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

arXiv:2608.01565 · cs.CL · Submitted 2026-08-03 · Read on arXiv

Dongyang Xie, Yao Tian, Hao Zhang, Yifei Yuan, Tieyun Qian, Ming Zhong, Jiawei Jiang, Yuanyuan Zhu

School of Computer Science, Wuhan University · The Hong Kong University of Science and Technology · The Chinese University of Hong Kong · ETH Zurich · School of Computer Science, Wuhan University · School of Computer Science, Wuhan University · School of Computer Science, Wuhan University · School of Computer Science, Wuhan University

cs.CL

Submitted: 2026-08-03

Comments: 19 pages, 5 figures, 16 tables

License: http://arxiv.org/licenses/nonexclusive-distrib/1.0/

Terminology

• RAG — 45× in this paper · explained in 3 episodes
• Benchmark — 29× in this paper · explained in 2 episodes
• Semantic Similarity — 13× in this paper · explained in 2 episodes
• Ablation — 12× in this paper · explained in 1 episode
• Sufficiency — 8× in this paper · explained in 2 episodes
• Accuracy — 7× in this paper · explained in 1 episode
• Embeddings — 7× in this paper · explained in 2 episodes
• Grounding — 7× in this paper · explained in 3 episodes
• Papers — 7× in this paper · explained in 3 episodes
• Graph Construction — 6× in this paper · explained in 3 episodes
• Evidence Fetch — 5× in this paper
• Faithfulness — 5× in this paper · explained in 2 episodes
• State Control — 5× in this paper
• Knowledge Graph — 4× in this paper · explained in 8 episodes
• Generator — 3× in this paper · explained in 2 episodes
• Hypergraph — 3× in this paper · explained in 2 episodes
• Lateral Navigation — 3× in this paper
• Structural Navigation — 3× in this paper
• Verification — 3× in this paper · explained in 2 episodes
• Abstraction — 2× in this paper · explained in 1 episode
• Agentic Framework — 2× in this paper · explained in 7 episodes
• Generalization — 2× in this paper · explained in 14 episodes
• Knowledge graphs — 2× in this paper · explained in 2 episodes
• Localization — 2× in this paper · explained in 2 episodes
• Retrieval-Augmented Generation (RAG) — 2× in this paper · explained in 21 episodes
• Transformer — 2× in this paper · explained in 2 episodes
• Transformers — 2× in this paper · explained in 2 episodes
• Adaptive Reasoning — 1× in this paper · explained in 2 episodes
• Agentic System — 1× in this paper · explained in 2 episodes
• Consistency — 1× in this paper · explained in 3 episodes
• Existing Retrieval-Augmented Generation — 1× in this paper
• Foundation Model — 1× in this paper · explained in 3 episodes
• Foundation Models — 1× in this paper · explained in 8 episodes
• Hallucination — 1× in this paper · explained in 4 episodes
• Iterative Refinement — 1× in this paper · explained in 5 episodes
• Language Models (LLMs) — 1× in this paper · explained in 2 episodes
• Large Language Models (LLMs) — 1× in this paper · explained in 9 episodes
• Pruning — 1× in this paper · explained in 4 episodes
• Robustness — 1× in this paper · explained in 6 episodes
• Semantic Correctness — 1× in this paper · explained in 2 episodes
• Structural Reasoning — 1× in this paper · explained in 2 episodes
• Training-Free Framework — 1× in this paper · explained in 2 episodes

Sources

• A-RAG: Scaling Agentic Retrieval-Augmented Generation via Hierarchical Retrieval Interfaces
• From Local to Global: A Graph RAG Approach to Query-Focused Summarization
• Ragas: Automated Evaluation of Retrieval Augmented Generation
• Hyper-RAG: Combating LLM Hallucinations using Hypergraph-Driven Retrieval-Augmented Generation
• Retrieval-Augmented Generation for Large Language Models: A Survey
• OpenScholar: Synthesizing Scientific Literature with Retrieval-augmented LMs
• LightRAG: Simple and Fast Retrieval-Augmented Generation
• HippoRAG: Neurobiologically Inspired Long-Term Memory for Large Language Models
• Graph Retrieval-Augmented Generation: A Survey
• Retrieval-Augmented Generation for Knowledge-Intensive NLP Tasks
• M3SciQA: A Multi-Modal Multi-Document Scientific QA Benchmark for Evaluating Foundation Models
• Plan*RAG: Efficient Test-Time Planning for Retrieval Augmented Generation
• HyperGraphRAG: Retrieval-Augmented Generation via Hypergraph-Structured Knowledge Representation
• Cross-Granularity Hypergraph Retrieval-Augmented Generation for Multi-hop Question Answering
• When to use Graphs in RAG: A Comprehensive Analysis for Graph Retrieval-Augmented Generation
• NodeRAG: Structuring Graph-based RAG with Heterogeneous Nodes
• LinearRAG: Linear Graph Retrieval Augmented Generation on Large-scale Corpora

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