LLM Safety

Multi-Agent Debate Systems Cut LLM Safety Testing Costs

New research demonstrates how multi-agent debate frameworks can evaluate LLM safety more efficiently than traditional methods, reducing costs while maintaining accuracy in identifying harmful model behaviors.

AI Security

Multi-Agent LLMs Team Up to Break AI Safety Guardrails

New research demonstrates how multiple LLMs working together can generate adaptive adversarial attacks that bypass AI safety filters. The technique uses collaborative reasoning to craft prompts that exploit model vulnerabilities more effectively than single-agent approaches.