Retrieval-Augmented Generation (RAG) is a technique that enhances an LLM's response by pulling in relevant information from an external knowledge source.

Authors

• Person: Not available Organization: NebulaGraph
  How NebulaGraph Fusion GraphRAG Bridges the Gap Between ...
• Person: Not available Organization: LinkedIn
  Enhancing LLMs with Knowledge Graphs: A Case Study - LinkedIn
• Person: Not available Organization: medRxiv
  Medical Hallucination in Foundation Models and Their Impact on ...

Sources

• How NebulaGraph Fusion GraphRAG Bridges the Gap Between ... nebula-graph.io NebulaGraph via serper
• Enhancing LLMs with Knowledge Graphs: A Case Study - LinkedIn www.linkedin.com LinkedIn via serper
• Medical Hallucination in Foundation Models and Their Impact on ... www.medrxiv.org medRxiv via serper

Referenced by nodes (2)

• Retrieval-Augmented Generation (RAG) concept
• external knowledge base concept