ICLR

2022–2026 LIVE

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Machine Learning

2026 · 5,351 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 · ICLR
Watermarking Diffusion Language Models
Thibaud Gloaguen, Robin Staab, Nikola Jovanović, Martin Vechev
Machine Learning
日本大学: 関与なし（対象大学）
2026 · ICLR
WavePolyp: Video Polyp Segmentation via Hierarchical Wavelet-Based Feature Aggregation and Inter-Frame Divergence Perception
Yuhua Zhang, Guilian Chen, Yuanqin He, Huisi Wu, Jing Qin
Machine Learning
日本大学: 関与なし（対象大学）
2026 · ICLR
WavefrontDiffusion: Dynamic Decoding Schedule for Improved Reasoning
Haojin Yang, Rui Hu, Zequn Sun, Rui Zhou, Yujun Cai, Yiwei Wang
Machine Learning
日本大学: 関与なし（対象大学）
2026 · ICLR
Wavelet Predictive Representations for Non-Stationary Reinforcement Learning
Min Wang, Xin Li, Ye He, Yao-Hui Li, Hasnaa Bennis, Riashat Islam, Mingzhong Wang
Machine Learning
日本大学: 関与なし（対象大学）
2026 · ICLR
We-Math 2.0: A Versatile MathBook System for Incentivizing Visual Mathematical Reasoning
Runqi Qiao, Qiuna qiuna, Peiqing Yang, Yanzi Wang, Xiaowan Wang, Enhui Wan, Guanting Dong, Shiqiang Lang, Sitong Zhou, Yida Xu, Yuchen Zeng, Jie Wang, Chong Sun, Chen Li, Honggang Zhang
Machine Learning
日本大学: 関与なし（対象大学）
2026 · ICLR
WeTok: Powerful Discrete Tokenization for High-Fidelity Visual Reconstruction
Shaobin Zhuang, Yiwei Guo, Fangyikang Wang, Canmiao Fu, Zhipeng Huang, Zeyue Tian, Xiaohui Li, Ying Zhang, Chen Li, Yali Wang
Machine Learning
日本大学: 関与なし（対象大学）
2026 · ICLR
Weak Correlations as the Underlying Principle for Linearization of Gradient-Based Learning Systems
Ori Shem-ur, Khen Cohen, Yaron Oz
Machine Learning
日本大学: 関与なし（対象大学）
2026 · ICLR
Weak-to-Strong Diffusion with Reflection
Lichen Bai, Masashi Sugiyama, Zeke Xie
Machine Learning
日本大学: 東京大学
2026 · ICLR
Weak-to-Strong Generalization with Failure Trajectories
Ruimeng Ye, Zihan Wang, Yang Xiao, Zinan Ling, Manling Li, Bo Hui
Machine Learning
日本大学: 関与なし（対象大学）
2026 · ICLR
WearVox: An Egocentric Multichannel Voice Assistant Benchmark for Wearables
Zhaojiang Lin, YONG XU, Kai Sun, Jing Zheng, Yin Huang, Surya Appini, Krish Narang, Renjie Tao, Ishan Jain, Siddhant Arora, Ruizhi Li, Yiteng Huang, Kaushik Patnaik, Wenfang Xu, Suwon Shon, Yue Liu, Ahmed Aly, Anuj Kumar, Florian Metze, Xin Dong
Machine Learning
日本大学: 関与なし（対象大学）
2026 · ICLR
Web-CogReasoner: Towards Multimodal Knowledge-Induced Cognitive Reasoning for Web Agents
Yuhan Guo, cong guo, Aiwen Sun, Hongliang He, Xinyu Yang, Yue Lu, Yingji Zhang, Xuntao Guo, Dong Zhang, Jianzhuang Liu, Jiang Duan, Yijia Xiao, Liangjian Wen, Hai-Ming Xu, Yong Dai
Machine Learning
日本大学: 関与なし（対象大学）
2026 · ICLR
