A survey of cross-lingual word embedding models
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Authors
Ruder, S
Vulić, I
Søgaard, A
Publication Date
2019Journal Title
Journal of Artificial Intelligence Research
ISSN
1076-9757
Publisher
AI Access Foundation
Volume
65
Pages
569-631
Type
Article
Metadata
Show full item recordCitation
Ruder, S., Vulić, I., & Søgaard, A. (2019). A survey of cross-lingual word embedding models. Journal of Artificial Intelligence Research, 65 569-631. https://doi.org/10.1613/JAIR.1.11640
Abstract
<jats:p>Cross-lingual representations of words enable us to reason about word meaning in multilingual contexts and are a key facilitator of cross-lingual transfer when developing natural language processing models for low-resource languages. In this survey, we provide a comprehensive typology of cross-lingual word embedding models. We compare their data requirements and objective functions. The recurring theme of the survey is that many of the models presented in the literature optimize for the same objectives, and that seemingly different models are often equivalent, modulo optimization strategies, hyper-parameters, and such. We also discuss the different ways cross-lingual word embeddings are evaluated, as well as future challenges and research horizons.</jats:p>
Sponsorship
European Research Council (648909)
Identifiers
External DOI: https://doi.org/10.1613/JAIR.1.11640
This record's URL: https://www.repository.cam.ac.uk/handle/1810/283100
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http://www.rioxx.net/licenses/all-rights-reserved
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