2025
Learning Diverse Attacks on Large Language Models for Robust Red-Teaming and Safety Tuning
ICLR 2025poster
Red-teaming, or identifying prompts that elicit harmful responses, is a critical step in ensuring the safe and responsible deployment of large language models (LLMs). Developing effective protection against many modes of attack prompts requires discovering diverse attacks. Automated red-teaming typi…