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awesome-graph-llm's Introduction

Awesome-Graph-LLM Awesome

A collection of AWESOME things about Graph-Related Large Language Models (LLMs).

Large Language Models (LLMs) have shown remarkable progress in natural language processing tasks. However, their integration with graph structures, which are prevalent in real-world applications, remains relatively unexplored. This repository aims to bridge that gap by providing a curated list of research papers that explore the intersection of graph-based techniques with LLMs.

Table of Contents

Datasets, Benchmarks & Surveys

  • (NAACL'21) Knowledge Graph Based Synthetic Corpus Generation for Knowledge-Enhanced Language Model Pre-training [paper][code]
  • (NeurIPS'23) Can Language Models Solve Graph Problems in Natural Language? [paper][code]
  • (IEEE Intelligent Systems 2023) Integrating Graphs with Large Language Models: Methods and Prospects [paper]
  • (ICLR'24) Talk like a Graph: Encoding Graphs for Large Language Models [paper]
  • (KDD'24) LLM4DyG: Can Large Language Models Solve Problems on Dynamic Graphs? [paper][code]
  • (arXiv 2023.05) GPT4Graph: Can Large Language Models Understand Graph Structured Data? An Empirical Evaluation and Benchmarking [paper][code]
  • (arXiv 2023.08) Graph Meets LLMs: Towards Large Graph Models [paper]
  • (arXiv 2023.10) Towards Graph Foundation Models: A Survey and Beyond [paper]
  • (arXiv 2023.11) Can Knowledge Graphs Reduce Hallucinations in LLMs? : A Survey [paper]
  • (arXiv 2023.11) A Survey of Graph Meets Large Language Model: Progress and Future Directions [paper][code]
  • (arXiv 2023.12) Large Language Models on Graphs: A Comprehensive Survey [paper][code]
  • (arXiv 2024.02) Towards Versatile Graph Learning Approach: from the Perspective of Large Language Models [paper]
  • (arXiv 2024.04) Graph Machine Learning in the Era of Large Language Models (LLMs) [paper]
  • (arXiv 2024.05) A Survey of Large Language Models for Graphs [paper][code]
  • (arXiv 2024.07) GLBench: A Comprehensive Benchmark for Graph with Large Language Models [paper][code]
  • (arXiv 2024.07) Learning on Graphs with Large Language Models(LLMs): A Deep Dive into Model Robustness [paper][code]

Prompting

  • (EMNLP'23) StructGPT: A General Framework for Large Language Model to Reason over Structured Data [paper][code]
  • (AAAI'24) Graph of Thoughts: Solving Elaborate Problems with Large Language Models [paper][code]
  • (arXiv 2023.05) PiVe: Prompting with Iterative Verification Improving Graph-based Generative Capability of LLMs [paper][code]
  • (arXiv 2023.08) Boosting Logical Reasoning in Large Language Models through a New Framework: The Graph of Thought [paper]
  • (arxiv 2023.10) Thought Propagation: An Analogical Approach to Complex Reasoning with Large Language Models [paper]
  • (arxiv 2024.01) Topologies of Reasoning: Demystifying Chains, Trees, and Graphs of Thoughts [paper]
  • (arxiv 2024.04) Graph Chain-of-Thought: Augmenting Large Language Models by Reasoning on Graphs [paper)

General Graph Model

  • (ICLR'24) One for All: Towards Training One Graph Model for All Classification Tasks [paper][code]
  • (arXiv 2023.08) Natural Language is All a Graph Needs [paper][code]
  • (arXiv 2023.10) GraphGPT: Graph Instruction Tuning for Large Language Models [paper][code][blog in Chinese]
  • (arXiv 2023.10) Graph Agent: Explicit Reasoning Agent for Graphs [paper]
  • (arXiv 2024.02) Let Your Graph Do the Talking: Encoding Structured Data for LLMs [paper]
  • (arXiv 2024.02) G-Retriever: Retrieval-Augmented Generation for Textual Graph Understanding and Question Answering [paper][code][blog]
  • (arXiv 2024.02) InstructGraph: Boosting Large Language Models via Graph-centric Instruction Tuning and Preference Alignment [paper][code]
  • (arXiv 2024.02) LLaGA: Large Language and Graph Assistant [paper][code]
  • (arXiv 2024.02) HiGPT: Heterogeneous Graph Language Model [paper][code]
  • (arXiv 2024.02) UniGraph: Learning a Cross-Domain Graph Foundation Model From Natural Language [paper]
  • (arXiv 2024.06) UniGLM: Training One Unified Language Model for Text-Attributed Graphs [paper][code]
  • (arXiv 2024.07) GOFA: A Generative One-For-All Model for Joint Graph Language Modeling [paper][code]

Large Multimodal Models (LMMs)

  • (NeurIPS'23) GraphAdapter: Tuning Vision-Language Models With Dual Knowledge Graph [paper][code]
  • (arXiv 2023.10) Multimodal Graph Learning for Generative Tasks [paper][code]
  • (arXiv 2024.02) Rendering Graphs for Graph Reasoning in Multimodal Large Language Models [paper]

