LLMs Simulate Big Five Personality Traits: Further Evidence
Fuente:
arXiv
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| Autores principales: | , , , |
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| Formato: | Preprint |
| Publicado: |
2024
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| Acceso en línea: | |
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| _version_ | 1866916113051287552 |
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| author | Sorokovikova, Aleksandra Fedorova, Natalia Rezagholi, Sharwin Yamshchikov, Ivan P. |
| author_facet | Sorokovikova, Aleksandra Fedorova, Natalia Rezagholi, Sharwin Yamshchikov, Ivan P. |
| contents | An empirical investigation into the simulation of the Big Five personality traits by large language models (LLMs), namely Llama2, GPT4, and Mixtral, is presented. We analyze the personality traits simulated by these models and their stability. This contributes to the broader understanding of the capabilities of LLMs to simulate personality traits and the respective implications for personalized human-computer interaction. |
| format | Preprint |
| id |
arxiv_https___arxiv_org_abs_2402_01765 |
| institution | arXiv |
| publishDate | 2024 |
| record_format | arxiv |
| spellingShingle | LLMs Simulate Big Five Personality Traits: Further Evidence Sorokovikova, Aleksandra Fedorova, Natalia Rezagholi, Sharwin Yamshchikov, Ivan P. Computation and Language Artificial Intelligence I.2.7; J.4; I.2.1 An empirical investigation into the simulation of the Big Five personality traits by large language models (LLMs), namely Llama2, GPT4, and Mixtral, is presented. We analyze the personality traits simulated by these models and their stability. This contributes to the broader understanding of the capabilities of LLMs to simulate personality traits and the respective implications for personalized human-computer interaction. |
| title | LLMs Simulate Big Five Personality Traits: Further Evidence |
| topic | Computation and Language Artificial Intelligence I.2.7; J.4; I.2.1 |
| url | https://arxiv.org/abs/2402.01765 |