Multimodal RAG

RAG: Retrieval-Augmented Generation

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10 papers in the last four weeks, against 2 the four weeks before. 0.1% of all new papers.

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TopoGraphRAG-Bench: Evaluating Multimodal GraphRAG on Layout-Grounded Evidence Reasoning
Oct 7, 2026Ruochi Li, Jianzhe Lin, Haoxuan Zhang +4Graph Retrieval-Augmented Generation Multimodal RAG
Department of Computer Science, North Carolina State University, USA · Independent Researcher · Department of Information Science, University of North Texas, USA +2
EC-RAG: Event Chain Retrieval-Augmented Generation for Long Video Understanding
Oct 6, 2026Yuhao Qin, Junbo Wang, Yuke Li +1Multimodal RAG Video-Language Models
Northwestern Polytechnical University Xi’an, China
Walking the Embedding Space: Datastore Extraction from Multimodal RAG
Oct 1, 2026Maria Carmen Jica, Ali Satvaty, Suzan Verberne +1Multimodal RAG Adversarial Attacks on VLMs
University of Groningen Groningen, The Netherlands
Faithful Chart Generation for Multimodal Deep Research: Frame-Evidence Co-Adaptation
Sep 30, 2026Yuxin Yue, Yingchen Zhang, Ruqing Zhang +3Multimodal RAG Data Visualization
State Key Laboratory of AI Safety Institute of Computing Technology, Chinese Academy of Sciences University of Chinese Academy of Sciences Beijing, China · University of Amsterdam Amsterdam, The Netherlands
TAEC: Trajectory-Aware Evidence Coordination for Multi-Step Visual RAG
Sep 29, 2026Yalun Wu, Bingzhou Wang, Boyang Wang +5Multimodal RAG Visual Question Answering
NExT++ Lab, National University of Singapore
UniK: Universal Knowledge Perception for Digital and Physical AI
Sep 21, 2026Nirmit Desai, Kunal Sawarkar, Aditya Mahakali +3Multimodal RAG Multimodal IR
AIntropy AI
PRISM-RAG: Multimodal Hypergraph Retrieval-Augmented Generation for Tobacco Product and Legislative Policy Reasoning
Sep 20, 2026Manuel Serna-Aguilera, Raegan Anderes, Page Dobbs +1Multimodal RAG Legal IR
Fay W. Boozman College of Public Health, University of Arkansas for Medical Sciences, Little Rock, Arkansas, 72205
Scientific Image Quality Assessment via Multi-modal Retrieval-Augmented Generation
Sep 17, 2026Yinuo Zhang, Bingshuo Liu, Zhiying Tu +6Multimodal RAG Image Quality Assessment
Harbin Institute of Technology · Tencent · Nanyang Technological University
Less Is More: Graph-free Multimodal RAG via Multi-signal Late Fusion
Sep 16, 2026Tithi Rakshit, Hongkuan Zhou, Lavdim Halilaj +1Multimodal RAG Multimodal IR
University of Tübingen, Tübingen, Germany · Corporate Research, Robert Bosch GmbH, Renningen, Germany · University of Stuttgart, Stuttgart, Germany
Navigating Sparse Evidence: Agentic Visual RAG via Explicit Context Selection and Consolidation
Sep 14, 2026Yucheng Shen, Lingyong Yan, Jiulong Wu +4Multimodal RAG Agentic RAG
School of Computer Science and Technology, Soochow University · Baidu Inc.
Beyond the Query: Do Retrieval Signals Improve Adaptive Multimodal RAG Routing?
Sep 14, 2026Qiaomu Li, Qiuyuan Zhang, Nong MingMultimodal RAG Adaptive Model Routing
College of Computing and Software Engineering Kennesaw State University Marietta, GA 30060, USA
Bridging the Semantic-Utility Gap in Multimodal RAG via Generator-in-the-Loop Alignment
Sep 8, 2026Zhan-Lun Chang, Dong-Jun Han, Seyyedali Hosseinalipour +2Multimodal RAG Multimodal Reranking
Elmore Family School of Electrical and Computer Engineering, Purdue University, West Lafayette, IN 47907, USA · Department of Computer Science and Engineering, Yonsei University, Seoul 03722, Republic of Korea · Department of Electrical Engineering, University at Buffalo–SUNY, Buffalo, NY 14260, USA
EM^2Mem: Event-Centric Multimodal Memory for Large Language Models
Sep 1, 2026Yijun Chen, Yaqi Zheng, Yanya Li +11Multimodal RAG Efficient Multimodal Inference
Zhejiang University · South China University of Technology · Lenovo Group Limited
Doc-REFRAG: Rethinking Multimodal Document Retrieval-Augmented Generation
Aug 31, 2026Ruofan Hu, Shengyang Xu, Minjie Hong +5Multimodal RAG Efficient Multimodal Inference
Zhejiang University
Does More Retrieved Evidence Help Visual Retrieval-Augmented Generation with Diffusion Language Models?
Aug 7, 2026Jiankun Wang, Yisen Gao, Ziwei Zhang +3Multimodal RAG Visual Question Answering
School of Computer Science and Engineering, Beihang University · Department of Computer Science and Engineering, The Hong Kong University of Science and Technology · School of Computer Science and Engineering, Guangxi Normal University +2
RAGOCR: Optical Compression of Retrieval-Augmented Text via Visual Representation
