ICML

2022–2026 LIVE

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Machine Learning

2026 · 6,341 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 · ICML
When Does Adaptation Win? Scaling Laws for Meta-Learning in Quantum Control
Nima Leclerc, Chris Miller, Nicholas Brawand
Machine Learning
日本大学: 関与なし（対象大学）
2026 · ICML
When Does Predictive Inverse Dynamics Outperform Behavior Cloning?
Lukas Schäfer, Pallavi Choudhury, Abdelhak Lemkhenter, Chris Lovett, Somjit Nath, Luis França, Matheus Mendonca, Alex Lamb, Riashat Islam, Siddhartha Sen, John Langford, Katja Hofmann, Sergio Valcarcel Macua
Machine Learning
日本大学: 関与なし（対象大学）
2026 · ICML
When Does Sparsity Mitigate the Curse of Depth in LLMs
Yao Yao, Xinyuan Song, Sebastian Pokutta, Max Zimmer, Nico Pelleriti, Thomas Hofmann, Shiwei Liu
Machine Learning
日本大学: 関与なし（対象大学）
2026 · ICML
When Drafts Evolve: Speculative Decoding Meets Online Learning
Yu-Yang Qian, Hao-Cong Wu, Yichao Fu, Hao Zhang, Peng Zhao
Machine Learning
日本大学: 関与なし（対象大学）
2026 · ICML
When Embedding-Based Defenses Fail: Rethinking Safety in LLM-Based Multi-Agent Systems
Lingxi Zhang, Guangtao Zheng, Hanjie Chen
Machine Learning
日本大学: 関与なし（対象大学）
2026 · ICML
When Generalized Zero-Shot Learning Meets PU Learning: A Plug-and-Play Framework for Seen-Class Bias Mitigation
Long Tang, Keyang Pu, Yingjie Tian
Machine Learning
日本大学: 関与なし（対象大学）
2026 · ICML
When Is Rank-1 Enough? Geometry-Guided Initialization for Parameter-Efficient Fine-Tuning
Haoran Zhao, Caren Han, Eduard Hovy
Machine Learning
日本大学: 関与なし（対象大学）
2026 · ICML
When LLMs Develop Languages: Symbolic Communication for Efficient Multi-Agent Reasoning
Zhengqi Pei, Qingming Huang, Shuhui Wang
Machine Learning
日本大学: 関与なし（対象大学）
2026 · ICML
When LLMs Encounter Open-world Graph Learning: A Fresh View on Unlabeled Data Uncertainty
Yanzhe Wen, Xunkai Li, Qi Zhang, Lei Zhu, Guang Zeng, Zhihan Zhang, Rong-Hua Li, Guoren Wang
Machine Learning
日本大学: 関与なし（対象大学）
2026 · ICML
When Labelers Stay Silent: The Power of Ties in Cost-Effective Preference Learning
JIAQI LYU, Zihan Zhang, CJ Y, Shiyu Xia, Ning Xu, Xin Geng
Machine Learning
日本大学: 関与なし（対象大学）
2026 · ICML
When Model Merging Breaks Routing: Training-Free Calibration for MoE
Canbin Huang, Tianyuan Shi, Xiaojun Quan, Jingang Wang, Jianfei Zhang, Qifan Wang
Machine Learning
日本大学: 関与なし（対象大学）
2026 · ICML
When More Data Doesn't Help: Limits of Adaptation in Multitask Learning
Steve Hanneke, Mingyue Xu
Machine Learning
