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All fields Title Creator / Publisher Keyword Year AND OR AND NOT All fields Title Creator / Publisher Keyword Year AND OR AND NOT All fields Title Creator / Publisher Keyword Year AND OR AND NOT All fields Title Creator / Publisher Keyword Year AND OR AND NOT All fields Title Creator / Publisher Keyword Year Sort by creator [A → Z]' creator [Z → A]' publishing year ↑ (asc)' publishing year ↓ (desc)' title [A → Z]' title [Z → A]' Simple Search Hits 1 – 8 of 8 1 Revisiting Negation in Neural Machine Translation ... The Joint Conference of the 59th Annual Meeting of the Association for Computational Linguistics and the 11th International Joint Conference on Natural Language Processing 2021; Nivre, Joakim; Rönchen, Philipp. - : Underline Science Inc., 2021 BASE Show details 2 Understanding Pure Character-Based Neural Machine Translation: The Case of Translating Finnish into English ... Tang, Gongbo; Sennrich, Rico; Nivre, Joakim. - : arXiv, 2020 Abstract: Recent work has shown that deeper character-based neural machine translation (NMT) models can outperform subword-based models. However, it is still unclear what makes deeper character-based models successful. In this paper, we conduct an investigation into pure character-based models in the case of translating Finnish into English, including exploring the ability to learn word senses and morphological inflections and the attention mechanism. We demonstrate that word-level information is distributed over the entire character sequence rather than over a single character, and characters at different positions play different roles in learning linguistic knowledge. In addition, character-based models need more layers to encode word senses which explains why only deeper models outperform subword-based models. The attention distribution pattern shows that separators attract a lot of attention and we explore a sparse word-level attention to enforce character hidden states to capture the full word-level information. ... : accepted by COLING 2020, camera-ready version ... Keyword: Computation and Language cs.CL; FOS Computer and information sciences URL: https://arxiv.org/abs/2011.03469 https://dx.doi.org/10.48550/arxiv.2011.03469 BASE Hide details 3 Understanding Pure Character-Based Neural Machine Translation: The Case of Translating Finnish into English ... Tang, Gongbo; Sennrich, Rico; Nivre, Joakim. - : International Committee on Computational Linguistics, 2020 BASE Show details 4 Understanding Pure Character-Based Neural Machine Translation: The Case of Translating Finnish into English Tang, Gongbo; Sennrich, Rico; Nivre, Joakim In: Tang, Gongbo; Sennrich, Rico; Nivre, Joakim (2020). Understanding Pure Character-Based Neural Machine Translation: The Case of Translating Finnish into English. In: Proceedings of the 28th International Conference on Computational Linguistics, Barcelona, Spain, 8 December 2020 - 13 December 2020, 4251-4262. (2020) BASE Show details 5 Encoders Help You Disambiguate Word Senses in Neural Machine Translation ... Tang, Gongbo; Sennrich, Rico; Nivre, Joakim. - : Association for Computational Linguistics, 2019 BASE Show details 6 Encoders Help You Disambiguate Word Senses in Neural Machine Translation ... Tang, Gongbo; Sennrich, Rico; Nivre, Joakim. - : arXiv, 2019 BASE Show details 7 An Analysis of Attention Mechanisms: The Case of Word Sense Disambiguation in Neural Machine Translation ... Tang, Gongbo; Sennrich, Rico; Nivre, Joakim. - : Association for Computational Linguistics, 2018 BASE Show details 8 An Analysis of Attention Mechanisms: The Case of Word Sense Disambiguation in Neural Machine Translation ... Tang, Gongbo; Sennrich, Rico; Nivre, Joakim. - : arXiv, 2018 BASE Show details

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