PoCoFL: POlicy-COmpliant Federated Learning

Paper recorded by Signals 4 on 2026-10-02 in cs.LG. Abstract reproduced from arXiv; link to the original below.

Published 2026-10-02 on arXiv · recorded by Signals 4 on 2026-10-05

Category: cs.LG · 机器学习 · first seen 2026-10-05

Abstract

Federated Learning (FL) is a privacy-oriented learning paradigm that enables collaborative model training while keeping training data local to participating clients. However, it does not guarantee that clients submit policy-compliant contributions or that aggregators process admitted contributions correctly. Existing verifiable FL systems tailor validation rules to specific FL settings, learning w

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