mlsanityData to 14 Oct 2026

A Survey of Graph Meets Large Language Model: Progress and Future Directions

arXiv 2311.12399 ↗First posted 21 Nov 2023cs.LG cs.CL cs.SIcited by 85

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Abstract (arXiv)

Graph plays a significant role in representing and analyzing complex relationships in real-world applications such as citation networks, social networks, and biological data. Recently, Large Language Models (LLMs), which have achieved tremendous success in various domains, have also been leveraged in graph-related tasks to surpass traditional Graph Neural Networks (GNNs) based methods and yield state-of-the-art performance. In this survey, we first present a comprehensive review and analysis of existing methods that integrate LLMs with graphs. First of all, we propose a new taxonomy, which organizes existing methods into three categories based on the role (i.e., enhancer, predictor, and alignment component) played by LLMs in graph-related tasks. Then we systematically survey the representative methods along the three categories of the taxonomy. Finally, we discuss the remaining limitations of existing studies and highlight promising avenues for future research. The relevant papers are summarized and will be consistently updated at: https://github.com/yhLeeee/Awesome-LLMs-in-Graph-tasks.

Key facts. Cited by 85 papers in the map (data through 14 Oct 2026). Builds on 82 of its 107 references that are in the map. First posted on arXiv 21 Nov 2023.

Builds on

82 of 107 references.

References · 82

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38 more
  1. 2022PaLM: Scaling Language Modeling with Pathwayscited by 5,326
  2. 2018How Powerful are Graph Neural Networks?cited by 4,393
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Cited by year (2026 to 14 Oct)

Citing papers per year: 2023: 2; 2024: 34; 2025: 27; 2026: 22.

85 papers.

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  1. 2024G-Retriever: Retrieval-Augmented Generation for Textual Graph Understanding and Question Answeringcited by 223
  2. 2023Large Language Models on Graphs: A Comprehensive Surveycited by 192
  3. 2025A Survey of Graph Retrieval-Augmented Generation for Customized Large Language Modelscited by 88
  4. 2024Position: Graph Foundation Models are Already Herecited by 86
  5. 2024GRAG: Graph Retrieval-Augmented Generationcited by 78
  6. 2024Demystifying Chains, Trees, and Graphs of Thoughtscited by 63
  7. 2023Graph Prompt Learning: A Comprehensive Survey and Beyondcited by 61
  8. 2024GraphCLIP: Enhancing Transferability in Graph Foundation Models for Text-Attributed Graphscited by 58
  9. 2024KG-RAG: Bridging the Gap Between Knowledge and Creativitycited by 56
  10. 2024Can Graph Learning Improve Planning in LLM-based Agents?cited by 43
  11. 2024GLBench: A Comprehensive Benchmark for Graph with Large Language Modelscited by 36
  12. 2024Graph Machine Learning in the Era of Large Language Models (LLMs)cited by 33
38 more
  1. 2024LLMs generate structurally realistic social networks but overestimate political homophilycited by 33
  2. 2024GraphWiz: An Instruction-Following Language Model for Graph Problemscited by 32
  3. 2024ProG: A Graph Prompt Learning Benchmarkcited by 29
  4. 2025Graphs Meet AI Agents: Taxonomy, Progress, and Future Opportunitiescited by 23
  5. 2025You Don't Need Pre-built Graphs for RAG: Retrieval Augmented Generation with Adaptive Reasoning Structurescited by 23
  6. 2024Entity Alignment with Noisy Annotations from Large Language Modelscited by 22
  7. 2025LLM as GNN: Graph Vocabulary Learning for Text-Attributed Graph Foundation Modelscited by 22
  8. 2025When Do LLMs Help With Node Classification? A Comprehensive Analysiscited by 21
  9. 2024Graph-oriented Instruction Tuning of Large Language Models for Generic Graph Miningcited by 20
  10. 2024Surveying the MLLM Landscape: A Meta-Review of Current Surveyscited by 20
  11. 2024GraphInsight: Unlocking Insights in Large Language Models for Graph Structure Understandingcited by 18
  12. 2024A Survey of Large Language Models on Generative Graph Analytics: Query, Learning, and Applicationscited by 17
  13. 2024HIGHT: Hierarchical Graph Tokenization for Molecule-Language Alignmentcited by 17
  14. 2024Advancing Graph Representation Learning with Large Language Models: A Comprehensive Survey of Techniquescited by 16
  15. 2024Domain-Specific Retrieval-Augmented Generation Using Vector Stores, Knowledge Graphs, and Tensor Factorizationcited by 15
  16. 2025EraRAG: Efficient and Incremental Retrieval Augmented Generation for Growing Corporacited by 15
  17. 2024Large Language Model Meets Graph Neural Network in Knowledge Distillationcited by 14
  18. 2024UniGAD: Unifying Multi-level Graph Anomaly Detectioncited by 14
  19. 2025GRAVER: Generative Graph Vocabularies for Robust Graph Foundation Models Fine-tuningcited by 13
  20. 2024GraphTeam: Facilitating Large Language Model-based Graph Analysis via Multi-Agent Collaborationcited by 12
  21. 2024A Survey on Self-Supervised Graph Foundation Models: Knowledge-Based Perspectivecited by 9
  22. 2024Intruding with Words: Towards Understanding Graph Injection Attacks at the Text Levelcited by 9
  23. 2024Beyond Efficiency: Molecular Data Pruning for Enhanced Generalizationcited by 9
  24. 2025GRAIL:Learning to Interact with Large Knowledge Graphs for Retrieval Augmented Reasoningcited by 7
  25. 2025KG-LLM-Bench: A Scalable Benchmark for Evaluating LLM Reasoning on Textualized Knowledge Graphscited by 6
  26. 2024Are Large-Language Models Graph Algorithmic Reasoners?cited by 5
  27. 2025Text-Attributed Graph Anomaly Detection via Multi-Scale Cross- and Uni-Modal Contrastive Learningcited by 5
  28. 2024Reducing Reasoning Costs: The Path of Optimization for Chain of Thought via Sparse Attention Mechanismcited by 4
  29. 2025Graph Foundation Models for Recommendation: A Comprehensive Surveycited by 4
  30. 2026Are LLM-Enhanced Graph Neural Networks Robust against Poisoning Attacks?cited by 4
  31. 2024All in One: Multi-Task Prompting for Graph Neural Networks (Extended Abstract)cited by 3
  32. 2024Strada-LLM: Graph LLM for traffic predictioncited by 3
  33. 2025Large Language Models for Cryptocurrency Transaction Analysis: A Bitcoin Case Studycited by 3
  34. 2025Foundation Models for Anomaly Detection: Vision and Challengescited by 3
  35. 2024Are You Being Tracked? Discover the Power of Zero-Shot Trajectory Tracing with LLMs!cited by 2
  36. 2025Scale-Free Graph-Language Modelscited by 2
  37. 2025A Survey of Cross-domain Graph Learning: Progress and Future Directionscited by 2
  38. 2025Language Models as Messengers: Enhancing Message Passing in Heterophilic Graph Learningcited by 2

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