Awesome-GraphRAG and RAG-Reading-List
About Awesome-GraphRAG
DEEP-PolyU/Awesome-GraphRAG
Awesome-GraphRAG: A curated list of resources (surveys, papers, benchmarks, and opensource projects) on graph-based retrieval-augmented generation.
This project compiles a comprehensive list of research and open-source tools related to Graph-based Retrieval-Augmented Generation (GraphRAG). It helps researchers, PhD students, and AI practitioners explore advanced methods for building more accurate and context-aware customized Large Language Models (LLMs). The project categorizes and explains various techniques for organizing knowledge, retrieving information, and integrating it with LLMs, moving beyond traditional text-chunking approaches.
About RAG-Reading-List
RUC-NLPIR/RAG-Reading-List
RAG methods, benchmarks, and toolkits
This reading list helps AI practitioners and researchers stay current with the rapidly evolving field of Retrieval-Augmented Generation (RAG). It provides a curated collection of recent academic papers and toolkits, categorized by method, benchmarks, and analysis for both text-only and multimodal applications. The list helps you understand the latest advancements, identify effective techniques, and discover resources to implement RAG in your projects.
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