Conferences · eligible papers

ICLR

2022–2026 LIVE

ICLR 公式サイト ↗

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。

  1. 2026 · ICLR

    STEDiff: Revealing the Spatial and Temporal Redundancy of Backdoor Attacks in Text-to-Image Diffusion Models

    Yu Pan, Jiahao Chen, Lin Wang, Bingrong Dai, Wenjie Wang

    Machine Learning

    日本大学: 関与なし(対象大学)

  2. 2026 · ICLR

    STEER AWAY FROM MODE COLLISIONS: IMPROVING COMPOSITION IN DIFFUSION MODELS

    Debottam Dutta, Jianchong Chen, Rajalaxmi Rajagopalan, Yu-Lin Wei, Romit Roy Choudhury

    Machine Learning

    日本大学: 関与なし(対象大学)

  3. 2026 · ICLR

    STEM: SCALING TRANSFORMERS WITH EMBEDDING MODULES

    Ranajoy Sadhukhan, Sheng Cao, Harry Dong, Changsheng Zhao, Attiano Purpura-Pontoniere, Yuandong Tian, Zechun Liu, Beidi Chen

    Machine Learning

    日本大学: 関与なし(対象大学)

  4. 2026 · ICLR

    STITCH: Simultaneous Thinking and Talking with Chunked Reasoning for Spoken Language Models

    Cheng-Han Chiang, Xiaofei Wang, Linjie Li, Chung-Ching Lin, Kevin Lin, Shujie LIU, Zhendong Wang, Zhengyuan Yang, Hung-yi Lee, Lijuan Wang

    Machine Learning

    日本大学: 関与なし(対象大学)

  5. 2026 · ICLR

    STORK: Faster Diffusion and Flow Matching Sampling by Resolving both Stiffness and Structure-Dependence

    Zheng Tan, Weizhen Wang, Andrea Bertozzi, Ernest Ryu

    Machine Learning

    日本大学: 関与なし(対象大学)

  6. 2026 · ICLR

    STORM: Synergistic Cross-Scale Spatio-Temporal Modeling for Weather Forecasting

    Qihe Huang, Zhengyang Zhou, Yangze Li, Jiaming Ma, Kuo Yang, Binwu Wang, Xu Wang, Yang Wang

    Machine Learning

    日本大学: 関与なし(対象大学)

  7. 2026 · ICLR

    STVG-R1: Incentivizing Instance-Level Reasoning and Grounding in Videos via Reinforcement Learning

    Xiaowen Zhang, Zhi Gao, Licheng Jiao, Lingling Li, Qing Li

    Machine Learning

    日本大学: 関与なし(対象大学)

  8. 2026 · ICLR

    STaMP: Sequence Transformation and Mixed Precision for Low-Precision Activation Quantization

    Marco Federici, Riccardo Del Chiaro, Boris van Breugel, Paul Whatmough, Markus Nagel

    Machine Learning

    日本大学: 関与なし(対象大学)

  9. 2026 · ICLR

    STream3R: Scalable Sequential 3D Reconstruction with Causal Transformer

    Yushi LAN, Yihang Luo, Fangzhou Hong, Shangchen Zhou, Honghua Chen, Zhaoyang Lyu, Bo DAI, Shuai Yang, Chen Change Loy, Xingang Pan

    Machine Learning

    日本大学: 関与なし(対象大学)

  10. 2026 · ICLR

    SUIT: Knowledge Editing with Subspace-Aware Key-Value Mappings

    Haewon Park, Sangwoo Kim, Yohan Jo

    Machine Learning

    日本大学: 関与なし(対象大学)

  11. 2026 · ICLR

    SURGE: Surprise-Guided Token Reduction for Efficient Video Understanding with VLMs

    Chong Tang, Sannara Ek, Dirk Koch, Robert Mullins, Alex Weddell, Jagmohan Chauhan

    Machine Learning

    日本大学: 関与なし(対象大学)

  12. 2026 · ICLR

    SUSD: Structured Unsupervised Skill Discovery through State Factorization

    Seyed Mohammad Hadi Hosseini, Mahdieh Baghshah

    Machine Learning

    日本大学: 関与なし(対象大学)

  13. 2026 · ICLR

    SVD Provably Denoises Nearest Neighbor Data

    Ravindran Kannan, Kijun Shin, David Woodruff

    Machine Learning

    日本大学: 関与なし(対象大学)

