DocNavRAG: Document-Structured Graph RAG with Stateful Evidence Construction for Complex Document Question Answering

• URL: http://arxiv.org/abs/2608.01565v1
• Date: Mon, 03 Aug 2026 00:48:05 GMT
• Title: DocNavRAG: Document-Structured Graph RAG with Stateful Evidence Construction for Complex Document Question Answering
• Abstract summary: We introduce DocNavRAG, which organizes document hierarchies and cross-region relations into a navigable graph.<n>Across four long- and multi-document QA benchmarks, DocNavRAG improves answer quality and context sufficiency over the strongest baseline by 7.8% and 17.7% on average.
• Score: 22.38959921864722
• License: http://arxiv.org/licenses/nonexclusive-distrib/1.0/
• Abstract: Answering complex questions over large document collections requires assembling complementary evidence across sections and documents. GraphRAG offers structured retrieval but typically uses fixed traversal, while agentic RAG operates over weakly structured interfaces. Our key insight is that agents should navigate document structure within and across documents rather than repeatedly search from scratch. We introduce DocNavRAG, which organizes document hierarchies and cross-region relations into a navigable graph, exposes graph operations for locating, navigating, expanding, and fetching, and maintains an evolving evidence state to guide retrieval until sufficient evidence is collected. Across four long- and multi-document QA benchmarks, DocNavRAG improves answer quality and context sufficiency over the strongest baseline by 7.8\% and 17.7\% on average.

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