Graph-Based Retrieval

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16 papers in the last four weeks, up 78% on the four weeks before. 0.2% of all new papers.

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MemGraphRAG: Memory-based Multi-Agent System for Graph Retrieval-Augmented Generation
May 30, 2026Chuanjie Wu, Zhishang Xiang, Yunbo Tang +3KG Construction Multi-Agent LLM Systems
Xiamen University1, 2 · Xiamen University2, 3 · Xiamen University1 +2
MoG: Mixture of Experts for Graph-based Retrieval-Augmented Generation
May 29, 2026Zheng Yuan, Chuang Zhou, Linhao Luo +4Retrieval-Augmented Generation Graph Retrieval-Augmented Generation
The Hong Kong Polytechnic University · Monash University · Tencent Youtu Lab
GRASP: Plan-Guided Graph Retrieval with Adaptive Fusion and Reranking on Semi-Structured Knowledge Bases
May 28, 2026Yicheng Tao, Yiqun Wang, Xiangchen Song +3Learning to Rank Graph-Based Retrieval
Department of Electrical Engineering and Computer Science, University of Michigan · Department of Computational Medicine and Bioinformatics, University of Michigan
DiagramRAG: A Lightweight Framework to Retrieve Scientific Diagram for Figure Generation
May 27, 2026Xinjiang Yu, Junyi Han, Zhuofan Chen +7Retrieval-Augmented Generation Graph-Based Retrieval
Beijing Institute of Technology
AstroRAG -- A Pagerank-Based Retrieval-Augmented Generation Pipeline for Question Answering in Astronomy
May 24, 2026Zhifeng Wang, Jason Jingshi Li, Kaihao Zhang +1Retrieval-Augmented Generation Scientific QA
Australian National University, Canberra, ACT, Australia · Learning Machines Pty Ltd, Canberra, ACT, Australia
SeedER: Seed-Expand-Retrieve for Efficient Knowledge Graph Retrieval
May 22, 2026Hamed Shirzad, Frederik Wenkel, Dominique Beaini +2Graph-Based Retrieval Knowledge Graph Question Answering
Valence Labs, Montréal, QC, Canada · Recursion, Salt Lake City, UT, USA · University of British Columbia, Department of Computer Science, Vancouver, BC, Canada
SciAtlas: A Large-Scale Knowledge Graph for Automated Scientific Research
May 20, 2026Shuofei Qiao, Yunxiang Wei, Jiazheng Fan +8KG Construction AI-Assisted Scientific Research
Zhejiang University · University College London
ContextRAG: Extraction-Free Hierarchical Graph Construction for Retrieval-Augmented Generation
May 19, 2026Roman Prosvirnin, Sergei Kuznetsov, Seungmin JinMulti-Hop QA Graph Retrieval-Augmented Generation
HSE University
Temporal Decay of Co-Citation Predictability: A 20-Year Statute Retrieval Benchmark from 396M Ukrainian Court Citations
May 17, 2026Volodymyr OvcharovLegal IR Temporal IR
LEX AI LLC, Kyiv, Ukraine
PRISM: Pareto-Efficient Retrieval over Intent-Aware Structured Memory for Long-Horizon Agents
May 12, 2026Jingyi Peng, Zhongwei Wan, Weiting Liu +1Graph-Based Retrieval Information Retrieval
Singapore Management University · The Ohio State University · Fudan University
SkillLens: Adaptive Multi-Granularity Skill Reuse for Cost-Efficient LLM Agents
May 8, 2026Ziyang Yu, Yongliang Miao, Liang Zhao +2LLM Agent Self-Improvement LLM Agent Skill Learning
Emory University
LARAG: Link-Aware Retrieval Strategy for RAG Systems in Hyperlinked Technical Documentation
May 8, 2026Giorgia Bolognesi, Claudio Estatico, Ulderico Fugacci +3Document Understanding Retrieval-Augmented Generation
1Rulex s.r.l., Genova, Italy · Department of Mathematics (DIMA), University of Genoa, Italy · Institute of Applied Mathematics and Information Technologies “Enrico Magenes” (IMATI), National Research Council, Italy +1
GraphReAct: Reasoning and Acting for Multi-step Graph Inference
May 8, 2026Xingtong Yu, Zhongwei Kuai, Chang Zhou +6Graph Representation Learning Graph-Based Retrieval
The Chinese University of Hong Kong · The University of Science and Technology of China · University of Electronic Science and Technology of China +3
LARGER: Lexically Anchored Repository Graph Exploration and Retrieval
May 8, 2026Yuntong Hu, Tongli Su, Liang Zhao +2AI Coding Agents Agentic Retrieval
Emory University
Topic Is Not Agenda: A Citation-Community Audit of Text Embeddings
May 8, 2026Junseon YooText Embedding Evaluation Graph-Based Retrieval
Pluto Labs
GATHER: Convergence-Centric Hyper-Entity Retrieval for Zero-Shot Cell-Type Annotation
