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Item Difficulty and Response Time Prediction with Large Language Models: An Empirical Analysis of USMLE Items
Download2024-06-20
Bulut, O., Gorgun, G., Tan, B.
This paper summarizes our methodology and results for the BEA 2024 Shared Task. This competition focused on predicting item difficulty and response time for retired multiple-choice items from the United States Medical Licensing Examination® (USMLE®). We extracted linguistic features from the item...
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