Stereotype and Skew: Quantifying Gender Bias in Pre-trained and Fine-tuned Language Models - researchr publication bibliographies

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Daniel de Vassimon Manela, David Errington, Thomas Fisher, Boris van Breugel, Pasquale Minervini. Stereotype and Skew: Quantifying Gender Bias in Pre-trained and Fine-tuned Language Models. In Paola Merlo, Jörg Tiedemann, Reut Tsarfaty, editors, Proceedings of the 16th Conference of the European Chapter of the Association for Computational Linguistics: Main Volume, EACL 2021, Online, April 19 - 23, 2021. pages 2232-2242, Association for Computational Linguistics, 2021. [doi]

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