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 …

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.

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

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.

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 …

Deep dive into advanced RAG variants: LongRAG for long contexts, Self-RAG with self-reflection, and GraphRAG using knowledge graphs. Compare architectures, use cases, and …

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

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

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