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When less is more in Neural Quality Estimation of Machine Translation. An industry case study., , , , , , и . MTSummit (2), стр. 228-235. European Association for Machine Translation, (2019)Crucial components in probabilistic inference pipelines., и . SAC, стр. 1887-1889. ACM, (2015)ABI Neural Ensemble Model for Gender Prediction., , , , и . GxG@CLIN, том 2453 из CEUR Workshop Proceedings, стр. 53-61. CEUR-WS.org, (2019)An Investigative Study of Multi-Modal Cross-Lingual Retrieval., , , , , и . CLSSTS@LREC, стр. 58-67. European Language Resources Association, (2020)Integration of a Multilingual Preordering Component into a Commercial SMT Platform., , , , и . Prague Bull. Math. Linguistics, (2017)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).Towards language-agnostic alignment of product titles and descriptions: a neural approach., , и . WWW (Companion Volume), стр. 387-392. ACM, (2019)A roadmap to neural automatic post-editing: an empirical approach., , , , , , , , и . Mach. Transl., 34 (2-3): 67-96 (2020)Machine Translationese: Effects of Algorithmic Bias on Linguistic Complexity in Machine Translation., , и . EACL, стр. 2203-2213. Association for Computational Linguistics, (2021)Combining PBSMT and NMT Back-translated Data for Efficient NMT., , , , и . RANLP, стр. 922-931. INCOMA Ltd., (2019)