WebArbiter: A Generative Reasoning Process Reward Model for Web Agents
Yao Zhang, Shijie Tang, Zeyu Li, Zhen Han, Volker Tresp
Machine Learning
日本大学: 関与なし（対象大学）
2026 · ICLR
WebDS: An End-to-End Benchmark for Web-based Data Science
Ethan Hsu, Hong Meng Yam, Ines Bouissou, Aaron John, Raj Thota, Josh Koe, Vivek Putta, G Dharesan, Alexander Spangher, Shikhar Murty, Tenghao Huang, Christopher Manning
Machine Learning
日本大学: 関与なし（対象大学）
2026 · ICLR
WebDevJudge: Evaluating (M)LLMs as Critiques for Web Development Quality
Chunyang Li, Yilun Zheng, Xinting Huang, Tianqing Fang, Jiahao Xu, Lihui Chen, Yangqiu Song, Winston Hu
Machine Learning
日本大学: 関与なし（対象大学）
2026 · ICLR
WebFactory: Automated Compression of Foundational Language Intelligence into Grounded Web Agents
SICHENG FAN, Qingyun Shi, Shengze Xu, Shengbo Cai, Tieyong Zeng, LI LING, Yanyi Shang, Dehan Kong
Machine Learning
日本大学: 関与なし（対象大学）
2026 · ICLR
WebGen-Agent: Enhancing Interactive Website Generation with Multi-Level Feedback and Step-Level Reinforcement Learning
Zimu Lu, Houxing Ren, Yunqiao Yang, Ke Wang, Zhuofan Zong, Junting Pan, Mingjie Zhan, Hongsheng Li
Machine Learning
日本大学: 関与なし（対象大学）
2026 · ICLR
WebSailor-V2: Bridging the Chasm to Proprietary Agents via Synthetic Data and Scalable Reinforcement Learning
Kuan Li, Zhongwang Zhang, Huifeng Yin, Rui Ye, Yida Zhao, Liwen Zhang, Litu Ou, Ding-Chu Zhang, Xixi Wu, Xinmiao Yu, Jialong Wu, Xinyu Wang, Zile Qiao, Zhen Zhang, Yong Jiang, Pengjun Xie, Fei Huang, Zhiqin Xu, Shuai Wang, Minhao Cheng, Jingren Zhou
Machine Learning
日本大学: 関与なし（対象大学）
2026 · ICLR
WebSeer: Training Deeper Search Agents through Reinforcement Learning with Self-Reflection
Guanzhong He, Zhen Yang, Jinxin Liu, Xu Bin, Lei Hou, Juanzi Li
Machine Learning
日本大学: 関与なし（対象大学）
2026 · ICLR
WebShaper: Agentically Data Synthesizing via Information-Seeking Formalization
Zhengwei Tao, Jialong Wu, Wenbiao Yin, Pu Wu, Junkai Zhang, Baixuan Li, Haiyang SHEN, Kuan Li, Liwen Zhang, Xinyu Wang, Wentao Zhang, Yong Jiang, Pengjun Xie, Fei Huang, Jingren Zhou
Machine Learning
日本大学: 関与なし（対象大学）
2026 · ICLR
WebWatcher: Breaking New Frontiers of Vision-Language Deep Research Agent
Xinyu Geng, Peng Xia, Zhen Zhang, Xinyu Wang, Qiuchen Wang, Ruixue Ding, Chenxi Wang, Jialong Wu, Kuan Li, Yida Zhao, Huifeng Yin, Yong Jiang, Pengjun Xie, Fei Huang, Huaxiu Yao, Yi R. Fung, Jingren Zhou
Machine Learning
日本大学: 関与なし（対象大学）
2026 · ICLR
WebWeaver: Structuring Web-Scale Evidence with Dynamic Outlines for Open-Ended Deep Research
Zijian Li, Xin Guan, Bo Zhang, Shen Huang, Houquan Zhou, Shaopeng Lai, Ming Yan, Yong Jiang, Pengjun Xie, Fei Huang, Jun Zhang, Jingren Zhou
