Urban Computing in the Era of LLMs

What is it about?

In this survey, we provide a detailed review of how large language models (LLMs) are being applied across various areas of urban computing, such as traffic prediction, environmental monitoring, and autonomous driving. We also compare traditional approaches with LLM-based methods, highlighting the differences in their application paradigms as well as their respective strengths and limitations. In addition, we summarize commonly used benchmarks in different domains and discuss potential future research directions.

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Photo by Joey Kyber on Unsplash

Photo by Joey Kyber on Unsplash

Why is it important?

This survey systematically summarizes how existing works have effectively applied large language models (LLMs) across various areas of urban computing to improve the efficiency of city operations, providing valuable insights and references for future research.

Perspectives