Multi-Hop Reasoning Enhancement in Retrieval-Augmented Generation using Hierarchical Graph Neural Networks
Keywords:
multi-hop reasoning, Retrieval-Augmented Generation, Hierarchical Graph Neural Networks, document retrieval, generative AIAbstract
Retrieval-Augmented Generation (RAG) systems are enhanced by transformative Hierarchical Graph Neural Networks (HGNNs) which helps in facilitating advanced multi-hop reasoning across multiple knowledge sources. The objective of this study is to introduce an HGNN-integrated RAG framework that helps in modelling the retrieved documents systematically as hierarchical graph structures which enables more precise traversal of interconnected semantic relationships.
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