10 citations · 16 across the 5 of their papers we have counts for
5 papers
GeoJSEval: An Automated Evaluation Framework for Large Language Models on JavaScript-Based Geospatial Computation and Visualization Code Generation
Guanyu Chen, Haoyue Jiao, Shuyang Hou +6
With the widespread adoption of large language models (LLMs) in code generation tasks, geospatial code generation has emerged as a critical frontier in the integration of artificia…
AutoGEEval++: A Multi-Level and Multi-Geospatial-Modality Automated Evaluation Framework for Large Language Models in Geospatial Code Generation on Google Earth Engine
Shuyang Hou, Zhangxiao Shen, Huayi Wu +10
Geospatial code generation is becoming a key frontier in integrating artificial intelligence with geo-scientific analysis, yet standardised automated evaluation tools for this task…
AutoGEEval: A Multimodal and Automated Framework for Geospatial Code Generation on GEE with Large Language Models
Shuyang Hou, Zhangxiao Shen, Huayi Wu +8
Geospatial code generation is emerging as a key direction in the integration of artificial intelligence and geoscientific analysis. However, there remains a lack of standardized to…
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…
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…