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Conference ProceedingsArtificial Intelligence & Machine Learning

Measuring Fairness with Biased Rulers: A Comparative Study on Bias Metrics for Pre-trained Language Models

Pieter Delobelle·Ewoenam Kwaku Tokpo·Toon Calders·Bettina Berendt
Conference of the North American Chapter of the Association for Computational Linguistics: Human Language Technologies (NAACL-HLT)2022

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Abstract & Overview

Pieter Delobelle, Ewoenam Tokpo, Toon Calders, Bettina Berendt. Proceedings of the 2022 Conference of the North American Chapter of the Association for Computational Linguistics: Human Language Technologies. 2022.

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Pieter Delobelle, Ewoenam Kwaku Tokpo, Toon Calders, Bettina Berendt (2022). Measuring Fairness with Biased Rulers: A Comparative Study on Bias Metrics for Pre-trained Language Models. Conference of the North American Chapter of the Association for Computational Linguistics: Human Language Technologies (NAACL-HLT). https://doi.org/10.18653/v1/2022.naacl-main.122

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Delobelle, P., Tokpo, E. K., Calders, T., & Berendt, B. (2022). Measuring Fairness with Biased Rulers: A Comparative Study on Bias Metrics for Pre-trained Language Models. Conference of the North American Chapter of the Association for Computational Linguistics: Human Language Technologies (NAACL-HLT). https://doi.org/10.18653/v1/2022.naacl-main.122
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