arXivDaily arXiv每日学术速递 周一至周五更新

高校专区

Imperial College London(帝国理工学院)

2026-01-27 至 2026-01-27 共收录 6
2601.18314 2026-01-27 cs.LG

A Master Class on Reproducibility: A Student Hackathon on Advanced MRI Reconstruction Methods

可重现性大师课:关于高级MRI重建方法的学生黑客松

Lina Felsner, Sevgi G. Kafali, Hannah Eichhorn, Agnes A. J. Leth, Aidas Batvinskas, Andre Datchev, Fabian Klemm, Jan Aulich, Puntika Leepagorn, Ruben Klinger, Daniel Rueckert, Julia A. Schnabel

机构 * Technical University of Munich (TUM)(技术大学慕尼黑) Institute of Machine Learning in Biomedical Imaging, Helmholtz Munich(生物医学成像机器学习研究所,海德堡慕尼黑) Munich Center for Machine Learning (MCML)(慕尼黑机器学习中心) School of Medicine and Health, TUM University Hospital Rechts der Isar(医学与健康学院,技术大学慕尼黑医院Rechts der Isar) Department of Computing, Imperial College London(计算学院,伦敦帝国理工学院)

AI总结 本文通过学生黑客松重现三个先进的MRI重建方法,探讨了可重现性代码库的构建实践和实验结果。

详情

展开后加载摘要…

URL PDF HTML 收藏
2601.07134 2026-01-27 cs.CR cs.CV cs.LG

Proof of Reasoning for Privacy Enhanced Federated Blockchain Learning at the Edge

边缘隐私增强联邦区块链学习的证明推理

James Calo, Benny Lo

机构 * Department of Computing(计算系) Department of Surgery and Cancer(外科与癌症系) Hamlyn Centre(哈姆林中心) Imperial College London(帝国理工学院伦敦分校)

AI总结 本文提出PoR共识机制,通过屏蔽自动编码器和边缘端分类器提升边缘联邦学习的隐私保护与聚合效率。

Comments 8 Pages, 5 figues, 9 tables, journal paper

详情

展开后加载摘要…

URL PDF HTML 收藏
2506.19893 2026-01-27 cs.LG cs.AI cs.IT eess.IV math.IT

Distillation-Enabled Knowledge Alignment for Generative Semantic Communications of AIGC Images

基于知识对齐的生成语义通信中的知识蒸馏

Jingzhi Hu, Geoffrey Ye Li

机构 * Department of Electrical and Electronic Engineering, Imperial College London(帝国理工学院伦敦分校电子与电气工程系)

AI总结 本文提出DeKA-g算法,通过知识蒸馏和低秩适应,提升生成语义通信中边缘与云生成图像的一致性及传输质量。

详情

展开后加载摘要…

URL PDF HTML 收藏
2601.17480 2026-01-27 cs.LG cs.AI cs.CL

Unintended Memorization of Sensitive Information in Fine-Tuned Language Models

在微调语言模型中意外记忆敏感信息

Marton Szep, Jorge Marin Ruiz, Georgios Kaissis, Paulina Seidl, Rüdiger von Eisenhart-Rothe, Florian Hinterwimmer, Daniel Rueckert

机构 * TUM University Hospital(慕尼黑工业大学医院) Technical University of Munich (TUM)(慕尼黑技术大学) Munich Center for Machine Learning (MCML)(慕尼黑机器学习中心) Department of Computing, Imperial College London(伦敦帝国学院计算系)

AI总结 研究揭示微调语言模型时意外记忆敏感信息的风险,分析影响因素并评估隐私保护方法的权衡。

Comments Accepted to EACL 2026. 20 pages

详情

展开后加载摘要…

URL PDF HTML 收藏
2412.12679 2026-01-27 cs.CL

Discourse Features Enhance Detection of Document-Level Machine-Generated Content

语篇特征增强文档级机器生成内容的检测

Yupei Li, Manuel Milling, Lucia Specia, Björn W. Schuller

机构 * Department of Computing Imperial College London London, UK Chair of Health Informatics Technical University of Munich Munich, Germany 5cm Department of Computing \& Chair of Health Informatics 5cm Imperial College London \& Technical University of Munich 5cm London, UK \& Munich, Germany 5cm

AI总结 本研究提出DTransformer模型,通过语篇分析预处理捕捉文档级结构特征,有效提升对机器生成内容的检测性能。

Comments Accepted by IJCNN 2025

Journal ref Proc. International Joint Conference on Neural Networks (IJCNN), 2025

详情

展开后加载摘要…

URL PDF HTML 收藏
2601.17107 2026-01-27 cs.CV

StealthMark: Harmless and Stealthy Ownership Verification for Medical Segmentation via Uncertainty-Guided Backdoors

StealthMark: 通过不确定性引导后门实现医疗分割的无害且隐蔽的所有权验证

Qinkai Yu, Chong Zhang, Gaojie Jin, Tianjin Huang, Wei Zhou, Wenhui Li, Xiaobo Jin, Bo Huang, Yitian Zhao, Guang Yang, Gregory Y. H. Lip, Yalin Zheng, Aline Villavicencio, Yanda Meng

机构 * Computer Science Department, University of Exeter(埃克塞特大学计算机科学系) Bioengineering Program, Biological and Environmental Science and Engineering Division (BESE), King Abdullah University of Science and Technology (KAUST)(科廷大学科学与技术学院生物工程项目) School of Advanced Technology, Xi’an Jiaotong-Liverpool University(西安交通大学利物浦大学分校高级技术学院) School of Computer Science and Informatics, Cardiff University(卡迪夫大学计算机科学与信息学院) College of Optoelectronic Engineering, Chongqing University(重庆大学光电工程学院) Ningbo Cixi Institute of Biomedical Engineering, Chinese Academy of Sciences(宁波慈溪生物医学工程研究所,中国科学院) School of Bioengineering, Imperial College London(伦敦帝国理工学院生物工程学院) Liverpool Centre for Cardiovascular Science at University of Liverpool, Liverpool John Moores University and Liverpool Heart & Chest Hospital(利物浦大学心血管科学中心,利物浦约翰摩尔斯大学,利物浦心脏和胸科医院) Eye and Vision Department, University of Liverpool(利物浦大学眼科学与视觉科学系)

AI总结 StealthMark通过不确定性引导后门实现医疗分割模型的隐蔽无害所有权验证,有效提升模型安全性与实用性。

Comments 15 pages,7 figures. Accepted to IEEE Transactions on Image Processing (TIP) 2026

详情

展开后加载摘要…

URL PDF HTML 收藏