Aug 1, 2026Jiayang Yu, Jialun Zhong, Lei ZouMultimodal RAG Retrieval-Augmented Generation
Wangxuan Institute of Computer Technology, Peking University Beijing, China
DualG-MRAG: Decoupling Macro-Reasoning and Micro-Matching for Multimodal Retrieval-Augmented Generation
Jul 30, 2026Jiacheng Tao, Qingyun Sun, Haonan Yuan +2Multimodal RAG Graph Retrieval-Augmented Generation
SKLCCSE, School of Computer Science and Engineering Beihang University Beijing, China
Salient Knowledge Pathways: Sparse Cross-Modal Routing for Efficient Knowledge-Intensive Multimodal Question Answering
Jul 28, 2026Noor Islam S. Mohammad, Uluğ BayazıtMultimodal RAG Efficient Multimodal Inference
Department of Computer Science, İTÜ, İstanbul, Türkiye · Faculty of Computer Engineering, İTÜ, İstanbul, Türkiye.
DeCoRAG: Cognitive Decoupling and Semantic-Aware Cropping for Complex Document Understanding
Jul 27, 2026Shuo Wang, Kai Zhang, Wenyuan Huang +5Document Understanding Multimodal RAG
QiYuanLab, Beijing, China · Beijing University of Posts and Telecommunications, Beijing, China
HVM-GraphRAG: Holistic-View Multimodal Graph Retrieval-Augmented Generation on Complex Document
Jul 26, 2026Xin He, Yili Wang, Wenqi Fan +4Multimodal RAG Retrieval-Augmented Generation
Jilin University Changchun, China · The Hong Kong Polytechnic University Hong Kong SAR, China
CRAG-MM-Diagnostics: Enabling Stage-Wise Analysis of Knowledge-Intensive VQA
Jul 23, 2026Hanseok Oh, Parishad BehnamGhader, Benno Krojer +4VLM Evaluation Multimodal RAG
New York University, New York NY, USA · Mila - Quebec AI Institute, Montreal, Canada · McGill University, Montreal, Canada +3
VizRAG: Enhancing Retrieval-Augmented Generation with Hypergraph Visualization
Jul 22, 2026Yanbin Wei, Yang Chen, Renling Gan +7Multimodal RAG Retrieval-Augmented Generation
1Southern University of Science and Technology · 2Hong Kong University of Science and Technology · 3Huawei Research +1
TAP-RAG: Task-Aware Policy Control for Long-Document Multimodal Question Answering
Jul 21, 2026Zhong Ji, Keqi Jin, Yan Zhang +1Multimodal RAG Retrieval-Augmented Generation
School of Electrical and Information Engineering, Tianjin University · The International Joint Institute of Tianjin University, Fuzhou, Tianjin University · Department of Automation, Tsinghua University
MonteRET: AI Agent Enhancing Multimodal LLMs with Multi-granularity Knowledge Retrieval for Chest CT Report Generation
Jul 15, 2026Yi Lin, Yihao Ding, Elana Benishay +8Radiology Report Generation Multimodal RAG
Department of Population Health Sciences, Weill Cornell Medicine, New York, USA · School of Physics, Mathematics and Computing, University of Western Australia, Crawley, Australia · Department of Radiology, Weill Cornell Medicine, New York, USA +4
EvoGraph-R1: Self-Evolving Multimodal Knowledge Hypergraphs for Agentic Retrieval
Jul 14, 2026Jiashi Lin, Changhong Jiang, Xiangru Lin +12Multimodal RAG Graph Retrieval-Augmented Generation
1Northwestern Polytechnical University · 3The University of Hong Kong · 5The Chinese University of Hong Kong (Shenzhen) +2
Trust Before Fusion: QIMG-7 and Source-Aware Resolution for Polluted Multimodal RAG
Jul 12, 2026Saadeldine Eletter, Owais Aijaz, Preslav NakovMultimodal RAG Retrieval-Augmented Generation
Mohamed bin Zayed University of Artificial Intelligence
MMAgent-R $^2$ : Learning to Rerank and Reject for Agentic mRAG
Jul 8, 2026Tao Zhang, Ziqi Zhang, Zongyang Ma +7Multimodal RAG Adaptive Retrieval
State Key Laboratory of Multimodal Artificial Intelligence Systems, CASIA · School of Artificial Intelligence, University of Chinese Academy of Sciences · Beijing Key Laboratory of Super Intelligent Security of Multi-Modal Information +3
VaseMuseum: Digital Intelligent Museum for Ancient Greek Pottery
Jul 7, 2026Jiazi Wang, Nonghai Zhang, Qiushi Xie +5Multimodal RAG Cultural Heritage
School of Computer Science and Technology, Beijing Jiaotong University, Beijing 100044, China · School of Computer Science, Peking University, Beijing 100871, China · Department of Computer Science and Information Technology, La Trobe University, Melbourne VIC 3000, Australia +1
Hierarchical Evidence-Driven Reasoning for Long Document Understanding
Jul 6, 2026Junyu Xiong, Yonghui Wang, Rongjian Gu +4Multi-Hop QA Document Understanding
University of Science and Technology of China · iFLYTEK Research
Modality Relevance is not Modality Utility: Post-hoc Selective Modality Escalation for Cost-Aware Multimodal RAG
Jul 3, 2026Xue Li, Yiming GaiMultimodal RAG Efficient Multimodal Inference
Hangzhou International Innovation Institute, Beihang University Hangzhou, China

