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  1. Welcome - GraphRAG

    Microsoft Research’s new approach, GraphRAG, creates a knowledge graph based on an input corpus. This graph, along with community summaries and graph machine learning outputs, are …

  2. GraphRAG with a Knowledge Graph

    Jul 11, 2025 · Design patterns for improving GenAI applications with a graph.

  3. GraphRAG - GitHub

    The GraphRAG project is a data pipeline and transformation suite that is designed to extract meaningful, structured data from unstructured text using the power of LLMs.

  4. Project GraphRAG - Microsoft Research

    Feb 13, 2024 · GraphRAG (Graphs + Retrieval Augmented Generation) is a technique for richly understanding text datasets by combining text extraction, network analysis, and LLM …

  5. Retrieval-Augmented Generation with Graphs (GraphRAG)

    Dec 31, 2024 · Following this motivation, we present a comprehensive and up-to-date survey on GraphRAG. Our survey first proposes a holistic GraphRAG framework by defining its key …

  6. GraphRAG: Insights, Benchmarks & Guides for Devs

    What is GraphRAG? GraphRAG represents a novel approach to Retrieval-Augmented Generation (RAG) by integrating knowledge graphs with large language models (LLMs).

  7. What is GraphRAG? - IBM

    GraphRAG is an advanced version of retrieval-augmented generation (RAG) that incorporates graph-structured data, such as knowledge graphs (KGs).

  8. What is GraphRAG? - GeeksforGeeks

    Jul 23, 2025 · GraphRAG stands apart from traditional RAG models by applying structured knowledge graph data for both retrieval and generation tasks. The system produces more …

  9. Intro to GraphRAG

    For us, it’s a set of RAG patterns that leverage a graph structure for retrieval. Each pattern demands a unique data structure, or graph pattern, to function effectively. On this site, we’ll …

  10. The Future of AI: GraphRAG – A better way to query interlinked ...

    Nov 13, 2024 · GraphRAG is a technique that combines the power of knowledge graphs and large language models (LLMs) to improve the accuracy and relevance of responses to user queries.