The AMG-RAG system configured with the PubMed-MKG and an 8B LLM backbone achieves an accuracy of 73.92% on the MEDQA benchmark, surpassing baseline models including Self-RAG (Asai et al., 2023), HyDE (Gao et al., 2022), GraphRAG (Edge et al., 2024), and MedRAG (Zhao et al., 2025).

Authors

• Person: Not available Organization: arXiv
  Bridging the Gap Between LLMs and Evolving Medical Knowledge

Sources

• Bridging the Gap Between LLMs and Evolving Medical Knowledge arxiv.org arXiv via serper

Referenced by nodes (3)

• AMG-RAG concept
• MEDQA concept
• MedRAG concept