日本大学: 関与なし（対象大学）
2026 · ICML
When More Experts Hurt: Underfitting in Multi-Expert Learning to Defer
Shuqi Liu, Yuzhou Cao, Lei Feng, Bo An, Luke Ong
Machine Learning
日本大学: 関与なし（対象大学）
2026 · ICML
When Planning Fails Despite Correct Execution: On Epistemic Calibration for LLM-Based Multi-Agent Systems
Zehao Wang, shilong jin, Zhao Cao, Lanjun Wang
Machine Learning
日本大学: 関与なし（対象大学）
2026 · ICML
When Preference Labels Fall Short: Aligning Diffusion Models from Real Data
Weiyan Chen, Weijian Deng, Yao Xiao, Weijie Tu, ZiYi Dong, Ibrahim Radwan, Liang Lin, Pengxu Wei
Machine Learning
日本大学: 関与なし（対象大学）
2026 · ICML
When RAG Hurts: Diagnosing and Mitigating Attention Distraction in Retrieval-Augmented LVLMs
Beidi Zhao, wenlong deng, Xinting Liao, Yushu Li, Nazim Shaikh, Yao Nie, Xiaoxiao Li
Machine Learning
日本大学: 関与なし（対象大学）
2026 · ICML
When RL Meets Adaptive Speculative Training: A Unified Training-Serving System
Junxiong Wang, Fengxiang Bie, Jisen Li, Zelei Shao, Qingyang Wu, Yinghui Liu, Yubo Wang, Avner May, Ben Athiwaratkun, Yineng Zhang, Shuaiwen Song, Zhongzhu Zhou, Chenfeng Xu, Xiaoxia (Shirley) Wu
Machine Learning
日本大学: 関与なし（対象大学）
2026 · ICML
When Random Saliency Looks Trained: Architectural Center Bias in CNN Interpretability
Keying Kuang, Iain Carmichael, Elizabeth Purdom
Machine Learning
日本大学: 関与なし（対象大学）
2026 · ICML
When Replanning Becomes the Bottleneck: Budgeted Replanning for Embodied Agents
Shuaijun Liu, Feiyang You, Xingwei Chen, Ningxin Su
Machine Learning
日本大学: 関与なし（対象大学）
2026 · ICML
When Sample Selection Bias Precipitates Model Collapse
Xinbao Qiao, Xianglong Du, Wei Liu, Jingqi Zhang, Peihua Mai, Meng Zhang, Yan (James) Pang
Machine Learning
日本大学: 関与なし（対象大学）
2026 · ICML
When Search Goes Wrong: Red-Teaming Web-Augmented Large Language Models
Haoran Ou, Kangjie Chen, Xingshuo Han, Gelei Deng, Jie Zhang, Han Qiu, Tianwei Zhang, Kwok Yan Lam
Machine Learning
日本大学: 関与なし（対象大学）
2026 · ICML
When Shared Knowledge Hurts: Spectral Over-Accumulation in Model Merging
Yayuan Li, Ze Peng, Jian Zhang, Jintao Guo, Yue Duan, Yinghuan Shi
Machine Learning
日本大学: 関与なし（対象大学）
2026 · ICML
When Simple Problems Wear Complex Costumes: Improving Efficiency in LRM's Adaptive Reasoning
Junnan Ren, Yan Zhang, Qian Chen, Yunhang Shen, Ke Li, Shengchuan Zhang, Liujuan Cao, Rongrong Ji
Machine Learning
日本大学: 関与なし（対象大学）
2026 · ICML
When Single Answer Is Not Enough: Rethinking Single-Step Retrosynthesis Benchmarks for LLMs
