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A collection of AWESOME things about Graph-Related LLMs.
| Date | Stars |
|---|---|
| 2026-07-31 | 2442 |
| 2026-08-06 | 2442 |
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# Awesome-Graph-LLM [](https://awesome.re)
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
- [Awesome-Graph-LLM ](#awesome-graph-llm-)
- [Table of Contents](#table-of-contents)
- [Datasets, Benchmarks \& Surveys](#datasets-benchmarks--surveys)
- [Prompting](#prompting)
- [General Graph Model](#general-graph-model)
- [Large Multimodal Models (LMMs)](#large-multimodal-models-lmms)
- [Applications](#applications)
- [Basic Graph Reasoning](#basic-graph-reasoning)
- [Node Classification](#node-classification)
- [Knowledge Graph](#knowledge-graph)
- [Molecular Graph](#molecular-graph)
- [Graph Retrieval Augmented Generation (GraphRAG)](#graph-retrieval-augmented-generation-graphrag)
- [Planning](#planning)
- [Multi-Agent Systems](#multi-agent-systems)
- [Graph Robustness](#graph-robustness)
- [Others](#others)
- [Resources \& Tools](#resources--tools)
- [Contributing](#contributing)
- [Star History](#star-history)
## Datasets, Benchmarks & Surveys
- (*NAACL'21*) Knowledge Graph Based Synthetic Corpus Generation for Knowledge-Enhanced Language Model Pre-training [[paper](https://aclanthology.org/2021.naacl-main.278/)][[code](https://github.com/google-research-datasets/KELM-corpus)]
- (*NeurIPS'23*) Can Language Models Solve Graph Problems in Natural Language? [[paper](https://arxiv.org/abs/2305.10037)][[code](https://github.com/Arthur-Heng/NLGraph)]
- (*IEEE Intelligent Systems 2023*) Integrating Graphs with Large Language Models: Methods and Prospects [[paper](https://arxiv.org/abs/2310.05499)]
- (*ICLR'24*) Talk like a Graph: Encoding Graphs for Large Language Models [[paper](https://arxiv.org/abs/2310.04560)]
- (*NeurIPS'24*) TEG-DB: A Comprehensive Dataset and Benchmark of Textual-Edge Graphs [[pdf](https://arxiv.org/abs/2406.10310)][[code](https://github.com/Zhuofeng-Li/TEG-Benchmark)][[datasets](https://huggingface.co/datasets/ZhuofengLi/TEG-Datasets/tree/main)]
- (*NAACL'24*) Can Knowledge Graphs Reduce Hallucinations in LLMs? : A Survey [[paper](https://arxiv.org/abs/2311.07914v1)]
- (*NeurIPS'24 D&B*) Can Large Language Models Analyze Graphs like Professionals? A Benchmark, Datasets and Models [[paper](https://arxiv.org/abs/2409.19667)][[code](https://github.com/BUPT-GAMMA/ProGraph)]
- (*NeurIPS'24 D&B*) GLBench: A Comprehensive Benchmark for Graph with Large Language Models [[paper](https://arxiv.org/abs/2407.07457)][[code](https://github.com/NineAbyss/GLBench)]
- (*NeurIPS'24 D&B*) DTGB: A Comprehensive Benchmark for Dynamic Text-Attributed Graphs [[paper](https://arxiv.org/abs/2406.12072)][[code](https://github.com/zjs123/DTGB)]
- (*NeurIPS'24 D&B*) UKnow: A Unified Knowledge Protocol with Multimodal Knowledge Graph Datasets for Reasoning and Vision-Language Pre-Training [[paper](https://arxiv.org/abs/2302.06891)]
- (*KDD'24*) A Survey of Large Language Models for Graphs [[paper](https://arxiv.org/abs/2405.08011)][[code](https://github.com/HKUDS/Awesome-LLM4Graph-Papers)].
matched fp:adf10f5438d9f9ad, llm:Repository title and description: 'Awesome-Graph-LLM' — 'A collection of AWESOME things about Graph-Related LLMs.' (curated list of resources on Graph-related large language models).
matched fp:adf10f5438d9f9ad, llm:Repository title and description: 'Awesome-Graph-LLM' — 'A collection of AWESOME things about Graph-Related LLMs.' (curated list of resources on Graph-related large language models).
matched fp:adf10f5438d9f9ad, llm:Repository title and description: 'Awesome-Graph-LLM' — 'A collection of AWESOME things about Graph-Related LLMs.' (curated list of resources on Graph-related large language models).