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The role of artificially generated negative data for quality estimation of machine translation., and . EAMT, European Association for Machine Translation, (2015)A Quality-based Active Sample Selection Strategy for Statistical Machine Translation., and . LREC, page 2690-2695. European Language Resources Association (ELRA), (2014)MARMOT: A Toolkit for Translation Quality Estimation at the Word Level., , and . LREC, European Language Resources Association (ELRA), (2016)Findings of the 2016 Conference on Machine Translation., , , , , , , , , and 11 other author(s). WMT, page 131-198. The Association for Computer Linguistics, (2016)Text Detoxification using Large Pre-trained Neural Models., , , , , , and . EMNLP (1), page 7979-7996. Association for Computational Linguistics, (2021)Findings of the WMT 2018 Shared Task on Quality Estimation., , , , and . WMT (shared task), page 689-709. Association for Computational Linguistics, (2018)Taxonomy Enrichment with Text and Graph Vector Representations., , , , , and . CoRR, (2022)Findings of the 2017 Conference on Machine Translation (WMT17)., , , , , , , , , and 6 other author(s). WMT, page 169-214. Association for Computational Linguistics, (2017)Human feedback in Statistical Machine Translation.. University of Sheffield, UK, (2017)British Library, EThOS.Robust Word Vectors: Context-Informed Embeddings for Noisy Texts., , and . NUT@EMNLP, page 54-63. Association for Computational Linguistics, (2018)