6 citations · 8 across the 7 of their papers we have counts for
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cs.CV2025
Multi-view Phase-aware Pedestrian-Vehicle Incident Reasoning Framework with Vision-Language Models
Hao Zhen, Yunxiang Yang, Jidong J. Yang
Pedestrian-vehicle incidents remain a critical urban safety challenge, with pedestrians accounting for over 20% of global traffic fatalities. Although existing video-based systems…
cs.CL2025
CrashSage: A Large Language Model-Centered Framework for Contextual and Interpretable Traffic Crash Analysis
Hao Zhen, Jidong J. Yang
Road crashes claim over 1.3 million lives annually worldwide and incur global economic losses exceeding $1.8 trillion. Such profound societal and financial impacts underscore the…
cs.LG2025★ 6 cited
Feature Group Tabular Transformer: A Novel Approach to Traffic Crash Modeling and Causality Analysis
Oscar Lares, Hao Zhen, Jidong J. Yang
Reliable and interpretable traffic crash modeling is essential for understanding causality and improving road safety. This study introduces a novel approach to predicting collision…