AI RESEARCH
Core-based Hierarchies for Efficient GraphRAG
arXiv CS.CL
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ArXi:2603.05207v2 Announce Type: replace-cross Retrieval-Augmented Generation (RAG) enhances large language models by incorporating external knowledge. However, existing vector-based methods often fail on global sensemaking tasks that require reasoning across many documents. GraphRAG addresses this by organizing documents into a knowledge graph with hierarchical communities that can be recursively summarized.