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When less is more in Neural Quality Estimation of Machine Translation. An industry case study., , , , , , and . MTSummit (2), page 228-235. European Association for Machine Translation, (2019)Crucial components in probabilistic inference pipelines., and . SAC, page 1887-1889. ACM, (2015)ABI Neural Ensemble Model for Gender Prediction., , , , and . GxG@CLIN, volume 2453 of CEUR Workshop Proceedings, page 53-61. CEUR-WS.org, (2019)An Investigative Study of Multi-Modal Cross-Lingual Retrieval., , , , , and . CLSSTS@LREC, page 58-67. European Language Resources Association, (2020)Design and Development of Probabilistic Inference Pipelines ; Ontwerp en ontwikkeling van een pijpleiding architectuur voor probabilistische inferentie.. Katholieke Universiteit Leuven, Belgium, (2015)base-search.net (ftunivleuven:oai:lirias.kuleuven.be:123456789/502578).Integration of a Multilingual Preordering Component into a Commercial SMT Platform., , , , and . Prague Bull. Math. Linguistics, (2017)Towards language-agnostic alignment of product titles and descriptions: a neural approach., , and . WWW (Companion Volume), page 387-392. ACM, (2019)A roadmap to neural automatic post-editing: an empirical approach., , , , , , , , and . Mach. Transl., 34 (2-3): 67-96 (2020)Machine Translationese: Effects of Algorithmic Bias on Linguistic Complexity in Machine Translation., , and . EACL, page 2203-2213. Association for Computational Linguistics, (2021)Combining PBSMT and NMT Back-translated Data for Efficient NMT., , , , and . RANLP, page 922-931. INCOMA Ltd., (2019)