Can debating LLMs detect phishing emails?
Debate-Driven Multi-Agent LLMs for Phishing Email Detection
March 31, 2025
https://arxiv.org/pdf/2503.22038This research explores using multiple LLMs in a "debate" format to detect phishing emails. Two "debater" LLMs argue for and against an email being phishing, while a "judge" LLM evaluates their arguments to make a final decision.
Key points:
- Heterogeneous agents perform better: Mixing different LLM types (e.g., GPT-4 and LLaMA-2) as debaters and judges improves accuracy compared to using the same LLM for all roles.
- Debate structure is sufficient: Additional prompting techniques like chain-of-thought or role prompting did not significantly improve results beyond the core debate structure. This suggests the debate format itself encourages effective reasoning.
- Relevance to multi-agent systems: This research highlights the potential of structured multi-agent interaction (debate) for enhancing LLM reasoning in complex tasks like phishing detection, offering a practical example of LLM-based multi-agent system design.