May 7, 2026Zhonghui Zhang, Feng Jiang, Shaowei Qin +2Zero-Shot Learning Graph Retrieval-Augmented Generation
Artificial Intelligence Research Institute, Shenzhen University of Advanced Technology Shenzhen, China · Software College, Northeastern University Shenyang, China
Sheet as Token: A Graph-Enhanced Representation for Multi-Sheet Spreadsheet Understanding
May 7, 2026Yiming Lei, Yiqi Wang, Yujia Zhang +5Graph-Based Retrieval Information Retrieval
Effyic Technology Co., Ltd · UCLA · McGill University
Text-Graph Synergy: A Bidirectional Verification and Completion Framework for RAG
May 7, 2026Jiarui Zhong, Hong Cai ChenRetrieval-Augmented Generation Graph Retrieval-Augmented Generation
School of Automation, Southeast University, Nanjing 210096, China
Query-Aware Flow Diffusion for Graph-Based RAG with Retrieval Guarantees
Apr 21, 2026Zhuoping Zhou, Davoud Ataee Tarzanagh, Sima Didari +7Multi-Hop QA Graph Retrieval-Augmented Generation
Samsung SDS Research America, Mountain View, CA, USA
LogosKG: Hardware-Optimized Scalable and Interpretable Knowledge Graph Retrieval
Apr 20, 2026He Cheng, Yifu Wu, Saksham Khatwani +5Graph-Based Retrieval Knowledge Graph Question Answering
LARK Lab, University of Colorado Anschutz · University of Colorado Boulder · Loyola University Chicago +3
EHRAG: Bridging Semantic Gaps in Lightweight GraphRAG via Hybrid Hypergraph Construction and Retrieval
Apr 19, 2026Yifan Song, Xingjian Tao, Zhicheng Yang +2Graph Retrieval-Augmented Generation Graph-Based Retrieval
1The Hong Kong University of Science and Technology (Guangzhou) · 2The Hong Kong University of Science and Technology
HSG: Hyperbolic Scene Graph
Apr 19, 2026Liyang Wang, Zeyu Zhang, Hao TangGraph Representation Learning Hierarchical Representation Learning
School of Computer Science, Peking University
RLM-on-KG: Heuristics First, LLMs When Needed: Adaptive Retrieval Control over Mention Graphs for Scattered Evidence
Apr 18, 2026Andrea Volpini, Elie RaadMulti-Hop QA LLM Reasoning with Graphs
WordLift
Integrating Graphs, Large Language Models, and Agents: Reasoning and Retrieval
Apr 17, 2026Hamed Jelodar, Samita Bai, Mohammad Meymani +3LLM Reasoning with Graphs Graph Retrieval-Augmented Generation
Canadian Institute for Cybersecurity, Faculty of Computer Science, University of New Brunswick, Fredericton, NB E3B 9W4, Canada
Efficient K-generalizable Learned Search
Mar 6, 2026Yifan Peng, Jiafei Fan, Xingda Wei +7Inference-Time Search Graph-Based Retrieval
Shanghai Jiao Tong University · Boston University · Alibaba Group
SpIDER: Spatially Informed Dense Embedding Retrieval for Software Issue Localization
Dec 18, 2025Shravan Chaudhari, Rahul Thomas Jacob, Jiajun Cao +3Software Engineering Software Engineering Benchmarks
Department of Computer Science, Johns Hopkins University, Baltimore, MD, USA · Work done while interning at AWS · AWS AI Labs, Seattle, WA, USA
KGFR: A Foundation Retriever for Generalized Knowledge Graph Question Answering
Nov 6, 2025Yuanning Cui, Zequn Sun, Wei Hu +1Multi-Hop QA LLM Grounding
School of Computer Science, Nanjing University of Information Science and Technology, Nanjing 210044, China · State Key Laboratory for Novel Software Technology, Nanjing University, Nanjing 210023, China · National Institute of Healthcare Data Science, Nanjing University, Nanjing 210093, China +2
The kernel of graph indices for vector search
Jun 25, 2025Mariano Tepper, Ted WillkeGraph-Based Retrieval Kernel Methods
IBM WatsonX
Divide by Question, Conquer by Agent: SPLIT-RAG with Question-Driven Graph Partitioning
May 20, 2025Ruiyi Yang, Hao Xue, Imran Razzak +3Multi-Hop QA Multi-Agent LLM Systems
University of New South Wales Sydney, NSW, Australia · Mohamed Bin Zayed University of Artificial Intelligence Abu Dhabi, UAE · Griffith University Queensland, Australia +1
Ontology-Guided Reverse Thinking Makes Large Language Models Stronger on Knowledge Graph Question Answering
Feb 17, 2025Runxuan Liu, Bei Luo, Jiaqi Li +5LLM Reasoning with Graphs Graph-Based Retrieval
Harbin Institute of Technology, Harbin, China · Beijing University of Posts and Telecommunications, Beijing, China · Joint Laboratory of HIT and iFLYTEK, Beijing, China +2

