17 citations · 24 across the 19 of their papers we have counts for
5 papers · 1 filter
CITYREP: A Unified Benchmark for Urban Representations Across Cities, Tasks, and Modalities
Junyuan Liu, Xinglei Wang, Zichao Zeng +5
Urban representation learning encodes complex urban environments into general-purpose embeddings for diverse downstream tasks and emerging urban foundation models. However, current…
Beyond AlphaEarth: Toward Human-Centered Geospatial Foundation Models via POI-Guided Contrastive Learning
Junyuan Liu, Quan Qin, Guangsheng Dong +4
Recent geospatial foundation models (GFMs) produce spatially extensive representations of the Earth's surface that capture rich physical and environmental patterns. Among them, the…
Into the Unknown: Applying Inductive Spatial-Semantic Location Embeddings for Predicting Individuals' Mobility Beyond Visited Places
Xinglei Wang, Tao Cheng, Stephen Law +6
Predicting individuals' next locations is a core task in human mobility modelling, with wide-ranging implications for urban planning, transportation, public policy and personalised…
Multimodal Contrastive Learning of Urban Space Representations from POI Data
Xinglei Wang, Tao Cheng, Stephen Law +3
Existing methods for learning urban space representations from Point-of-Interest (POI) data face several limitations, including issues with geographical delineation, inadequate spa…
Where Would I Go Next? Large Language Models as Human Mobility Predictors
Xinglei Wang, Meng Fang, Zichao Zeng +1
Accurate human mobility prediction underpins many important applications across a variety of domains, including epidemic modelling, transport planning, and emergency responses. Due…