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RAGMedium· GNN· Inference & Serving· Graph RAG
Why train a graph neural network for knowledge-graph re...
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See plansThe primary motivation for using a GNN is to split the process into two phases: graph learning offline, and scoring/path extraction at inference. This trades a one-time training cost for a reduction in per-query, per-hop LLM costs. While GNN-RAG is often less precise than the symbolic, LLM-driven route, the primary goal is to improve throughput and reduce latency.