Safe-FedLLM: Delving into the Safety of Federated Large Language Models 事件

Safe-FedLLM: Delving into the Safety of Federated Large Language Models arXiv:2601.07177v5 Announce Type: replace-cross Abstract: Federated learning (FL) addresses privacy and data-silo issues in the training of large language models (LLMs). Most prior work focuses on improving the efficiency of federated learning for LLMs (FedLLM). However, security in open federated environments, particularly defenses against malicious clients, remains underexplored. To investigate the security of FedLLM, we