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Benefiting from Language Similarity in the Multilingual MT Training: Case Study of Indonesian and Malaysian.

, и . LoResMT@COLING, стр. 84-92. Association for Computational Linguistics, (2022)

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Understanding Meanings in Multilingual Customer Feedback., , , , и . CoRR, (2018)Combining PBSMT and NMT Back-translated Data for Efficient NMT., , , , и . RANLP, стр. 922-931. INCOMA Ltd., (2019)Extracting In-domain Training Corpora for Neural Machine Translation Using Data Selection Methods., , , и . WMT, стр. 224-231. Association for Computational Linguistics, (2018)Facilitating Access to Multilingual COVID-19 Information via Neural Machine Translation., , , , , и . CoRR, (2020)ADAPT Centre Cone Team at IJCNLP-2017 Task 5: A Similarity-Based Logistic Regression Approach to Multi-choice Question Answering in an Examinations Shared Task., , , и . IJCNLP (Shared Tasks), стр. 67-72. Asian Federation of Natural Language Processing, (2017)Investigating Backtranslation in Neural Machine Translation., , , , и . EAMT, стр. 269-278. (2018)Rakuten's Participation in WAT 2022: Parallel Dataset Filtering by Leveraging Vocabulary Heterogeneity., , , , , и . WAT@COLING, стр. 68-72. International Conference on Computational Linguistics, (2022)Extending Feature Decay Algorithms Using Alignment Entropy., , и . FETLT, том 10341 из Lecture Notes in Computer Science, стр. 170-182. Springer, (2016)Rapid Development of Competitive Translation Engines for Access to Multilingual COVID-19 Information., , , , , и . Informatics, 7 (2): 19 (2020)Improved feature decay algorithms for statistical machine translation., , и . Nat. Lang. Eng., 28 (1): 71-91 (2022)