Applications

Basic Graph Reasoning

  • (KDD'24) GraphWiz: An Instruction-Following Language Model for Graph Problems [paper][code][project]
  • (arXiv 2023.04) Graph-ToolFormer: To Empower LLMs with Graph Reasoning Ability via Prompt Augmented by ChatGPT [paper][code]
  • (arXiv 2023.10) GraphText: Graph Reasoning in Text Space [paper]
  • (arXiv 2023.10) GraphLLM: Boosting Graph Reasoning Ability of Large Language Model [paper][code]

Node Classification

  • (ICLR'24) Explanations as Features: LLM-Based Features for Text-Attributed Graphs [paper][code]
  • (ICLR'24) Label-free Node Classification on Graphs with Large Language Models (LLMS) [paper]
  • (WWW'24) Can GNN be Good Adapter for LLMs? [paper][code]
  • (arXiv 2023.07) Exploring the Potential of Large Language Models (LLMs) in Learning on Graphs [paper][code]
  • (arXiv 2023.09) Can LLMs Effectively Leverage Structural Information for Graph Learning: When and Why [paper][code]
  • (arXiv 2023.10) Empower Text-Attributed Graphs Learning with Large Language Models (LLMs) [paper]
  • (arXiv 2023.10) Disentangled Representation Learning with Large Language Models for Text-Attributed Graphs [paper]
  • (arXiv 2023.11) Large Language Models as Topological Structure Enhancers for Text-Attributed Graphs [paper]
  • (arXiv 2024.01) Efficient Tuning and Inference for Large Language Models on Textual Graphs [paper][code]
  • (arXiv 2024.02) Similarity-based Neighbor Selection for Graph LLMs [paper] [code]
  • (arXiv 2024.02) Distilling Large Language Models for Text-Attributed Graph Learning [paper]
  • (arXiv 2024.02) GraphEdit: Large Language Models for Graph Structure Learning [paper][code]
  • (arXiv 2024.05) LOGIN: A Large Language Model Consulted Graph Neural Network Training Framework [paper][code]
  • (arXiv 2024.06) GAugLLM: Improving Graph Contrastive Learning for Text-Attributed Graphs with Large Language Models [paper][code]

Graph Classification/Regression

  • (arXiv 2023.06) GIMLET: A Unified Graph-Text Model for Instruction-Based Molecule Zero-Shot Learning [paper][code]
  • (arXiv 2023.07) Can Large Language Models Empower Molecular Property Prediction? [paper][code]

Knowledge Graph

  • (AAAI'22) Enhanced Story Comprehension for Large Language Models through Dynamic Document-Based Knowledge Graphs [paper]
  • (EMNLP'22) Language Models of Code are Few-Shot Commonsense Learners [paper][code]
  • (SIGIR'23) Schema-aware Reference as Prompt Improves Data-Efficient Knowledge Graph Construction [paper][code]
  • (TKDE‘23) AutoAlign: Fully Automatic and Effective Knowledge Graph Alignment enabled by Large Language Models [paper][code]
  • (AAAI'24) Graph Neural Prompting with Large Language Models [paper][code]
  • (NAACL'24) zrLLM: Zero-Shot Relational Learning on Temporal Knowledge Graphs with Large Language Models [paper]
  • (ICLR'24) Think-on-Graph: Deep and Responsible Reasoning of Large Language Model on Knowledge Graph [paper][code]
  • (arXiv 2023.04) CodeKGC: Code Language Model for Generative Knowledge Graph Construction [paper][code]
  • (arXiv 2023.05) Knowledge Graph Completion Models are Few-shot Learners: An Empirical Study of Relation Labeling in E-commerce with LLMs [paper]
  • (arXiv 2023.08) MindMap: Knowledge Graph Prompting Sparks Graph of Thoughts in Large Language Models [paper][code]
  • (arXiv 2023.10) Faithful Path Language Modelling for Explainable Recommendation over Knowledge Graph [paper]
  • (arXiv 2023.10) Reasoning on Graphs: Faithful and Interpretable Large Language Model Reasoning [paper][code]
  • (arXiv 2023.11) Zero-Shot Relational Learning on Temporal Knowledge Graphs with Large Language Models [paper]
  • (arXiv 2023.12) KGLens: A Parameterized Knowledge Graph Solution to Assess What an LLM Does and Doesn’t Know [paper]
  • (arXiv 2024.02) Large Language Model Meets Graph Neural Network in Knowledge Distillation [paper]
  • (arXiv 2024.02) Large Language Models Can Learn Temporal Reasoning [paper][code]
  • (arXiv 2024.03) Call Me When Necessary: LLMs can Efficiently and Faithfully Reason over Structured Environments [paper]
  • (arXiv 2024.04) Evaluating the Factuality of Large Language Models using Large-Scale Knowledge Graphs [paper][code]
  • (arXiv 2024.04) Extract, Define, Canonicalize: An LLM-based Framework for Knowledge Graph Construction [paper]
  • (arXiv 2024.05) FiDeLiS: Faithful Reasoning in Large Language Model for Knowledge Graph Question Answering [paper]
  • (arXiv 2024.06) Explore then Determine: A GNN-LLM Synergy Framework for Reasoning over Knowledge Graph [paper]

