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CommunityKG-RAG: Leveraging Community Structures in Knowledge Graphs for Advanced Retrieval-Augmented Generation in Fact-Checking

A novel zero-shot framework integrating community structures with RAG systems to enhance fact-checking.

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CommunityKG-RAG: Leveraging Community Structures in Knowledge Graphs for Advanced Retrieval-Augmented Generation in Fact-Checking

By Rong-Ching Chang, Jiawei ZhangarXiv (Cornell University)
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This paper introduces CommunityKG-RAG, a framework that combines knowledge graphs and retrieval-augmented generation to improve fact-checking. It utilizes multi-hop community structures within KGs to enhance accuracy and relevance of information retrieval.

Experimental results show that CommunityKG-RAG outperforms traditional methods in fact-checking.

Abstract

This paper introduces CommunityKG-RAG, a framework that combines knowledge graphs and retrieval-augmented generation to improve fact-checking. It utilizes multi-hop community structures within KGs to enhance accuracy and relevance of information retrieval. Experimental results show that CommunityKG-RAG outperforms traditional methods in fact-checking.

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fact-checkingcommunity structuresknowledge graphsretrieval-augmented generationzero-shot frameworkKnowledge GraphsRetrieval & RAGLarge Language ModelsSemantic Interoperability
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