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Attaining the Unattainable? Reassessing Claims of Human Parity in Neural Machine Translation., , , and . WMT, page 113-123. Association for Computational Linguistics, (2018)DELA Corpus - A Document-Level Corpus Annotated with Context-Related Issues., , , and . WMT@EMNLP, page 566-577. Association for Computational Linguistics, (2021)Do online Machine Translation Systems Care for Context? What About a GPT Model?, , , and . EAMT, page 393-417. European Association for Machine Translation, (2023)On Context Span Needed for Machine Translation Evaluation., , and . LREC, page 3735-3742. European Language Resources Association, (2020)Improving Machine Translation of Educational Content via Crowdsourcing., , , , , , , , , and 4 other author(s). LREC, European Language Resources Association (ELRA), (2018)Deep Dive Machine Translation., , , , , , , , , and 9 other author(s). European Language Equality, Springer, (2023)On the Same Page? Comparing Inter-Annotator Agreement in Sentence and Document Level Human Machine Translation Evaluation.. WMT@EMNLP, page 1150-1159. Association for Computational Linguistics, (2020)Does post-editing increase usability? A study with Brazilian Portuguese as target language., , , and . EAMT, page 183-190. European Association for Machine Translation, (2014)Chan Sin-Wai (ed): The human factor in machine translation - Routledge Studies in Translation Technology, Routledge, 1st edition (2018), xii+256pp, ISBN 781-13-855-1213 (Hardback), 978-13-151-4753-6 (e-book).. Mach. Transl., 33 (3): 259-268 (2019)Translation Crowdsourcing: Creating a Multilingual Corpus of Online Educational Content., , , , , , , , , and . LREC, European Language Resources Association (ELRA), (2018)