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

cs.AI, cs.CL

Submitted: 2026-10-07

Updated: 2026-10-07

Comments: Accepted at the 40th Conference on Neural Information Processing Systems (NeurIPS 2026)

Project page: https://richardlrc.github.io/TopoGraphRAG-Bench

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

Sources

• Benchmarking Retrieval-Augmented Multimodal Generation for Document Question Answering
• From Local to Global: A Graph RAG Approach to Query-Focused Summarization
• RAG-Anything: All-in-One RAG Framework
• MegaRAG: Multimodal Knowledge Graph-Based Retrieval Augmented Generation
• ViDoRe V3: A Comprehensive Evaluation of Retrieval Augmented Generation in Complex Real-World Scenarios
• DocHop-QA: Towards Multi-Hop Reasoning over Multimodal Document Collections
• UNIDOC-BENCH: A Unified Benchmark for Document-Centric Multimodal RAG
• BRIDGE: Benchmark for multi-hop Reasoning In long multimodal Documents with Grounded Evidence
• When to use Graphs in RAG: A Comprehensive Analysis for Graph Retrieval-Augmented Generation
• Benchmarking Multimodal RAG through a Chart-based Document Question-Answering Generation Framework
• In-depth Analysis of Graph-based RAG in a Unified Framework

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