Papers with calibration of models

1 papers
Reducing Confusion in Active Learning for Part-Of-Speech Tagging (2021.tacl-1)

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Challenge: Existing algorithms for annotating parts of speech are not optimal for all languages.
Approach: They propose to use a data selection algorithm to select useful training samples to minimize annotation cost.
Outcome: The proposed strategy outperforms existing strategies on six typologically diverse languages.

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