Tootfinder

CityLens: Benchmarking Large Language-Vision Models for Urban Socioeconomic Sensing
Tianhui Liu, Jie Feng, Hetian Pang, Xin Zhang, Tianjian Ouyang, Zhiyuan Zhang, Yong Li
https://arxiv.org/abs/2506.00530

CityLens: Benchmarking Large Language-Vision Models for Urban Socioeconomic Sensing
Understanding urban socioeconomic conditions through visual data is a challenging yet essential task for sustainable urban development and policy planning. In this work, we introduce $\textbf{CityLens}$, a comprehensive benchmark designed to evaluate the capabilities of large language-vision models (LLVMs) in predicting socioeconomic indicators from satellite and street view imagery. We construct a multi-modal dataset covering a total of 17 globally distributed cities, spanning 6 key domains: e…

This https://arxiv.org/abs/2410.24120 has been replaced.
initial toot: https://mastoxiv.page/@arX…

Impact of normal lung volume choices on radiation pneumonitis risk prediction in locally advanced NSCLC radiotherapy
This study is to evaluate the impact of lung volume choices on predicting radiation pneumonitis (RP) risk in patients with locally advanced NSCLC undergoing radiotherapy. Dosimetric variables V20, V5, and mean lung dose (MLD) were extracted from the treatment plans of 442 patients enrolled in the NRG Oncology RTOG 0617 trial. Three lung volumes were defined: total lung excluding gross-tumor-target (TL-GTV), total lung excluding clinical-target-volume (TL-CTV), and total lung excluding planning-…