Graph Retrieval-Augmented Generation

Also known as GraphRAG

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Overview

Graph Retrieval-Augmented Generation studies how to use entities, relations, and document structure to help language models find and combine relevant evidence. Systems build knowledge graphs or hypergraphs from documents, then retrieve evidence through paths, graph traversal, community summaries, or hybrid graph-and-vector search; some use agents to plan and verify multi-step retrieval. The methods are tested on knowledge-graph and multi-hop question answering, long-document tasks, and specialized settings such as medicine, law, and engineering, where traceable evidence can improve factuality. A central tension is whether richer graph structure improves answers enough to justify its construction and retrieval costs: performance depends on graph quality and query type, and more retrieved context does not always yield better answers.

Latest papers

CardsList

232 papers19 papers in the last four weeks, down 21% on the four weeks before. 0.1% of all new papers.

  1. GraphRAGProv: GraphRAG Meets How-Provenance

    Oct 27, 2026Wadie El Amrani, Luis GalárragaGraph Retrieval-Augmented GenerationData Provenance

    Independent Toulouse, France · INRIA Rennes, France

  2. SpectRAG: Weighted Chunk Graphs for Token-Budgeted Context Selection in Multi-Hop Retrieval-Augmented Generation

    Oct 27, 2026Zafer Sahinoglu, Abdulazeez Mohammed, Buse Yaren Kazangirler +1Graph Retrieval-Augmented GenerationMulti-Hop QA

    Mitsubishi Electric US Cambridge, 5900-A Katella Avenue California 90630, USA · Mitsubishi Electric Innovation Center (MELIC) Cambridge, MA 02139, USA · Institute of Graduate Programs, Dept. of Computer Engineering, Karabuk University, Karabuk, 78050, Turkey

  3. RouteDRAG: Learning to Route and Control Agentic Execution for Multimodal Document RAG

    Oct 27, 2026Zekai Chen, Hao Zhu, Yu Liu +5Agentic RAGMultimodal RAG

    Beijing Institute of Technology, Beijing, China · Chinese Academy of Sciences, China · Zhejiang University, Hangzhou, China +3

  4. UniGFM-RAG: Unify Graph Foundation Models and Large Language Models for End-to-End Retrieval and Reasoning

    Oct 26, 2026Zicheng Zhao, Linhao Luo, Zongji Yu +4Graph Retrieval-Augmented GenerationLLM Reasoning with Graphs

    School of Automation and Intelligent Sensing, Shanghai Jiao Tong University, Shanghai 200240, China. · Department of Data Science and AI, Monash University, Melbourne, Australia. · Tencent Youtu Lab, Shanghai 200240, China. +2

  5. Schema-Free Text-to-SQL: Learning Enterprise Database Structure from Query Logs

    Oct 24, 2026Ömer Faruk Akgül, Nikhil Kapahi, Prajit Reddy MuppidiText-to-SQLGraph Retrieval-Augmented Generation

    University of Southern California · Amazon

  6. Towards a Learnable Retriever for Textual Graph Question Answering

    Oct 24, 2026Kaifeng Jin, Yuchen Yan, Zhichen Zeng +4Graph-Based RetrievalGraph Retrieval-Augmented Generation

    University of Illinois Urbana-Champaign · Wayne State University · Meta

  7. GEMS-RAG: Graph-grounded Engineering Multimodal Standards Retrieval-Augmented Generation

    Oct 23, 2026Abdul Hannan Azad, Irvin Wang, Jiwan Jiang +6Multimodal RAGRetrieval-Augmented Generation

    Texas A&M University, College Station, USA · A&M Consolidated High School College Station, USA · University of Wisconsin, Madison, USA

  8. ActionRAG: Evidence-Refining Graph Diffusion for Long-Term Memory in LLM Agents

    Oct 23, 2026Navyansh Mahla, Sashank VandrangiLLM Agent MemoryGraph-Based Agent Memory

