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    <abstract>Pre-trained language models (PLMs) play a crucial role in various applications, including sensitive domains such as the hiring process. However, extensive research has unveiled that these models tend to replicate social biases present in their pre-training data, raising ethical concerns. In this study, we propose the TagDebias method, which proposes debiasing a dataset using type tags. It then proceeds to fine-tune PLMs on this debiased dataset. Experiments show that our proposed TagDebias model, when applied to a ranking task, exhibits significant improvements in bias scores.</abstract>
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%0 Conference Proceedings
%T TagDebias: Entity and Concept Tagging for Social Bias Mitigation in Pretrained Language Models
%A Moslemi, Mehrnaz
%A Zouaq, Amal
%Y Duh, Kevin
%Y Gomez, Helena
%Y Bethard, Steven
%S Findings of the Association for Computational Linguistics: NAACL 2024
%D 2024
%8 June
%I Association for Computational Linguistics
%C Mexico City, Mexico
%F moslemi-zouaq-2024-tagdebias
%X Pre-trained language models (PLMs) play a crucial role in various applications, including sensitive domains such as the hiring process. However, extensive research has unveiled that these models tend to replicate social biases present in their pre-training data, raising ethical concerns. In this study, we propose the TagDebias method, which proposes debiasing a dataset using type tags. It then proceeds to fine-tune PLMs on this debiased dataset. Experiments show that our proposed TagDebias model, when applied to a ranking task, exhibits significant improvements in bias scores.
%U https://aclanthology.org/2024.findings-naacl.101
%P 1553-1567

Markdown (Informal)

[TagDebias: Entity and Concept Tagging for Social Bias Mitigation in Pretrained Language Models](https://aclanthology.org/2024.findings-naacl.101) (Moslemi & Zouaq, Findings 2024)

• TagDebias: Entity and Concept Tagging for Social Bias Mitigation in Pretrained Language Models (Moslemi & Zouaq, Findings 2024)

ACL

• Mehrnaz Moslemi and Amal Zouaq. 2024. TagDebias: Entity and Concept Tagging for Social Bias Mitigation in Pretrained Language Models. In Findings of the Association for Computational Linguistics: NAACL 2024, pages 1553–1567, Mexico City, Mexico. Association for Computational Linguistics.