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        <title>On Shortcuts and Biases: How Finetuned Language Models Distinguish Audience-Specific Instructions in Italian and English</title>
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        <namePart type="given">Nicola</namePart>
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            <title>Proceedings of the 5th Workshop on Gender Bias in Natural Language Processing (GeBNLP)</title>
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            <namePart type="given">Agnieszka</namePart>
            <namePart type="family">Faleńska</namePart>
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        <name type="personal">
            <namePart type="given">Christine</namePart>
            <namePart type="family">Basta</namePart>
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            <namePart type="given">Marta</namePart>
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            <namePart type="given">Debora</namePart>
            <namePart type="family">Nozza</namePart>
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    <abstract>Instructional texts for different audience groups can help to address specific needs, but at the same time run the risk of perpetrating biases. In this paper, we extend previous findings on disparate social norms and subtle stereotypes in wikiHow in two directions: We explore the use of fine-tuned language models to determine how audience-specific instructional texts can be distinguished and we transfer the methodology to another language, Italian, to identify cross-linguistic patterns. We find that language models mostly rely on group terms, gender markings, and attributes reinforcing stereotypes.</abstract>
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%0 Conference Proceedings
%T On Shortcuts and Biases: How Finetuned Language Models Distinguish Audience-Specific Instructions in Italian and English
%A Fanton, Nicola
%A Roth, Michael
%Y Faleńska, Agnieszka
%Y Basta, Christine
%Y Costa-jussà, Marta
%Y Goldfarb-Tarrant, Seraphina
%Y Nozza, Debora
%S Proceedings of the 5th Workshop on Gender Bias in Natural Language Processing (GeBNLP)
%D 2024
%8 August
%I Association for Computational Linguistics
%C Bangkok, Thailand
%F fanton-roth-2024-shortcuts
%X Instructional texts for different audience groups can help to address specific needs, but at the same time run the risk of perpetrating biases. In this paper, we extend previous findings on disparate social norms and subtle stereotypes in wikiHow in two directions: We explore the use of fine-tuned language models to determine how audience-specific instructional texts can be distinguished and we transfer the methodology to another language, Italian, to identify cross-linguistic patterns. We find that language models mostly rely on group terms, gender markings, and attributes reinforcing stereotypes.
%U https://aclanthology.org/2024.gebnlp-1.6
%P 78-93

Markdown (Informal)

[On Shortcuts and Biases: How Finetuned Language Models Distinguish Audience-Specific Instructions in Italian and English](https://aclanthology.org/2024.gebnlp-1.6) (Fanton & Roth, GeBNLP-WS 2024)

• On Shortcuts and Biases: How Finetuned Language Models Distinguish Audience-Specific Instructions in Italian and English (Fanton & Roth, GeBNLP-WS 2024)

ACL

• Nicola Fanton and Michael Roth. 2024. On Shortcuts and Biases: How Finetuned Language Models Distinguish Audience-Specific Instructions in Italian and English. In Proceedings of the 5th Workshop on Gender Bias in Natural Language Processing (GeBNLP), pages 78–93, Bangkok, Thailand. Association for Computational Linguistics.