  14. 2026 · ICLR

    SWE-RM: Execution-free Feedback for Software Engineering Agents

    KaShun SHUM, Binyuan Hui, Jiawei Chen, Lei Zhang, X. W., Jiaxi Yang, Yuzhen Huang, Junyang Lin, Junxian He

    Machine Learning

    日本大学: 関与なし(対象大学)

  15. 2026 · ICLR

    SWERank: Software Issue Localization with Code Ranking

    Revanth Gangi Reddy, Tarun Suresh, JaeHyeok Doo, Ye Liu, Xuan-Phi Nguyen, Yingbo Zhou, Semih Yavuz, Caiming Xiong, Heng Ji, Shafiq Joty

    Machine Learning

    日本大学: 関与なし(対象大学)

  16. 2026 · ICLR

    SWINGARENA: Adversarial Programming Arena for Long-context GitHub Issue Solving

    Wendong XU, Jing Xiong, Chenyang Zhao, Qiujiang Chen, Haoran Wang, Hui Shen, Zhongwei Wan, Jianbo Dai, Taiqiang Wu, He Xiao, Chaofan Tao, Zhuoqing Mao, Ying Sheng, Zhijiang Guo, Hongxia Yang, Bei Yu, Lingpeng Kong, Quanquan Gu, Ngai Wong

    Machine Learning

    日本大学: 関与なし(対象大学)

  17. 2026 · ICLR

    SYNC: Measuring and Advancing Synthesizability in Structure-Based Drug Design

    Yunfan Liu, Lirong Wu, Zhifeng Gao, Yufei Huang, Cheng Tan, Haitao Lin, Zicheng Liu, Changxi Chi, Chang Yu, Stan Z Li

    Machine Learning

    日本大学: 関与なし(対象大学)

  18. 2026 · ICLR

    Saddle-To-Saddle Dynamics in Deep ReLU Networks: Low-Rank Bias in the First Saddle Escape

    Ioannis Bantzis, James Simon, Arthur Jacot

    Machine Learning

    日本大学: 関与なし(対象大学)

  19. 2026 · ICLR

    Saddle-to-Saddle Dynamics Explains A Simplicity Bias Across Neural Network Architectures

    Yedi Zhang, Andrew Saxe, Peter Latham

    Machine Learning

    日本大学: 関与なし(対象大学)

  20. 2026 · ICLR

    Safe Continuous-time Multi-Agent Reinforcement Learning via Epigraph Form

    Xuefeng Wang, Lei Zhang, Henglin Pu, Husheng Li, Ahmed Hussain Qureshi

    Machine Learning

    日本大学: 関与なし(対象大学)

  21. 2026 · ICLR

    Safe Exploration via Policy Priors

    Manuel Wendl, Yarden As, Manish Prajapat, Anton Pollak, Stelian Coros, Andreas Krause

    Machine Learning

    日本大学: 関与なし(対象大学)

  22. 2026 · ICLR

    SafeDPO: A Simple Approach to Direct Preference Optimization with Enhanced Safety

    Geon-Hyeong Kim, Yu Jin Kim, Byoungjip Kim, Honglak Lee, Kyunghoon Bae, Youngsoo Jang, Moontae Lee

    Machine Learning

    日本大学: 関与なし(対象大学)

  23. 2026 · ICLR

    SafeDialBench: A Fine-Grained Safety Evaluation Benchmark for Large Language Models in Multi-Turn Dialogues with Diverse Jailbreak Attacks

    Hongye Cao, Sijia Jing, Yanming Wang, Ziyue Peng, Zhixin Bai, Zhe Cao, Meng Fang, Fan Feng, JIAHENG LIU, Boyan Wang, Tianpei Yang, Jing Huo, Yang Gao, Fanyu Meng, Xi Yang, Chao Deng, Junlan Feng

    Machine Learning

    日本大学: 関与なし(対象大学)

  24. 2026 · ICLR

    SafeFlowMatcher: Safe and Fast Planning using Flow Matching with Control Barrier Functions

    Jeongyong Yang, Seunghwan Jang, SooJean Han

    Machine Learning

    日本大学: 関与なし(対象大学)

  25. 2026 · ICLR

    SafeMPO: Constrained Reinforcement Learning with Probabilistic Incremental Improvement

