Understanding Undesirable Word Embedding Associations
Published • Jan 1, 2019
NobleIDNI1P23W88R84S66
Authors:,,
Kawin Ethayarajh
David Duvenaud
Graeme Hirst
Abstract
Word embeddings are often criticized for capturing undesirable word associations such as gender stereotypes. However, methods for measuring and removing such biases remain poorly understood. We show that for any embedding model that implicitly does matrix factorization, debiasing vectors post hoc us...
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