AutoGEEval: A Multimodal and Automated Evaluation Framework for Geospatial Code Generation on GEE with Large Language Models
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 tools for automatic evaluation in this domain. To address this gap, we propose AutoGEEval, the first multimodal, unit-leve...
Saved in:
| Main Authors: | Huayi Wu, Zhangxiao Shen, Shuyang Hou, Jianyuan Liang, Haoyue Jiao, Yaxian Qing, Xiaopu Zhang, Xu Li, Zhipeng Gui, Xuefeng Guan, Longgang Xiang |
|---|---|
| Format: | Article |
| Language: | English |
| Published: |
MDPI AG
2025-06-01
|
| Series: | ISPRS International Journal of Geo-Information |
| Subjects: | |
| Online Access: | https://www.mdpi.com/2220-9964/14/7/256 |
| Tags: |
Add Tag
No Tags, Be the first to tag this record!
|
Similar Items
-
GEE-OPs: an operator knowledge base for geospatial code generation on the Google Earth Engine platform powered by large language models
by: Shuyang Hou, et al.
Published: (2025-05-01) -
Chain-of-programming (CoP): empowering large language models for geospatial code generation task
by: Shuyang Hou, et al.
Published: (2025-08-01) -
Can large language models generate geospatial code?
by: Shuyang Hou, et al.
Published: (2025-08-01) -
GeoGraphRAG: A graph-based retrieval-augmented generation approach for empowering large language models in automated geospatial modeling
by: Jianyuan Liang, et al.
Published: (2025-08-01) -
Design and application of a semantic-driven geospatial modeling knowledge graph based on large language models
by: Jianyuan Liang, et al.
Published: (2025-04-01)