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41
In Neural Machine Translation, What Does Transfer Learning Transfer? ...
Aji, Alham Fikri; Bogoychev, Nikolay; Heafield, Kenneth. - : Association for Computational Linguistics, 2020
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42
Understanding Pure Character-Based Neural Machine Translation: The Case of Translating Finnish into English
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)
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43
Domain robustness in neural machine translation
In: Müller, Mathias; Rios, Annette; Sennrich, Rico (2020). Domain robustness in neural machine translation. In: 14th Conference of the Association for Machine Translation in the Americas (AMTA 2020), Virtual, 6 October 2020 - 9 October 2020. Association for Machine Translation in the Americas, 151-164. (2020)
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44
In Neural Machine Translation, What Does Transfer Learning Transfer?
In: Aji, Alham Fikri; Bogoychev, Nikolay; Heafield, Kenneth; Sennrich, Rico (2020). In Neural Machine Translation, What Does Transfer Learning Transfer? In: Proceedings of the 58th Annual Meeting of the Association for Computational Linguistics, Online, 5 July 2020 - 10 July 2020, 7701-7710. (2020)
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45
On Exposure Bias, Hallucination and Domain Shift in Neural Machine Translation
In: Wang, Chaojun; Sennrich, Rico (2020). On Exposure Bias, Hallucination and Domain Shift in Neural Machine Translation. In: Proceedings of the 58th Annual Meeting of the Association for Computational Linguistics, Online, 5 July 2020 - 10 July 2020. Association for Computational Linguistics, 3544-3552. (2020)
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46
Lost in translation: loss and decay of linguistic richness in machine translation
In: Way, Andy orcid:0000-0001-5736-5930 , Shterionov, Dimitar orcid:0000-0001-6300-797X and Vanmassenhove, Eva orcid:0000-0003-1162-820X (2019) Lost in translation: loss and decay of linguistic richness in machine translation. In: MT Summit XVII, 19-23 Aug 2019, Dublin,Ireland. (2019)
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47
Analyzing Multi-Head Self-Attention: Specialized Heads Do the Heavy Lifting, the Rest Can Be Pruned ...
Voita, Elena; Talbot, David; Moiseev, Fedor. - : Association for Computational Linguistics, 2019
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48
Improving Deep Transformer with Depth-Scaled Initialization and Merged Attention ...
Zhang, Biao; Titov, Ivan; Sennrich, Rico. - : Association for Computational Linguistics, 2019
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49
The Bottom-up Evolution of Representations in the Transformer: A Study with Machine Translation and Language Modeling Objectives ...
Voita, Elena; Sennrich, Rico; Titov, Ivan. - : Association for Computational Linguistics, 2019
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50
Revisiting Low-Resource Neural Machine Translation: A Case Study ...
Sennrich, Rico; Zhang, Biao. - : Association for Computational Linguistics, 2019
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51
Context-Aware Monolingual Repair for Neural Machine Translation ...
Voita, Elena; Sennrich, Rico; Titov, Ivan. - : Association for Computational Linguistics, 2019
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52
A Lightweight Recurrent Network for Sequence Modeling ...
Zhang, Biao; Sennrich, Rico. - : Association for Computational Linguistics, 2019
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53
Encoders Help You Disambiguate Word Senses in Neural Machine Translation ...
Tang, Gongbo; Sennrich, Rico; Nivre, Joakim. - : Association for Computational Linguistics, 2019
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54
Encoders Help You Disambiguate Word Senses in Neural Machine Translation ...
Abstract: Neural machine translation (NMT) has achieved new state-of-the-art performance in translating ambiguous words. However, it is still unclear which component dominates the process of disambiguation. In this paper, we explore the ability of NMT encoders and decoders to disambiguate word senses by evaluating hidden states and investigating the distributions of self-attention. We train a classifier to predict whether a translation is correct given the representation of an ambiguous noun. We find that encoder hidden states outperform word embeddings significantly which indicates that encoders adequately encode relevant information for disambiguation into hidden states. Decoders could provide further relevant information for disambiguation. Moreover, the attention weights and attention entropy show that self-attention can detect ambiguous nouns and distribute more attention to the context. Note that this is a revised version. The content related to decoder hidden states has been updated. ... : Update with corrections. Here is the link to the erratum: https://www.aclweb.org/anthology/D19-1149e1.pdf ...
Keyword: Computation and Language cs.CL; FOS Computer and information sciences
URL: https://dx.doi.org/10.48550/arxiv.1908.11771
https://arxiv.org/abs/1908.11771
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55
When a Good Translation is Wrong in Context: Context-Aware Machine Translation Improves on Deixis, Ellipsis, and Lexical Cohesion ...
Voita, Elena; Sennrich, Rico; Titov, Ivan. - : Association for Computational Linguistics, 2019
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56
Widening the Representation Bottleneck in Neural Machine Translation with Lexical Shortcuts ...
Emelin, Denis; Titov, Ivan; Sennrich, Rico. - : Association for Computational Linguistics, 2019
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57
Samsung and University of Edinburgh’s System for the IWSLT 2019
In: Wetesko, Joanna; Chochowski, Marcin; Przybysz, Pawel; Williams, Philip; Grundkiewicz, Roman; Sennrich, Rico; Haddow, Barry; Miceli Barone, Antonio Valerio; Birch, Alexandra (2019). Samsung and University of Edinburgh’s System for the IWSLT 2019. In: 16th International Workshop on Spoken Language Translation 2019, Hong Kong, 2 November 2019 - 3 November 2019. (2019)
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58
Evaluating MT for massive open online courses : A multifaceted comparison between PBSMT and NMT systems [<Journal>]
DNB Subject Category Language
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59
Improving machine translation of educational content via crowdsourcing
In: Behnke, Maximiliana, Miceli Barone, Antonio Valerio, Sennrich, Rico, Sosoni, Vilelmini, Naskos, Thanasis, Takoulidou, Eirini, Stasimioti, Maria, Menno, van Zaanen, Castilho, Sheila orcid:0000-0002-8416-6555 , Gaspari, Federico orcid:0000-0003-3808-8418 , Georgakopoulou, Panayota orcid:0000-0001-9780-1813 , Kordoni, Valia, Egg, Markus and Kermanidis, Katia Lida orcid:0000-0002-3270-5078 (2018) Improving machine translation of educational content via crowdsourcing. In: LREC 2018 - 11th International Conference on Language Resources and Evaluation, Miyazaki, Japan. ISBN 979-10-95546-19-1 (2018)
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60
Evaluating Discourse Phenomena in Neural Machine Translation
In: 16th Annual Conference of the North American Chapter of the Association for Computational Linguistics: Human Language Technologies ; https://hal.archives-ouvertes.fr/hal-01800739 ; 16th Annual Conference of the North American Chapter of the Association for Computational Linguistics: Human Language Technologies, 2018, New Orleans, United States. pp.1304-1313 (2018)
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