    Alexander Mattick, Dominik Seuß, Christopher Mutschler

    Machine Learning

    日本大学: 関与なし(対象大学)

  26. 2026 · ICLR

    SafeMoE: Safe Fine-Tuning for MoE LLMs by Aligning Harmful Input Routing

    Jaehan Kim, Minkyoo Song, Seungwon Shin, Sooel Son

    Machine Learning

    日本大学: 関与なし(対象大学)

  27. 2026 · ICLR

    Safeguarding Multimodal Knowledge Copyright in the RAG-as-a-Service Environment

    Tianyu Chen, Jian Lou, Wenjie Wang

    Machine Learning

    日本大学: 関与なし(対象大学)

  28. 2026 · ICLR

    Safety Instincts: LLMs Learn to Trust Their Internal Compass for Self-Defense

    Guobin Shen, Dongcheng Zhao, Haibo Tong, Jindong Li, Feifei Zhao, Yi Zeng

    Machine Learning

    日本大学: 関与なし(対象大学)

  29. 2026 · ICLR

    Safety Mirage: How Spurious Correlations Undermine VLM Safety Fine-Tuning and Can Be Mitigated by Machine Unlearning

    Yiwei Chen, Yuguang Yao, Yihua Zhang, Bingquan Shen, Gaowen Liu, Sijia Liu

    Machine Learning

    日本大学: 関与なし(対象大学)

  30. 2026 · ICLR

    Safety Subspaces are Not Linearly Distinct: A Fine-Tuning Case Study

    Kaustubh Ponkshe, Shaan Shah, Raghav Singhal, Praneeth Vepakomma

    Machine Learning

    日本大学: 関与なし(対象大学)

  31. 2026 · ICLR

    Safety at One Shot: Patching Fine-Tuned LLMs with A Single Instance

    Jiawen Zhang, Lipeng He, Kejia Chen, Jian Lou, Jian Liu, Xiaohu Yang, Ruoxi Jia

    Machine Learning

    日本大学: 関与なし(対象大学)

  32. 2026 · ICLR

    Salient Object Ranking via Cyclical Perception-Viewing Interaction Modeling

    Rongjin Guo, Ke Xu, Rynson W Lau

    Machine Learning

    日本大学: 関与なし(対象大学)

  33. 2026 · ICLR

    Same Content, Different Representations: A Controlled Study for Table QA

    Yue Zhang, Seiji Maekawa, Nikita Bhutani

    Machine Learning

    日本大学: 関与なし(対象大学)

  34. 2026 · ICLR

    Sample Complexity and Representation Ability of Test-time Scaling Paradigms

    Baihe Huang, Shanda Li, Tianhao Wu, Yiming Yang, Ameet Talwalkar, Kannan Ramchandran, Michael Jordan, Jiantao Jiao

    Machine Learning

    日本大学: 関与なし(対象大学)

  35. 2026 · ICLR

    Sample Efficient Offline RL via T-Symmetry Enforced Latent State-Stitching

    Peng Cheng, Zhihao Wu, Jianxiong Li, Ziteng He, Haoran Xu, Wei Sun, Youfang Lin, Yunxin Liu, Xianyuan Zhan

    Machine Learning

    日本大学: 関与なし(対象大学)

  36. 2026 · ICLR

    Sample Lottery: Unsupervised Discovery of Critical Instances for LLM Reasoning

    Zhiping Xiao, Yusheng Zhao, Qixin ZHANG, Jiaye Xie, Wanjia Zhao, Weizhi Zhang, Xiao Luo, Philip Yu, Ming Zhang

    Machine Learning

    日本大学: 関与なし(対象大学)

  37. 2026 · ICLR

    Sample More to Think Less: Group Filtered Policy Optimization for Concise Reasoning

    Vaishnavi Shrivastava, Ahmed H Awadallah, Vidhisha Balachandran, Shivam Garg, Harkirat Behl, Dimitris Papailiopoulos

    Machine Learning

    日本大学: 関与なし(対象大学)

  38. 2026 · ICLR

    Sample Reward Soups: Query-efficient Multi-Reward Guidance for Text-to-Image Diffusion Models

    Yinghua Yao, Yuangang Pan, Guoji Fu, Ivor Tsang

    Machine Learning

    日本大学: 関与なし(対象大学)

