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19942023
most citedMassively Multilingual Neural Machine Translation in the Wild: Findings and Challenges

293 citations · 839 across the 16 of their papers we have counts for

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Showing 2021Show all

2 papers · 1 filter

cs.CL2021★ 263 cited

Experts, Errors, and Context: A Large-Scale Study of Human Evaluation for Machine Translation

Markus Freitag, George Foster, David Grangier +3

Human evaluation of modern high-quality machine translation systems is a difficult problem, and there is increasing evidence that inadequate evaluation procedures can lead to erron…

cs.CL2021

Assessing Reference-Free Peer Evaluation for Machine Translation

Sweta Agrawal, George Foster, Markus Freitag +1

Reference-free evaluation has the potential to make machine translation evaluation substantially more scalable, allowing us to pivot easily to new languages or domains. It has been…