mlsanityData to 14 Oct 2026

When to use Graphs in RAG: A Comprehensive Analysis for Graph Retrieval-Augmented Generation

arXiv 2506.05690 ↗First posted 6 Jun 2025cs.CLcited by 48

On the map: Retrieval-augmented generation → Knowledge-graph and structured-knowledge RAG

Abstract (arXiv)

Graph retrieval-augmented generation (GraphRAG) has emerged as a powerful paradigm for enhancing large language models (LLMs) with external knowledge. It leverages graphs to model the hierarchical structure between specific concepts, enabling more coherent and effective knowledge retrieval for accurate reasoning.Despite its conceptual promise, recent studies report that GraphRAG frequently underperforms vanilla RAG on many real-world tasks. This raises a critical question: Is GraphRAG really effective, and in which scenarios do graph structures provide measurable benefits for RAG systems? To address this, we propose GraphRAG-Bench, a comprehensive benchmark designed to evaluate GraphRAG models onboth hierarchical knowledge retrieval and deep contextual reasoning. GraphRAG-Bench features a comprehensive dataset with tasks of increasing difficulty, coveringfact retrieval, complex reasoning, contextual summarization, and creative generation, and a systematic evaluation across the entire pipeline, from graph constructionand knowledge retrieval to final generation. Leveraging this novel benchmark, we systematically investigate the conditions when GraphRAG surpasses traditional RAG and the underlying reasons for its success, offering guidelines for its practical application. All related resources and analyses are collected for the community at https://github.com/GraphRAG-Bench/GraphRAG-Benchmark.

Key facts. Cited by 48 papers in the map (data through 14 Oct 2026). Placed in Knowledge-graph and structured-knowledge RAG, one of 15 directions in Retrieval-augmented generation. Builds on 56 of its 74 references that are in the map. First posted on arXiv 6 Jun 2025.

Builds on

56 of 74 references.

Closest ancestors · 14

Same direction, newest first

  1. 2025In-depth Analysis of Graph-based RAG in a Unified Framework6 Mar
  2. 2025PathRAG: Pruning Graph-based Retrieval Augmented Generation with Relational Paths18 Feb
  3. 2025RAG vs. GraphRAG: A Systematic Evaluation and Key Insights17 Feb
  4. 2025ArchRAG: Attributed Community-based Hierarchical Retrieval-Augmented Generation14 Feb
  5. 2025KET-RAG: A Cost-Efficient Multi-Granular Indexing Framework for Graph-RAG13 Feb
  6. 2025CG-RAG: Research Question Answering by Citation Graph Retrieval-Augmented LLMs25 Jan
  7. 2025A Survey of Graph Retrieval-Augmented Generation for Customized Large Language Models21 Jan
  8. 2024Retrieval-Augmented Generation with Graphs (GraphRAG)31 Dec
  9. 2024LightRAG: Simple and Fast Retrieval-Augmented Generation8 Oct
  10. 2024KAG: Boosting LLMs in Professional Domains via Knowledge Augmented Generation10 Sep
  11. 2024Graph Retrieval-Augmented Generation: A Survey15 Aug
  12. 2024GRAG: Graph Retrieval-Augmented Generation26 May
2 more
  1. 2024From Local to Global: A Graph RAG Approach to Query-Focused Summarization24 Apr
  2. 2024RAPTOR: Recursive Abstractive Processing for Tree-Organized Retrieval31 Jan