Bogdan Zagribelnyy, Ivan Ilin, Maksim Kuznetsov, Nikita Bondarev, Roman Schutski, Thomas MacDougall, Rim Shayakhmetov, Zulfat Miftahutdinov, Mikolaj Mizera, Vladimir Aladinskiy, Alex Aliper, Alex Zhavoronkov
Machine Learning
日本大学: 関与なし（対象大学）
2026 · ICML
When Softmax Fails at the Top: Extreme‑Value Corrections for InfoNCE
Hasan Sabri Melihcan Erol, Suat Evren, Oktay Ozel, Alexander Morgan, Jongha (Jon) Ryu, Lizhong Zheng
Machine Learning
日本大学: 関与なし（対象大学）
2026 · ICML
When Tabular Foundation Models Meet Strategic Tabular Data: A Prior Alignment Approach
Xinpeng Lv, Yunxin Mao, Renzhe Xu, Chunyuan Zheng, Yikai Chen, Haoxuan Li, Jinxuan Yang, Yuanlong Chen, Kun Kuang, Mingyang Geng, Shixuan Liu, Wanrong Huang, Shaowu Yang, Wenjing Yang, Zhouchen Lin, Haotian Wang
Machine Learning
日本大学: 関与なし（対象大学）
2026 · ICML
When and How Human Curation Backfires: Preference Alignment under Multi-Model Self-Consuming Loop
Yang Zhang, Xiukun Wei, Xueru Zhang
Machine Learning
日本大学: 関与なし（対象大学）
2026 · ICML
When the Prompt Becomes Visual: Vision-Centric Jailbreak Attacks for Large Image Editing Models
Jiacheng Hou, Yining Sun, Ruochong Jin, Haochen Han, Fangming Liu, Victor Chan, Alex Jinpeng Wang
Machine Learning
日本大学: 関与なし（対象大学）
2026 · ICML
When to Memorize and When to Stop: Gated Recurrent Memory for Long-Context Reasoning
Leheng Sheng, Yongtao Zhang, Wenchang Ma, Yaorui Shi, Ting Huang, Xiang Wang, An Zhang, Ke Shen, Tat-Seng Chua
Machine Learning
日本大学: 関与なし（対象大学）
2026 · ICML
When to Think, When to Speak: Learning Disclosure Policies for LLM Reasoning
Jiaqi Wei, Xuehang Guo, Pengfei Yu, Xiang Zhang, Wanli Ouyang, Siqi Sun, Qingyun Wang, Chenyu You
Machine Learning
日本大学: 関与なし（対象大学）
2026 · ICML
When to Trust the Cheap Check: Weak and Strong Verification for Reasoning
Shayan Kiyani, Sima Noorani, George Pappas, Hamed Hassani
Machine Learning
日本大学: 関与なし（対象大学）
2026 · ICML
Where Concept Erasure Should Occur: Concept–Layer Alignment in Text-to-Video Diffusion Models
Yiwei Xie, Ping Liu, Zheng Zhang
Machine Learning
日本大学: 関与なし（対象大学）
2026 · ICML
Where Detectors Fail: Probing Generative Space for Generalizable AI-Generated Image Detection
Zijie Cao, Weijie Tu, Yao Xiao, Weijian Deng, Weiyan Chen, Liang Lin, Pengxu Wei
Machine Learning
日本大学: 関与なし（対象大学）
2026 · ICML
Where Rectified Flows Leak: Characterising Membership Signals Along the Interpolation Path
Thomas Sesmat, Gabriel Meseguer-Brocal, Geoffroy Peeters
Machine Learning
日本大学: 関与なし（対象大学）
2026 · ICML
Which Algorithms Can Graph Neural Networks Learn?
