36 citations · 81 across the 15 of their papers we have counts for
15 papers
Variational Adapter for Cross-modal Similarity Representation
WenZhang Wei, Zhipeng Gui, Dehua Peng +2
The core of vision-language models lies in measuring cross-modal similarity within a unified representation space. However, most image-text matching or multi-class image classifica…
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…
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…
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…
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…
Research on the Spatial Data Intelligent Foundation Model
Shaohua Wang, Xing Xie, Yong Li +28
This report focuses on spatial data intelligent large models, delving into the principles, methods, and cutting-edge applications of these models. It provides an in-depth discussio…
Sampling-enabled scalable manifold learning unveils the discriminative cluster structure of high-dimensional data
Dehua Peng, Zhipeng Gui, Wenzhang Wei +4
As a pivotal branch of machine learning, manifold learning uncovers the intrinsic low-dimensional structure within complex nonlinear manifolds in high-dimensional space for visuali…
Interpreting the Curse of Dimensionality from Distance Concentration and Manifold Effect
Dehua Peng, Zhipeng Gui, Huayi Wu
The characteristics of data like distribution and heterogeneity, become more complex and counterintuitive as dimensionality increases. This phenomenon is known as curse of dimensio…
MeanCut: A Greedy-Optimized Graph Clustering via Path-based Similarity and Degree Descent Criterion
Dehua Peng, Zhipeng Gui, Huayi Wu
As the most typical graph clustering method, spectral clustering is popular and attractive due to the remarkable performance, easy implementation, and strong adaptability. Classica…
A Robust and Efficient Boundary Point Detection Method by Measuring Local Direction Dispersion
Dehua Peng, Zhipeng Gui, Jie Gui +1
Boundary point detection aims to outline the external contour structure of clusters and enhance the inter-cluster discrimination, thus bolstering the performance of the downstream…
Dynamic Visual Semantic Sub-Embeddings and Fast Re-Ranking
Wenzhang Wei, Zhipeng Gui, Changguang Wu +3
The core of cross-modal matching is to accurately measure the similarity between different modalities in a unified representation space. However, compared to textual descriptions o…