Scaling Neural Machine Translation to 200 Languages
Team, 2024, Scaling neural machine translation to 200 languages (Nature, vol. 630)
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Discussion
- What early real-world impact did NLLB-200 have?Four months after release it was the third most used machine translation engine among Wikipedia editors, with the lowest share of deleted articles (0.13%) among translation services; the authors stress that technology alone can’t close language gaps without education, access and literacy policies.
- Team, 2024, Scaling neural machine translation to 200 languages (Nature, vol. 630), Discussion, p. 845
Source
- NLLB Team. 2024. Scaling neural machine translation to 200 languages. In Nature, vol. 630, pp. 841–846. License: CC BY 4.0. Flashcards adapted from this work. doi:10.1038/s41586-024-07335-x