Solveig Wittig, Antonis Vasileiou, Robert R. Nerem, Timo Stoll, Floris Geerts, Yusu Wang, Christopher Morris
Machine Learning
日本大学: 関与なし（対象大学）
2026 · ICML
Which Heads Matter for Reasoning? RL-Guided KV Cache Compression
Wenjie Du, Li Jiang, Keda TAO, Xue Liu, Huan Wang
Machine Learning
日本大学: 関与なし（対象大学）
2026 · ICML
WhisperSplat: Lossless Steganography in 3D Gaussian Splatting
Nicole Meng, Ronak Sahu, Miao Yin, Faysal Hossain Shezan, Yingjie Lao
Machine Learning
日本大学: 関与なし（対象大学）
2026 · ICML
Who Evaluates AI's Social Impacts? Mapping Coverage and Gaps in First and Third Party Evaluations
Anka Reuel, Avijit Ghosh, Jenny Chim, Andrew Tran, Yanan Long, Jennifer Mickel, Usman Gohar, Srishti Yadav, Pawan Sasanka Ammanamanchi, Mowafak Allaham, Hossein A. Rahmani, Mubashara Akhtar, Felix Friedrich, Robert Scholz, Michael Riegler, Jan Batzner, Eliya Habba, Arushi Saxena, Anastassia Kornilova, Kevin Wei, Prajna Soni, Yohan Mathew, Kevin Klyman, Jeba Sania, Subramanyam Sahoo, Olivia B Bruvik, Pouya Sadeghi, Sujata Goswami, Angelina Wang, Yacine Jernite, Zeerak Talat, Stella Biderman, Mykel Kochenderfer, Sanmi Koyejo, Irene Solaiman
Machine Learning
日本大学: 関与なし（対象大学）
2026 · ICML
Who Gets Credit or Blame? Attributing Accountability in Modern AI Systems
Shichang Zhang, Hongzhe Du, Jiaqi Ma, Himabindu Lakkaraju
Machine Learning
日本大学: 関与なし（対象大学）
2026 · ICML
Who Said Neural Networks Aren't Linear?
Nimrod Berman, Assaf Hallak, Assaf Shocher
Machine Learning
日本大学: 関与なし（対象大学）
2026 · ICML
Who Transfers Safety? Identifying and Targeting Cross-Lingual Shared Safety Neurons
Xianhui Zhang, Chengyu Xie, Linxia Zhu, Yonghui Yang, Weixiang Zhao, Zifeng Cheng, Cong Wang, Fei Shen, Tat-Seng Chua
Machine Learning
日本大学: 関与なし（対象大学）
2026 · ICML
Who can we trust? LLM-as-a-jury for Comparative Assessment
Mengjie Qian, Guangzhi Sun, Mark Gales, Kate Knill
Machine Learning
日本大学: 関与なし（対象大学）
2026 · ICML
Whom to Query for What: Adaptive Group Elicitation via Multi-Turn LLM Interactions
Ruomeng Ding, Tianwei Gao, Tom Zollo, Eitan Bachmat, Richard Zemel, Xinyu Yang
Machine Learning
日本大学: 関与なし（対象大学）
2026 · ICML
Who’s in Charge? Disempowerment Patterns in Real-World LLM Usage
Mrinank Sharma, Miles McCain, Raymond Douglas, David Duvenaud
Machine Learning
日本大学: 関与なし（対象大学）
2026 · ICML
Why Agentic Theorem Prover Works: A Statistical Provability Theory of Mathematical Reasoning Models
Sho Sonoda, Shunta Akiyama, Yuya Uezato
Machine Learning
日本大学: 関与なし（対象大学）
2026 · ICML
Why Are Linear RNNs More Parallelizable?
William Merrill, Hongjian Jiang, Yanhong Li, Anthony Lin, Ashish Sabharwal
Machine Learning
日本大学: 関与なし（対象大学）
2026 · ICML
Why DDIM Hallucinates More Than DDPM: A Theoretical Analysis of Reverse Dynamics
Muhammad H Ashiq, Samanyu Arora, Abhinav Narayan Harish, Ishaan Kharbanda, Hung Yun Tseng, Grigorios Chrysos
