Why Neighborhoods Matter: Traversal Context and Provenance in Agentic GraphRAG

ArXi:2605.15109v1 Announce Type: new Retrieval-Augmented Generation can improve factuality by grounding answers in external evidence, but Agentic GraphRAG complicates what it means for citations to be faithful. In these systems, an agent explores a knowledge graph before producing an answer and a small set of citations. We frame citation faithfulness as a trajectory-level problem: final citations should not only the answer, but also account for the graph traversal, structure, and visited-but-uncited entities that may influence it.