Papers with GNN-RAG

1 papers
GNN-RAG: Graph Neural Retrieval for Efficient Large Language Model Reasoning on Knowledge Graphs (2025.findings-acl)

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Challenge: Existing approaches to retrieval-augmented generation (RAG) rely on costly LLM calls to generate relation paths or traverse the KG.
Approach: They propose a framework that uses lightweight Graph Neural Networks to enhance retrieval.
Outcome: The proposed framework outperforms existing methods on multi-hop and multi-entity questions.

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