  39. 2026 · ICLR

    Sample Smart, Not Hard: Correctness-First Decoding for Better Reasoning in LLMs

    Xueyan Li, Guinan Su, Mrinmaya Sachan, Jonas Geiping

    Machine Learning

    日本大学: 関与なし(対象大学)

  40. 2026 · ICLR

    Sample-Efficient Distributionally Robust Multi-Agent Reinforcement Learning via Online Interaction

    Zain Ulabedeen Farhat, Debamita Ghosh, George Atia, Yue Wang

    Machine Learning

    日本大学: 関与なし(対象大学)

  41. 2026 · ICLR

    Sample-efficient and Scalable Exploration in Continuous-Time RL

    Klemens Iten, Lenart Treven, Bhavya, Florian Dorfler, Andreas Krause

    Machine Learning

    日本大学: 関与なし(対象大学)

  42. 2026 · ICLR

    Sample-efficient evidence estimation of score based priors for model selection

    Frederic Wang, Katherine Bouman

    Machine Learning

    日本大学: 関与なし(対象大学)

  43. 2026 · ICLR

    Samples Are Not Equal: A Sample Selection Approach for Deep Clustering

    Zhengxing Jiao, Yaxin Hou, Jun Ma, Yuhang Li, Ding Ding, Yuheng Jia, Hui LIU, Junhui Hou

    Machine Learning

    日本大学: 関与なし(対象大学)

  44. 2026 · ICLR

    Sampling Complexity of TD and PPO in RKHS

    LU ZOU, Wendi Ren, WEIZHONG ZHANG, Liang Ding, Shuang Li

    Machine Learning

    日本大学: 関与なし(対象大学)

  45. 2026 · ICLR

    Sampling-aware Adversarial Attacks Against Large Language Models

    Tim Beyer, Yan Scholten, Leo Schwinn, Stephan Günnemann

    Machine Learning

    日本大学: 関与なし(対象大学)

  46. 2026 · ICLR

    Sapiens2

    Rawal Khirodkar, He Wen, Julieta Martinez, Yuan Dong, Zhaoen Su, Shunsuke Saito

    Machine Learning

    日本大学: 関与なし(対象大学)

  47. 2026 · ICLR

    Sat3DGen: Comprehensive Street-Level 3D Scene Generation from Single Satellite Image

    Ming Qian, Zimin Xia, Changkun Liu, Shuailei Ma, Wen Wang, Zeran Ke, Bin Tan, Hang Zhang, Gui-Song Xia

    Machine Learning

    日本大学: 関与なし(対象大学)

  48. 2026 · ICLR

    SatDreamer360: Multiview-Consistent Generation of Ground-Level Scenes from Satellite Imagery

    Xianghui Ze, Beiyi Zhu, Zhenbo Song, Jianfeng Lu, Yujiao Shi

    Machine Learning

    日本大学: 関与なし(対象大学)

  49. 2026 · ICLR

    Scaf-GRPO: Scaffolded Group Relative Policy Optimization for Enhancing LLM Reasoning

    Xichen Zhang, Sitong Wu, Yinghao Zhu, Haoru Tan, Shaozuo Yu, Ziyi He, Jiaya Jia

    Machine Learning

    日本大学: 関与なし(対象大学)

  50. 2026 · ICLR

    Scalable Chain of Thoughts via Elastic Reasoning

    Yuhui Xu, Hanze Dong, Lei Wang, Doyen Sahoo, Junnan Li, Caiming Xiong

    Machine Learning

    日本大学: 関与なし(対象大学)

  51. 2026 · ICLR

    Scalable Energy-Based Models via Adversarial Training: Unifying Discrimination and Generation

    Xuwang Yin, Claire Zhang, Julie Steele, Nir Shavit, Tony Wang

    Machine Learning

    日本大学: 関与なし(対象大学)

  52. 2026 · ICLR

    Scalable Exploration for High-Dimensional Continuous Control via Value-Guided Flow

    Yunyue Wei, Chenhui Zuo, Yanan Sui

    Machine Learning

    日本大学: 関与なし(対象大学)

  53. 2026 · ICLR

    Scalable In-Context Q-Learning

    Jinmei Liu, Fuhong Liu, Zhenhong Sun, Jianye Hao, Huaxiong Li, Bo Wang, Daoyi Dong, Chunlin Chen, Zhi Wang

