(Q49985142)

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Learning Word Vectors for 157 Languages

scientific article published on 19 February 2018

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title

Learning Word Vectors for 157 Languages (English)

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1

Edouard Grave

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Armand Joulin

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4

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Armand Joulin

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Piotr Bojanowski

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2

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Piotr Bojanowski

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Tomáš Mikolov

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5

object named as

Tomas Mikolov

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Prakhar Gupta

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3

object named as

Prakhar Gupta

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publication date

19 February 2018

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full work available at URL

https://arxiv.org/pdf/1802.06893.pdf

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published in

Proceedings of the 11th edition of the Language Resources and Evaluation Conference

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describes a project that uses

fastText

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Wikipedia

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Common Crawl

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Google analogy test set

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arXiv classification

cs.CL

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cs.LG

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cites work

Polyglot: Distributed Word Representations for Multilingual NLP

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Enriching Word Vectors with Subword Information

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A unified architecture for natural language processing: deep neural networks with multitask learning

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Efficient Estimation of Word Representations in Vector Space

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Distributed Representations of Words and Phrases and their Compositionality

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Advances in Pre-Training Distributed Word Representations

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GloVe: Global Vectors for Word Representation

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1802.06893

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(Q49985142)

Learning Word Vectors for 157 Languages

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