Learning
日本大学: 関与なし（対象大学）
2025 · ICML
Kernel-based Unsupervised Embedding Alignment for Enhanced Visual Representation in Vision-language Models
Shizhan Gong, Yankai Jiang, Qi Dou, Farzan Farnia
Machine Learning
日本大学: 関与なし（対象大学）
2025 · ICML
KernelBench: Can LLMs Write Efficient GPU Kernels?
Anne Ouyang, Simon Guo, Simran Arora, Alex L Zhang, William Hu, Christopher Re, Azalia Mirhoseini
Machine Learning
日本大学: 関与なし（対象大学）
2025 · ICML
KinDEL: DNA-Encoded Library Dataset for Kinase Inhibitors
Benson Chen, Tomasz Danel, Gabriel H. S. Dreiman, Patrick J. Mcenaney, Nikhil Jain, Kirill Novikov, Spurti Umesh Akki, Joshua L. Turnbull, Virja Atul Pandya, Boris P. Belotserkovskii, Jared Bryce Weaver, Ankita Biswas, Dat Nguyen, Kent Gorday, Mohammad Sultan, Nathaniel Stanley, Daniel M Whalen, Divya Kanichar, Christoph Klein, Emily Fox, R. Edward Watts
Machine Learning
日本大学: 関与なし（対象大学）
2025 · ICML
Kinetic Langevin Diffusion for Crystalline Materials Generation
François R J Cornet, Federico Bergamin, Arghya Bhowmik, Juan Maria Garcia-Lastra, Jes Frellsen, Mikkel N. Schmidt
Machine Learning
日本大学: 関与なし（対象大学）
2025 · ICML
Knowledge Retention in Continual Model-Based Reinforcement Learning
Haotian Fu, Yixiang Sun, Michael Littman, George Konidaris
Machine Learning
日本大学: 関与なし（対象大学）
2025 · ICML
Knowledge Swapping via Learning and Unlearning
Mingyu Xing, Lechao Cheng, Shengeng Tang, Yaxiong Wang, Zhun Zhong, Meng Wang
Machine Learning
日本大学: 関与なし（対象大学）
2025 · ICML
Knowledge-Guided Wasserstein Distributionally Robust Optimization
Zitao Wang, Ziyuan Wang, Molei Liu, Nian Si
Machine Learning
日本大学: 関与なし（対象大学）
2025 · ICML
KoNODE: Koopman-Driven Neural Ordinary Differential Equations with Evolving Parameters for Time Series Analysis
Hanru Bai, Weiyang Ding
Machine Learning
日本大学: 関与なし（対象大学）
2025 · ICML
Kona: An Efficient Privacy-Preservation Framework for KNN Classification by Communication Optimization
Guopeng Lin, Ruisheng Zhou, Shuyu Chen, Weili Han, Jin Tan, Wenjing Fang, Lei Wang, Tao Wei
Machine Learning
日本大学: 関与なし（対象大学）
2025 · ICML
KoopSTD: Reliable Similarity Analysis between Dynamical Systems via Approximating Koopman Spectrum with Timescale Decoupling
Shimin Zhang, Ziyuan Ye, Yinsong Yan, Zeyang Song, Yujie Wu, Jibin Wu
Machine Learning
日本大学: 関与なし（対象大学）
2025 · ICML
L-Diffusion: Laplace Diffusion for Efficient Pathology Image Segmentation
Weihan Li, Linyun Zhou, Jian Yang, Shengxuming Zhang, Xiangtong Du, Xiuming Zhang, Jing Zhang, Chaoqing Xu, Mingli Song, Zunlei Feng
Machine Learning
日本大学: 関与なし（対象大学）
2025 · ICML
L3A: Label-Augmented Analytic Adaptation for Multi-Label Class Incremental Learning
Xiang Zhang, Run He, Chen Jiao, Di Fang, Ming Li, Ziqian Zeng, Cen Chen, Huiping Zhuang
Machine Learning
日本大学: 関与なし（対象大学）
2025 · ICML
LADA: Scalable Label-Specific CLIP Adapter for Continual Learning
Mao-Lin Luo, Zi-Hao Zhou, Tong Wei, Min-Ling Zhang
Machine Learning
日本大学: 関与なし（対象大学）
2025 · ICML
LAION-C: An Out-of-Distribution Benchmark for Web-Scale Vision Models
Fanfei Li, Thomas Klein, Wieland Brendel, Robert Geirhos, Roland S. Zimmermann
Machine Learning
日本大学: 関与なし（対象大学）
2025 · ICML
LARM: Large Auto-Regressive Model for Long-Horizon Embodied Intelligence
