Papers with multiclass debiasing

1 papers
Black is to Criminal as Caucasian is to Police: Detecting and Removing Multiclass Bias in Word Embeddings (N19-1)

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Challenge: Existing methods to debias word embeddings in binary settings such as gender and religion are limited to binary labels, whereas word2vec embedders can be used to propagate biases.
Approach: They propose a method to debias word embeddings in multiclass settings such as gender and religion, extending the work of Bolukbasi et al. (2016).
Outcome: The proposed method maintains the efficacy in standard NLP tasks while maintaining the utility of embeddings.

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