1 citations · 1 across the 10 of their papers we have counts for
10 papers
Learning Continuous Regional Temperature Fields with Lead-Time and Resolution Queries
Chunlei Shi, Jiong Wang, Yi-Lin Wei +4
Accurate regional near-surface temperature forecasting is fundamental to short-range weather services and downstream risk assessment. Existing deep learning-based regional forecast…
WaveOp-LiteFM: Lightweight Neural-Operator Flow Matching for Satellite-to-Radar Precipitation Retrieval
Chunlei Shi, Yecheng Zhang, Yufeng Zhu +4
Satellite-to-radar (S2R) retrieval refers to estimating ground-based radar precipitation from geostationary satellite observations, enabling precipitation monitoring in regions wit…
Mapping the City Through the Lens of Language Models
Wanqi Liu, Rong Zhao, Zhizhou Sha +2
Language models often complete an underspecified reference to a city with unstated assumptions about urban size, form, infrastructure, environment, and function. We measure those a…
LangRetrieval: Language-Guided Self-Evolving Satellite-to-Radar Retrieval via CSI-Driven Reward
Chunlei Shi, Junming Hou, Yi-Lin Wei +5
Satellite-to-radar (S2R) retrieval estimates ground radar precipitation from geostationary satellite observations, providing a critical solution for precipitation monitoring in rad…
Culturally uneven urban perception in large language models
Rong Zhao, Wanqi Liu, Zhizhou Sha +3
Large language models (LLMs) are increasingly used to describe and evaluate cities, yet the cultural structure of their urban judgments remains understudied. Here we introduce a me…
UrbanAlign: Post-hoc Semantic Calibration for VLM-Human Preference Alignment
Yecheng Zhang, Rong Zhao, Zhizhou Sha +10
Vision-language models (VLMs) can describe urban scenes in rich detail, yet consistently fail to produce reliable human preference labels in domain-specific tasks such as safety as…
WaveC2R: Wavelet-Driven Coarse-to-Refined Hierarchical Learning for Radar Retrieval
Chunlei Shi, Han Xu, Yinghao Li +4
Satellite-based radar retrieval methods are widely employed to fill coverage gaps in ground-based radar systems, especially in remote areas affected by terrain blockage and limited…
GenAI Models Capture Urban Science but Oversimplify Complexity
Yecheng Zhang, Rong Zhao, Zimu Huang +3
Generative artificial intelligence (GenAI) models are increasingly used for scientific data generation, yet their alignment with empirical knowledge in urban science remains unclea…
CMAB: A First National-Scale Multi-Attribute Building Dataset in China Derived from Open Source Data and GeoAI
Yecheng Zhang, Huimin Zhao, Ying Long
Rapidly acquiring three-dimensional (3D) building data, including geometric attributes like rooftop, height and orientations, as well as indicative attributes like function, qualit…
Inferring ghost cities on the globe in newly developed urban areas based on urban vitality with multi-source data
Yecheng Zhang, Tangqi Tu, Ying long
Due to rapid urbanization over the past 20 years, many newly developed areas have lagged in socio-economic maturity, creating an imbalance with older cities and leading to the rise…