Defensible Narrow Conclusion: Graph Diffusion Helps on Curated Template-Based Prerequisite QA Only Under Aligned, Controlled First-Stage Retrieval
The paper's defensible conclusion is narrow: graph-based diffusion helps on curated, template-based prerequisite QA when the first-stage retrieval interface is well aligned and carefully controlled, but graph-specific deltas are easy to overstate without (i) strict parity, (ii) stronger split audits, (iii) separate token-cap diagnostics, (iv) external-validity boundary checks, and (v) traceable artifacts. The conclusion deliberately scopes positive graph-RAG claims to the curated prerequisite setting and ties their credibility to the simultaneous presence of all five methodological safeguards.
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Auditable Strict-Parity Evaluation of Prerequisite-Graph Retrieval for RAG under Leakage Controls