most citedGeospatial Representation Learning: A Survey from Deep Learning to The LLM Era

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cs.AI2026

Perceive to Hypothesize, Verify to Ground: An Agentic Reasoning Framework for Open-World Geo-Localization

Yutian Jiang, Ruijie Li, Sisuo Lyu +4

Open-world geo-localization requires models to reason over ambiguous visual cues through multi-step reasoning and external knowledge grounding. While recent large vision-language m…

cs.AI2026

Multi-Agent Collaborative Reasoning with Tool-Augmented Evidence for Urban Region Profiling

Xixuan Hao, Yutian Jiang, Jiabo Liu +4

Urban region profiling constitutes a core problem in urban computing, supporting applications such as population estimation, economic assessment, and environmental monitoring. Exis…

cs.AI2026

Think Before You Act: Intention-Guided Reasoning for LLM-Based Location Prediction

Qingxiang Liu, Anqi Liang, Zhuoyang Jiang +5

Predicting a user's next Point-of-Interest (POI) based on their historical check-in records is a fundamental task in location-based services. While recent methods incorporating lar…

cs.AI2026

ActivityEditor: Learning to Synthesize Physically Valid Human Mobility

Chenjie Yang, Yutian Jiang, Anqi Liang +3

Human mobility modeling is indispensable for diverse urban applications. However, existing data-driven methods often suffer from data scarcity, limiting their applicability in regi…

cs.AI2025

Urban-R1: Reinforced MLLMs Mitigate Geospatial Biases for Urban General Intelligence

Qiongyan Wang, Xingchen Zou, Yutian Jiang +4

Rapid urbanization intensifies the demand for Urban General Intelligence (UGI), referring to AI systems that can understand and reason about complex urban environments. Recent stud…