A sparsely gated mixture-of-experts model trained on newly mined low-resource data achieves 44% relative BLEU improvement across 200 languages while adding human safety evaluation.
Shashi Shekhar, Dilip Kumar Sharma, and MM Sufyan Beg
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No Language Left Behind: Scaling Human-Centered Machine Translation
A sparsely gated mixture-of-experts model trained on newly mined low-resource data achieves 44% relative BLEU improvement across 200 languages while adding human safety evaluation.