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20162026
most citedGeoCode-GPT: A Large Language Model for Geospatial Code Generation Tasks

36 citations · 89 across the 13 of their papers we have counts for

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Showing cs.SEShow all

5 papers · 1 filter

cs.SE202510 cited

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…

cs.SE20251 cited

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…

cs.SE2025

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…

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…