{"ID":2872484,"CreatedAt":"2026-06-01T04:54:23.091178241Z","UpdatedAt":"2026-06-01T04:54:23.091178241Z","DeletedAt":null,"paper_url":"https://arxiv.org/abs/2509.08355","arxiv_id":"2509.08355","title":"Automatic Detection of Inauthentic Templated Responses in English Language Assessments","abstract":"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.","short_abstract":"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-b...","url_abs":"https://arxiv.org/abs/2509.08355","url_pdf":"https://arxiv.org/pdf/2509.08355v1","authors":"[\"Yashad Samant\",\"Lee Becker\",\"Scott Hellman\",\"Bradley Behan\",\"Sarah Hughes\",\"Joshua Southerland\"]","published":"2025-09-10T07:45:02Z","proceeding":"cs.CL","tasks":"[\"cs.CL\",\"cs.AI\"]","methods":"[]","has_code":false}