263 citations · 284 across the 4 of their papers we have counts for
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Toward More Effective Human Evaluation for Machine Translation
Belén Saldías, George Foster, Markus Freitag +1
Improvements in text generation technologies such as machine translation have necessitated more costly and time-consuming human evaluation procedures to ensure an accurate signal.…
High Quality Rather than High Model Probability: Minimum Bayes Risk Decoding with Neural Metrics
Markus Freitag, David Grangier, Qijun Tan +1
In Neural Machine Translation, it is typically assumed that the sentence with the highest estimated probability should also be the translation with the highest quality as measured…
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…
Learning to Evaluate Translation Beyond English: BLEURT Submissions to the WMT Metrics 2020 Shared Task
Thibault Sellam, Amy Pu, Hyung Won Chung +5
The quality of machine translation systems has dramatically improved over the last decade, and as a result, evaluation has become an increasingly challenging problem. This paper de…