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cs.CL2024
From 'Showgirls' to 'Performers': Fine-tuning with Gender-inclusive Language for Bias Reduction in LLMs
Marion Bartl, Susan Leavy
Gender bias is not only prevalent in Large Language Models (LLMs) and their training data, but also firmly ingrained into the structural aspects of language itself. Therefore, adap…
cs.HC2024★ 32 cited
Listening to the Voices: Describing Ethical Caveats of Conversational User Interfaces According to Experts and Frequent Users
Thomas Mildner, Orla Cooney, Anna-Maria Meck +9
Advances in natural language processing and understanding have led to a rapid growth in the popularity of conversational user interfaces (CUIs). While CUIs introduce novel benefits…