Machine Learning
日本大学: 関与なし（対象大学）
2026 · ICLR
Webscale-RL: Automated Data Pipeline for Scaling RL Data to Pretraining Levels
Zhepeng Cen, Haolin Chen, Shiyu Wang, Zuxin Liu, Zhiwei Liu, DING ZHAO, Caiming Xiong, Huan Wang, Weiran Yao
Machine Learning
日本大学: 関与なし（対象大学）
2026 · ICLR
Weight Decay may matter more than µP for Learning Rate Transfer in Practice
Atli Kosson, Jeremy Welborn, Yang Liu, Martin Jaggi, Xi Chen
Machine Learning
日本大学: 関与なし（対象大学）
2026 · ICLR
Weight Space Representation Learning on Diverse NeRF Architectures
Francesco Ballerini, Pierluigi Zama Ramirez, Luigi Di Stefano, Samuele Salti
Machine Learning
日本大学: 関与なし（対象大学）
2026 · ICLR
Weight-Space Linear Recurrent Neural Networks
Roussel Nzoyem, Nawid Keshtmand, Enrique Crespo Fernandez, Idriss TSAYEM, Raul Santos-Rodriguez, David Barton, Tom Deakin
Machine Learning
日本大学: 関与なし（対象大学）
2026 · ICLR
Welfarist Formulations for Diverse Similarity Search
Siddharth Barman, Nirjhar Das, Shivam Gupta, Kirankumar Shiragur
Machine Learning
日本大学: 関与なし（対象大学）
2026 · ICLR
What "Not" to Detect: Negation-Aware VLMs via Structured Reasoning and Token Merging
Inha Kang, Youngsun Lim, Seonho Lee, Jiho Choi, Junsuk Choe, Hyunjung Shim
Machine Learning
日本大学: 関与なし（対象大学）
2026 · ICLR
What Do Large Language Models Know About Opinions?
Erfan Jahanparast, Zhiqing Hong, Serina Chang
Machine Learning
日本大学: 関与なし（対象大学）
2026 · ICLR
What Exactly Does Guidance Do in Masked Discrete Diffusion Models
Ye He, Kevin Rojas, Molei Tao
Machine Learning
日本大学: 関与なし（対象大学）
2026 · ICLR
What Generative Search Engines Like and How to Optimize Web Content Cooperatively
Yujiang Wu, Shanshan Zhong, Yubin Kim, Chenyan Xiong
Machine Learning
日本大学: 関与なし（対象大学）
2026 · ICLR
What Happens Next? Anticipating Future Motion by Generating Point Trajectories
Gabrijel Boduljak, Laurynas Karazija, Iro Laina, Christian Rupprecht, Andrea Vedaldi
Machine Learning
日本大学: 関与なし（対象大学）
2026 · ICLR
What Layers When: Learning to Skip Compute in LLMs with Residual Gates
Filipe Laitenberger, Dawid Kopiczko, Cees G Snoek, Yuki Asano
Machine Learning
日本大学: 関与なし（対象大学）
2026 · ICLR
What Matters for Batch Online Reinforcement Learning in Robotics?
Perry Dong, Suvir Mirchandani, Dorsa Sadigh, Chelsea Finn
Machine Learning
日本大学: 関与なし（対象大学）
2026 · ICLR
What Scales in Cross-Entropy Scaling Law?
Junxi Yan, Zixi Wei, Qingyao Ai, Yiqun LIU, Jingtao Zhan
Machine Learning
日本大学: 関与なし（対象大学）
2026 · ICLR
What happens when generative AI models train recursively on each others' outputs?
Hung Vu, Galen Reeves, Emily Wenger
Machine Learning
日本大学: 関与なし（対象大学）
2026 · ICLR
What matters for Representation Alignment: Global Information or Spatial Structure?
