arXivDaily arXiv每日学术速递 周一至周五更新

高校专区

University of Cambridge(剑桥大学)

2025-12-02 至 2025-12-02 共收录 5
2511.06309 2025-12-02 cs.AI cs.MA

The Station: An Open-World Environment for AI-Driven Discovery

The Station:一个面向AI驱动发现的开放世界环境

Stephen Chung, Wenyu Du

机构 * DualverseAI University of Cambridge(剑桥大学) University of Hong Kong(香港大学)

AI总结 STATION是一个开放世界多智能体环境,通过自主科学发现的涌现行为实现AI驱动的科学突破。

Comments 55 pages

详情

展开后加载摘要…

URL PDF HTML 收藏
2512.00748 2025-12-02 cs.CV cs.AI

Probabilistic Modeling of Multi-rater Medical Image Segmentation for Diversity and Personalization

多评分者医学图像分割的概率建模用于多样性和个性化

Ke Liu, Shangde Gao, Yichao Fu, Shangqi Gao, Chunhua Shen

机构 * Zhejiang University(浙江大学) University of Cambridge(剑桥大学) Carnegie Mellon University(卡内基梅隆大学)

AI总结 ProSeg通过概率建模实现医学图像分割的多样化和个性化,结合专家偏好和边界模糊性,提升分割结果的多样性和个性化水平。

详情

展开后加载摘要…

URL PDF HTML 收藏
2512.00434 2025-12-02 cs.LG cs.CR stat.ML

Privacy-Preserving Generative Modeling and Clinical Validation of Longitudinal Health Records for Chronic Disease

隐私保护的生成建模与慢性病纵向健康记录的临床验证

Benjamin D. Ballyk, Ankit Gupta, Sujay Konda, Kavitha Subramanian, Chris Landon, Ahmed Ammar Naseer, Georg Maierhofer, Sumanth Swaminathan, Vasudevan Venkateshwaran

机构 * Vironix Health Inc(Vironix健康公司) University of Oxford(牛津大学) University of Cambridge(剑桥大学) Stanford University(斯坦福大学) University of Southern California(南加州大学)

AI总结 本文提出DP-TimeGAN模型,通过隐私保护生成模型处理纵向健康记录,提升慢性病诊断的隐私与效用平衡。

Comments To appear in Proceedings of Machine Learning Research Volume 297 - Proceedings of ML4H 2025

详情

展开后加载摘要…

URL PDF HTML 收藏
2503.08594 2025-12-02 cs.CV cs.LG

PointNSP: Autoregressive 3D Point Cloud Generation with Next-Scale Level-of-Detail Prediction

PointNSP: 通过下一尺度细节预测实现自回归3D点云生成

Ziqiao Meng, Qichao Wang, Zhiyang Dou, Zixing Song, Zhipeng Zhou, Irwin King, Peilin Zhao

机构 * National University of Singapore(新加坡国立大学) Nanyang Technological University(南洋理工大学) University of Hong Kong(香港大学) University of Cambridge(剑桥大学) The Chinese University of Hong Kong(香港中文大学) Shanghai Jiao Tong University(上海交通大学)

AI总结 PointNSP通过下一尺度细节预测实现自回归3D点云生成,首次在自回归范式中达到最先进的生成质量,并在参数、训练和推理效率上超越扩散基线。

Comments 24 pages; Previously this version appeared as arXiv:2510.05613 which was submitted as a new work by accident

详情

展开后加载摘要…

URL PDF HTML 收藏
2412.02138 2025-12-02 cs.CL

Misalignment of Semantic Relation Knowledge between WordNet and Human Intuition

词网与人类直觉之间语义关系知识的不一致

Zhihan Cao, Hiroaki Yamada, Simone Teufel, Takenobu Tokunaga

机构 * Institute of Science Tokyo(东京科学研究所) University of Cambridge(剑桥大学)

AI总结 研究发现词网与人类直觉在语义关系知识上存在系统性不一致,影响其应用与改进。

Comments Accepted by Global WordNet Conference 2025

Journal ref Proceedings of the 13th Global Wordnet Conference (GWC2025), pages 25-36

详情

展开后加载摘要…

URL PDF HTML 收藏