Machine Learning
日本大学: 関与なし（対象大学）
2026 · ICML
Why Dedicated Critics: Eliminating Target Drift in Multi-Constraint RL
Yue Yang, Chenghao Huang, Hao Wang
Machine Learning
日本大学: 関与なし（対象大学）
2026 · ICML
Why Deep Jacobian Spectra Separate: Depth-Induced Scaling and Singular-Vector Alignment
Nathanaël Haas, François Gatine, Augustin Cosse, Zied Bouraoui
Machine Learning
日本大学: 関与なし（対象大学）
2026 · ICML
Why Do We Need Warm-up? A Theoretical Perspective
Foivos Alimisis, Rustem Islamov, Aurelien Lucchi
Machine Learning
日本大学: 関与なし（対象大学）
2026 · ICML
Why Linear Recurrent Memory Works in Partially Observable Reinforcement Learning
Yike Zhao, Onno Eberhard, Malek khammassi, Ali Sayed, Michael Muehlebach
Machine Learning
日本大学: 関与なし（対象大学）
2026 · ICML
Why ReLU? A Bit-Model Dichotomy for Deep Network Training
Ilan Doron-Arad, Elchanan Mossel
Machine Learning
日本大学: 関与なし（対象大学）
2026 · ICML
Why Self-Distillation Helps and Hurts: Denoising vs. Signal Forgetting
Mingqi Wu, Archer Yang, Qiang Sun
Machine Learning
日本大学: 関与なし（対象大学）
2026 · ICML
Why Specialist Models Still Matter: A Heterogeneous Multi-Agent Paradigm for Medical Artificial Intelligence
Yanan Wang, Shuaicong Hu, Jian Liu, Guohui Zhou, Aiguo Wang, Cuiwei Yang
Machine Learning
日本大学: 関与なし（対象大学）
2026 · ICML
Why Tree-Style Branching Matters for Thought Advantage Estimation in GRPO
Hongcheng Wang, Yinuo Huang, Sukai Wang, Guanghui Ren, Hao Dong
Machine Learning
日本大学: 関与なし（対象大学）
2026 · ICML
Width Independent Bounds for the Local Lipschitz Constant of Deep Neural Networks at Random Initialization and after Lazy Training
Apostolos Evangelidis, Felix Krahmer
Machine Learning
日本大学: 関与なし（対象大学）
2026 · ICML
WildActor: Unconstrained Identity-Preserving Video Generation
Qin Guo, Tianyu Yang, Xuanhua He, Fei Shen, Yong Zhang, Zhuoliang Kang, Xiaoming Wei, Dan Xu
Machine Learning
日本大学: 関与なし（対象大学）
2026 · ICML
WildCat: Near-Linear Attention in Theory and Practice
Tobias Schröder, Lester Mackey
Machine Learning
日本大学: 関与なし（対象大学）
2026 · ICML
WinDeskGround: A Benchmark for Robust GUI Grounding in Complex Multi-Window Desktop Environments
Haoren Zhao, Tianyi Chen, Zhen Wang
Machine Learning
日本大学: 関与なし（対象大学）
2026 · ICML
WinQ: Accelerating Quantization-Aware Training of Language Models Around Saddle Points
Dongyue Li, Zechun Liu, Kai Yi, Zhenshuo Zhang, Changsheng Zhao, Raghuraman Krishnamoorthi, Harshit Khaitan, Hongyang Zhang, Steven Li
Machine Learning
日本大学: 関与なし（対象大学）
2026 · ICML
Winformer: Transcending Pairwise Similarity for Time-series Generation
Haoyi Zhou, Xin Xue, Tianyu Chen, lanhao li, Lijun SUN, Jianxin Li
Machine Learning
日本大学: 関与なし（対象大学）
2026 · ICML
With Argus Eyes: Assessing Retrieval Gaps via Uncertainty Scoring to Detect and Remedy Retrieval Blind Spots
Zeinab Taghavi, Ali Modarressi, Hinrich Schuetze, Andreas Marfurt
