373 citations · 387 across the 4 of their papers we have counts for
4 papers
Added Toxicity Mitigation at Inference Time for Multimodal and Massively Multilingual Translation
Marta R. Costa-jussà, David Dale, Maha Elbayad +1
Added toxicity in the context of translation refers to the fact of producing a translation output with more toxicity than there exists in the input. In this paper, we present MinTo…
SeamlessM4T: Massively Multilingual & Multimodal Machine Translation
Seamless Communication, Loïc Barrault, Yu-An Chung +65
What does it take to create the Babel Fish, a tool that can help individuals translate speech between any two languages? While recent breakthroughs in text-based models have pushed…
Efficiently Upgrading Multilingual Machine Translation Models to Support More Languages
Simeng Sun, Maha Elbayad, Anna Sun +1
With multilingual machine translation (MMT) models continuing to grow in size and number of supported languages, it is natural to reuse and upgrade existing models to save computat…
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,…