arXiv Computation and Language October 8, 2026 By Ruochi Li, Jianzhe Lin, Haoxuan Zhang, Haihua Chen, Junhua Ding, Edward Gehringer, Yang Zhang

TopoGraphRAG-Bench: Evaluating Multimodal GraphRAG on Layout-Grounded Evidence Reasoning

Read the original on arXiv Computation and Language →

The paper introduces TOPOGRAPHRAG-BENCH, a benchmark for evaluating multimodal Graph Retrieval-Augmented Generation (GraphRAG) systems on layout‑grounded evidence reasoning. It contains 2,024 questions derived from 201 long, visually rich documents, designed around three controlled topologies—single‑hop retrieval, bridge‑chain reasoning, and multi‑source synthesis—while employing counterfactual validation to ensure question integrity. Experiments show that multimodal GraphRAG outperforms text‑only and page‑level visual retrieval models, yet still struggles with incomplete visual‑textual alignment and multi‑unit composition, highlighting the need for GraphRAG systems that explicitly model document layouts and cross‑modal evidence alignment.

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