collaborators

5 papers

cs.SE2024

GEE-OPs: An Operator Knowledge Base for Geospatial Code Generation on the Google Earth Engine Platform Powered by Large Language Models

Shuyang Hou, Jianyuan Liang, Anqi Zhao +1

As the scale and complexity of spatiotemporal data continue to grow rapidly, the use of geospatial modeling on the Google Earth Engine (GEE) platform presents dual challenges: impr…

cs.SE2024

Chain-of-Programming (CoP) : Empowering Large Language Models for Geospatial Code Generation

Shuyang Hou, Haoyue Jiao, Zhangxiao Shen +5

With the rapid growth of interdisciplinary demands for geospatial modeling and the rise of large language models (LLMs), geospatial code generation technology has seen significant…

cs.SE2024

Geo-FuB: A Method for Constructing an Operator-Function Knowledge Base for Geospatial Code Generation Tasks Using Large Language Models

Shuyang Hou, Anqi Zhao, Jianyuan Liang +2

The rise of spatiotemporal data and the need for efficient geospatial modeling have spurred interest in automating these tasks with large language models (LLMs). However, general L…

cs.SE2024

GeoCode-GPT: A Large Language Model for Geospatial Code Generation Tasks

Shuyang Hou, Zhangxiao Shen, Anqi Zhao +5

The increasing demand for spatiotemporal data and modeling tasks in geosciences has made geospatial code generation technology a critical factor in enhancing productivity. Although…

cs.SE2024

Can Large Language Models Generate Geospatial Code?

Shuyang Hou, Zhangxiao Shen, Jianyuan Liang +4

With the growing demand for spatiotemporal data processing and geospatial modeling, automating geospatial code generation has become essential for productivity. Large language mode…