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Found 2 papers, 1 papers with code
An Empirical Analysis of Parameter-Efficient Methods for Debiasing Pre-Trained Language Models
The increasingly large size of modern pretrained language models not only makes them inherit more human-like biases from the training corpora, but also makes it computationally expensive to mitigate such biases.
Counter-GAP: Counterfactual Bias Evaluation through Gendered Ambiguous Pronouns
Bias-measuring datasets play a critical role in detecting biased behavior of language models and in evaluating progress of bias mitigation methods.
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