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A Survey of Cross-lingual Word Embedding Models
2019
The Journal of Artificial Intelligence Research
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
doi:10.1613/jair.1.11640
fatcat:vwlgtzzmhfdlnlyaokx2whxgva