mlsanityData to 7 Oct 2026

GraphInsight: Unlocking Insights in Large Language Models for Graph Structure Understanding

arXiv 2409.03258 ↗First posted 5 Sep 2024cs.CLcited by 18

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Abstract (arXiv)

Although Large Language Models (LLMs) have demonstrated potential in processing graphs, they struggle with comprehending graphical structure information through prompts of graph description sequences, especially as the graph size increases. We attribute this challenge to the uneven memory performance of LLMs across different positions in graph description sequences, known as ''positional biases''. To address this, we propose GraphInsight, a novel framework aimed at improving LLMs' comprehension of both macro- and micro-level graphical information. GraphInsight is grounded in two key strategies: 1) placing critical graphical information in positions where LLMs exhibit stronger memory performance, and 2) investigating a lightweight external knowledge base for regions with weaker memory performance, inspired by retrieval-augmented generation (RAG). Moreover, GraphInsight explores integrating these two strategies into LLM agent processes for composite graph tasks that require multi-step reasoning. Extensive empirical studies on benchmarks with a wide range of evaluation tasks show that GraphInsight significantly outperforms all other graph description methods (e.g., prompting techniques and reordering strategies) in understanding graph structures of varying sizes.

Key facts. Cited by 18 papers in the map (data through 7 Oct 2026). Builds on 39 of its 55 references that are in the map. First posted on arXiv 5 Sep 2024.

Builds on

39 of 55 references.

References · 39

  1. 2020Language Models are Few-Shot Learnerscited by 32,199
  2. 2022Chain-of-Thought Prompting Elicits Reasoning in Large Language Modelscited by 12,302
  3. 2020Retrieval-Augmented Generation for Knowledge-Intensive NLP Taskscited by 9,160
  4. 2023Lost in the Middle: How Language Models Use Long Contextscited by 3,383
  5. 2023Efficient Streaming Language Models with Attention Sinkscited by 2,115
  6. 2023Graph of Thoughts: Solving Elaborate Problems with Large Language Modelscited by 873
  7. 2023ExpeL: LLM Agents Are Experiential Learnerscited by 814
  8. 2023Time-LLM: Time Series Forecasting by Reprogramming Large Language Modelscited by 680
  9. 2023Unifying Large Language Models and Knowledge Graphs: A Roadmapcited by 663
  10. 2023A Comprehensive Overview of Large Language Modelscited by 639
  11. 2018A Survey on Deep Learning for Named Entity Recognitioncited by 281
  12. 2022TabLLM: Few-shot Classification of Tabular Data with Large Language Modelscited by 273
27 more
  1. 2023Exploring the Potential of Large Language Models (LLMs) in Learning on Graphscited by 271
  2. 2023Can Language Models Solve Graph Problems in Natural Language?cited by 249
  3. 2023GPT4Graph: Can Large Language Models Understand Graph Structured Data ? An Empirical Evaluation and Benchmarkingcited by 209
  4. 2023OpenAGI: When LLM Meets Domain Expertscited by 196
  5. 2023Talk like a Graph: Encoding Graphs for Large Language Modelscited by 175
  6. 2023Knowledge-Augmented Language Model Prompting for Zero-Shot Knowledge Graph Question Answeringcited by 119
  7. 2024Make Your LLM Fully Utilize the Contextcited by 118
  8. 2023Table Meets LLM: Can Large Language Models Understand Structured Table Data? A Benchmark and Empirical Studycited by 116
  9. 2024Let Your Graph Do the Talking: Encoding Structured Data for LLMscited by 112
  10. 2024Found in the Middle: Calibrating Positional Attention Bias Improves Long Context Utilizationcited by 97
  11. 2021Learning Intents behind Interactions with Knowledge Graph for Recommendationcited by 94
  12. 2023A Survey of Graph Meets Large Language Model: Progress and Future Directionscited by 84
  13. 2023Temporal Data Meets LLM -- Explainable Financial Time Series Forecastingcited by 77
  14. 2024Beyond the Limits: A Survey of Techniques to Extend the Context Length in Large Language Modelscited by 71
  15. 2024GraphInstruct: Empowering Large Language Models with Graph Understanding and Reasoning Capabilitycited by 57
  16. 2020Understanding graph embedding methods and their applicationscited by 50
  17. 2024Understanding the Capabilities and Limitations of Large Language Models for Cultural Commonsensecited by 50
  18. 2023CLIPSyntel: CLIP and LLM Synergy for Multimodal Question Summarization in Healthcarecited by 43
  19. 2023Found in the Middle: Permutation Self-Consistency Improves Listwise Ranking in Large Language Modelscited by 30
  20. 2019Demystifying Graph Databases: Analysis and Taxonomy of Data Organization, System Designs, and Graph Queriescited by 22
  21. 2024A Survey of Large Language Models on Generative Graph Analytics: Query, Learning, and Applicationscited by 17
  22. 2024GraCoRe: Benchmarking Graph Comprehension and Complex Reasoning in Large Language Modelscited by 13
  23. 2024GraphEval36K: Benchmarking Coding and Reasoning Capabilities of Large Language Models on Graph Datasetscited by 12
  24. 2024RAGE Against the Machine: Retrieval-Augmented LLM Explanationscited by 8
  25. 2023Modeling Dynamic Heterogeneous Graph and Node Importance for Future Citation Predictioncited by 7
  26. 2024Attention Instruction: Amplifying Attention in the Middle via Promptingcited by 6
  27. 2023Enhance Sketch Recognition's Explainability via Semantic Component-Level Parsingcited by 1

