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Visualizing Neural Machine Translation Attention and Confidence.

, , and . Prague Bull. Math. Linguistics, (2017)

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Debugging Translations of Transformer-based Neural Machine Translation Systems., and . Balt. J. Mod. Comput., (2018)Customized Neural Machine Translation Systems for the Swiss Legal Domain., , , , and . AMTA (2), page 217-223. Association for Machine Translation in the Americas, (2020)Machine Translation for Livonian: Catering to 20 Speakers., , , , and . ACL (2), page 508-514. Association for Computational Linguistics, (2022)Revisiting Context Choices for Context-aware Machine Translation., and . LREC/COLING, page 14073-14079. ELRA and ICCL, (2024)AIST AIRC Submissions to the WMT23 Shared Task., and . WMT, page 155-161. Association for Computational Linguistics, (2023)Visualizing Neural Machine Translation Attention and Confidence., , and . Prague Bull. Math. Linguistics, (2017)Effective Online Learning Implementation for Statistical Machine Translation., , , and . DB&IS, volume 838 of Communications in Computer and Information Science, page 302-313. Springer, (2018)Fragmented and Valuable: Following Sentiment Changes in Food Tweets., and . CoRR, (2021)Tilde's Machine Translation Systems for WMT 2019., , and . WMT (2), page 327-334. Association for Computational Linguistics, (2019)C-3MA: Tartu-Riga-Zurich Translation Systems for WMT17., , , and . WMT, page 382-388. Association for Computational Linguistics, (2017)