Jaskirat Singh, Xingjian Leng, Zongze Wu, Liang Zheng, Richard Zhang, Eli Shechtman, Saining Xie
Machine Learning
日本大学: 関与なし（対象大学）
2026 · ICLR
What's In My Human Feedback? Learning Interpretable Descriptions of Preference Data
Rajiv Movva, Smitha Milli, Sewon Min, Emma Pierson
Machine Learning
日本大学: 関与なし（対象大学）
2026 · ICLR
What's the plan? Metrics for implicit planning in LLMs and their application to rhyme generation and question answering
Jim Maar, Denis Paperno, Callum McDougall, Neel Nanda
Machine Learning
日本大学: 関与なし（対象大学）
2026 · ICLR
Whatever Remains Must Be True: Filtering Drives Reasoning in LLMs, Shaping Diversity
Germàn Kruszewski, Pierre ERBACHER, Jos Rozen, Marc Dymetman
Machine Learning
日本大学: 関与なし（対象大学）
2026 · ICLR
When AI Agents Collude Online: Financial Fraud Risks by Collaborative LLM Agents on Social Platforms
Qibing Ren, Zhijie Zheng, Jiaxuan Guo, Junchi Yan, Lizhuang Ma, Jing Shao
Machine Learning
日本大学: 関与なし（対象大学）
2026 · ICLR
When Agents “Misremember” Collectively: Exploring the Mandela Effect in LLM-based Multi-Agent Systems
Naen Xu, Hengyu An, Shuo Shi, Jinghuai Zhang, Chunyi Zhou, Changjiang Li, Tianyu Du, Zhihui Fu, Jun Wang, Shouling Ji
Machine Learning
日本大学: 関与なし（対象大学）
2026 · ICLR
When Bias Meets Trainability: Connecting Theories of Initialization
Alberto Bassi, Marco Baity-Jesi, Aurelien Lucchi, Carlo Albert, Emanuele Francazi
Machine Learning
日本大学: 関与なし（対象大学）
2026 · ICLR
When Data is the Algorithm: A Systematic Study and Curation of Preference Optimization Datasets
Aladin Djuhera, Farhan Ahmed, Swanand Kadhe, Syed Zawad, Heiko Ludwig, Holger Boche
Machine Learning
日本大学: 関与なし（対象大学）
2026 · ICLR
When Does Divide and Conquer Work for Long Context LLM? A Noise Decomposition Framework
Zach Xu, Shang Zhu, Jue Wang, Junlin Wang, Ben Athiwaratkun, Chi Wang, James Y Zou, Ce Zhang
Machine Learning
日本大学: 関与なし（対象大学）
2026 · ICLR
When Flatness Does (Not) Guarantee Adversarial Robustness
Nils Philipp Walter, Linara Adilova, Jilles Vreeken, Michael Kamp
Machine Learning
日本大学: 関与なし（対象大学）
2026 · ICLR
When Foundation Models are One-Liners: Limitations and Future Directions for Time Series Anomaly Detection
Xiaokun Zhu, Louis Carpentier, Mathias Verbeke
Machine Learning
日本大学: 関与なし（対象大学）
2026 · ICLR
When Greedy Wins: Emergent Exploitation Bias in Meta-Bandit LLM Training
Sanxing Chen, Xiaoyin Chen, Yukun Huang, Roy Xie, Bhuwan Dhingra
Machine Learning
日本大学: 関与なし（対象大学）
2026 · ICLR
When Is Diversity Rewarded in Cooperative Multi-Agent Learning?
