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Bibliographic Details
Main Authors:	Samant, Yashad, Becker, Lee, Hellman, Scott, Behan, Bradley, Hughes, Sarah, Southerland, Joshua
Format:	Preprint
Published:	2025
Subjects:	Computation and Language Artificial Intelligence
Online Access:	https://arxiv.org/abs/2509.08355
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Table of Contents:

In high-stakes English Language Assessments, low-skill test takers may employ memorized materials called ``templates'' on essay questions to ``game'' or fool the automated scoring system. In this study, we introduce the automated detection of inauthentic, templated responses (AuDITR) task, describe a machine learning-based approach to this task and illustrate the importance of regularly updating these models in production.