Papers with cross-lingual sequence labeling

2 papers
Unsupervised Cross-Lingual Representation Learning (P19-4)

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Challenge: a comprehensive survey of cutting-edge weakly-supervised and unsupervised cross-lingual word representations is presented .
Approach: This tutorial provides a comprehensive survey of recent work on weakly-supervised and unsupervised cross-lingual word representations.
Outcome: This tutorial provides a comprehensive survey of cutting-edge weakly-supervised and unsupervised word representations.
Low-Resource Sequence Labeling via Unsupervised Multilingual Contextualized Representations (D19-1)

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Challenge: Existing approaches to cross-lingual sequence labeling require bilingual resources and require linguistic knowledge.
Approach: They propose a multilingual language model with deep semantic Alignment to generate language-independent representations for cross-lingual sequence labeling.
Outcome: The proposed model achieves state-of-the-art NER and POS performance across European languages and on distant language pairs such as English and Chinese.

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