Machine Learning
日本大学: 関与なし（対象大学）
2026 · ICML
Words & Weights: Streamlining Multi-Turn Interactions via Co-Adaptation
Chenxing Wei, Hong Wang, Ying He, Zhongxiang Dai, Bo Jiang, Fei Yu, Yao Shu
Machine Learning
日本大学: 関与なし（対象大学）
2026 · ICML
Words Towards Explainability: Caption Label-Free Learning via Dual Loop Agentic Time Series Captioning
Difei Hou, Jiaqi Yue, Chunhui Zhao
Machine Learning
日本大学: 関与なし（対象大学）
2026 · ICML
World Guidance: World Modeling in Condition Space for Action Generation
Yue Su, Sijin Chen, Haixin Shi, Mingyu Liu, Zhengshen Zhang, Ningyuan Huang, Weiheng Zhong, Zhengbang Zhu, Yuxiao Liu, Xihui Liu
Machine Learning
日本大学: 関与なし（対象大学）
2026 · ICML
World Models in Pieces: Structural Certification for General Agents
Yikai Lu, Yifei Wu, Xinyu Lu, Tongxin Li
Machine Learning
日本大学: 関与なし（対象大学）
2026 · ICML
World-Model Inspired Emotion-aware Token Refinement for Training-Free Multimodal Emotion Recognition
Kejun Liu, Yuanyuan Liu, Ke Wang, Zhe Chen, Yibing Zhan, Wei Xiang, Hongyan Zhang
Machine Learning
日本大学: 関与なし（対象大学）
2026 · ICML
World-R1: Reinforcing 3D Constraints for Text-to-Video Generation
Weijie Wang, Xiaoxuan He, Youping Gu, Yifan Yang, Zeyu Zhang, Yefei He, Yanbo Ding, Xirui Hu, Donny Y. Chen, Zhiyuan He, Yuqing Yang, Bohan Zhuang
Machine Learning
日本大学: 関与なし（対象大学）
2026 · ICML
World-Shaper: A Unified Framework for 360° Panoramic Editing
Dong Liang, yuhao liu, Jinyuan Jia, Youjun Zhao, Rynson W Lau
Machine Learning
日本大学: 関与なし（対象大学）
2026 · ICML
WorldCache: Accelerating World Models for Free via Heterogeneous Token Caching
Weilun Feng, Guoxin Fan, Haotong Qin, Mingqiang Wu, Yuqi Li, Xiangqi Li, Zhulin An, Libo Huang, Dingrui Wang, Longlong Liao, Michele Magno, Yongjun Xu, Chuanguang Yang
Machine Learning
日本大学: 関与なし（対象大学）
2026 · ICML
WorldComp2D: Spatio-semantic Representations of Object Identity and Location from Local Views
SeongMin Jin, Doo Seok Jeong
Machine Learning
日本大学: 関与なし（対象大学）
2026 · ICML
WorldCompass: Reinforcement Learning for Long-Horizon World Models
Zehan Wang, Tengfei Wang, Haiyu Zhang, Xuhui Zuo, Junta Wu, Haoyuan Wang, Wenqiang Sun, Zhenwei Wang, Chenjie Cao, Hengshuang Zhao, Chunchao Guo, Zhou Zhao
Machine Learning
日本大学: 関与なし（対象大学）
2026 · ICML
WorldMirror: Universal 3D World Reconstruction with Any-Prior Prompting
Yifan Liu, Zhiyuan Min, Zhenwei Wang, Junta Wu, Tengfei Wang, Yixuan Yuan, Yawei Luo, Chunchao Guo
Machine Learning
日本大学: 関与なし（対象大学）
2026 · ICML
WorldPlay: Towards Long-Term Geometric Consistency for Real-Time Interactive World Modeling
Wenqiang Sun, Haiyu Zhang, Haoyuan Wang, Junta Wu, Zehan Wang, Zhenwei Wang, Yunhong Wang, Jun Zhang, Tengfei Wang, Chunchao Guo
Machine Learning
日本大学: 関与なし（対象大学）
2026 · ICML
WorldTravel: A Realistic Multimodal Travel-Planning Benchmark with Tightly Coupled Constraints
