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dc.contributor.authorRuder, S
dc.contributor.authorVulić, I
dc.contributor.authorSøgaard, A
dc.date.accessioned2018-10-03T04:45:38Z
dc.date.available2018-10-03T04:45:38Z
dc.date.issued2019
dc.identifier.issn1076-9757
dc.identifier.urihttps://www.repository.cam.ac.uk/handle/1810/283100
dc.description.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>
dc.publisherAI Access Foundation
dc.titleA survey of cross-lingual word embedding models
dc.typeArticle
prism.endingPage631
prism.publicationDate2019
prism.publicationNameJournal of Artificial Intelligence Research
prism.startingPage569
prism.volume65
dc.identifier.doi10.17863/CAM.30462
dcterms.dateAccepted2018-05-02
rioxxterms.versionofrecord10.1613/JAIR.1.11640
rioxxterms.licenseref.urihttp://www.rioxx.net/licenses/all-rights-reserved
rioxxterms.licenseref.startdate2019-01-01
dc.identifier.eissn1943-5037
rioxxterms.typeJournal Article/Review
pubs.funder-project-idEuropean Research Council (648909)
cam.issuedOnline2019-08-12
rioxxterms.freetoread.startdate2019-10-02


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