Let Large Language Models Judge Each Other: Multi-Agent Peer-Reviewed Reasoning for Medical Question Answering
The method uses multiple LLM agents to independently generate reasoning for medical questions and then have them peer-review each other's work for correctness and logic. This multi-agent approach consistently outperformed single models and majority voting ensembles in medical question answering benchmarks, proving that quality of reasoning matters more than just answer agreement.