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| Main Authors: | , , , , |
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| Format: | Preprint |
| Published: |
2025
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| Subjects: | |
| Online Access: | https://arxiv.org/abs/2502.08265 |
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| _version_ | 1866929711884533760 |
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| author | Molchanova, Maria Mikhailova, Anna Korzanova, Anna Ostyakova, Lidiia Dolidze, Alexandra |
| author_facet | Molchanova, Maria Mikhailova, Anna Korzanova, Anna Ostyakova, Lidiia Dolidze, Alexandra |
| contents | With the advancement of large language models (LLMs), the focus in Conversational AI has shifted from merely generating coherent and relevant responses to tackling more complex challenges, such as personalizing dialogue systems. In an effort to enhance user engagement, chatbots are often designed to mimic human behaviour, responding within a defined emotional spectrum and aligning to a set of values. In this paper, we aim to simulate personal traits according to the Big Five model with the use of LLMs. Our research showed that generating personality-related texts is still a challenging task for the models. As a result, we present a dataset of generated texts with the predefined Big Five characteristics and provide an analytical framework for testing LLMs on a simulation of personality skills. |
| format | Preprint |
| id |
arxiv_https___arxiv_org_abs_2502_08265 |
| institution | arXiv |
| publishDate | 2025 |
| record_format | arxiv |
| spellingShingle | Exploring the Potential of Large Language Models to Simulate Personality Molchanova, Maria Mikhailova, Anna Korzanova, Anna Ostyakova, Lidiia Dolidze, Alexandra Computation and Language Artificial Intelligence With the advancement of large language models (LLMs), the focus in Conversational AI has shifted from merely generating coherent and relevant responses to tackling more complex challenges, such as personalizing dialogue systems. In an effort to enhance user engagement, chatbots are often designed to mimic human behaviour, responding within a defined emotional spectrum and aligning to a set of values. In this paper, we aim to simulate personal traits according to the Big Five model with the use of LLMs. Our research showed that generating personality-related texts is still a challenging task for the models. As a result, we present a dataset of generated texts with the predefined Big Five characteristics and provide an analytical framework for testing LLMs on a simulation of personality skills. |
| title | Exploring the Potential of Large Language Models to Simulate Personality |
| topic | Computation and Language Artificial Intelligence |
| url | https://arxiv.org/abs/2502.08265 |