    Machine Learning

    日本大学: 関与なし(対象大学)

  54. 2026 · ICLR

    Scalable Multi-Task Low-Rank Model Adaptation

    Zichen Tian, Antoine Ledent, Qianru Sun

    Machine Learning

    日本大学: 関与なし(対象大学)

  55. 2026 · ICLR

    Scalable Multilingual Multimodal Machine Translation with Speech-Text Fusion

    Yexing Du, Youcheng Pan, Zekun Wang, Zheng Chu, yichong huang, Kaiyuan Liu, Bo Yang, Yang Xiang, Ming Liu, Bing Qin

    Machine Learning

    日本大学: 関与なし(対象大学)

  56. 2026 · ICLR

    Scalable Offline Model-Based RL with Action Chunks

    Kwanyoung Park, Seohong Park, Youngwoon Lee, Sergey Levine

    Machine Learning

    日本大学: 関与なし(対象大学)

  57. 2026 · ICLR

    Scalable Random Wavelet Features: Efficient Non-Stationary Kernel Approximation with Convergence Guarantees

    Sawan Kumar, Souvik Chakraborty

    Machine Learning

    日本大学: 関与なし(対象大学)

  58. 2026 · ICLR

    Scalable Second-order Riemannian Optimization for $K$-means Clustering

    Peng Xu, Chun Ying Hou, Xiaohui Chen, Richard Zhang

    Machine Learning

    日本大学: 関与なし(対象大学)

  59. 2026 · ICLR

    Scalable Spatio-Temporal SE(3) Diffusion for Long-Horizon Protein Dynamics

    Nima Shoghi, Yuxuan Liu, Yuning Shen, Rob Brekelmans, Pan Li, Quanquan Gu

    Machine Learning

    日本大学: 関与なし(対象大学)

  60. 2026 · ICLR

    Scalable Training for Vector-Quantized Networks with 100% Codebook Utilization

    Yifan Chang, Jie Qin, Limeng Qiao, Xiaofeng Wang, Zheng Zhu, Lin Ma, Xingang Wang

    Machine Learning

    日本大学: 関与なし(対象大学)

  61. 2026 · ICLR

    Scalable and Adaptive Trust-Region Learning via Projection Convex Hull

    Hongyang Jia, Qingchun Hou, Bojun Du, Xiao Cai, Ning Zhang, Chongqing Kang

    Machine Learning

    日本大学: 関与なし(対象大学)

  62. 2026 · ICLR

    Scale-wise Distillation of Diffusion Models

    Nikita Starodubcev, Ilya Drobyshevskiy, Denis Kuznedelev, Artem Babenko, Dmitry Baranchuk

    Machine Learning

    日本大学: 関与なし(対象大学)

  63. 2026 · ICLR

    ScaleCUA: Scaling Open-Source Computer Use Agents with Cross-Platform Data

    Zhaoyang Liu, JingJing Xie, Zichen Ding, Zehao Li, Bowen Yang, Zhenyu Wu, Xuehui Wang, Qiushi Sun, Shi Liu, Weiyun Wang, Shenglong Ye, Qingyun Li, Zeyue Tian, Gen Luo, Xiangyu Yue, Biqing Qi, Kai Chen, Bowen Zhou, Yu Qiao, Qifeng Chen, Wenhai Wang

    Machine Learning

    日本大学: 関与なし(対象大学)

  64. 2026 · ICLR

    ScaleCap: Scalable Image Captioning via Dual-Modality Debiasing

    Long Xing, Qidong Huang, Xiaoyi Dong, Pan Zhang, Yuhang Zang, Yuhang Cao, Jinsong Li, Shuangrui Ding, Weiming Zhang, Nenghai Yu, Jiaqi Wang, Feng Wu, Dahua Lin

    Machine Learning

    日本大学: 関与なし(対象大学)

  65. 2026 · ICLR

    ScaleLong: A Multi-Timescale Benchmark for Long Video Understanding

    David Ma, Huaqing Yuan, Xingjian Wang, Qianbo ZANG, Tianci Liu, Xinyang He, Yanbin Wei, Jiawei Guo, nijiahui, Zhenzhu Yang, Meng Cao, Shanghaoran Quan, Yizhi Li, Wangchunshu Zhou, JIAHENG LIU, Wenhao Huang, Ge Zhang, Shiwen Ni, Xiaojie Jin