Zexuan Wang, Chenghao Yang, Yingqi Que, Zhoufutu Wen, Zaiyuan Wang, Jiashuo Liu, Zhixin Yao, Zhenzhu Yang, Huaqing Yuan, Yiwen Wang, Zhengxuan Jiang, Shengjie Fang, Zhenhe Wu, Zhaohui Wang, JinCheng Ren, Yuzhen Li, YangYang, Jiaheng Liu, Jian Yang, Ge Zhang, Wenhao Huang
Machine Learning
日本大学: 関与なし（対象大学）
2026 · ICML
X-EviProbe: Post-hoc Parameter-Free Evidential Uncertainty Quantification for Frozen Graph Neural Networks
Chenghua Guo, Sihong Xie, Xi Zhang
Machine Learning
日本大学: 関与なし（対象大学）
2026 · ICML
X-MoGe: A Cross-Modal Adaptation Framework with Mixture-of-Experts and Geometry Guidance for Heterogeneous Collaborative Perception
Wenkai Lin, Zhihong Liu, Chenglu Wen
Machine Learning
日本大学: 関与なし（対象大学）
2026 · ICML
XDomainBench: Diagnosing Reasoning Collapse in High-Dimensional Scientific Knowledge Composition
Zhiren Gong, Tiantong Wu, Jiaming Zhang, Fuyao Zhang, CHE WANG, Yurong Hao, Yikun Hou, Foo Ping, Yilei Zhao, Fei Huang, Chau Yuen, Wei Yang Bryan Lim
Machine Learning
日本大学: 関与なし（対象大学）
2026 · ICML
XPERT: Expert Knowledge Transfer for Effective Training of Language Models
Chang Liu, boyu shi, Xu Yang, Xin Geng
Machine Learning
日本大学: 関与なし（対象大学）
2026 · ICML
XR-1: Towards Versatile Vision-Language-Action Models via Learning Unified Vision-Motion Representations
Shichao Fan, Kun Wu, Zhengping Che, Xinhua Wang, Di Wu, Fei Liao, Ning Liu, Yixue Zhang, Zhen Zhao, Zhiyuan Xu, Meng Li, Qingjie Liu, Shanghang Zhang, Min Wan, Jian Tang
Machine Learning
日本大学: 関与なし（対象大学）
2026 · ICML
XRPO: Pushing the Limits of GRPO with Targeted Exploration and Exploitation
Udbhav Bamba, Minghao Fang, Yifan Yu, Haizhong Zheng, Fan Lai
Machine Learning
日本大学: 関与なし（対象大学）
2026 · ICML
XSkill: Continual Learning from Experience and Skills in Multimodal Agents
Guanyu Jiang, Zhaochen Su, Xiaoye Qu, Yi Fung
Machine Learning
日本大学: 関与なし（対象大学）
2026 · ICML
XSpecMesh: Quality-Preserving Auto-Regressive Mesh Generation Acceleration via Multi-Head Speculative Decoding
Dian Chen, Yansong Qu, Xinyang Li, Ming Li, Shengchuan Zhang
Machine Learning
日本大学: 関与なし（対象大学）
2026 · ICML
XTransfer: Modality-Agnostic Few-Shot Model Transfer for Human Sensing at the Edge
Yu Zhang, Xi Zhang, Hualin zhou, Xinyuan Chen, Shang Gao, Hong Jia, Jianfei Yang, Yuankai Qi, Tao Gu
Machine Learning
日本大学: 関与なし（対象大学）
2026 · ICML
XYZFlow: Scaling Multidimensional Shortcut Flows for Efficient Generative Modeling
Jinxiu Liu, Xuanming Liu, Kangfu Mei, Yandong Wen, Weiyang Liu
Machine Learning
日本大学: 関与なし（対象大学）
2026 · ICML
You Can Learn Tokenization End-to-End with Reinforcement Learning
Sam Dauncey, Roger Wattenhofer
Machine Learning
日本大学: 関与なし（対象大学）
2026 · ICML
You Don't Protect if You Don't Expect: Breaking the Key Assumption behind CLIP's Test-Time Defenses
Ruize Zhang, Yu Li, Zhang Wan, Juan Cao, Jie Zhang, Sheng Tang
