3 papers
cs.CL2025
Toward Machine Translation Literacy: How Lay Users Perceive and Rely on Imperfect Translations
Yimin Xiao, Yongle Zhang, Dayeon Ki +5
As Machine Translation (MT) becomes increasingly commonplace, understanding how the general public perceives and relies on imperfect MT is crucial for contextualizing MT research i…
cs.CL2018
An Empirical Exploration of Curriculum Learning for Neural Machine Translation
Xuan Zhang, Gaurav Kumar, Huda Khayrallah +6
Machine translation systems based on deep neural networks are expensive to train. Curriculum learning aims to address this issue by choosing the order in which samples are presente…
cs.CL2018
Fluency Over Adequacy: A Pilot Study in Measuring User Trust in Imperfect MT
Marianna J. Martindale, Marine Carpuat
Although measuring intrinsic quality has been a key factor in the advancement of Machine Translation (MT), successfully deploying MT requires considering not just intrinsic quality…