Graphs and Language Models: A New Path for Data Analysis

Graphs are everywhere, from social networks to biological systems. They help us understand complex relationships. Recently, large language models (LLMs) have entered this scene and shocked us with their ability to handle many tasks without extra training. This makes them super useful for graph analytics.

But how do these models tackle the challenges of graphs? One way is by simplifying tasks that traditionally need human effort, like labeling data manually. With LLMs, this might not be necessary anymore. This survey explores these capabilities and shows us a new perspective on tasks like query processing and graph learning. However, nothing is perfect. The study also looks at the current struggles and suggests where we should go next in this blend of AI and data analysis. It weighs the pros and cons of using LLMs here, giving a fair view of the situation.

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