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Cited by year (2026 to 7 Oct)

Citing papers per year: 2024: 1; 2025: 13; 2026: 4.

18 papers.

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  1. 2025PathRAG: Pruning Graph-based Retrieval Augmented Generation with Relational Pathscited by 60
  2. 2025ArchRAG: Attributed Community-based Hierarchical Retrieval-Augmented Generationcited by 27
  3. 2025Complexity Control Facilitates Reasoning-Based Compositional Generalization in Transformerscited by 19
  4. 2025Exploring Graph Learning Tasks with Pure LLMs: A Comprehensive Benchmark and Investigationcited by 11
  5. 2025GraphThought: Graph Combinatorial Optimization with Thought Generationcited by 9
  6. 2025Model Generalization on Text Attribute Graphs: Principles with Large Language Modelscited by 8
  7. 2024LEGO-GraphRAG: Modularizing Graph-based Retrieval-Augmented Generation for Design Space Explorationcited by 7
  8. 2025MA-GTS: A Multi-Agent Framework for Solving Complex Graph Problems in Real-World Applicationscited by 3
  9. 2025When Structure Doesn't Help: LLMs Do Not Read Text-Attributed Graphs as Effectively as We Expectedcited by 3
  10. 2025DuetGraph: Coarse-to-Fine Knowledge Graph Reasoning with Dual-Pathway Global-Local Fusioncited by 2
  11. 2025See or Say Graphs: Agent-Driven Scalable Graph Structure Understanding with Vision-Language Modelscited by 2
  12. 2026<SOG_k>: One LLM Token for Explicit Graph Structural Understandingcited by 2
6 more
  1. 2025H4G: Unlocking Faithful Inference for Zero-Shot Graph Learning in Hyperbolic Spacecited by 1
  2. 2026Learning Transferable Topology Priors for Multi-Agent LLM Collaboration Across Domainscited by 1
  3. 2025Path Pooling: Training-Free Structure Enhancement for Efficient Knowledge Graph Retrieval-Augmented Generationcited by 0
  4. 2025GraphShaper: Geometry-aware Alignment for Improving Transfer Learning in Text-Attributed Graphscited by 0
  5. 2026Are Large Language Models Suitable for Graph Computation? Progress and Prospectscited by 0
  6. 2026HyGRAIL: Cost-Aware and Evidence-Grounded Scientific Hypothesis Discovery over Knowledge Graphscited by 0

Similar, not cited

Close in wording, no citation either way

  1. 2024A Hierarchical Language Model For Interpretable Graph Reasoning
  2. 2023Evaluating Large Language Models on Graphs: Performance Insights and Comparative Analysis
  3. 2024GUNDAM: Aligning Large Language Models with Graph Understanding
  4. 2026Formalizing and Mitigating Structural Distortion in LLM Attention for Graph Reasoning
  5. 2025GraphCogent: Mitigating LLMs' Working Memory Constraints via Multi-Agent Collaboration in Complex Graph Understanding
  6. 2026Teaching LLMs to See Graphs: Unifying Text and Structural Reasoning
  7. 2024Can LLM Graph Reasoning Generalize beyond Pattern Memorization?
  8. 2026Detecting Differences Is Not Understanding Structure: Large Language Models Fail at Graph Isomorphism