5 papers
Doxing via the Lens: Revealing Location-related Privacy Leakage on Multi-modal Large Reasoning Models
Weidi Luo, Tianyu Lu, Qiming Zhang +8
Recent advances in multi-modal large reasoning models (MLRMs) have shown significant ability to interpret complex visual content. While these models enable impressive reasoning cap…
Whose Truth? Pluralistic Geo-Alignment for (Agentic) AI
Krzysztof Janowicz, Zilong Liu, Gengchen Mai +5
AI (super) alignment describes the challenge of ensuring (future) AI systems behave in accordance with societal norms and goals. While a quickly evolving literature is addressing b…
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…
Identifying rich clubs in spatiotemporal interaction networks
Jacob Kruse, Song Gao, Yuhan Ji +3
Spatial networks are widely used in various fields to represent and analyze interactions or relationships between locations or spatially distributed entities.There is a network sci…
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-…