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Assumptions, expectations and outliers in post-editing., and . EAMT, page 93-97. European Association for Machine Translation, (2014)Human versus automatic quality evaluation of NMT and PBSMT., , , , , and . Mach. Transl., 32 (3): 217-235 (2018)Improving KantanMT Training Efficiency with fast_align., , , , , and . AMTA (2), page 222-231. The Association for Machine Translation in the Americas, (2016)KantanLQR: a platform for human evaluation of machine translation output to drive engine rapid improvement.. EAMT (Projects/Products), Baltic Journal of Modern Computing, (2016)