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2026-03-05 至 2026-03-05 共收录 1 信号源:cs.AI, cs.CL, cs.LG, cs.SE

1. 其他Agent 1 篇

2507.15796 2026-03-05 cs.AI 80%

From Privacy to Trust in the Agentic Era: A Taxonomy of Challenges in Trustworthy Federated Learning Through the Lens of Trust Report 2.0

从隐私到信任在代理时代:通过信任报告2.0的视角,对可信联邦学习中挑战的分类

Nuria Rodríguez-Barroso, Mario García-Márquez, M. Victoria Luzón, Francisco Herrera

机构 * Department of Computer Science and Artificial Intelligence, Andalusian Research Institute in Data Science and Computational Intelligence (DaSCI) University of Granada(计算机科学与人工智能系,数据科学与计算智能安达卢西亚研究 institute,格拉纳达大学) Department of Software Engineering, Andalusian Research Institute in Data Science and Computational Intelligence (DaSCI) University of Granada(软件工程系,数据科学与计算智能安达卢西亚研究 institute,格拉纳达大学)

专题命中 其他Agent :agentic(title,abstract);分类 cs.AI

AI总结 本文通过信任报告2.0提出可信联邦学习的挑战分类,强调信任作为持续维持的操作条件,并引入协调蓝图以处理跨要求的权衡和治理对齐。

Comments Already published in Information Fusion

Journal ref Rodríguez-Barroso, et. al. (2026). From Privacy to Trust in the Agentic Era: A Taxonomy of Challenges in Trustworthy Federated Learning Through the Lens of Trust Report 2.0. Information Fusion, 104236

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