373 citations · 392 across the 8 of their papers we have counts for
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cs.CL2022
Fixing MoE Over-Fitting on Low-Resource Languages in Multilingual Machine Translation
Maha Elbayad, Anna Sun, Shruti Bhosale
Sparsely gated Mixture of Experts (MoE) models have been shown to be a compute-efficient method to scale model capacity for multilingual machine translation. However, for low-resou…
cs.CL2022★ 373 cited
No Language Left Behind: Scaling Human-Centered Machine Translation
NLLB Team, Marta R. Costa-jussà, James Cross +36
Driven by the goal of eradicating language barriers on a global scale, machine translation has solidified itself as a key focus of artificial intelligence research today. However,…