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Found 3 papers, 1 papers with code
Model-based Counterfactual Generator for Gender Bias Mitigation
Counterfactual Data Augmentation (CDA) has been one of the preferred techniques for mitigating gender bias in natural language models.
Text Style Transfer for Bias Mitigation using Masked Language Modeling
Our style transfer model improves on the limitations of many existing style transfer techniques such as loss of content information.
Measuring Fairness with Biased Rulers: A Survey on Quantifying Biases in Pretrained Language Models
We survey the existing literature on fairness metrics for pretrained language models and experimentally evaluate compatibility, including both biases in language models as in their downstream tasks.
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