Papers by Declan Groves

1 papers
Leveraging Pre-trained Language Models for Gender Debiasing (2022.lrec-1)

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Challenge: Existing methods to reduce gender bias in natural language are costly and time-consuming.
Approach: They propose a method to generate gender variants for a given text using pre-trained language models as the resource without any task-specific labelled data.
Outcome: The proposed method can reduce gender bias in a language generation context without a task-specific labelled data.

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