Boosting Q&A Accuracy with GraphRAG Using PyG and Graph Databases – NVIDIA Technical Blog News and tutorials for developers, data scientists, and IT admins 2025-04-09T16:18:06Z http://www.open-lab.net/blog/feed/ Brian Shi <![CDATA[Boosting Q&A Accuracy with GraphRAG Using PyG and Graph Databases]]> http://www.open-lab.net/blog/?p=97900 2025-04-03T18:46:06Z 2025-03-26T21:41:08Z Large language models (LLMs) often struggle with accuracy when handling domain-specific questions, especially those requiring multi-hop reasoning or access to...]]> Large language models (LLMs) often struggle with accuracy when handling domain-specific questions, especially those requiring multi-hop reasoning or access to...Decorative image.

Large language models (LLMs) often struggle with accuracy when handling domain-specific questions, especially those requiring multi-hop reasoning or access to proprietary data. While retrieval-augmented generation (RAG) can help, traditional vector search methods often fall short. In this tutorial, we show you how to implement GraphRAG in combination with fine-tuned GNN+LLM models to achieve��

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