A Survey of Graph Meets Large Language Model: Progress and Future Directions

arXiv:2311.12399v4 Announce Type: replace-cross
Abstract: Graph plays a significant role in representing and analyzing complex relationships in real-world applications such as citation networks, social networks, and biological data. Recently, Large Language Models (LLMs), which have achieved tremendous success in various domains, have also been leveraged in graph-related tasks to surpass traditional Graph Neural Networks (GNNs) based methods and yield state-of-the-art performance. In this survey, we first present a comprehensive review and analysis of existing methods that integrate LLMs with graphs. …

arxiv cs.cl cs.lg cs.si future graph language language model large language large language model progress survey type