Feb. 12, 2024, 5:41 a.m. | Qiheng Mao Zemin Liu Chenghao Liu Zhuo Li Jianling Sun

cs.LG updates on arXiv.org arxiv.org

The integration of Large Language Models (LLMs) with Graph Representation Learning (GRL) marks a significant evolution in analyzing complex data structures. This collaboration harnesses the sophisticated linguistic capabilities of LLMs to improve the contextual understanding and adaptability of graph models, thereby broadening the scope and potential of GRL. Despite a growing body of research dedicated to integrating LLMs into the graph domain, a comprehensive review that deeply analyzes the core components and operations within these models is notably lacking. Our …

adaptability capabilities collaboration cs.ai cs.cl cs.lg data evolution graph graph representation integration language language models large language large language models llms marks representation representation learning survey understanding

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