Regularized masked-language modeling and name-masking reduce gender bias in embeddings, but the contextual results rely heavily on evaluation metrics aligned with the training objective.
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Mitigating Gender Bias in Contextual Word Embeddings
Regularized masked-language modeling and name-masking reduce gender bias in embeddings, but the contextual results rely heavily on evaluation metrics aligned with the training objective.