mlsanityData to 7 Oct 2026

Can we Soft Prompt LLMs for Graph Learning Tasks?

arXiv 2402.10359 ↗First posted 15 Feb 2024cs.LG cs.CLcited by 52

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Abstract (arXiv)

Graph plays an important role in representing complex relationships in real-world applications such as social networks, biological data and citation networks. In recent years, Large Language Models (LLMs) have achieved tremendous success in various domains, which makes applying LLMs to graphs particularly appealing. However, directly applying LLMs to graph modalities presents unique challenges due to the discrepancy and mismatch between the graph and text modalities. Hence, to further investigate LLMs' potential for comprehending graph information, we introduce GraphPrompter, a novel framework designed to align graph information with LLMs via soft prompts. Specifically, GraphPrompter consists of two main components: a graph neural network to encode complex graph information and an LLM that effectively processes textual information. Comprehensive experiments on various benchmark datasets under node classification and link prediction tasks demonstrate the effectiveness of our proposed method. The GraphPrompter framework unveils the substantial capabilities of LLMs as predictors in graph-related tasks, enabling researchers to utilize LLMs across a spectrum of real-world graph scenarios more effectively.

Key facts. Cited by 52 papers in the map (data through 7 Oct 2026). Builds on 20 of its 26 references that are in the map. First posted on arXiv 15 Feb 2024.

Builds on

20 of 26 references.

References · 20

  1. 2020Language Models are Few-Shot Learnerscited by 32,199
  2. 2022Training language models to follow instructions with human feedbackcited by 15,712
  3. 2017Graph Attention Networkscited by 8,854
  4. 2022PaLM: Scaling Language Modeling with Pathwayscited by 5,304
  5. 2022Solving Quantitative Reasoning Problems with Language Modelscited by 1,359
  6. 2021Do Prompt-Based Models Really Understand the Meaning of their Prompts?cited by 324
  7. 2023LLMRec: Large Language Models with Graph Augmentation for Recommendationcited by 171
  8. 2022GreaseLM: Graph REASoning Enhanced Language Models for Question Answeringcited by 170
  9. 2022Learning on Large-scale Text-attributed Graphs via Variational Inferencecited by 153
  10. 2023Knowledge Graph Prompting for Multi-Document Question Answeringcited by 150
  11. 2021GraphFormers: GNN-nested Transformers for Representation Learning on Textual Graphcited by 143
  12. 2024Democratizing Large Language Models via Personalized Parameter-Efficient Fine-tuningcited by 87
8 more
  1. 2022Neighborhood Contrastive Learning for Scientific Document Representations with Citation Embeddingscited by 75
  2. 2023Graph Neural Prompting with Large Language Modelscited by 64
  3. 2023Augmenting Low-Resource Text Classification with Graph-Grounded Pre-training and Promptingcited by 62
  4. 2023ConGraT: Self-Supervised Contrastive Pretraining for Joint Graph and Text Embeddingscited by 32
  5. 2023Train Your Own GNN Teacher: Graph-Aware Distillation on Textual Graphscited by 29
  6. 2023Leveraging Large Language Models for Node Generation in Few-Shot Learning on Text-Attributed Graphscited by 23
  7. 2021Minimally-Supervised Structure-Rich Text Categorization via Learning on Text-Rich Networkscited by 11
  8. 2022Metadata-Induced Contrastive Learning for Zero-Shot Multi-Label Text Classificationcited by 10

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Cited by year (2026 to 7 Oct)

Citing papers per year: 2024: 9; 2025: 27; 2026: 16.

52 papers.

