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TagRAG: Tag-guided Hierarchical Knowledge Graph Retrieval-Augmented Generation

A framework for efficient global reasoning and scalable graph maintenance in knowledge graphs.

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TagRAG: Tag-guided Hierarchical Knowledge Graph Retrieval-Augmented Generation

By Wenbiao Tao, Xinyuan Li, Yunshi Lan, Weining QianarXiv (Cornell University)
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The authors propose a tag-guided hierarchical knowledge graph retrieval-augmented generation (RAG) framework, called TagRAG. It introduces two key components: Tag Knowledge Graph Construction and Tag-Guided Retrieval-Augmented Generation.

This design aims to improve efficiency and adaptability in global reasoning and graph maintenance.

Abstract

The authors propose a tag-guided hierarchical knowledge graph retrieval-augmented generation (RAG) framework, called TagRAG. It introduces two key components: Tag Knowledge Graph Construction and Tag-Guided Retrieval-Augmented Generation. This design aims to improve efficiency and adaptability in global reasoning and graph maintenance.

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tag-guided hierarchical knowledge graphretrieval-augmented generationefficient global reasoningscalable graph maintenanceKnowledge GraphsRetrieval & RAGLarge Language ModelsSemantic Interoperability
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