most citedIntegrating Spatiotemporal Vision Transformer into Digital Twins for High-Resolution Heat Stress Forecasting in Campus Environments

2 citations · 2 across the 5 of their papers we have counts for

collaborators

5 papers

cs.CV2026

RAPID: A Reproducible Multi-Agent Pipeline for Interpretable Disaster Damage Assessment from Satellite and Street-View Imagery

Yifan Yang, Wenjing Gong, Kaili Zhang +5

Due to the increasing frequency and intensity of extreme climate events, there is a clear demand for intelligent, scalable, and autonomous approaches to disaster damage assessment.…

cs.IR2026

GIScholarBench: Benchmarking LLM Overconfidence in GIS Research

Zongrng Li, Mingzheng Yang, Lei Zou +8

Large language models (LLMs) are increasingly used in academic research workflows, but scholarly tasks require high factual precision and therefore expose a key weakness: overconfi…

cs.LG2026

Earth Embeddings Reveal Diverse Urban Signals from Space

Wenjing Gong, Udbhav Srivastava, Yuchen Wang +6

Conventional urban indicators derived from censuses, surveys, and administrative records are often costly, spatially inconsistent, and slow to update. Recent geospatial foundation…

cs.CV2026

DamageArbiter: A Multimodal Arbitration Framework for Disaster Damage Assessment from Street-View Imagery

Yifan Yang, Lei Zou, Wenjing Gong +6

Analyzing street-view imagery with computer vision models offers a promising approach for rapid, hyperlocal disaster damage assessment, but existing approaches typically rely on bl…

cs.CV20252 cited

Integrating Spatiotemporal Vision Transformer into Digital Twins for High-Resolution Heat Stress Forecasting in Campus Environments

Wenjing Gong, Xinyue Ye, Keshu Wu +4

Extreme heat events, exacerbated by climate change, pose significant challenges to urban resilience and planning. This study introduces a climate-responsive digital twin framework…