    Actioneer, Mountain View, California, USA

  9. Federated Graph Retrieval-Augmented Generation

    Oct 22, 2026Xiaobao Wang, Renda Han, Zhiliang Xia +3Graph Retrieval-Augmented GenerationPrivacy-Preserving RAG

    College of Intelligence and Computing, Tianjin University, Tianjin, China · Henan University, Zhengzhou, China · National University of Defense Technology, Changsha, China

  10. Graph Topology Meets Energy-Driven Pathfinding: Preserving Contextual Consistency in Retrieval-Augmented Generation

    Oct 21, 2026Yufeng Li, Zaijing Li, Fuchen Zhang +3Graph Retrieval-Augmented GenerationRetrieval-Augmented Reasoning

    Central South University, Changsha, China · Harbin Institute of Technology, Shenzhen, China

  11. GraphRAG-LTM: A Layered Threat Modeling Framework for Attacks on Graph Retrieval-Augmented Generation

    Oct 14, 2026Yining Tang, Junyu Zhang, Haomiao Qiu +5Graph Retrieval-Augmented GenerationRAG Security

    Zhejiang University · Harbin Institute of Technology, Shenzhen · Great Bay University +1

  12. CultureBot: A Framework for Retrieval-Augmented Exploration of Cultural Heritage Data

    Oct 12, 2026Vasileios Karampinis, Angelos Vlachos, Giorgos Filandrianos +4Digital Cultural HeritageCultural Heritage

    School of Electrical and Computer Engineering, AILS Laboratory National Technical University of Athens

  13. SEEK: Agentic Knowledge Graph Retrieval for Secure Code Generation

    Oct 10, 2026Varun Gadey, Markus Tohn, Lichao Wu +2Secure Code GenerationRAG Security

    University of Duisburg-Essen, Germany · University of Bristol, UK · Technical University of Darmstadt, Germany

  14. Verifiable Retrieval for Legal Reasoning through Structure-driven Knowledge Graph

    Oct 9, 2026Ibrahim Siddig, Sviatoslav Tugeev, Munir GeorgesLegal IRGraph Retrieval-Augmented Generation

    Technische Hochschule Ingolstadt, Esplanade 10, 85049 Ingolstadt, Germany

  15. Chronos Enables Code Agents to Reason over Software Evolution

    Oct 8, 2026Xin Yin, Yiang Zhang, Zhiyuan Peng +3LLM Agent MemoryRepository-Level Code Generation

    Zhejiang University, China · National Industrial Information Security Development Research Center, China

  16. From Retrieval to Reconstruction: Constructing Evolvable Cognitive Memory for Long-Term Dialogue

    Oct 8, 2026Zirui Liao, Zhengxian Wu, Zhuohong Chen +4Long-Term Conversational MemoryAgentic RAG

    Tsinghua University Shenzhen International Graduate School, Shenzhen, China

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

    Oct 7, 2026Ruochi Li, Jianzhe Lin, Haoxuan Zhang +4Graph Retrieval-Augmented GenerationMultimodal RAG

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

  18. BEACON-SP: Ontology-Grounded GraphRAG Framework for Clinical Suicide Risk Assessment

    Oct 6, 2026Kemal Davaslioglu, Nathan Conger, Sastry Kompella +2Graph Retrieval-Augmented GenerationClinical Decision Support

    Nexcepta, Gaithersburg, MD, USA · United States Military Academy, West Point, NY, USA

  19. Trustworthy Domain-Specific AI for Structured Knowledge Retrieval and Reasoning

    Oct 6, 2026Ryan C. BarronInformation RetrievalGraph Retrieval-Augmented Generation

  20. Hop-Decayed Influence: New Vulnerabilities of Structural Auxiliary Indexing in GraphRAG Pipelines with LLM

    Oct 1, 2026Jisung Park, John Le, Heath CooperRAG Poisoning AttacksGraph Retrieval-Augmented Generation

