No Language Left Behind: Scaling Human-Centered Machine Translation — mentioned by mortimerp9

Fri, 01 Dec 2023 20:30:43 GMT

Sorry if I wasn't clear, internally we've been talking about it a lot, but I forgot that it doesn't have such a solid definition outside of our work. Thankfully, we try to define it in section 7.3 of the NLLB paper: https://arxiv.org/pdf/2207.04672.pdf The tldr is that if you say: "Thank you for this job offer." you wouldn't want it to be (mis)translated as "Go F*k yourself.". But if you do say "Go F yourself", you still want it to be translated as that.

Paper and discussion history. A mention is not an endorsement.

No Language Left Behind: Scaling Human-Centered Machine Translation — mentioned by mortimerp9

Fri, 01 Dec 2023 20:25:11 GMT

Our goal is to have a good recall, sometimes to the detriment of precision, so for words with multiple meanings, it might consider them toxic when in the actual context they are used in, they are not. The toxicity mitigation algorithm will search for alternative translations that have the correct meaning but not the potentially toxic word so that there is no added toxicity in the output. This means that sometimes the model might prefer a less coloquial phrasing than what a human would. You can find details on how the multi-language creation of the toxicity lists was done in section 7.3 of the…

Paper and discussion history. A mention is not an endorsement.

No Language Left Behind: Scaling Human-Centered Machine Translation · HackerPapers discussions

No Language Left Behind: Scaling Human-Centered Machine Translation — mentioned by mortimerp9

No Language Left Behind: Scaling Human-Centered Machine Translation — mentioned by mortimerp9