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A Large Labeled Corpus for Online Harassment Research.

, , , , , , , , , , , , , , , , , , , , , , , , , , , и . WebSci, стр. 229-233. ACM, (2017)

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Marianna Hricová

Marianna Tsaroucha

Marianna Eichenlaub

Marianna Cortese

Marianna Michaloudaki

 

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When the How Outweighs the What: the Pivotal Importance of Context., , , , , , и . BIBM, стр. 2149-2156. IEEE, (2019)Identifying Fluently Inadequate Output in Neural and Statistical Machine Translation., , , и . MTSummit (1), стр. 233-243. European Association for Machine Translation, (2019)An Exploration of Placeholding in Neural Machine Translation., , , и . MTSummit (1), стр. 182-192. European Association for Machine Translation, (2019)A Study of Style in Machine Translation: Controlling the Formality of Machine Translation Output., , и . EMNLP, стр. 2814-2819. Association for Computational Linguistics, (2017)Class-based N-gram language difference models for data selection., , , и . IWSLT, (2015)Can Statistical Post-Editing with a Small Parallel Corpus Save a Weak MT Engine?. LREC, стр. 2138-2142. European Language Resources Association (ELRA), (2012)Understanding and Detecting Hallucinations in Neural Machine Translation via Model Introspection., , , , и . CoRR, (2023)An Empirical Exploration of Curriculum Learning for Neural Machine Translation., , , , , , , , и . CoRR, (2018)Fluency Over Adequacy: A Pilot Study in Measuring User Trust in Imperfect MT., и . AMTA (1), стр. 13-25. Association for Machine Translation in the Americas, (2018)MoJo: Bringing Hybrid MT to the Center for Applied Machine Translation.. AMTA (2), стр. 654-714. The Association for Machine Translation in the Americas, (2016)