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LLM gender bias amplified by personality traits in English and Hindi stories

By PulseAugur Editorial · [1 sources] ·

A new study investigated how personality traits influence gender bias in Large Language Models (LLMs) when they adopt specific personas. Researchers generated over 23,000 stories in English and Hindi, varying persona gender, occupation, and personality. The findings indicate that 'Dark Triad' personality traits are linked to more gender-stereotypical narratives compared to 'HEXACO' traits, with variations observed across different LLMs and languages. This suggests that persona-conditioned LLMs could perpetuate uneven representational harms and reinforce gender stereotypes in various applications. AI

IMPACT Persona-conditioned LLMs may introduce uneven representational harms, reinforcing gender stereotypes in generated content.

RANK_REASON Academic paper investigating bias in LLMs.

Read on arXiv cs.CL →

AI-generated summary · Google Gemini · from 1 sources. How we write summaries →

LLM gender bias amplified by personality traits in English and Hindi stories

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Academic paper investigating bias in LLMs.
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142 days old
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COVERAGE [1]

  1. arXiv cs.CL TIER_1 English(EN) · Tanay Kumar, Shreya Gautam, Aman Chadha, Vinija Jain, Francesco Pierri ·

    Personality Shapes Gender Bias in Persona-Conditioned LLM Narratives Across English and Hindi: An Empirical Investigation

    arXiv:2604.23600v1 Announce Type: new Abstract: Large Language Models (LLMs) are increasingly deployed in persona-driven applications such as education, customer service, and social platforms, where models are prompted to adopt specific personas when interacting with users. While…

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