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  1. 2025A Survey of Graph Retrieval-Augmented Generation for Customized Large Language Modelscited by 85
  2. 2024Towards Graph Foundation Models: Learning Generalities Across Graphs via Task-Treescited by 30
  3. 2025AgentRouter: A Knowledge-Graph-Guided LLM Router for Collaborative Multi-Agent Question Answeringcited by 29
  4. 2025GraphICL: Unlocking Graph Learning Potential in LLMs through Structured Prompt Designcited by 21
  5. 2025LLM as GNN: Graph Vocabulary Learning for Text-Attributed Graph Foundation Modelscited by 21
  6. 2025Beyond Message Passing: Neural Graph Pattern Machinecited by 17
  7. 2025GRAPHGPT-O: Synergistic Multimodal Comprehension and Generation on Graphscited by 17
  8. 2026Graph is a Substrate Across Data Modalitiescited by 13
  9. 2025Graph2text or Graph2token: A Perspective of Large Language Models for Graph Learningcited by 12
  10. 2025MLaGA: Multimodal Large Language and Graph Assistantcited by 12
  11. 2024Taxonomy Tree Generation from Citation Graphcited by 11
  12. 2025One Prompt Fits All: Universal Graph Adaptation for Pretrained Modelscited by 11
38 more
  1. 2024A Survey on Self-Supervised Graph Foundation Models: Knowledge-Based Perspectivecited by 9
  2. 2025Graph-MLLM: Harnessing Multimodal Large Language Models for Multimodal Graph Learningcited by 9
  3. 2025NG-Router: Graph-Supervised Multi-Agent Collaboration for Nutrition Question Answeringcited by 9
  4. 2024Urban Region Pre-training and Prompting: A Graph-based Approachcited by 8
  5. 2024Training MLPs on Graphs without Supervisioncited by 8
  6. 2025From Nodes to Narratives: Explaining Graph Neural Networks with LLMs and Graph Contextcited by 6
  7. 2025TrustGLM: Evaluating the Robustness of GraphLLMs Against Prompt, Text, and Structure Attackscited by 5
  8. 2025Large Language Models Meet Text-Attributed Graphs: A Survey of Integration Frameworks and Applicationscited by 5
  9. 2024Demystifying Higher-Order Graph Neural Networkscited by 4
  10. 2024How to Make LMs Strong Node Classifiers?cited by 4
  11. 2025Graph-Grounded LLMs: Leveraging Graphical Function Calling to Minimize LLM Hallucinationscited by 4
  12. 2025TrumorGPT: Graph-Based Retrieval-Augmented Large Language Model for Fact-Checkingcited by 4
  13. 2025GraphRunner: A Multi-Stage Framework for Efficient and Accurate Graph-Based Retrievalcited by 4
  14. 2026AgentGL: Towards Agentic Graph Learning with LLMs via Reinforcement Learningcited by 4
  15. 2025Integrating Structural and Semantic Signals in Text-Attributed Graphs with BiGTexcited by 3
  16. 2025Adversarial Attacks and Defenses on Graph-aware Large Language Models (LLMs)cited by 3
  17. 2025GLTW: Joint Improved Graph Transformer and LLM via Three-Word Language for Knowledge Graph Completioncited by 2
  18. 2025Toward a Graph Foundation Model: Pre-Training Transformers With Random Walkscited by 2
  19. 2025From Aggregation to Selection: User-Validated Distributed Social Recommendationcited by 1
  20. 2025GLOW: Graph-Language Co-Encoding for Agentic Workflow Performance Predictioncited by 1
  21. 2026Colorful Talks with Graphs: Human-Interpretable Graph Encodings for Large Language Modelscited by 1
  22. 2026GraphVLM: Benchmarking Vision Language Models for Multimodal Graph Learningcited by 1
  23. 2026Riemannian Geometry Speaks Louder Than Words: From Graph Foundation Model to Next-Generation Graph Intelligencecited by 1
  24. 2026G2LoRA: Gradient Orthogonal Low-Rank Adaptation Framework for Graph Continual Learning on Text-Attributed Graphscited by 1
  25. 2026Surprisingly Simple and Effective Multi-Domain Graph Foundation Model through Graph-to-Table Alignmentcited by 1
  26. 2024See Where You Read with Eye Gaze Tracking and Large Language Modelcited by 0
  27. 2024Fusion Matrix Prompt Enhanced Self-Attention Spatial-Temporal Interactive Traffic Forecasting Frameworkcited by 0
  28. 2025MuTRAP: Multi-trigger Trojans Attacking Robot Task Planning Systemscited by 0
  29. 2025Scalability Matters: Overcoming Challenges in InstructGLM with Similarity-Degree-Based Samplingcited by 0
  30. 2025Masked Language Models are Good Heterogeneous Graph Generalizerscited by 0
  31. 2025Modeling Code: Is Text All You Need?cited by 0
  32. 2026NAG: A Unified Native Architecture for Encoder-free Text-Graph Modeling in Language Modelscited by 0
  33. 2026Multi-Scale Temporal Homeostasis Enables Efficient and Robust Neural Networkscited by 0
  34. 2026Differentially Private and Communication Efficient Large Language Model Split Inference via Stochastic Quantization and Soft Promptcited by 0
  35. 2026LoReC: Rethinking Large Language Models for Graph Data Analysiscited by 0
  36. 2026When Graph Tokens Sink: A Mechanistic Analysis of Graph Language Modelscited by 0
  37. 2026GraspLLM: Towards Zero-Shot Generalization on Text-Attributed Graphs with LLMscited by 0
  38. 2026PromptGNN-sim: Deep Fusion and Alignment of GNN and LLMs for Text-Attributed Graph Learningcited by 0

50 most cited of 52 All 52 (JSON)