Papers with subspace projection

1 papers
Understanding Undesirable Word Embedding Associations (P19-1)

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Challenge: Word embeddings are often criticized for capturing undesirable word associations such as gender stereotypes.
Approach: They propose to use subspace projection to debias vectors post hoc using a model that implicitly does matrix factorization to debunk gender bias.
Outcome: The proposed test overestimates gender bias in word embeddings by using subspace projection, a method that is widely used in training.

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