Zhuoling Li, Xiaogang Xu, Zhenhua Xu, Ser-Nam Lim, Hengshuang Zhao
Machine Learning
日本大学: 関与なし（対象大学）
2025 · ICML
LASER: Attention with Exponential Transformation
Sai Surya Duvvuri, Inderjit S Dhillon
Machine Learning
日本大学: 関与なし（対象大学）
2025 · ICML
LAST SToP for Modeling Asynchronous Time Series
Shubham Gupta, Thibaut Durand, Graham W. Taylor, Lilian Bialokozowicz
Machine Learning
日本大学: 関与なし（対象大学）
2025 · ICML
LAuReL: Learned Augmented Residual Layer
Gaurav Menghani, Ravi Kumar, Sanjiv Kumar
Machine Learning
日本大学: 関与なし（対象大学）
2025 · ICML
LBI-FL: Low-Bit Integerized Federated Learning with Temporally Dynamic Bit-Width Allocation
Li Ding, Hao Zhang, Wenrui Dai, Chenglin Li, Weijia Lu, Zhifei Yang, Xiaodong Zhang, Xiaofeng Ma, Junni Zou, Hongkai Xiong
Machine Learning
日本大学: 関与なし（対象大学）
2025 · ICML
LDMol: A Text-to-Molecule Diffusion Model with Structurally Informative Latent Space Surpasses AR Models
Jinho Chang, Jong Chul Ye
Machine Learning
日本大学: 関与なし（対象大学）
2025 · ICML
LEAPS: A discrete neural sampler via locally equivariant networks
Peter Holderrieth, Michael Samuel Albergo, Tommi Jaakkola
Machine Learning
日本大学: 関与なし（対象大学）
2025 · ICML
LEMoN: Label Error Detection using Multimodal Neighbors
Haoran Zhang, Aparna Balagopalan, Nassim Oufattole, Hyewon Jeong, Yan Wu, Jiacheng Zhu, Marzyeh Ghassemi
Machine Learning
日本大学: 関与なし（対象大学）
2025 · ICML
LETS Forecast: Learning Embedology for Time Series Forecasting
Abrar Majeedi, Viswanatha Reddy Gajjala, Satya Sai Srinath Namburi Gnvv, Nada Magdi Elkordi, Yin Li
Machine Learning
日本大学: 関与なし（対象大学）
2025 · ICML
LEVIS: Large Exact Verifiable Input Spaces for Neural Networks
Mohamad Fares El Hajj Chehade, Wenting Li, Brian Wesley Bell, Russell Bent, Saif R. Kazi, Hao Zhu
Machine Learning
日本大学: 関与なし（対象大学）
2025 · ICML
LGDM: Latent Guidance in Diffusion Models for Perceptual Evaluations
Shreshth Saini, Ru-Ling Liao, Yan Ye, Alan Bovik
Machine Learning
日本大学: 関与なし（対象大学）
2025 · ICML
LIFT the Veil for the Truth: Principal Weights Emerge after Rank Reduction for Reasoning-Focused Supervised Fine-Tuning
Zihang Liu, Tianyu Pang, Oleg Balabanov, Chaoqun Yang, Tianjin Huang, Lu Yin, Yaoqing Yang, Shiwei Liu
Machine Learning
日本大学: 関与なし（対象大学）
2025 · ICML
LIMEFLDL: A Local Interpretable Model-Agnostic Explanations Approach for Label Distribution Learning
Xiuyi Jia, Jinchi Li, Yunan Lu, Weiwei Li
Machine Learning
日本大学: 関与なし（対象大学）
2025 · ICML
LIVS: A Pluralistic Alignment Dataset for Inclusive Public Spaces
Rashid Mushkani, Shravan Nayak, Hugo Berard, Allison Cohen, Shin Koseki, Hadrien Bertrand
Machine Learning
日本大学: 関与なし（対象大学）
2025 · ICML
LLM Alignment as Retriever Optimization: An Information Retrieval Perspective
Bowen Jin, Jinsung Yoon, Zhen Qin, Ziqi Wang, Wei Xiong, Yu Meng, Jiawei Han, Sercan O Arik
Machine Learning
日本大学: 関与なし（対象大学）
2025 · ICML
LLM Data Selection and Utilization via Dynamic Bi-level Optimization
Yang Yu, Kai Han, Hang Zhou, Yehui Tang, Kaiqi Huang, Yunhe Wang, Dacheng Tao
Machine Learning
日本大学: 関与なし（対象大学）
2025 · ICML
LLM Enhancers for GNNs: An Analysis from the Perspective of Causal Mechanism Identification
