170 citations · 245 across the 4 of their papers we have counts for
4 papers
Evaluating the Effectiveness of Large Language Models in Representing Textual Descriptions of Geometry and Spatial Relations
Yuhan Ji, Song Gao
This research focuses on assessing the ability of large language models (LLMs) in representing geometries and their spatial relations. We utilize LLMs including GPT-2 and BERT to e…
On the Opportunities and Challenges of Foundation Models for Geospatial Artificial Intelligence
Gengchen Mai, Weiming Huang, Jin Sun +11
Large pre-trained models, also known as foundation models (FMs), are trained in a task-agnostic manner on large-scale data and can be adapted to a wide range of downstream tasks by…
GeoAI at ACM SIGSPATIAL: The New Frontier of Geospatial Artificial Intelligence Research
Dalton Lunga, Yingjie Hu, Shawn Newsam +4
Geospatial Artificial Intelligence (GeoAI) is an interdisciplinary field enjoying tremendous adoption. However, the efficient design and implementation of GeoAI systems face many o…
A Review of Location Encoding for GeoAI: Methods and Applications
Gengchen Mai, Krzysztof Janowicz, Yingjie Hu +5
A common need for artificial intelligence models in the broader geoscience is to represent and encode various types of spatial data, such as points (e.g., points of interest), poly…