@@ -37,9 +37,13 @@ Large Language Models (LLMs) have shown remarkable progress in natural language
- (*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)]
- (*IJCAI'24*) A Survey of Graph Meets Large Language Model: Progress and Future Directions [[paper](https://arxiv.org/abs/2311.12399)][[code](https://github.com/yhLeeee/Awesome-LLMs-in-Graph-tasks)]
- (*TKDE'24*) Large Language Models on Graphs: A Comprehensive Survey [[paper](https://arxiv.org/abs/2312.02783)][[code](https://github.com/PeterGriffinJin/Awesome-Language-Model-on-Graphs)]
- (*ICLR'25*) GraphArena: Evaluating and Exploring Large Language Models on Graph Computation [[paper](https://arxiv.org/abs/2407.00379)][[code](https://github.com/squareRoot3/GraphArena)]
- (*ICLR'25*) How Do Large Language Models Understand Graph Patterns? A Benchmark for Graph Pattern Comprehension [[paper](https://arxiv.org/abs/2410.05298)]
- (*arxiv 2023.05*) GPT4Graph: Can Large Language Models Understand Graph Structured Data? An Empirical Evaluation and Benchmarking [[paper](https://arxiv.org/abs/2305.15066)]
- (*arXiv 2023.08*) Graph Meets LLMs: Towards Large Graph Models [[paper](http://arxiv.org/abs/2308.14522)]
- (*arXiv 2023.10*) Towards Graph Foundation Models: A Survey and Beyond [[paper](https://arxiv.org/abs/2310.11829v1)]
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@@ -75,18 +79,20 @@ Large Language Models (LLMs) have shown remarkable progress in natural language
- (*EACL'24'*) Natural Language is All a Graph Needs [[paper](https://arxiv.org/abs/2308.07134)][[code](https://github.com/agiresearch/InstructGLM)]
- (*KDD'25*) UniGraph: Learning a Cross-Domain Graph Foundation Model From Natural Language [[paper](https://arxiv.org/abs/2402.13630)]
- (*WSDM '25*) UniGLM: Training One Unified Language Model for Text-Attributed Graph Embedding [[paper](https://arxiv.org/abs/2406.12052)][[code](https://github.com/NYUSHCS/UniGLM)]
- (*ICLR'25*) GOFA: A Generative One-For-All Model for Joint Graph Language Modeling [[paper](https://arxiv.org/abs/2407.09709)][[code](https://github.com/JiaruiFeng/GOFA)]
- (*arXiv 2024.02*) Let Your Graph Do the Talking: Encoding Structured Data for LLMs [[paper](https://arxiv.org/abs/2402.05862)]
- (*arXiv 2024.06*) UniGLM: Training One Unified Language Model for Text-Attributed Graphs [[paper](https://arxiv.org/abs/2406.12052)][[code](https://github.com/NYUSHCS/UniGLM)]
- (*arXiv 2024.07*) GOFA: A Generative One-For-All Model for Joint Graph Language Modeling [[paper](https://arxiv.org/abs/2407.09709)][[code](https://github.com/JiaruiFeng/GOFA)]
- (*arXiv 2024.08*) AnyGraph: Graph Foundation Model in the Wild [[paper](https://arxiv.org/abs/2408.10700)][[code](https://github.com/HKUDS/AnyGraph)]
- (*arXiv 2024.10*) NT-LLM: A Novel Node Tokenizer for Integrating Graph Structure into Large Language Models [[paper](https://arxiv.org/abs/2410.10743)]
- (*arXiv 2025.03*) LLM as GNN: Graph Vocabulary Learning for Text-Attributed Graph Foundation Models [[paper](https://arxiv.org/abs/2503.03313)]
@@ -139,7 +145,13 @@ Large Language Models (LLMs) have shown remarkable progress in natural language
- (*TKDE‘23*) AutoAlign: Fully Automatic and Effective Knowledge Graph Alignment enabled by Large Language Models [[paper](https://arxiv.org/abs/2307.11772)][[code](https://github.com/ruizhang-ai/AutoAlign)]
- (*ICLR'24*) Think-on-Graph: Deep and Responsible Reasoning of Large Language Model on Knowledge Graph [[paper](https://arxiv.org/abs/2307.07697)][[code](https://github.com/IDEA-FinAI/ToG)]
- (*ICLR‘24*) Reasoning on Graphs: Faithful and Interpretable Large Language Model Reasoning [[paper](https://arxiv.org/abs/2310.01061)][[code](https://github.com/RManLuo/reasoning-on-graphs)]
- (*AAAI'24*) Graph Neural Prompting with Large Language Models [[paper](https://arxiv.org/abs/2309.15427)][[code](https://github.com/meettyj/GNP)]
- (*NeurIPS'24*) Construction and Application of Materials Knowledge Graph in Multidisciplinary Materials Science via Large Language Model [[paper](https://arxiv.org/abs/2404.03080)][[code](https://github.com/MasterAI-EAM/Material-Knowledge-Graph)]
