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Improving Arabic Clinical Question Quality through Domain-Adaptive Masked Language Modeling

2025-11-19

Abstract excerpt

<title>Abstract</title> <p>Arabic clinical NLP systems often receive short, vague, or incomplete questions, which yields weak downstream answers even with strong encoders. We address this bottleneck by making question quality a first-class, measurable objective. Using domain-adaptive (continued) pretraining with a masked-language objective (DAPT-MLM) on AHQAD (~ 808k Arabic health Q–A pairs), we adapt two widely...

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Literature Corpus work: bbedcdb6-841c-5f93-abe9-d418de21274b
DOI: 10.21203/rs.3.rs-8007820/v1

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