20 papers
RoadBench: Benchmarking MLLMs on Fine-Grained Spatial Understanding and Reasoning under Urban Road Scenarios
Jun Zhang, Xin Zhang, Jie Feng +5
Multimodal large language models (MLLMs) have demonstrated powerful capabilities in general spatial understanding and reasoning. However, their fine-grained spatial understanding a…
EventOD: Event-Aware OD Flow Generation via LLM-Guided Semantic Modulation
Jie Zhao, Jie Feng, Can Rong +3
Estimating origin-destination (OD) flows under disruptive events is important for disaster response and urban resilience. Existing deep OD models trained on routine mobility often…
DynaOD: Dynamic Origin-Destination Flow Generation with Discrete-to-Continuous Temporal Semantic Modeling
Jie Zhao, Xianqi Dai, Jie Feng +2
Dynamic origin-destination (OD) flow generation seeks to synthesize realistic mobility dynamics from temporal context alone, without relying on historical OD observations. A key ch…
SpatialAct: Probing Spatial Reasoning-to-Action Capabilities of VLM Agents in 3D Scenes
Tianhui Liu, Jie Feng, Zhiheng Zheng +6
Humans can effortlessly perceive spatial layouts, form cognitive representations, reason about spatial relations, and translate such reasoning into actions in everyday 3D environme…
CityLens: Evaluating Large Vision-Language Models for Urban Socioeconomic Sensing
Tianhui Liu, Hetian Pang, Xin Zhang +5
Understanding urban socioeconomic conditions through visual data is a challenging yet essential task for sustainable urban development and policy planning. In this work, we introdu…
Breaking Data Silos: Towards Open and Scalable Mobility Foundation Models via Generative Continual Learning
Yuan Yuan, Yukun Liu, Chonghua Han +2
Human mobility is a fundamental pillar of urban science and sustainability, providing critical insights into energy consumption, carbon emissions, and public health. However, the d…