Reflect-Guard: Enhancing LLM Safeguards against Adversarial Prompts via Logical Self-Reflection 事件

Reflect-Guard: Enhancing LLM Safeguards against Adversarial Prompts via Logical Self-Reflection arXiv:2605.24834v1 Announce Type: cross Abstract: Large language model (LLM) safety classifiers such as Llama Guard are effective at detecting overtly harmful prompts but remain vulnerable to adversarial jailbreak attacks that disguise malicious intent through role-play scenarios, fictional framing, and indirect requests. We present Reflect-Guard, a method that augments LLM-based safety classifiers w