Hang Gao, Huang Wenxuan, Fengge Wu, Zhao Junsuo, Changwen Zheng, Huaping Liu
Machine Learning
日本大学: 関与なし（対象大学）
2025 · ICML
LLM-Assisted Semantically Diverse Teammate Generation for Efficient Multi-agent Coordination
Lihe Li, Lei Yuan, Pengsen Liu, Tao Jiang, Yang Yu
Machine Learning
日本大学: 関与なし（対象大学）
2025 · ICML
LLM-Augmented Chemical Synthesis and Design Decision Programs
Haorui Wang, Jeff Guo, Lingkai Kong, Rampi Ramprasad, Philippe Schwaller, Yuanqi Du, Chao Zhang
Machine Learning
日本大学: 関与なし（対象大学）
2025 · ICML
LLM-SRBench: A New Benchmark for Scientific Equation Discovery with Large Language Models
Parshin Shojaee, Ngoc-Hieu Nguyen, Kazem Meidani, Amir Barati Farimani, Khoa D Doan, Chandan K. Reddy
Machine Learning
日本大学: 関与なし（対象大学）
2025 · ICML
LLMScan: Causal Scan for LLM Misbehavior Detection
Mengdi Zhang, Goh Kai Kiat, Peixin Zhang, Jun Sun, Lin Xin Rose, Hongyu Zhang
Machine Learning
日本大学: 関与なし（対象大学）
2025 · ICML
LLMs Can Reason Faster Only If We Let Them
Bilgehan Sel, Lifu Huang, Naren Ramakrishnan, Ruoxi Jia, Ming Jin
Machine Learning
日本大学: 関与なし（対象大学）
2025 · ICML
LLMs can see and hear without any training
Kumar Ashutosh, Yossi Gandelsman, Xinlei Chen, Ishan Misra, Rohit Girdhar
Machine Learning
日本大学: 関与なし（対象大学）
2025 · ICML
LLMs on the Line: Data Determines Loss-to-Loss Scaling Laws
Prasanna Mayilvahanan, Thaddäus Wiedemer, Sayak Mallick, Matthias Bethge, Wieland Brendel
Machine Learning
日本大学: 関与なし（対象大学）
2025 · ICML
LLaVA-ReID: Selective Multi-image Questioner for Interactive Person Re-Identification
Yiding Lu, Mouxing Yang, Dezhong Peng, Peng Hu, Yijie Lin, Xi Peng
Machine Learning
日本大学: 関与なし（対象大学）
2025 · ICML
LMAct: A Benchmark for In-Context Imitation Learning with Long Multimodal Demonstrations
Anian Ruoss, Fabio Pardo, Harris Chan, Bonnie Li, Volodymyr Mnih, Tim Genewein
Machine Learning
日本大学: 関与なし（対象大学）
2025 · ICML
LMRL Gym: Benchmarks for Multi-Turn Reinforcement Learning with Language Models
Marwa Abdulhai, Isadora White, Charlie Victor Snell, Charles Sun, Joey Hong, Yuexiang Zhai, Kelvin Xu, Sergey Levine
Machine Learning
日本大学: 関与なし（対象大学）
2025 · ICML
LOB-Bench: Benchmarking Generative AI for Finance - an Application to Limit Order Book Data
Peer Nagy, Sascha Yves Frey, Kang Li, Bidipta Sarkar, Svitlana Vyetrenko, Stefan Zohren, Ani Calinescu, Jakob Nicolaus Foerster
Machine Learning
日本大学: 関与なし（対象大学）
2025 · ICML
LOCATE 3D: Real-World Object Localization via Self-Supervised Learning in 3D
Paul Mcvay, Sergio Arnaud, Ada Martin, Arjun Majumdar, Krishna Murthy Jatavallabhula, Phillip Thomas, Ruslan Partsey, Daniel Dugas, Abha Gejji, Alexander Sax, Vincent-Pierre Berges, Mikael Henaff, Ayush Jain, Ang Cao, Ishita Prasad, Mrinal Kalakrishnan, Michael Rabbat, Nicolas Ballas, Mido Assran, Oleksandr Maksymets, Aravind Rajeswaran, Franziska Meier
Machine Learning
日本大学: 関与なし（対象大学）
2025 · ICML
LOGO — Long cOntext aliGnment via efficient preference Optimization
Zecheng Tang, Zechen Sun, Juntao Li, Qiaoming Zhu, Min Zhang
Machine Learning
日本大学: 関与なし（対象大学）
2025 · ICML
LRA-QViT: Integrating Low-Rank Approximation and Quantization for Robust and Efficient Vision Transformers
Beom Jin Kang, Namjoon Kim, Hyun Kim
Machine Learning
日本大学: 関与なし（対象大学）
