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cs.CL2023★ 1 cited
An Empirical Analysis of Parameter-Efficient Methods for Debiasing Pre-Trained Language Models
Zhongbin Xie, Thomas Lukasiewicz
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 exp…
cs.CL2023
Counter-GAP: Counterfactual Bias Evaluation through Gendered Ambiguous Pronouns
Zhongbin Xie, Vid Kocijan, Thomas Lukasiewicz +1
Bias-measuring datasets play a critical role in detecting biased behavior of language models and in evaluating progress of bias mitigation methods. In this work, we focus on evalua…