3 papers
cs.AI2025
Self-Supervised Representation Learning for Geospatial Objects: A Survey
Yile Chen, Weiming Huang, Kaiqi Zhao +2
The proliferation of various data sources in urban and territorial environments has significantly facilitated the development of geospatial artificial intelligence (GeoAI) across a…
cs.CL2024
LAMP: A Language Model on the Map
Pasquale Balsebre, Weiming Huang, Gao Cong
Large Language Models (LLMs) are poised to play an increasingly important role in our lives, providing assistance across a wide array of tasks. In the geospatial domain, LLMs have…
cs.DB2024
City Foundation Models for Learning General Purpose Representations from OpenStreetMap
Pasquale Balsebre, Weiming Huang, Gao Cong +1
Pre-trained Foundation Models (PFMs) have ushered in a paradigm-shift in Artificial Intelligence, due to their ability to learn general-purpose representations that can be readily…