activity
20242026
most citedGeoJSEval: An Automated Evaluation Framework for Large Language Models on JavaScript-Based Geospatial Computation and Visualization Code Generation

10 citations · 14 across the 7 of their papers we have counts for

collaborators

7 papers

cs.CV2026

AEF-Econ: Toward Plug-and-Play Socioeconomic Foundation Embeddings from AlphaEarth for Urban Remote Sensing

Shuyang Hou, Ziqi Liu, Haoyue Jiao +7

AlphaEarth Foundations (AEF) unify global remote sensing foundation embeddings through multimodal self-supervised learning, but their pretraining focuses on physical land-surface s…

cs.CV2026

Slum Detection and Density Mapping with AlphaEarth Foundations: A Representation Learning Evaluation Across 12 Global Cities

Shuyang Hou, Ziqi Liu, Haoyue Jiao +7

Pixel-level slum mapping has long been constrained by limited cross-city generalisation, the absence of continuous density estimation, and weak global comparability. AlphaEarth Fou…

cs.DB2025

GeoSQL-Eval: First Evaluation of LLMs on PostGIS-Based NL2GeoSQL Queries

Shuyang Hou, Haoyue Jiao, Ziqi Liu +5

Large language models (LLMs) have shown strong performance in natural language to SQL (NL2SQL) tasks within general databases. However, extending to GeoSQL introduces additional co…

cs.SE2025★ 10 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.SE2025★ 1 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★ 3 cited

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…