A Survey on Large Language Model Hallucination via a Creativity Perspective
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arXiv
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| Auteurs principaux: | , , , , , |
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| Format: | Preprint |
| Publié: |
2024
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| _version_ | 1866910325574467584 |
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| author | Jiang, Xuhui Tian, Yuxing Hua, Fengrui Xu, Chengjin Wang, Yuanzhuo Guo, Jian |
| author_facet | Jiang, Xuhui Tian, Yuxing Hua, Fengrui Xu, Chengjin Wang, Yuanzhuo Guo, Jian |
| contents | Hallucinations in large language models (LLMs) are always seen as limitations. However, could they also be a source of creativity? This survey explores this possibility, suggesting that hallucinations may contribute to LLM application by fostering creativity. This survey begins with a review of the taxonomy of hallucinations and their negative impact on LLM reliability in critical applications. Then, through historical examples and recent relevant theories, the survey explores the potential creative benefits of hallucinations in LLMs. To elucidate the value and evaluation criteria of this connection, we delve into the definitions and assessment methods of creativity. Following the framework of divergent and convergent thinking phases, the survey systematically reviews the literature on transforming and harnessing hallucinations for creativity in LLMs. Finally, the survey discusses future research directions, emphasizing the need to further explore and refine the application of hallucinations in creative processes within LLMs. |
| format | Preprint |
| id |
arxiv_https___arxiv_org_abs_2402_06647 |
| institution | arXiv |
| publishDate | 2024 |
| record_format | arxiv |
| spellingShingle | A Survey on Large Language Model Hallucination via a Creativity Perspective Jiang, Xuhui Tian, Yuxing Hua, Fengrui Xu, Chengjin Wang, Yuanzhuo Guo, Jian Artificial Intelligence Human-Computer Interaction Hallucinations in large language models (LLMs) are always seen as limitations. However, could they also be a source of creativity? This survey explores this possibility, suggesting that hallucinations may contribute to LLM application by fostering creativity. This survey begins with a review of the taxonomy of hallucinations and their negative impact on LLM reliability in critical applications. Then, through historical examples and recent relevant theories, the survey explores the potential creative benefits of hallucinations in LLMs. To elucidate the value and evaluation criteria of this connection, we delve into the definitions and assessment methods of creativity. Following the framework of divergent and convergent thinking phases, the survey systematically reviews the literature on transforming and harnessing hallucinations for creativity in LLMs. Finally, the survey discusses future research directions, emphasizing the need to further explore and refine the application of hallucinations in creative processes within LLMs. |
| title | A Survey on Large Language Model Hallucination via a Creativity Perspective |
| topic | Artificial Intelligence Human-Computer Interaction |
| url | https://arxiv.org/abs/2402.06647 |