@@ -164,7 +164,7 @@ Large Language Models (LLMs) have shown remarkable progress in natural language
- (*arXiv 2023.10*) Graph Neural Architecture Search with GPT-4 [[paper](https://arxiv.org/abs/2310.01436)]
- (*arXiv 2023.11*) Biomedical knowledge graph-enhanced prompt generation for large language models [[paper](https://arxiv.org/abs/2311.17330)][[code](https://github.com/BaranziniLab/KG_RAG)]
- (*arXiv 2023.11*) Graph-Guided Reasoning for Multi-Hop Question Answering in Large Language Models [[paper](https://arxiv.org/abs/2311.09762)]
- (*arXiv 2024.02*) Microstructures and Accuracy of Graph Recall by Large Language Models [[paper](https://arxiv.org/abs/2402.11821)]
- (*NeurIPS'24*) Microstructures and Accuracy of Graph Recall by Large Language Models [[paper](https://arxiv.org/abs/2402.11821)][[code](https://github.com/Abel0828/llm-graph-recall)]
- (*arXiv 2024.02*) Causal Graph Discovery with Retrieval-Augmented Generation based Large Language Models [[paper](https://arxiv.org/abs/2402.15301)]
- (*arXiv 2024.02*) Graph-enhanced Large Language Models in Asynchronous Plan Reasoning [[paper](https://arxiv.org/abs/2402.02805)][[code](https://github.com/fangru-lin/graph-llm-asynchow-plan)]
- (*arXiv 2024.02*) Efficient Causal Graph Discovery Using Large Language Models [[paper](https://arxiv.org/abs/2402.01207)]
