12 citations · 15 across the 5 of their papers we have counts for
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cs.CL2023
Model-based Counterfactual Generator for Gender Bias Mitigation
Ewoenam Kwaku Tokpo, Toon Calders
Counterfactual Data Augmentation (CDA) has been one of the preferred techniques for mitigating gender bias in natural language models. CDA techniques have mostly employed word subs…
cs.CL2023★ 1 cited
How Far Can It Go?: On Intrinsic Gender Bias Mitigation for Text Classification
Ewoenam Tokpo, Pieter Delobelle, Bettina Berendt +1
To mitigate gender bias in contextualized language models, different intrinsic mitigation strategies have been proposed, alongside many bias metrics. Considering that the end use o…