- (*NeurIPS'24*) UrbanKGent: A Unified Large Language Model Agent Framework for Urban Knowledge Graph Construction [[paper](https://arxiv.org/abs/2402.06861)][[code](https://github.com/usail-hkust/UrbanKGent)]
- (*NeurIPS'24*) Plan-on-Graph: Self-Correcting Adaptive Planning of Large Language Model on Knowledge Graphs [[paper](https://arxiv.org/abs/2410.23875)]
- (*NeurIPS'24*) Large Language Models-guided Dynamic Adaptation for Temporal Knowledge Graph Reasoning [[paper](https://arxiv.org/abs/2405.14170)][[code](https://github.com/jiapuwang/LLM-DA)]
- (*NeurIPS'24*) KnowGPT: Knowledge Graph based PrompTing for Large Language Models [[paper](https://arxiv.org/abs/2312.06185)]
- (*AAAI'24*) Graph Neural Prompting with Large Language Models [[paper](https://arxiv.org/abs/2309.15427)][[code](https://github.com/meettyj/GNP)]
- (*EMNLP'24*) Extract, Define, Canonicalize: An LLM-based Framework for Knowledge Graph Construction [[paper](https://arxiv.org/abs/2404.03868)][[code](https://github.com/clear-nus/edc)]
- (*EMNLP'24*) LLM-Based Multi-Hop Question Answering with Knowledge Graph Integration in Evolving Environments [[paper](https://arxiv.org/abs/2408.15903)]
- (*ACL'24*) Graph Language Models [[paper](https://aclanthology.org/2024.acl-long.245/)][[code](https://github.com/Heidelberg-NLP/GraphLanguageModels)]
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@@ -161,6 +173,7 @@ Large Language Models (LLMs) have shown remarkable progress in natural language
### Molecular Graph
- (*NeurIPS'23*) GIMLET: A Unified Graph-Text Model for Instruction-Based Molecule Zero-Shot Learning [[paper](https://arxiv.org/abs/2306.13089)][[code](https://github.com/zhao-ht/GIMLET)]
- (*NeurIPS'24*) LLaMo: Large Language Model-based Molecular Graph Assistant [[paper](https://arxiv.org/abs/2411.00871)][[code](https://github.com/mlvlab/LLaMo)]
- (*arXiv 2023.07*) Can Large Language Models Empower Molecular Property Prediction? [[paper](https://arxiv.org/abs/2307.07443)][[code](https://github.com/ChnQ/LLM4Mol)]
- (*arXiv 2024.06*) MolecularGPT: Open Large Language Model (LLM) for Few-Shot Molecular Property Prediction [[paper](https://arxiv.org/abs/2406.12950)][[code](https://github.com/NYUSHCS/MolecularGPT)]
- (AAAI'25) Bootstrapping Heterogeneous Graph Representation Learning via Large Language Models: A Generalized Approach [[paper](https://arxiv.org/abs/2412.08038)]
- (*ICLR'25*) RepoGraph: Enhancing AI Software Engineering with Repository-level Code Graph [[paper](https://arxiv.org/abs/2410.14684)] [[code](https://github.com/ozyyshr/RepoGraph)]
- (*ICLR'25*) GraphRouter: A Graph-based Router for LLM Selections [[paper](https://arxiv.org/abs/2410.03834)][[code](https://github.com/ulab-uiuc/GraphRouter)]
- (*arXiv 2023.03*) Ask and You Shall Receive (a Graph Drawing): Testing ChatGPT’s Potential to Apply Graph Layout Algorithms [[paper](https://arxiv.org/abs/2303.08819)]
- (*arXiv 2023.05*) Graph Meets LLM: A Novel Approach to Collaborative Filtering for Robust Conversational Understanding [[paper](https://arxiv.org/abs/2305.14449)]
- (*arXiv 2023.05*) ChatGPT Informed Graph Neural Network for Stock Movement Prediction [[paper](https://arxiv.org/abs/2306.03763)][[code](https://github.com/ZihanChen1995/ChatGPT-GNN-StockPredict)]
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@@ -224,7 +238,6 @@ Large Language Models (LLMs) have shown remarkable progress in natural language
- (*arXiv 2024.07*) LLMExplainer: Large Language Model based Bayesian Inference for Graph Explanation Generation [[paper](https://arxiv.org/abs/2407.15351)]
- (*arXiv 2024.08*) CodexGraph: Bridging Large Language Models and Code Repositories via Code Graph Databases [[paper](https://arxiv.org/abs/2408.03910)][[code](https://github.com/modelscope/modelscope-agent/tree/master/apps/codexgraph_agent)][[project](https://laptype.github.io/CodexGraph-page/)]
- (*arXiv 2024.10*) Graph Linearization Methods for Reasoning on Graphs with Large Language Models [[paper](https://arxiv.org/abs/2410.19494)]
- (*arXiv 2024.10*) GraphRouter: A Graph-based Router for LLM Selections [[paper](https://arxiv.org/abs/2410.03834)][[code](https://github.com/ulab-uiuc/GraphRouter)]
## Resources & Tools
-[GraphGPT: Extrapolating knowledge graphs from unstructured text using GPT-3](https://github.com/varunshenoy/GraphGPT)
