The study explores how inducing personalities in large language models (LLMs) affects their Theory-of-Mind (ToM) reasoning abilities. Personality traits, particularly from the Dark Triad, have a significant impact on LLMs' performance across different ToM tasks. The findings suggest that caution is necessary when assigning specific personas with personalities to LLMs due to their unexpected effects on reasoning abilities.
Recent advances show that while LLMs excel in many natural language processing tasks compared to humans, they struggle with social-cognitive reasoning like ToM. The study investigates how inducing certain personalities through prompts influences ToM abilities in LLMs. Results indicate that personality traits can alter LLMs' reasoning capabilities significantly across various ToM tasks.
The research combines insights from psychology on personality traits and NLP research on role-play prompting to analyze the relationship between personality prompting and ToM reasoning abilities in LLMs. Findings reveal that inducing specific personas can lead to both positive and negative effects on social-cognitive reasoning, emphasizing the importance of evaluating the personas adopted by LLMs.
Key points include exploring eight different personality prompts' effects on three theory-of-mind reasoning tasks, highlighting variations in performance across models and tasks based on induced personalities like those from the Dark Triad. The study underscores the need for further research into positive traits benefiting LLMs' social-cognitive reasoning and mitigating negative traits detrimental to their performance.
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Önemli Bilgiler Şuradan Elde Edildi
by Fiona Anting... : arxiv.org 03-05-2024
https://arxiv.org/pdf/2403.02246.pdfDaha Derin Sorular