Purely machine-translated corpus reaches SOTA French biomedical pretraining

Pretraining on purely machine-translated text reportedly reaches state-of-the-art results on French life-sciences downstream tasks, accompanied by a released 36.4GB French life-sciences corpus.

Low-resource languages and domains have long been constrained by scarce native corpora; the author team claims this route bypasses that bottleneck, and has released the TransCorpus toolkit, the pretrained TransBERT-bio-fr model, and reproducible code.

All performance conclusions come from the authors' own evaluations (self-reported), on French life-sciences downstream tasks, with no third-party comparison numbers; accepted to EMNLP 2025 Findings, with no independent reproduction yet — for most readers this is a method signal for low-resource language/domain modeling to track.