Papers by Flor Plaza-del-Arco

2 papers
Divine LLaMAs: Bias, Stereotypes, Stigmatization, and Emotion Representation of Religion in Large Language Models (2024.findings-emnlp)

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Challenge: Previous work has shown that LLMs display biases in emotion attribution along gender lines.
Approach: They examine how different religions are represented in LLMs by examining emotion attribution and cultural biases.
Outcome: The findings highlight the need to address and rectify these biases in LLMs.
Angry Men, Sad Women: Large Language Models Reflect Gendered Stereotypes in Emotion Attribution (2024.acl-long)

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Challenge: Large language models reflect societal norms and biases, especially about gender.
Approach: They propose to use large language models to examine gendered emotion attribution in five state-of-the-art LLMs to investigate whether emotions are genderes and whether they are influenced by societal stereotypes.
Outcome: The proposed models exhibit gendered emotions, influenced by gender stereotypes, and the results are consistent with established research in psychology and gender studies.

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