Michael Amir, Matteo Bettini, Amanda Prorok
Machine Learning
日本大学: 関与なし（対象大学）
2026 · ICLR
When LLMs get significantly worse: A statistical approach to detect model degradations
Jonas Kübler, Kailash Budhathoki, Matthäus Kleindessner, Xiong Zhou, Junming Yin, Ashish Khetan, George Karypis
Machine Learning
日本大学: 関与なし（対象大学）
2026 · ICLR
When Language Models Lose Their Mind: The Consequences of Brain Misalignment
Gabriele Merlin, Mariya Toneva
Machine Learning
日本大学: 関与なし（対象大学）
2026 · ICLR
When Large Multimodal Models Confront Evolving Knowledge: Challenges and Explorations
Kailin Jiang, yuntao du, Yukai Ding, Yuchen Ren, Ning Jiang, Zhi Gao, Zilong Zheng, Lei Liu, Bin Li, Qing Li
Machine Learning
日本大学: 関与なし（対象大学）
2026 · ICLR
When MLLMs Meet Compression Distortion: A Coding Paradigm Tailored to MLLMs
Jinming Liu, Zhaoyang Jia, Jiahao Li, Bin Li, Xin Jin, Wenjun Zeng, Yan Lu
Machine Learning
日本大学: 関与なし（対象大学）
2026 · ICLR
When Machine Learning Gets Personal: Evaluating Prediction and Explanation
Louisa Cornelis, Guillermo Bernardez, Haewon Jeong, Nina Miolane
Machine Learning
日本大学: 関与なし（対象大学）
2026 · ICLR
When More is Less: Understanding Chain-of-Thought Length in LLMs
Yuyang Wu, Yifei Wang, Ziyu Ye, Tianqi Du, Stefanie Jegelka, Yisen Wang
Machine Learning
日本大学: 関与なし（対象大学）
2026 · ICLR
When Priors Backfire: On the Vulnerability of Unlearnable Examples to Pretraining
Zhihao Li, Gezheng Xu, Jiale Cai, Ruiyi Fang, Di Wu, Qicheng Lao, Charles Ling, Boyu Wang
Machine Learning
日本大学: 関与なし（対象大学）
2026 · ICLR
When Reasoning Meets Compression: Understanding the Effects of LLMs Compression on Large Reasoning Models
Nan Zhang, Eugene Kwek, Yusen Zhang, Hieu Nguyen, Prasenjit Mitra, Rui Zhang
Machine Learning
日本大学: 関与なし（対象大学）
2026 · ICLR
When Scores Learn Geometry: Rate Separations under the Manifold Hypothesis
Xiang Li, Zebang Shen, Ya-Ping Hsieh, Niao He
Machine Learning
日本大学: 関与なし（対象大学）
2026 · ICLR
When Shift Happens - Confounding Is to Blame
Gowtham Reddy Abbavaram, Celia Rubio-Madrigal, Rebekka Burkholz, Krikamol Muandet
Machine Learning
日本大学: 関与なし（対象大学）
2026 · ICLR
When Silence Is Golden: Can LLMs Learn to Abstain in Temporal QA and Beyond?
Xinyu Zhou, Chang Jin, Carsten Eickhoff, Zhijiang Guo, Seyed Ali Bahrainian
Machine Learning
日本大学: 関与なし（対象大学）
2026 · ICLR
When Style Breaks Safety: Defending LLMs Against Superficial Style Alignment
Yuxin Xiao, Sana Tonekaboni, Walter Gerych, Vinith Suriyakumar, Marzyeh Ghassemi
Machine Learning
日本大学: 関与なし（対象大学）
2026 · ICLR
When Thinking Backfires: Mechanistic Insights into Reason-induced Misalignment
Hanqi Yan, Hainiu Xu, Siya Qi, Shu Yang, Yulan He
Machine Learning
日本大学: 関与なし（対象大学）