May 30, 2026, cs.IRJ/K move · Enter open · S save

MemGraphRAG: Memory-based Multi-Agent System for Graph Retrieval-Augmented Generation

Chuanjie Wu, Zhishang Xiang, Yunbo Tang, Zerui Chen+2

Xiamen University1, 2 · Xiamen University2, 3 · Xiamen University1+2

KG Construction Multi-Agent LLM Systems Graph Retrieval-Augmented Generation Graph-Based Retrieval Memory-Augmented Language Model Agents

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Retrieval-Augmented Generation (RAG) has become an essential method for mitigating hallucinations in Large Language Models (LLMs) by leveraging external knowledge. Although effective for simple queries, traditional RAG struggles with large-scale, unstructured corpora where information is highly fragmented. Graph-based RAG (GraphRAG) incorporates knowledge graphs to capture structural relationships, enabling more comprehensive retrieval for complex reasoning. However, existing GraphRAG methods rely on isolated, fragment-level extraction for graph construction, lacking a global perspective on the whole corpus. As a result, these methods frequently lead to thematically inconsistent, logically conflicting, and structurally fragmented graphs that degrade retrieval performance. In this paper, we propose MemGraphRAG, a novel framework that introduces a memory-based multi-agent system to ensure high-quality graph construction. Specifically, MemGraphRAG employs a collaborative society of agents supported by shared memory, which provides a unified global context throughout the extraction process. This mechanism allows agents to dynamically resolve logical conflicts and maintain structural connectivity throughout the corpus. Furthermore, we propose a memory-aware hierarchical retrieval algorithm tailored for the constructed graph. Extensive experiments on multiple benchmarks demonstrate that MemGraphRAG outperforms the state-of-the-art baseline models with comparable efficiency. Our code is available at https://github.com/XMUDeepLIT/MemGraphRAG.

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