2025 · ICML
LSCD: Lomb–Scargle Conditioned Diffusion for Time series Imputation
Elizabeth Fons, Alejandro Sztrajman, Yousef El-Laham, Luciana Ferrer, Svitlana Vyetrenko, Manuela Veloso
Machine Learning
日本大学: 関与なし（対象大学）
2025 · ICML
LV-XAttn: Distributed Cross-Attention for Long Visual Inputs in Multimodal Large Language Models
Tzu-Tao Chang, Shivaram Venkataraman
Machine Learning
日本大学: 関与なし（対象大学）
2025 · ICML
La RoSA: Enhancing LLM Efficiency via Layerwise Rotated Sparse Activation
Kai Liu, Bowen Xu, Shaoyu Wu, Xin Chen, Hao Zhou, Yongliang Tao, Lulu Hu
Machine Learning
日本大学: 関与なし（対象大学）
2025 · ICML
LaCache: Ladder-Shaped KV Caching for Efficient Long-Context Modeling of Large Language Models
Dachuan Shi, Yonggan Fu, Xiangchi Yuan, Zhongzhi Yu, Haoran You, Sixu Li, Xin Dong, Jan Kautz, Pavlo Molchanov, Yingyan Celine Lin
Machine Learning
日本大学: 関与なし（対象大学）
2025 · ICML
LaMAGIC2: Advanced Circuit Formulations for Language Model-Based Analog Topology Generation
Chen-Chia Chang, Wan-Hsuan Lin, Yikang Shen, Yiran Chen, Xin Zhang
Machine Learning
日本大学: 関与なし（対象大学）
2025 · ICML
LaRA: Benchmarking Retrieval-Augmented Generation and Long-Context LLMs – No Silver Bullet for LC or RAG Routing
Kuan Li, Liwen Zhang, Yong Jiang, Pengjun Xie, Fei Huang, Shuai Wang, Minhao Cheng
Machine Learning
日本大学: 関与なし（対象大学）
2025 · ICML
Label Distribution Propagation-based Label Completion for Crowdsourcing
Tong Wu, Liangxiao Jiang, Wenjun Zhang, Chaoqun Li
Machine Learning
日本大学: 関与なし（対象大学）
2025 · ICML
Ladder-Residual: Parallelism-Aware Architecture for Accelerating Large Model Inference with Communication Overlapping
Muru Zhang, Mayank Mishra, Zhongzhu Zhou, William Brandon, Jue Wang, Yoon Kim, Jonathan Ragan-Kelley, Shuaiwen Leon Song, Ben Athiwaratkun, Tri Dao
Machine Learning
日本大学: 関与なし（対象大学）
2025 · ICML
LangDAug: Langevin Data Augmentation for Multi-Source Domain Generalization in Medical Image Segmentation
Piyush Tiwary, Kinjawl Bhattacharyya, Prathosh Ap
Machine Learning
日本大学: 関与なし（対象大学）
2025 · ICML
LangTime: A Language-Guided Unified Model for Time Series Forecasting with Proximal Policy Optimization
Wenzhe Niu, Zongxia Xie, Yanru Sun, Wei He, Man Xu, Chao Hao
Machine Learning
日本大学: 関与なし（対象大学）
2025 · ICML
Language Models May Verbatim Complete Text They Were Not Explicitly Trained On
Ken Liu, Christopher A. Choquette-Choo, Matthew Jagielski, Peter Kairouz, Sanmi Koyejo, Percy Liang, Nicolas Papernot
Machine Learning
日本大学: 関与なし（対象大学）
2025 · ICML
Language Models as Implicit Tree Search
Ziliang Chen, Zhao-Rong Lai, Yufeng Yang, Liangda Fang, Zhanfu Yang, Liang Lin
Machine Learning
日本大学: 関与なし（対象大学）
2025 · ICML
Language Models over Canonical Byte-Pair Encodings
Tim Vieira, Tianyu Liu, Clemente Pasti, Yahya Emara, Brian Dusell, Benjamin Lebrun, Mario Giulianelli, Juan Luis Gastaldi, Timothy J. O’Donnell, Ryan Cotterell
Machine Learning
日本大学: 関与なし（対象大学）
2025 · ICML
LapSum - One Method to Differentiate Them All: Ranking, Sorting and Top-k Selection
Łukasz Struski, Michal B. Bednarczyk, Igor T. Podolak, Jacek Tabor
Machine Learning
日本大学: 関与なし（対象大学）
2025 · ICML
Laplace Transform Based Low-Complexity Learning of Continuous Markov Semigroups