Oct 7, 2026, cs.AIJ/K move · Enter open · S save

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

Ruochi Li, Jianzhe Lin, Haoxuan Zhang, Haihua Chen+3

Department of Computer Science, North Carolina State University, USA · Independent Researcher · Department of Information Science, University of North Texas, USA+2

Graph Retrieval-Augmented Generation Multimodal RAG RAG Evaluation

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Real-world documents distribute evidence across text, tables, figures, and captions within complex page layouts. Answering complex questions over such documents therefore requires more than retrieving relevant passages: systems must recover the evidence topology that connects heterogeneous evidence units. Existing GraphRAG evaluations remain largely text-centered, while multimodal document RAG benchmarks assess cross-modal retrieval and generation without directly evaluating recovery of the intended evidence topology. We introduce TOPOGRAPHRAG-BENCH, a layout-grounded benchmark for multimodal evidence reasoning in GraphRAG, comprising 2,024 questions over 201 long, visually rich documents. Questions are constructed bottom-up from text, figure, and table evidence units under three controlled topologies: single-hop retrieval, bridge-chain reasoning, and multi-source synthesis. To ensure that questions preserve their intended structure, we apply counterfactual validation for shortcut resistance, modality necessity, and evidence necessity. We evaluate text-only GraphRAG, page-level visual retrieval, and multimodal GraphRAG systems using retrieval, generation, and topology-aware reasoning metrics. Multimodal GraphRAG systems achieve the strongest overall performance, but still fail when visual-textual evidence alignment or multi-unit composition is incomplete. Text-only GraphRAG struggles when key dependencies are grounded in figures or tables, while page-level visual retrieval lacks the fine-grained structure needed for topology recovery. These findings motivate GraphRAG systems that move beyond text-derived entity relation graphs to explicitly model document layouts, cross-modal evidence alignment, and the reasoning roles of evidence units. Code and data are available at https://richardlrc.github.io/TopoGraphRAG-Bench/.

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