Papers by Linglong Kong

1 papers
Debiasing with Sufficient Projection: A General Theoretical Framework for Vector Representations (2024.naacl-long)

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Challenge: Pre-trained vector representations can inadvertently encode undesirable social biases.
Approach: They propose a framework for reducing bias by transforming vector representations to an unbiased subspace using sufficient projection.
Outcome: The proposed framework mitigates bias across debiasing and fairness tasks and across various vector representation types, including word embeddings and output representations of transformer models.

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