OriginRAG: Harnessing GraphRAG by Tracing Evidence Origins

GraphRAG gathers supporting evidence for multi-hop questions from corpus graphs. However, prior methods do not explicitly expose where retrieved evidence originates and how retrieval decisions connect to source grounding. We propose OriginRAG, a novel framework that harnesses GraphRAG by maintaining a set of demand-specific provenance lineages as its retrieval state. It derives evidence demands from the query and initializes one provenance lineage per demand. Each lineage is expanded by demand-conditioned graph retrieval, so every candidate preserves its origin: the demand that triggered its retrieval. Such origin tracing helps an agent choose complementary passages while completing a lineage. Once a demand is satisfied, it is grounded in a verbatim span from the selected evidence. On representative multi-hop QA benchmarks, OriginRAG surpasses leading GraphRAG baselines in R@5, EM, and F1, with an average improvement of 4.90 points.