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TransBERT: A Framework for Synthetic Translation in Domain-Specific Language Modeling

arXiv · AI, language, vision and robotics · article · Sep 22, 2026 · UTC

The scarcity of non-English language data in specialized domains significantly limits the development of effective Natural Language Processing (NLP) tools. We present TransBERT, a novel framework for pre-training language models using exclusively synthetically translated text, and introduce TransCorpus, a scalable translation toolkit. Focusing on the life sciences domain in French, our approach demonstrates that state-of-the-art performance on various downstream tasks can be achieved solely by leveraging synthetically translated data. We release the TransCorpus toolkit, the TransCorpus-bio-fr

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Evidence & attribution

First collected: 2026-09-23T04:11:12.117Z. This is not the publication date.