Molecular Graph

  • (arXiv 2024.06) MolecularGPT: Open Large Language Model (LLM) for Few-Shot Molecular Property Prediction [paper][code]
  • (arXiv 2024.06) HIGHT: Hierarchical Graph Tokenization for Graph-Language Alignment [paper][project]

Others

  • (WSDM'24) LLMRec: Large Language Models with Graph Augmentation for Recommendation [paper][code][blog in Chinese].
  • (arXiv 2023.03) Ask and You Shall Receive (a Graph Drawing): Testing ChatGPT’s Potential to Apply Graph Layout Algorithms [paper]
  • (arXiv 2023.05) Graph Meets LLM: A Novel Approach to Collaborative Filtering for Robust Conversational Understanding [paper]
  • (arXiv 2023.05) ChatGPT Informed Graph Neural Network for Stock Movement Prediction [paper][code]
  • (arXiv 2023.10) Graph Neural Architecture Search with GPT-4 [paper]
  • (arXiv 2023.11) Biomedical knowledge graph-enhanced prompt generation for large language models [paper][code]
  • (arXiv 2023.11) Graph-Guided Reasoning for Multi-Hop Question Answering in Large Language Models [paper]
  • (arXiv 2024.02) Microstructures and Accuracy of Graph Recall by Large Language Models [paper]
  • (arXiv 2024.02) Causal Graph Discovery with Retrieval-Augmented Generation based Large Language Models [paper]
  • (arXiv 2024.02) Graph-enhanced Large Language Models in Asynchronous Plan Reasoning [paper][code]
  • (arXiv 2024.03) Exploring the Potential of Large Language Models in Graph Generation [paper]
  • (arXiv 2024.05) Don't Forget to Connect! Improving RAG with Graph-based Reranking [paper]
  • (arXiv 2024.05) Can Graph Learning Improve Task Planning? [paper][code]
  • (arXiv 2024.06) GNN-RAG: Graph Neural Retrieval for Large Language Modeling Reasoning [paper][code]

Resources & Tools

Contributing

👍 Contributions to this repository are welcome!

If you have come across relevant resources, feel free to open an issue or submit a pull request.

- (*conference|journal*) paper_name [[pdf](link)][[code](link)]

Star History

Star History Chart

awesome-graph-llm's People

Contributors

arthur-heng avatar karthiksoman avatar lechengkong avatar mistyreed63849 avatar samridh3215 avatar tjb-tech avatar weiwei1206 avatar xiaoxinhe avatar xiongsiheng avatar xmhzz2018 avatar zihanchen1995 avatar

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awesome-graph-llm's Issues

Add a new paper

Hi Xiaoxin,

We have recently published a paper titled "Efficient Tuning and Inference for Large Language Models on Textual Graphs ". This paper introduces an efficient training and inference algorithm specifically designed for Large Language Models (LLMs) on text-attributed graphs.

We would greatly appreciate it if you could include this paper in your repository, specifically in the "Node Classification" section.

  • (arXiv 2024.01) Efficient Tuning and Inference for Large Language Models on Textual Graphs [pdf][code]

Best,
Yun

Potential related work

Hi, thanks for this awesome repo! We would like to introduce a related work on using the graph structure of general tasks to enhance complex reasoning with LLMs "Thought Propagation: An Analogical Approach to Complex Reasoning with Large Language Models". We hope our suggestion could enrich this awesome paper list ☺️ !

Potential related papers

Dear authors,

Thank you so much for making this great repo! Could you please add these three papers? The first two are about representation learning with large pretrained language models on graphs associated with textual information, while the last is about pretraining large language models on text-rich networks.

[1] Heterformer: A Transformer Architecture for Node Representation Learning on Heterogeneous Text-Rich Networks. KDD 2023.

[2] Edgeformers: Graph-Empowered Transformers for Representation Learning on Textual-Edge Networks. ICLR 2023.

[3] Patton: Language Model Pretraining on Text-rich Networks. ACL 2023.

Thanks!

Add a new paper

(arXiv 2024.02) Similarity-based Neighbor Selection for Graph LLMs [paper]

This paper should belong to the node classification part.

We would like to introduce another paper that complements this topic: "GIMLET: A Unified Graph-Text Model for Instruction-Based Molecule Zero-Shot Learning."

Thank you for sharing your insightful paper list!
We would like to introduce another paper that complements this topic: "GIMLET: A Unified Graph-Text Model for Instruction-Based Molecule Zero-Shot Learning." This paper integrates the graph modality into the language model and employs an instruction-based learning approach to address graph property prediction tasks. We would be delighted if our suggestion contributes to the enrichment of this awesome paper list ☺️ !

wrong paper link

the link of this paper is wrong:
(arXiv 2024.03) Exploring the Potential of Large Language Models in Graph Generation

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