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Document-level Neural MT: A Systematic Comparison.

, , , , and . EAMT, page 225-234. European Association for Machine Translation, (2020)

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Continuous Learning from Human Post-Edits for Neural Machine Translation., , , and . Prague Bull. Math. Linguistics, (2017)Unbabel's Submission to the WMT2019 APE Shared Task: BERT-Based Encoder-Decoder for Automatic Post-Editing., , , , and . WMT (3), page 118-123. Association for Computational Linguistics, (2019)Online Word Alignment for Online Adaptive Machine Translation., , and . HaCaT@EACL, page 84-92. Association for Computational Linguistics, (2014)WAGS: A Beautiful English-Italian Benchmark Supporting Word Alignment Evaluation on Rare Words., , , and . LREC, European Language Resources Association (ELRA), (2016)Multi-Domain Neural Machine Translation through Unsupervised Adaptation., , , and . WMT, page 127-137. Association for Computational Linguistics, (2017)FBK's machine translation systems for the IWSLT 2013 evaluation campaign., , , , and . IWSLT (Evaluation Campaign), (2013)FBK's Neural Machine Translation Systems for IWSLT 2016., , , , , , , , , and . IWSLT, International Workshop on Spoken Language Translation, (2016)Tower: An Open Multilingual Large Language Model for Translation-Related Tasks., , , , , , , , , and 3 other author(s). CoRR, (2024)Is Context Helpful for Chat Translation Evaluation?, , , , and . CoRR, (2024)Unbabel's Participation in the WMT19 Translation Quality Estimation Shared Task., , , , , , , and . WMT (3), page 78-84. Association for Computational Linguistics, (2019)