most citedFoundation Models for Geospatial Reasoning: Assessing Capabilities of Large Language Models in Understanding Geometries and Topological Spatial Relations

32 citations · 32 across the 5 of their papers we have counts for

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cs.CL2025★ 32 cited

Foundation Models for Geospatial Reasoning: Assessing Capabilities of Large Language Models in Understanding Geometries and Topological Spatial Relations

Yuhan Ji, Song Gao, Ying Nie +2

Applying AI foundation models directly to geospatial datasets remains challenging due to their limited ability to represent and reason with geographical entities, specifically vect…

cs.CL2024

Evaluating the Effectiveness of Large Language Models in Representing and Understanding Movement Trajectories

Yuhan Ji, Song Gao

This research focuses on assessing the ability of AI foundation models in representing the trajectories of movements. We utilize one of the large language models (LLMs) (i.e., GPT-…