2026 · ICLR
When Weak LLMs Speak with Confidence, Preference Alignment Gets Stronger
Amirabbas Afzali, Myeongho Jeon, Maria Brbic
Machine Learning
日本大学: 関与なし（対象大学）
2026 · ICLR
When a Robot is More Capable than a Human: Learning from Constrained Demonstrators
Xinhu Li, Ayush Jain, Zhaojing Yang, Yigit Korkmaz, Erdem Bıyık
Machine Learning
日本大学: 関与なし（対象大学）
2026 · ICLR
When and Where to Reset Matters for Long-Term Test-Time Adaptation
Taejun Lim, Joong-Won Hwang, Kibok Lee
Machine Learning
日本大学: 関与なし（対象大学）
2026 · ICLR
When to Ensemble: Identifying Token-Level Points for Stable and Fast LLM Ensembling
Heecheol Yun, Kwangmin Ki, Jung Hyun Lee, Eunho Yang
Machine Learning
日本大学: 関与なし（対象大学）
2026 · ICLR
When to Retrain after Drift: A Data-Only Test of Post-Drift Data Size Sufficiency
Ren Fujiwara, Yasuko Matsubara, Yasushi Sakurai
Machine Learning
日本大学: 大阪大学
2026 · ICLR
When to use Graphs in RAG: A Comprehensive Analysis for Graph Retrieval-Augmented Generation
Zhishang Xiang, Chuanjie Wu, Qinggang Zhang, Shengyuan Chen, Zijin Hong, Xiao Huang, Jinsong Su
Machine Learning
日本大学: 関与なし（対象大学）
2026 · ICLR
When would Vision-Proprioception Policies Fail in Robotic Manipulation?
Jingxian Lu, Wenke Xia, Yuxuan Wu, Zhiwu Lu, Di Hu
Machine Learning
日本大学: 関与なし（対象大学）
2026 · ICLR
Where Did It Go Wrong? Attributing Undesirable LLM Behaviors via Representation Gradient Tracing
Zhe Li, Wei Zhao, Yige Li, Jun Sun
Machine Learning
日本大学: 関与なし（対象大学）
2026 · ICLR
Where Did This Sentence Come From? Tracing Provenance in LLM Reasoning Distillation
kaiyuan liu, Shaotian Yan, Rui Miao, Bing Wang, Chen Shen, Jun Zhang, Jieping Ye
Machine Learning
日本大学: 関与なし（対象大学）
2026 · ICLR
Who Matters Matters: Agent-Specific Conservative Offline MARL
Haosheng Chen, Yun Hua, Wenhao Li, Shiqin Wang, Xiangfeng Wang
Machine Learning
日本大学: 関与なし（対象大学）
2026 · ICLR
WholeBodyVLA: Towards Unified Latent VLA for Whole-body Loco-manipulation Control
Haoran Jiang, Jin Chen, Qingwen Bu, Li Chen, Modi Shi, Yanjie Zhang, Delong Li, Chuanzhe Suo, wang chuang, zhihui peng, Hongyang Li
Machine Learning
日本大学: 関与なし（対象大学）
2026 · ICLR
Why Adversarially Train Diffusion Models?
Maria Rosaria Briglia, Mujtaba Mirza, Giuseppe Lisanti, Iacopo Masi
Machine Learning
日本大学: 関与なし（対象大学）
2026 · ICLR
Why Ask One When You Can Ask $k$? Learning-to-Defer to the Top-$k$ Experts
Yannis Montreuil, Axel Carlier, Lai Xing Ng, Wei Tsang Ooi
Machine Learning
日本大学: 関与なし（対象大学）
2026 · ICLR
Why Attention Patterns Exist: A Unifying Temporal Perspective Analysis
Qingyue Yang, Jie Wang, Xing Li, Yinqi Bai, Tong Xialiang, Huiling Zhen, Jianye Hao, Mingxuan Yuan, Bin Li
Machine Learning
日本大学: 関与なし（対象大学）
2026 · ICLR
