Papers with DebIE

1 papers
DebIE: A Platform for Implicit and Explicit Debiasing of Word Embedding Spaces (2021.eacl-demos)

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Challenge: Recent research has shown that distributional word vector spaces often encode stereotypical human biases, such as racism and sexism.
Approach: They propose a platform that measures and mitigates bias in word embeddings by executing two (mutually composable) debiasing models.
Outcome: The proposed platform can measure and mitiga bias in word embeddings.

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