    Machine Learning

    日本大学: 関与なし(対象大学)

  66. 2026 · ICLR

    Scaling Agent Learning via Experience Synthesis

    Zhaorun Chen, Zhuokai Zhao, Kai Zhang, Bo Liu, Qi Qi, Yifan Wu, Tarun Kalluri, Xuefei Cao, Yuanhao Xiong, Haibo Tong, Huaxiu Yao, Hengduo Li, Jiacheng Zhu, Xian Li, Dawn Song, Bo Li, Jason E Weston, Dat Huynh

    Machine Learning

    日本大学: 関与なし(対象大学)

  67. 2026 · ICLR

    Scaling Agents via Continual Pre-training

    Liangcai Su, Zhen Zhang, Guangyu Li, Zhuo Chen, Chenxi Wang, Maojia Song, Xinyu Wang, Kuan Li, Jialong Wu, Xuanzhong Chen, Zile Qiao, Zhongwang Zhang, Huifeng Yin, Shihao Cai, Runnan Fang, Zhengwei Tao, Wenbiao Yin, Rui Ye, Yong Jiang, Ningyu Zhang, Pengjun Xie, Fei Huang, Kai Ye, Kewei Tu, Chenxiong Qian, Jingren Zhou

    Machine Learning

    日本大学: 関与なし(対象大学)

  68. 2026 · ICLR

    Scaling Atomistic Protein Binder Design with Generative Pretraining and Test-Time Compute

    Kieran Didi, Zuobai Zhang, Guoqing Zhou, Danny Reidenbach, Zhonglin Cao, Sooyoung Cha, Tomas Geffner, Christian Dallago, Jian Tang, Michael Bronstein, Martin Steinegger, Emine Kucukbenli, Arash Vahdat, Karsten Kreis

    Machine Learning

    日本大学: 関与なし(対象大学)

  69. 2026 · ICLR

    Scaling Attention via Feature Sparsity

    Yan Xie, Tiansheng Wen, Tang Da Huang, Bo Chen, Chenyu You, Stefanie Jegelka, Yifei Wang

    Machine Learning

    日本大学: 関与なし(対象大学)

  70. 2026 · ICLR

    Scaling Behavior of Discrete Diffusion Language Models

    Dimitri von Rütte, Janis Fluri, Omead Pooladzandi, Bernhard Schölkopf, Thomas Hofmann, Antonio Orvieto

    Machine Learning

    日本大学: 関与なし(対象大学)

  71. 2026 · ICLR

    Scaling Direct Feedback Learning with Jacobian Alignment Guarantees

    Paul Caillon, Erwan Fagnou, Blaise Delattre, Alexandre Allauzen

    Machine Learning

    日本大学: 東京科学大学

  72. 2026 · ICLR

    Scaling Generalist Data-Analytic Agents

    Shuofei Qiao, Yanqiu Zhao, Zhisong Qiu, Xiaobin Wang, Jintian Zhang, Zhao Bin, Ningyu Zhang, Yong Jiang, Pengjun Xie, Fei Huang, Huajun Chen

    Machine Learning

    日本大学: 関与なし(対象大学)

  73. 2026 · ICLR

    Scaling Goal-conditioned Reinforcement Learning with Multistep Quasimetric Distances

    Bill Zheng, Vivek Myers, Benjamin Eysenbach, Sergey Levine

    Machine Learning

    日本大学: 関与なし(対象大学)

  74. 2026 · ICLR

    Scaling Group Inference for Diverse and High-Quality Generation

    Gaurav Parmar, Or Patashnik, Daniil Ostashev, Kuan-Chieh Wang, Kfir Aberman, Srinivasa Narasimhan, Jun-Yan Zhu

    Machine Learning

    日本大学: 関与なし(対象大学)

  75. 2026 · ICLR

    Scaling Knowledge Editing in LLMs to 100,000 Facts with Neural KV Database

    Weizhi Fei, Hao Shi, Jing Xu, Jingchen Peng, Jiazheng Li, Jingzhao Zhang, Bo Bai, Wei Han, zy chen, Xueyan Niu

    Machine Learning

    日本大学: 関与なし(対象大学)

