3 ms·
How does this work? I understand the issues with "baseline RAG", as I experienced them myself. They make sense to me, if I query "what are the major themes of
by k__ 2y ago
How does this work?
I understand the issues with "baseline RAG", as I experienced them myself. They make sense to me, if I query "what are the major themes of this dataset" on a list of articles, and the RAG tries to find content that's similar to that query, it probably won't find much.
Why does GraphRAG find something here? What's happening with my query that it suddenly "matches" the dataset?
- madacol 2y agofrom https://www.microsoft.com/en-us/research/blog/graphrag-new-tool-for-complex-data-discovery-now-on-github/ https://www.microsoft.com/en-us/research/blog/graphrag-new-t... > It does this by detecting “communities” of densely connected nodes in a hierarchical fashion, partitioning the graph at multiple levels from high-level themes to low-level topics, as illustrated in Figure 1. Using an LLM to summarize each of these communities creates a hierarchical summary of the data, providing an overview of a dataset without needing to know which questions to ask in advance. Each community serves as the basis of a community summary that describes its entities and their relationships.
- rooftopzen 2y agoHere's a write up the differences of GraphRAG - TLDR is it's expensive but can improve accuracy (possibly pertaining to LLM definition of the nodes), so if it's worth it to your app. https://medium.com/@jonathan.bennion/graphrag-analysis-part-1-how-indexing-elevates-knowledge-graph-performance-in-rag-1c15da59ae6a https://medium.com/@jonathan.bennion/graphrag-analysis-part-...