AutoDefense: Multi-Agent LLM Defense against Jailbreak Attacks

arXiv:2403.04783v1 Announce Type: cross
Abstract: Despite extensive pre-training and fine-tuning in moral alignment to prevent generating harmful information at user request, large language models (LLMs) remain vulnerable to jailbreak attacks. In this paper, we propose AutoDefense, a response-filtering based multi-agent defense framework that filters harmful responses from LLMs. This framework assigns different roles to LLM agents and employs them to complete the defense task collaboratively. The division in tasks enhances the overall instruction-following of LLMs and enables the integration of …

agent arxiv attacks cs.cl cs.cr cs.lg defense jailbreak llm