HVM-GraphRAG: Holistic-View Multimodal Graph Retrieval-Augmented Generation on Complex Document

• URL: http://arxiv.org/abs/2607.24861v1
• Date: Sun, 26 Jul 2026 12:47:25 GMT
• Title: HVM-GraphRAG: Holistic-View Multimodal Graph Retrieval-Augmented Generation on Complex Document
• Abstract summary: Multimodal GraphRAG provides a promising direction by organizing document evidence with graph structures.<n>HVM-GraphRAG uses a holistic view to guide graph construction, thereby reducing noisy and conflicting graph updates.<n> Experiments on three datasets show that HVM-GraphRAG achieves the best answer performance in most evaluated settings.
• Score: 36.46869470798395
• License: http://creativecommons.org/licenses/by/4.0/
• Abstract: Question answering (QA) over complex documents requires models to retrieve and integrate evidence distributed across distant document regions and modalities. Multimodal GraphRAG provides a promising direction by organizing document evidence with graph structures. However, existing methods often suffer from unreliable cross-modal evidence indexing and expensive graph traversal. To address these issues, we propose HVM-GraphRAG, a holistic-view multimodal GraphRAG framework on complex document. HVM-GraphRAG uses a holistic view to guide graph construction, thereby reducing noisy and conflicting graph updates and building reliable indices between concept-level graph nodes and supporting multimodal chunks. During retrieval, HVM-GraphRAG searches over a compact concept-level graph and directly accesses supporting evidence through the constructed index, avoiding costly traversal over dense entity-level graphs. After obtaining the retrieved evidence, HVM-GraphRAG further reorganizes chunks into modality-specific groups, enabling the answering model to better integrate heterogeneous evidence. Experiments on three datasets show that HVM-GraphRAG achieves the best answer performance in most evaluated settings while substantially improving online retrieval efficiency over representative graph-based baselines.

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