  76. 2026 · ICLR

    Scaling Knowledge Graph Construction through Synthetic Data Generation and Distillation

    Prafulla Kumar Choubey, Xin Su, Man Luo, XIANGYU PENG, Caiming Xiong, Tiep Le, Shachar Rosenman, Vasudev Lal, Phil Mui, Ricky Ho, Phillip Howard, Chien-Sheng Wu

    Machine Learning

    日本大学: 関与なし(対象大学)

  77. 2026 · ICLR

    Scaling Large Vision-Language Model RL Training via Efficient Load Balancing

    Zerui Wang, Qinghao Hu, Chang Chen, Jiecheng Zhou, Haojie Duanmu, Xingcheng Zhang, Peng Sun, Dahua Lin

    Machine Learning

    日本大学: 関与なし(対象大学)

  78. 2026 · ICLR

    Scaling Laws Meet Model Architecture: Toward Inference-Efficient LLMs

    Song Bian, Tao Yu, Shivaram Venkataraman, Youngsuk Park

    Machine Learning

    日本大学: 関与なし(対象大学)

  79. 2026 · ICLR

    Scaling Laws Revisited: Modeling the Role of Data Quality in Language Model Pretraining

    Anirudh Subramanyam, Yuxin Chen, Robert Grossman

    Machine Learning

    日本大学: 関与なし(対象大学)

  80. 2026 · ICLR

    Scaling Laws and Spectra of Shallow Neural Networks in the Feature Learning Regime

    Leonardo Defilippis, Yizhou Xu, Julius Girardin, Vittorio Erba, Emanuele Troiani, Lenka Zdeborova, Bruno Loureiro, Florent Krzakala

    Machine Learning

    日本大学: 関与なし(対象大学)

  81. 2026 · ICLR

    Scaling Laws and Symmetry, Evidence from Neural Force Fields

    Nhat Khang Ngo, Siamak Ravanbakhsh

    Machine Learning

    日本大学: 関与なし(対象大学)

  82. 2026 · ICLR

    Scaling Laws for Diffusion Transformers

    Zhengyang Liang, Hao He, Ceyuan Yang, Bo DAI

    Machine Learning

    日本大学: 関与なし(対象大学)

  83. 2026 · ICLR

    Scaling Laws of SignSGD in Linear Regression: When Does It Outperform SGD?

    Jihwan Kim, Dogyoon Song, Chulhee Yun

    Machine Learning

    日本大学: 関与なし(対象大学)

  84. 2026 · ICLR

    Scaling Linear Attention Capacity with Sparse State Expansion

    Yuqi Pan, Yongqi An, Zheng Li, Yuhong Chou, Rui-Jie Zhu, Xiaohui Wang, Mingxuan Wang, Jinqiao Wang, Guoqi Li

    Machine Learning

    日本大学: 関与なし(対象大学)

  85. 2026 · ICLR

    Scaling Multi-Task Bayesian Optimization with Large Language Models

    Yimeng Zeng, Natalie Maus, Haydn Jones, Jeffrey Tao, Fangping Wan, Marcelo Der Torossian Torres, Cesar de la Fuente, Ryan Marcus, Osbert Bastani, Jacob Gardner

    Machine Learning

    日本大学: 関与なし(対象大学)

  86. 2026 · ICLR

    Scaling Reasoning Hop Exposes Weaknesses: Demystifying and Improving Hop Generalization in Large Language Models

    Zhaoyi Li, Jiatong Li, Gangwei Jiang, Linqi Song, Defu Lian, Ying Wei

    Machine Learning

    日本大学: 関与なし(対象大学)

  87. 2026 · ICLR

    Scaling Sequence-to-Sequence Generative Neural Rendering

    Shikun Liu, Kam Woh Ng, Wonbong Jang, Jiadong Guo, Junlin Han, Haozhe Liu, Yiannis Douratsos, Juan Perez, Zijian Zhou, Khanh Chi Phung, Tao Xiang, Juan-Manuel Perez-Rua

    Machine Learning

    日本大学: 関与なし(対象大学)

  88. 2026 · ICLR

    Scaling Speech Tokenizers with Diffusion Autoencoders

    Yuancheng Wang, Zhenyu Tang, Yun Wang, Arthur Hinsvark, Yingru Liu, Yinghao Li, Kainan Peng, Junyi Ao, Mingbo Ma, Mike Seltzer, Qing He, Xubo Liu

