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Author

Rejwanul Haque

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#artificial intelligence Preprint Oct 2026

Investigating Model Compression for Neural Machine Translation in the Biomedical Domain

Large-scale pretrained transformer models have achieved state-of-the-art performance across diverse machine translation tasks, including multilingual settings. Knowledge distillation has emerged as a sustainable approach for model compression, transferring knowledge from large teacher models to smaller, more efficient...

Maria Zafar, Souhail Bakkali, Rejwanul Haque · 0 citations
Review Open access Jul 2026

A survey of gender bias mitigation in neural machine translation

Transformer-based models are the current state-of-the-art in machine translation (MT) research. These systems can generate fluent and contextually appropriate translations for many translation tasks and languages. These models are trained on large amounts of unlabelled data, often consisting of billions of examples, an...

Neha Gajakos, Christopher Staff, Brenda Murphy et al. · 0 citations

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