Other references · 42

  1. 2020Language Models are Few-Shot Learnerscited by 32,419
  2. 2023GPT-4 Technical Reportcited by 18,396
  3. 2020Retrieval-Augmented Generation for Knowledge-Intensive NLP Taskscited by 9,297
  4. 2022PaLM: Scaling Language Modeling with Pathwayscited by 5,326
  5. 2018HotpotQA: A Dataset for Diverse, Explainable Multi-hop Question Answeringcited by 3,754
  6. 2023Retrieval-Augmented Generation for Large Language Models: A Surveycited by 2,212
  7. 2023Self-RAG: Learning to Retrieve, Generate, and Critique through Self-Reflectioncited by 1,839
  8. 2023A Survey on Hallucination in Large Language Models: Principles, Taxonomy, Challenges, and Open Questionscited by 1,601
  9. 2021Improving language models by retrieving from trillions of tokenscited by 1,293
  10. 2022Atlas: Few-shot Learning with Retrieval Augmented Language Modelscited by 952
  11. 2023Active Retrieval Augmented Generationcited by 516
  12. 2020UnifiedQA: Crossing Format Boundaries With a Single QA Systemcited by 476
30 more
  1. 2024HippoRAG: Neurobiologically Inspired Long-Term Memory for Large Language Modelscited by 281
  2. 2024MultiHop-RAG: Benchmarking Retrieval-Augmented Generation for Multi-Hop Queriescited by 257
  3. 2023RECOMP: Improving Retrieval-Augmented LMs with Compression and Selective Augmentationcited by 256
  4. 2024AlphaEdit: Null-Space Constrained Knowledge Editing for Language Modelscited by 236
  5. 2025From RAG to Memory: Non-Parametric Continual Learning for Large Language Modelscited by 231
  6. 2020Generation-Augmented Retrieval for Open-domain Question Answeringcited by 186
  7. 2023Knowledge Graph Prompting for Multi-Document Question Answeringcited by 152
  8. 2022Internet-augmented language models through few-shot prompting for open-domain question answeringcited by 131
  9. 2024Next-Generation Database Interfaces: A Survey of LLM-based Text-to-SQLcited by 120
  10. 2022Re2G: Retrieve, Rerank, Generatecited by 102
  11. 2024Searching for Best Practices in Retrieval-Augmented Generationcited by 83
  12. 2025MedRAG: Enhancing Retrieval-augmented Generation with Knowledge Graph-Elicited Reasoning for Healthcare Copilotcited by 83
  13. 2025AnyEdit: Edit Any Knowledge Encoded in Language Modelscited by 76
  14. 2024StructRAG: Boosting Knowledge Intensive Reasoning of LLMs via Inference-time Hybrid Information Structurizationcited by 71
  15. 2024Chinese SimpleQA: A Chinese Factuality Evaluation for Large Language Modelscited by 43
  16. 2023LeanContext: Cost-Efficient Domain-Specific Question Answering Using LLMscited by 40
  17. 2023SAIL: Search-Augmented Instruction Learningcited by 33
  18. 2023KnowGPT: Knowledge Graph based Prompting for Large Language Modelscited by 31
  19. 2024FairGT: A Fairness-aware Graph Transformercited by 29
  20. 2024MBA-RAG: a Bandit Approach for Adaptive Retrieval-Augmented Generation through Question Complexitycited by 29
  21. 2024PipeRAG: Fast Retrieval-Augmented Generation via Algorithm-System Co-designcited by 28
  22. 2024Entity Alignment with Noisy Annotations from Large Language Modelscited by 22
  23. 2025PIKE-RAG: sPecIalized KnowledgE and Rationale Augmented Generationcited by 18
  24. 2025Empowering GraphRAG with Knowledge Filtering and Integrationcited by 15
  25. 2024FairGP: A Scalable and Fair Graph Transformer Using Graph Partitioningcited by 11
  26. 2023DBCopilot: Natural Language Querying over Massive Databases via Schema Routingcited by 10
  27. 2025LightPROF: A Lightweight Reasoning Framework for Large Language Model on Knowledge Graphcited by 8
  28. 2024Chinese SafetyQA: A Safety Short-form Factuality Benchmark for Large Language Modelscited by 7
  29. 2025Benchmarking LLMs' Mathematical Reasoning with Unseen Random Variables Questionscited by 7
  30. 2025GeoEdit: Geometric Knowledge Editing for Large Language Modelscited by 6

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Cited by year (2026 to 14 Oct)

Citing papers per year: 2025: 15; 2026: 33.

48 papers.