Why DPO is a Misspecified Estimator and How to Fix It
Aditya Gopalan, Sayak Ray Chowdhury, Debangshu Banerjee
Machine Learning
日本大学: 関与なし（対象大学）
2026 · ICLR
Why Do Unlearnable Examples Work: A Novel Perspective of Mutual Information
Yifan Zhu, Yibo Miao, Yinpeng Dong, XIAOSHAN GAO
Machine Learning
日本大学: 関与なし（対象大学）
2026 · ICLR
Why High-rank Neural Networks Generalize?: An Algebraic Framework with RKHSs
Yuka Hashimoto, Sho Sonoda, Isao Ishikawa, Masahiro Ikeda
Machine Learning
日本大学: 京都大学
2026 · ICLR
Why Keep Your Doubts to Yourself? Trading Visual Uncertainties among Vision-Language Models
jusheng zhang, Yijia Fan, Kaitong Cai, Jing Yang, Jiawei Yao, Jian Wang, Guanlong Qu, Ziliang Chen, Keze Wang
Machine Learning
日本大学: 関与なし（対象大学）
2026 · ICLR
Why Less is More (Sometimes): A Theory of Data Curation
Elvis Dohmatob, Mohammad Pezeshki, Reyhane Askari Hemmat
Machine Learning
日本大学: 関与なし（対象大学）
2026 · ICLR
Why Low-Precision Transformer Training Fails: An Analysis on Flash Attention
Haiquan Qiu, Quanming Yao
Machine Learning
日本大学: 関与なし（対象大学）
2026 · ICLR
Why Prototypes Collapse: Diagnosing and Preventing Partial Collapse in Prototypical Self-Supervised Learning
Gabriel Y. Arteaga, Marius Aasan, Rwiddhi Chakraborty, Martine Hjelkrem-Tan, Thalles Santos Silva, Michael Kampffmeyer, Adín Ramírez Rivera
Machine Learning
日本大学: 関与なし（対象大学）
2026 · ICLR
Why Reinforcement Fine-Tuning Enables MLLMs Preserve Prior Knowledge Better: A Data Perspective
Zhihao Zhang, Qiaole Dong, Qi Zhang, Enyu Zhou, Jun Zhao, Zhiheng Xi, Senjie Jin, Xiaoran Fan, Yuhao Zhou, Mingqi Wu, Yanwei Fu, Tao Ji, Tao Gui, Xuanjing Huang, Kai Chen
Machine Learning
日本大学: 関与なし（対象大学）
2026 · ICLR
Why We Need New Benchmarks for Local Intrinsic Dimension Estimation
Piotr Tempczyk, Dominik Filipiak, Łukasz Garncarek, Ksawery Smoczynski, Adam Kurpisz
Machine Learning
日本大学: 関与なし（対象大学）
2026 · ICLR
Why is Your Language Model a Poor Implicit Reward Model?
Noam Razin, Yong Lin, Jiarui Yao, Sanjeev Arora
Machine Learning
日本大学: 関与なし（対象大学）
2026 · ICLR
Wide-In, Narrow-Out: Revokable Decoding for Efficient and Effective DLLMs
Feng Hong, Geng Yu, Yushi Ye, Haicheng Huang, Huangjie Zheng, Ya Zhang, Yanfeng Wang, Jiangchao Yao
Machine Learning
日本大学: 関与なし（対象大学）
2026 · ICLR
WideSearch: Benchmarking Agentic Broad Info-Seeking
Ryan Wong, Jiawei Wang, Junjie zhao, Li Chen, Yan Gao, Zhanglong, Xuan Zhou, Zuo Wang, Kai Xiang, Ge Zhang, Wenhao Huang, YANG WANG, Ke Wang
Machine Learning
日本大学: 関与なし（対象大学）
2026 · ICLR
Wiki-R1: Incentivizing Multimodal Reasoning for Knowledge-based VQA via Data and Sampling Curriculum
Shan Ning, Longtian Qiu, Xuming He
Machine Learning
日本大学: 関与なし（対象大学）
2026 · ICLR
