arXiv CS
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FuseRAG: Fusing Structure and Evidence into Inference for Cost-Efficient Graph-based RAG
Graph-based retrieval-augmented generation (RAG) exploits relationships among evidence to support multi-hop question answering. However, conveying retrieved graphs through non-unique linear textual contexts to Large Language Models (LLMs) leads to graph-structure degradation and inefficient KV-cache
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