    Machine Learning

    日本大学: 関与なし(対象大学)

  89. 2026 · ICLR

    Scaling Synthetic Task Generation for Agents via Exploration

    Ram Ramrakhya, Andrew Szot, Omar Attia, Bogdan Mazoure, Anh Nguyen, Yuhao Yang, Zhe Gan, Harsh Agrawal, Alexander Toshev

    Machine Learning

    日本大学: 関与なし(対象大学)

  90. 2026 · ICLR

    Scaling Up, Speeding Up: A Benchmark of Speculative Decoding for Efficient LLM Test-Time Scaling

    Shengyin Sun, Yiming Li, Xing Li, Yingzhao Lian, Weizhe Lin, Huiling Zhen, Zhiyuan Yang, Xianzhi Yu, Chen Chen, Mingxuan Yuan, Chen Ma

    Machine Learning

    日本大学: 関与なし(対象大学)

  91. 2026 · ICLR

    Scaling up Memory for Robotic Control via Experience Retrieval

    Ajay Sridhar, Jennifer Pan, Satvik Sharma, Chelsea Finn

    Machine Learning

    日本大学: 関与なし(対象大学)

  92. 2026 · ICLR

    Scaling with Collapse: Efficient and Predictable Training of LLM Families

    Shane Bergsma, Bin Zhang, Nolan Dey, Shaheer Muhammad, Gurpreet Gosal, Joel Hestness

    Machine Learning

    日本大学: 関与なし(対象大学)

  93. 2026 · ICLR

    ScalingCache: Extreme Acceleration of DiTs through Difference Scaling and Dynamic Interval Caching

    Lihui Gu, Jingbin He, Lianghao Su, Kang He, Wenxiao Wang, Yuliang Liu

    Machine Learning

    日本大学: 関与なし(対象大学)

  94. 2026 · ICLR

    SceneCOT: Eliciting Grounded Chain-of-Thought Reasoning in 3D Scenes

    Xiongkun Linghu, Jiangyong Huang, Ziyu Zhu, Baoxiong Jia, Siyuan Huang

    Machine Learning

    日本大学: 関与なし(対象大学)

  95. 2026 · ICLR

    SceneStreamer: Continuous Scenario Generation as Next Token Group Prediction

    Zhenghao Peng, Yuxin Liu, Bolei Zhou

    Machine Learning

    日本大学: 関与なし(対象大学)

  96. 2026 · ICLR

    SceneTransporter: Optimal Transport-Guided Compositional Latent Diffusion for Single-Image Structured 3D Scene Generation

    Ling Wang, Hao-Xiang Guo, Xinzhou Wang, Fuchun Sun, Kai Sun, Pengkun Liu, Hang Xiao, Zhong Wang, Guangyuan Fu, Eric Li, Yang Liu, Yikai Wang

    Machine Learning

    日本大学: 関与なし(対象大学)

  97. 2026 · ICLR

    Scenethesis: A Language and Vision Agentic Framework for 3D Scene Generation

    Lu Ling, Chen-Hsuan Lin, Tsung-Yi Lin, Yifan Ding, Yu Zeng, Yichen Sheng, Yunhao Ge, Ming-Yu Liu, Aniket Bera, Max Li

    Machine Learning

    日本大学: 関与なし(対象大学)

  98. 2026 · ICLR

    Scheduling Your LLM Reinforcement Learning with Reasoning Trees

    Hong Wang, Zhezheng Hao, Jian Luo, Chenxing Wei, Yao Shu, Lei Liu, Qiang Lin, Hande Dong, Jiawei Chen

    Machine Learning

    日本大学: 関与なし(対象大学)

  99. 2026 · ICLR

    Sci2Pol: Evaluating and Fine-tuning LLMs on Scientific-to-Policy Brief Generation

    Weimin Wu, Alexander Furnas, Eddie Yang, Gefei Liu, Akhil Pandey Akella, Xuefeng Song, Dashun Wang, Han Liu

    Machine Learning

    日本大学: 関与なし(対象大学)

  100. 2026 · ICLR

    SciNav: A General Agent Framework for Scientific Coding Tasks

    Tianshu Zhang, Huan Sun

    Machine Learning

    日本大学: 関与なし(対象大学)