2 papers
cs.CL2025
MQM Re-Annotation: A Technique for Collaborative Evaluation of Machine Translation
Parker Riley, Daniel Deutsch, Mara Finkelstein +3
Human evaluation of machine translation is in an arms race with translation model quality: as our models get better, our evaluation methods need to be improved to ensure that quali…
cs.CL2025
Don't Sweat the Small Stuff: Segment-Level Meta-Evaluation Based on Pairwise Difference Correlation
Colten DiIanni, Daniel Deutsch
This paper introduces Pairwise Difference Pearson (PDP), a novel segment-level meta-evaluation metric for Machine Translation (MT) that address limitations in previous Pearson's $ρ…