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An Empirical Exploration of Curriculum Learning for Neural Machine Translation., , , , , , , , and . CoRR, (2018)The JHU Machine Translation Systems for WMT 2017., , , , , and . WMT, page 276-282. Association for Computational Linguistics, (2017)The JHU Parallel Corpus Filtering Systems for WMT 2018., , and . WMT (shared task), page 896-899. Association for Computational Linguistics, (2018)Simulated multiple reference training improves low-resource machine translation., , , and . EMNLP (1), page 82-89. Association for Computational Linguistics, (2020)HABLex: Human Annotated Bilingual Lexicons for Experiments in Machine Translation., , , , , and . EMNLP/IJCNLP (1), page 1382-1387. Association for Computational Linguistics, (2019)Improved Lexically Constrained Decoding for Translation and Monolingual Rewriting., , , , , , and . NAACL-HLT (1), page 839-850. Association for Computational Linguistics, (2019)Overcoming Catastrophic Forgetting During Domain Adaptation of Neural Machine Translation., , , , and . NAACL-HLT (1), page 2062-2068. Association for Computational Linguistics, (2019)The JHU Machine Translation Systems for WMT 2016., , , , and . WMT, page 272-280. The Association for Computer Linguistics, (2016)Paradigm Completion for Derivational Morphology., , , , and . EMNLP, page 714-720. Association for Computational Linguistics, (2017)An Interactive Teaching Tool for Introducing Novices to Machine Translation., , , and . SIGCSE, page 1276. ACM, (2019)