Vladimir R Kostic, Karim Lounici, Hélène Halconruy, Timothée Devergne, Pietro Novelli, Massimiliano Pontil
Machine Learning
日本大学: 関与なし（対象大学）
2025 · ICML
Large Continual Instruction Assistant
Jingyang Qiao, Zhizhong Zhang, Xin Tan, Yanyun Qu, Shouhong Ding, Yuan Xie
Machine Learning
日本大学: 関与なし（対象大学）
2025 · ICML
Large Displacement Motion Transfer with Unsupervised Anytime Interpolation
Guixiang Wang, Jianjun Li
Machine Learning
日本大学: 関与なし（対象大学）
2025 · ICML
Large Language Model-driven Large Neighborhood Search for Large-Scale MILP Problems
Huigen Ye, Hua Xu, An Yan, Yaoyang Cheng
Machine Learning
日本大学: 関与なし（対象大学）
2025 · ICML
Large Language Models are Demonstration Pre-Selectors for Themselves
Jiarui Jin, Yuwei Wu, Haoxuan Li, Xiaoting He, Weinan Zhang, Yiming Yang, Yong Yu, Jun Wang, Mengyue Yang
Machine Learning
日本大学: 関与なし（対象大学）
2025 · ICML
Large Language Models to Diffusion Finetuning
Edoardo Cetin, Tianyu Zhao, Yujin Tang
Machine Learning
日本大学: 関与なし（対象大学）
2025 · ICML
Large Language-Geometry Model: When LLM meets Equivariance
Zongzhao Li, Jiacheng Cen, Bing Su, Tingyang Xu, Yu Rong, Deli Zhao, Wenbing Huang
Machine Learning
日本大学: 関与なし（対象大学）
2025 · ICML
Larger or Smaller Reward Margins to Select Preferences for LLM Alignment?
Kexin Huang, Junkang Wu, Ziqian Chen, Xue Wang, Jinyang Gao, Bolin Ding, Jiancan Wu, Xiangnan He, Xiang Wang
Machine Learning
日本大学: 関与なし（対象大学）
2025 · ICML
Latent Action Learning Requires Supervision in the Presence of Distractors
Alexander Nikulin, Ilya Zisman, Denis Tarasov, Lyubaykin Nikita, Andrei Polubarov, Igor Kiselev, Vladislav Kurenkov
Machine Learning
日本大学: 関与なし（対象大学）
2025 · ICML
Latent Diffusion Planning for Imitation Learning
Amber Xie, Oleh Rybkin, Dorsa Sadigh, Chelsea Finn
Machine Learning
日本大学: 関与なし（対象大学）
2025 · ICML
Latent Imputation before Prediction: A New Computational Paradigm for De Novo Peptide Sequencing
Ye Du, Chen Yang, Nanxi Yu, Wanyu Lin, Qian Zhao, Shujun Wang
Machine Learning
日本大学: 関与なし（対象大学）
2025 · ICML
Latent Mamba Operator for Partial Differential Equations
Karn Tiwari, Niladri Dutta, N M Anoop Krishnan, Prathosh Ap
Machine Learning
日本大学: 関与なし（対象大学）
2025 · ICML
Latent Preference Coding: Aligning Large Language Models via Discrete Latent Codes
Zhuocheng Gong, Jian Guan, Wei Wu, Huishuai Zhang, Dongyan Zhao
Machine Learning
日本大学: 関与なし（対象大学）
2025 · ICML
Latent Score-Based Reweighting for Robust Classification on Imbalanced Tabular Data
Yunze Tong, Fengda Zhang, Zihao Tang, Kaifeng Gao, Kai Huang, Pengfei Lyu, Jun Xiao, Kun Kuang
Machine Learning
日本大学: 関与なし（対象大学）
2025 · ICML
Latent Thought Models with Variational Bayes Inference-Time Computation
Deqian Kong, Minglu Zhao, Dehong Xu, Bo Pang, Shu Wang, Edouardo Honig, Zhangzhang Si, Chuan Li, Jianwen Xie, Sirui Xie, Ying Nian Wu
Machine Learning
日本大学: 関与なし（対象大学）
2025 · ICML
Latent Variable Causal Discovery under Selection Bias
Haoyue Dai, Yiwen Qiu, Ignavier Ng, Xinshuai Dong, Peter Spirtes, Kun Zhang
Machine Learning
日本大学: 関与なし（対象大学）
2025 · ICML
Latent Variable Estimation in Bayesian Black-Litterman Models
Thomas Yuan-Lung Lin, Jerry Yao-Chieh Hu, Paul W. Chiou, Peter Lin
Machine Learning
日本大学: 関与なし（対象大学）