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 used to …

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.

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

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 …

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

May 27, 2025 · GraphRAG revolutionises domain-specific LLM applications by leveraging structured knowledge to organise and retrieve information, enhancing performance and reliability. It can be …

Jan 7, 2026 · GraphRAG is a retrieval-augmented generation technique that represents documents as knowledge graphs instead of vector embeddings.

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 contextually accurate …

GraphRAG represents a novel approach to Retrieval-Augmented Generation (RAG) by integrating knowledge graphs with large language models (LLMs). This system addresses the limitations of …

Jan 27, 2025 · The GraphRAG Toolkit is an open source Python library that you can use both to index your data into a graph and a vector store, and build question-answering solutions that then retrieve …