AINeutralarXiv – CS AI · 8h ago6/10
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SEMA-RAG: A Self-Evolving Multi-Agent Retrieval-Augmented Generation Framework for Medical Reasoning
SEMA-RAG introduces a multi-agent framework that decouples medical reasoning tasks into three specialized agents to improve retrieval-augmented generation for clinical question answering. The approach achieves 6.46 percentage point accuracy improvements over existing baselines by addressing hallucinations and knowledge obsolescence through iterative, evidence-driven retrieval rather than single-round static lookups.