3 papers
cs.CL2025
Identification of Potentially Misclassified Crash Narratives using Machine Learning (ML) and Deep Learning (DL)
Sudesh Bhagat, Ibne Farabi Shihab, Jonathan Wood
This research investigates the efficacy of machine learning (ML) and deep learning (DL) methods in detecting misclassified intersection-related crashes in police-reported narrative…
cs.LG2025
Unlocking Insights Addressing Alcohol Inference Mismatch through Database-Narrative Alignment
Sudesh Bhagat, Raghupathi Kandiboina, Ibne Farabi Shihab +3
Road traffic crashes are a significant global cause of fatalities, emphasizing the urgent need for accurate crash data to enhance prevention strategies and inform policy developmen…
cs.CL2025
Accuracy is Not Agreement: Expert-Aligned Evaluation of Crash Narrative Classification Models
Sudesh Ramesh Bhagat, Ibne Farabi Shihab, Anuj Sharma
This study investigates the relationship between deep learning (DL) model accuracy and expert agreement in classifying crash narratives. We evaluate five DL models -- including BER…