    Institute of Cybersecurity and Cryptology, University of Wollongong

  21. Corpus-Guided Dual-Path Propagation for Graph Retrieval-Augmented Generation

    Sep 29, 2026Baoxian Liu, Tong WeiMulti-Hop QAGraph Retrieval-Augmented Generation

    College of Software Engineering, Southeast University, Nanjing 210096, China · Key Laboratory of Computer Network and Information Integration (Southeast University), Ministry of Education, China · School of Computer Science and Engineering, Southeast University, Nanjing 210096, China

  22. ConRAG: Lightweight inference of multi-hop relations

    Sep 28, 2026Kilian Bänziger, Sonia Laguna, Markus Kreft +4Graph Retrieval-Augmented GenerationRelational Reasoning

    Agentic Systems Lab ETH Zurich · Agentic Systems Lab, ETH Zurich Norwegian University of Science and Technology

  23. STITCH-RAG: Spatio-Temporal Influence Tracing over Topic Hypergraphs for Multi-Hop Retrieval-Augmented Generation

    Sep 28, 2026Haodong Yang, Mengzhu Chen, Jia CaiMulti-Hop QARetrieval-Augmented Generation

    School of Statistics And Data Science, Guangdong University of Finance & Economics Guangzhou, China

  24. HyperReCo: Retrieving and Connecting Evidence with Hypergraph Neural Networks for LLM Multi-hop Reasoning

    Sep 26, 2026Zicheng Zhao, Linhao Luo, Junnan Dong +4Graph Retrieval-Augmented GenerationMulti-Hop QA

    Shanghai Jiao Tong University · Singapore University of Technology and Design · Monash University +3

  25. LEGO: Synergizing Expert GraphRAG and Expert Chain-of-Thought for Legal Reasoning

    Sep 22, 2026Qingjing Chen, Junkai Zhang, Shaochun Wang +7LLM Reasoning with GraphsGraph Retrieval-Augmented Generation

    Alma AI, University of Bologna, Italy · Tsinghua University, China · Modelbest Inc. +2

  26. FeatLens: Feature-Guided Dynamic Code Graph Construction and Retrieval for Repository-Level Code Generation

    Sep 22, 2026Xutian Li, Bo Xiong, Yifeng Zhu +6Graph Retrieval-Augmented GenerationRepository-Level Code Generation

    Peking University

  27. LADDER: Graph-Guided Diffusion Language Models for Efficient Multi-Hop Reasoning

    Sep 21, 2026Senlei Zhang, Linhao Luo, Qian-Wen Zhang +4LLM Reasoning with GraphsGraph Retrieval-Augmented Generation

    Huazhong University of Science and Technology · Monash University · Tencent Youtu Lab

  28. Knowledge-Graph Based Augmentation versus Retrieval Augmented Generation for Cultural-Related Question Answering

    Sep 16, 2026Pablo Poulenard, Yannis Karmim, Valentin BarrièreRetrieval-Augmented GenerationGraph Retrieval-Augmented Generation

    DCC, Universidad de Chile, Santiago, Chile · École Polytechnique, Palaiseau, France · Inria, Almanach, Paris, France +2

  29. WFM: Wiki Foundation Model for Complex Agentic Reasoning

    Sep 16, 2026Junnan Dong, Linhao Luo, Senlei Zhang +9Graph Representation LearningGraph Retrieval-Augmented Generation

    Tencent Youtu Lab · Monash University · Hong Kong Baptist University +1

  30. When Is Graph Structure Worth Its Cost? The Case for Structure Pricing in Retrieval-Augmented Generation

    Sep 16, 2026Yuzhong Zhang, Haoyang Ma, Chao Peng +3Retrieval-Augmented GenerationGraph Retrieval-Augmented Generation

    The Chinese University of Hong Kong, Shenzhen · The Hong Kong University of Science and Technology · University of Edinburgh +1