Rethinking the Transferable Adversarial Attacks and Robust Defense in Federated Learning
DGX agentarXiv:2608.25133v1 Announce Type: new Abstract: The development of federated learning (FL) techniques has helped improve the privacy preservation of users' data and extended the applications of machin