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A survey of cross-lingual word embedding models

Accepted version
Peer-reviewed

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Type

Article

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Authors

Ruder, S 
Vulić, I 
Søgaard, A 

Abstract

jats:pCross-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>

Description

Keywords

4603 Computer Vision and Multimedia Computation, 46 Information and Computing Sciences, 4602 Artificial Intelligence, 4611 Machine Learning

Journal Title

Journal of Artificial Intelligence Research

Conference Name

Journal ISSN

1076-9757
1943-5037

Volume Title

65

Publisher

AI Access Foundation
Sponsorship
European Research Council (648909)