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  1. 2025A Survey of Context Engineering for Large Language Modelscited by 126
  2. 2025LinearRAG: Linear Graph Retrieval Augmented Generation on Large-scale Corporacited by 49
  3. 2025LiCoMemory: Lightweight and Cognitive Agentic Memory for Efficient Long-Term Reasoningcited by 38
  4. 2025You Don't Need Pre-built Graphs for RAG: Retrieval Augmented Generation with Adaptive Reasoning Structurescited by 23
  5. 2025HiChunk: Evaluating and Enhancing Retrieval-Augmented Generation with Hierarchical Chunkingcited by 12
  6. 2026MemSyco-Bench: Benchmarking Sycophancy in Agent Memorycited by 12
  7. 2025G-reasoner: Foundation Models for Unified Reasoning over Graph-structured Knowledgecited by 9
  8. 2025AutoGraph-R1: End-to-End Reinforcement Learning for Knowledge Graph Constructioncited by 7
  9. 2025AGRAG: Advanced Graph-based Retrieval-Augmented Generation for LLMscited by 7
  10. 2025Beyond Chunks and Graphs: Retrieval-Augmented Generation through Triplet-Driven Thinkingcited by 6
  11. 2026RAGRouter-Bench: A Dataset and Benchmark for Adaptive RAG Routingcited by 6
  12. 2026CSRv2: Unlocking Ultra-Sparse Embeddingscited by 6
36 more
  1. 2026LegalGraphRAG: Multi-Agent Graph Retrieval-Augmented Generation for Reliable Legal Reasoningcited by 5
  2. 2025HGMEM: Hypergraph-based Working Memory to Improve Multi-step RAG for Long-Context Complex Relational Modelingcited by 4
  3. 2026The Reasoning Bottleneck in Graph-RAG: Structured Prompting and Context Compression for Multi-Hop QAcited by 4
  4. 2025LoSemB: Logic-Guided Semantic Bridging for Inductive Tool Retrievalcited by 3
  5. 2026Beyond RAG for Cyber Threat Intelligence: A Systematic Evaluation of Graph-Based and Agentic Retrievalcited by 3
  6. 2026Pruning Minimal Reasoning Graphs for Efficient Retrieval-Augmented Generationcited by 2
  7. 2026LARGER: Lexically Anchored Repository Graph Exploration and Retrievalcited by 2
  8. 2026When Confidence Takes the Wrong Path: Diagnosing Retrieval-State Lock-In in RAGcited by 2
  9. 2025MARC: Multimodal and Multi-Task Agentic Retrieval-Augmented Generation for Cold-Start Recommender Systemcited by 1
  10. 2025Detecting Hallucinations in Graph Retrieval-Augmented Generation via Attention Patterns and Semantic Alignmentcited by 1
  11. 2026HELP: HyperNode Expansion and Logical Path-Guided Evidence Localization for Accurate and Efficient GraphRAGcited by 1
  12. 2026GAM-RAG: Gain-Adaptive Memory for Evolving Retrieval in Retrieval-Augmented Generationcited by 1
  13. 2026SAG: SQL-Retrieval Augmented Generation with Query-Time Dynamic Hyperedgescited by 1
  14. 2026SkillZip: Contract-Preserving Graph Compression for Scalable Agent Skill Librariescited by 1
  15. 2026Coding Agents Aren't Enough! Evaluating an Enterprise Security Brain for Agentic Cloud Investigationscited by 1
  16. 2025GOSU: Retrieval-Augmented Generation with Global-Level Optimized Semantic Unit-Centric Frameworkcited by 0
  17. 2025Evaluating Small Language Models for Agentic On-Farm Decision Support Systemscited by 0
  18. 2026A Navigational Approach for Comprehensive RAG via Traversal over Proposition Graphscited by 0
  19. 2026ROZA Graphs: Self-Improving Near-Deterministic RAG through Evidence-Centric Feedbackcited by 0
  20. 2026AtomicRAG: Atom-Entity Graphs for Retrieval-Augmented Generationcited by 0
  21. 2026GraphInfer-Bench: Benchmarking LLM's Inference Capability on Graphscited by 0
  22. 2026TRIAGE: Trustworthy Retrieval Instrumentation And Graph Evaluationcited by 0
  23. 2026MARS: Multi-hop Adaptive Retrieval and SPARQL Generation for KGQAcited by 0
  24. 2026Beyond Memory Leaderboards: Evaluating Scientific Memory as Budgeted Context Restorationcited by 0
  25. 2026Structure Over Scale: Schema-Constrained Causal Graphs for RAGcited by 0
  26. 2026A corrective agentic hybrid RAG and an operations-grounded evaluation for a scientific facilitycited by 0
  27. 2026SAG: SQL-Retrieval Augmented Generation with Query-Time Dynamic Hyperedgescited by 0
  28. 2026EviReform: Evidence-Guided Query Reformulation for Multi-Hop Graph Retrievalcited by 0
  29. 2026GTA-RAG: Graph-Trajectory-Augmented Reinforcement Learning for Multi-Turn Retrieval-Augmented Reasoningcited by 0
  30. 2026AdaPath: Query-Adaptive Path-Finding via Path-Bank for Multi-Hop Implicit Biomedical KGQAcited by 0
  31. 2026Seed-Anchored Budget-Bounded Graph Rendering for Question Answering on Industry-Standard Power-Grid Information and Exchange Modelscited by 0
  32. 2026Building Trustworthy Graph-Agentic RAG for Social Good: Architectures, Failure Propagation, and Assurance by Constructioncited by 0
  33. 2026When Is Graph Structure Worth Its Cost? The Case for Structure Pricing in Retrieval-Augmented Generationcited by 0
  34. 2026HyperReCo: Retrieving and Connecting Evidence with Hypergraph Neural Networks for LLM Multi-hop Reasoningcited by 0
  35. 2026Corpus-Guided Dual-Path Propagation for Graph Retrieval-Augmented Generationcited by 0
  36. 2026TopoGraphRAG-Bench: Evaluating Multimodal GraphRAG on Layout-Grounded Evidence Reasoningcited by 0

Similar, not cited

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  1. 2026Use Graph When It Needs: Efficiently and Adaptively Integrating Retrieval-Augmented Generation with Graphs
  2. 2025Graph-based Approaches and Functionalities in Retrieval-Augmented Generation: A Comprehensive Survey
  3. 2025NodeRAG: Structuring Graph-based RAG with Heterogeneous Nodes
  4. 2026Is GraphRAG Needed? From Basic RAG to Graph-/Agentic Solutions with Context Optimization
  5. 2025Beyond Static Retrieval: Opportunities and Pitfalls of Iterative Retrieval in GraphRAG
  6. 2025XGraphRAG: Interactive Visual Analysis for Graph-based Retrieval-Augmented Generation
  7. 2025LeanRAG: Knowledge-Graph-Based Generation with Semantic Aggregation and Hierarchical Retrieval
  8. 2024LEGO-GraphRAG: Modularizing Graph-based Retrieval-Augmented Generation for Design Space Exploration