GNN-RAG: Graph Neural Networks for Retrieval-Augmented Generation

GNN-RAG proposes using Graph Neural Networks as a reasoning layer between the knowledge graph and the LLM. The GNN processes local subgraphs around query-relevant entities, performing multi-hop reasoning to identify relevant paths and nodes. Combines structural reasoning of GNNs with language understanding of LLMs.