WinT3R: Window-Based Streaming Reconstruction with Camera Token Pool
Zizun Li, Jianjun Zhou, Yifan Wang, Haoyu Guo, Wenzheng Chang, Yang Zhou, Haoyi Zhu, Junyi Chen, Chunhua Shen, Tong He
Machine Learning
日本大学: 関与なし（対象大学）
2026 · ICLR
Winter Soldier: Backdooring Language Models at Pre-Training with Indirect Data Poisoning
Wassim Bouaziz, Mathurin VIDEAU, Nicolas Usunier, El-Mahdi El-Mhamdi
Machine Learning
日本大学: 関与なし（対象大学）
2026 · ICLR
WithAnyone: Toward Controllable and ID Consistent Image Generation
Hengyuan Xu, Wei Cheng, Peng Xing, Yixiao Fang, Shuhan Wu, Rui Wang, Xianfang Zeng, Daxin Jiang, Gang Yu, Xingjun Ma, Yu-Gang Jiang
Machine Learning
日本大学: 関与なし（対象大学）
2026 · ICLR
World-In-World: World Models in a Closed-Loop World
Jiahan Zhang, Muqing Jiang, Nanru Dai, Taiming Lu, Arda Uzunoglu, Shunchi Zhang, Yana Wei, Jiahao Wang, Vishal Patel, Paul Liang, Daniel Khashabi, Cheng Peng, Rama Chellappa, Tianmin Shu, Alan Yuille, Yilun Du, Jieneng Chen
Machine Learning
日本大学: 関与なし（対象大学）
2026 · ICLR
World2Minecraft: Occupancy-Driven Simulated Scenes Construction
Lechao Zhang, Haoran Xu, Jingyu Gong, Xuhong Wang, Yuan Xie, Xin Tan
Machine Learning
日本大学: 関与なし（対象大学）
2026 · ICLR
WorldEdit: Towards Open-World Image Editing with a Knowledge-Informed Benchmark
Wang Lin, Feng Wang, Majun Zhang, Wentao Hu, Tao Jin, Zhou Zhao, Fei Wu, Jingyuan Chen, Sucheng Ren, Alan Yuille
Machine Learning
日本大学: 関与なし（対象大学）
2026 · ICLR
WorldGym: World Model as An Environment for Policy Evaluation
Julian Quevedo, Ansh Kumar Sharma, Yixiang Sun, Varad Suryavanshi, Percy Liang, Sherry Yang
Machine Learning
日本大学: 関与なし（対象大学）
2026 · ICLR
WorldSense: Evaluating Real-world Omnimodal Understanding for Multimodal LLMs
Jack Hong, Shilin Yan, Jiayin Cai, Xiaolong Jiang, Yao Hu, Weidi Xie
Machine Learning
日本大学: 関与なし（対象大学）
2026 · ICLR
WorldSplat: Gaussian-Centric Feed-Forward 4D Scene Generation for Autonomous Driving
Ziyue Zhu, Zhanqian Wu, Zhenxin Zhu, Lijun Zhou, Haiyang Sun, Bing Wang, Kun Ma, Guang Chen, Hangjun Ye, Jin Xie, jian Yang
Machine Learning
日本大学: 関与なし（対象大学）
2026 · ICLR
WorldTree: Towards 4D Dynamic Worlds from Monocular Video using Tree-Chains
Qisen Wang, Yifan Zhao, Jia Li
Machine Learning
日本大学: 関与なし（対象大学）
2026 · ICLR
X-VLA: Soft-Prompted Transformer as Scalable Cross-Embodiment Vision-Language-Action Model
Jinliang Zheng, Jianxiong Li, Zhihao Wang, Dongxiu Liu, Xirui Kang, Yuchun Feng, Yinan Zheng, Jiayin Zou, Yilun Chen, Jia Zeng, Tai Wang, Ya-Qin Zhang, Jingjing Liu, Xianyuan Zhan
Machine Learning
日本大学: 関与なし（対象大学）
2026 · ICLR
XIL: Cross-Expanding Incremental Learning
Heayoun Choi, Hyundong Jin, Eunwoo Kim
Machine Learning
日本大学: 関与なし（対象大学）