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Document Flattening: Beyond Concatenating Context for Document-Level Neural Machine Translation.

, , , and . EACL, page 448-462. Association for Computational Linguistics, (2023)

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Statistical Machine Translation for Bilingually Low-Resource Scenarios: A Round-Tripping Approach., , and . CIST, page 261-265. IEEE, (2018)Leveraging Linguistic Resources for Improving Neural Text Classification., , , and . ALTA, page 34-42. (2017)Inter-document Contextual Language model., , and . HLT-NAACL, page 762-766. The Association for Computational Linguistics, (2016)Tutorial on Inductive Semi-supervised Learning Methods: with Applicability to Natural Language Processing., and . HLT-NAACL, The Association for Computational Linguistics, (2006)Feature-based Learning for Diverse and Privacy-Preserving Counterfactual Explanations., , , , , , and . KDD, page 2211-2222. ACM, (2023)Bayesian Extraction of Minimal SCFG Rules for Hierarchical Phrase-based Translation., , and . WMT@EMNLP, page 533-541. Association for Computational Linguistics, (2011)Iterative Back-Translation for Neural Machine Translation., , , and . NMT@ACL, page 18-24. Association for Computational Linguistics, (2018)Learning Coupled Policies for Simultaneous Machine Translation using Imitation Learning., , and . EACL, page 2709-2719. Association for Computational Linguistics, (2021)A Hierarchical Neural Model for Learning Sequences of Dialogue Acts., , and . EACL (1), page 428-437. Association for Computational Linguistics, (2017)Homotopy-Based Semi-Supervised Hidden Markov Models for Sequence Labeling., and . COLING, page 305-312. (2008)