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Christiane Fellbaum

2 accepted papers

2022

MABEL: Attenuating Gender Bias using Textual Entailment Data

EMNLP 2022main

Pre-trained language models encode undesirable social biases, which are further exacerbated in downstream use. To this end, we propose MABEL (a Method for Attenuating Gender Bias using Entailment Labels), an intermediate pre-training approach for mitigating gender bias in contextualized representati…