Retrieval Augmented Generation (RAG) is a framework designed to enhance Question Answering (QA) by integrating relevant external knowledge into the generation process.

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
• Unlocking the Potential of Generative AI through Neuro-Symbolic ... arxiv.org arXiv via serper
• Large Language Models Meet Knowledge Graphs for Question ... arxiv.org arXiv via serper

Referenced by nodes (2)

• Retrieval-Augmented Generation (RAG) concept
• Question Answering concept