Microsoft Research
Retrieval-augmented generation (RAG) helps AI systems provide more information to a large language model (LLM) when generating responses to user queries. A new method for conducting “global” queries can optimize the performance of global search in GraphRAG. The post GraphRAG: Improving global search via dynamic community selection appeared first on Microsoft Research. Dynamic global search is the second of several major optimizations to GraphRAG that are being explored. If you are interested in optimizations for local questions, please check out our recent blog post on DRIFT search. Stay tuned for our upcoming work, where we explore a radically different approach to graph-enabled RAG that is significantly more cost-efficient while improving answer quality for both local and global questions. Opens in a new tabThe post GraphRAG: Improving global search via dynamic community selection appeared first on Microsoft Research.
Published: 2024-11-15T16:52:47
