From Conflict to Consensus: Boosting Medical Reasoning via Multi-Round Agentic RAG

Researchers developed MA-RAG, a Multi-Round Agentic RAG framework that improves medical AI reasoning by iteratively refining responses through conflict detection and external evidence retrieval. The system achieved a substantial +6.8 point accuracy improvement over baseline models across 7 medical Q&A benchmarks by addressing hallucinations and outdated knowledge in healthcare AI applications.