Machine Learning
日本大学: 関与なし（対象大学）
2026 · ICML
You Don’t Need All That Attention: Surgical Memorization Mitigation in Text-to-Image Diffusion Models
Kairan Zhao, Eleni Triantafillou, Peter Triantafillou
Machine Learning
日本大学: 関与なし（対象大学）
2026 · ICML
You Need Better Attention Priors
Elon Litman, Gabe Guo
Machine Learning
日本大学: 関与なし（対象大学）
2026 · ICML
Z-Erase: Enabling Concept Erasure in Single Stream Diffusion Transformers
Nanxiang Jiang, Zhaoxin Fan, Baisen Wang, Daiheng Gao, Junhang Cheng, Jifeng Guo, Yalan Qin, Yeying Jin, Hongwei Zheng, Faguo Wu, wenjun wu
Machine Learning
日本大学: 関与なし（対象大学）
2026 · ICML
Zero Sum SVD: Balancing Loss Sensitivity for Low Rank LLM Compression
Ali Abbasi, Chayne Thrash, Haoran Qin, Shansita Sharma, Sepehr Seifi, Soheil Kolouri
Machine Learning
日本大学: 関与なし（対象大学）
2026 · ICML
Zero-Flow Encoders
Yakun Wang, Leyang Wang, Song Liu, Taiji Suzuki
Machine Learning
日本大学: 東京大学
2026 · ICML
Zero-Shot 3D Question Answering via Hierarchical View-to-Token Transportation
Dongsheng Wang, Dawei Su, Hui Huang
Machine Learning
日本大学: 関与なし（対象大学）
2026 · ICML
Zero-Shot Off-Policy Learning
Arip Asadulaev, Maksim Bobrin, Salem Lahlou, Dmitry V. Dylov, Fakhri Karray, Martin Takac
Machine Learning
日本大学: 関与なし（対象大学）
2026 · ICML
Zero-Shot Rankability: Revealing Latent Ordinal Structure in Multimodal Large Language Models via Language
Nam Hyeon-Woo, Yebin Moon, Sohwi Lim, Kwon Byung-Ki, Tae-Hyun Oh
Machine Learning
日本大学: 関与なし（対象大学）
2026 · ICML
Zero-Shot Text-to-Motion Evaluation using Video Language Models
Yuwen Ji, Donglin Wang, Yue Zhang
Machine Learning
日本大学: 関与なし（対象大学）
2026 · ICML
Zero-shot Active Mapping via Fused 360-BEV Representations and Vision–Language Models
Yuanze Wang, Dianxi Shi, Yuetian Wang, Shiming Song, Haikuo Peng, Chunping Qiu, Mengzhu Wang
Machine Learning
日本大学: 関与なし（対象大学）
2026 · ICML
Zero-source LLM Hallucination Detection with Human-like Criteria Probing
Jiahao Yang, Shuhai Zhang, Hailong Kang, Feng Liu, Qi Chen, Mingkui Tan
Machine Learning
日本大学: 関与なし（対象大学）
2026 · ICML
ZeroBench: An Impossible Visual Benchmark for Contemporary Large Multimodal Models
Jonathan Roberts, Mohammad Reza Taesiri, Ansh Sharma, Akash Gupta, Samuel Roberts, Ioana Croitoru, Vlad Bogolin, Jialu Tang, Florian Langer, Vyas Raina, Vatsal Raina, Hanyi Xiong, Vishaal Udandarao, Jingyi Lu, Chen Shiyang, Sam Purkis, Tianshuo Yan, Wenye Lin, Gyungin Shin, Qiaochu Yang, Anh Nguyen, David Atkinson, Alexandru Coca, Mikah Đặng, Sebastian Dziadzio, Jakob D. Kunz, Kaiqu Liang, Alexander Lo, Brian Pulfer, Steven Walton, Charig Yang, Kai Han, Samuel Albanie
Machine Learning
日本大学: 関与なし（対象大学）
2026 · ICML
ZeroDiff: Zero-Shot Time Series Reconstruction via Informed-Prior Diffusion
Yingda Fan, Dan Lu, Xiaowei Jia
Machine Learning
日本大学: 関与なし（対象大学）