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On Using Very Large Target Vocabulary for Neural Machine Translation
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Sébastien Jean, Kyunghyun Cho, Roland Memisevic, Yoshua Bengio. Proceedings of the 53rd Annual Meeting of the Association for Computational Linguistics and the 7th International Joint Conference on Natural Language Processing (Volume 1: Long Papers). 2015.
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Copying unknown words into the target text is a reasonable strategy for names.
“Copying unknown words into the target text, as done by (Jean et al., 2015;Luong et al., 2015b), is a reasonable strategy for names”
From Neural Machine Translation of Rare Words with Subword Units (2016) · cites this paper as Jean et al., 2015
The paper's architecture is simpler and more effective than using large vocabularies and back-off dictionaries.
“We find our architecture simpler and more effective than using large vocabularies and back-off dictionaries (Jean et al., 2015;Luong et al., 2015b).”
From Neural Machine Translation of Rare Words with Subword Units (2016) · cites this paper as Jean et al., 2015
For word-level NMT models, the translation of out-of-vocabulary words has been addressed through a back-off to a dictionary look-up.
“For word-level NMT models, the translation of out-of-vocabulary words has been addressed through a back-off to a dictionary look-up (Jean et al., 2015;Luong et al., 2015b).”
From Neural Machine Translation of Rare Words with Subword Units (2016) · cites this paper as Jean et al., 2015
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Metadata
- Authors
- Jean, S., Cho, K., Memisevic, R., & Bengio, Y.
- Affiliations
- Université de Montréal (CA)
- Venue
- Proceedings of the 53rd Annual Meeting of the Association for Computational Linguistics and the 7th International Joint Conference on Natural Language Processing (Volume 1: Long Papers)
- Published
- 2015
- Pages
- 1-10
- OpenAlex
- W2100664567
- Cited by
- 862
- References
- 2
- Citations by year
- 2026: 11 · 2025: 12 · 2024: 28 · 2023: 54 · 2022: 51 · 2021: 76 · 2020: 109 · 2019: 130 · 2018: 153 · 2017: 114 · 2016: 98 · 2015: 23
- FWCI
- 69.64
- Type
- conference paper
- Language
- en
- Open access
- gold
- doi.org
- Licence
- cc-by
- Funders
- Canadian Institute for Advanced Research
- Compute Canada
- Canada Research Chairs
- Samsung
- Natural Sciences and Engineering Research Council of Canada
- Topics
- Physical Sciences › Computer Science › Artificial Intelligence › Natural Language Processing Techniques
- Physical Sciences › Computer Science › Artificial Intelligence › Topic Modeling
- Physical Sciences › Computer Science › Artificial Intelligence › Speech Recognition and Synthesis
- Keywords
- neural machine translation, vocabulary size, low-resource languages
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