A Survey on Large Language Model Hallucination via a Creativity Perspective
February 02, 2024 Β· The Cartographer Β· π arXiv.org
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"Title-pattern auto-detect: A Survey on Large Language Model Hallucination via a Creativity Perspective"
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Authors
Xuhui Jiang, Yuxing Tian, Fengrui Hua, Chengjin Xu, Yuanzhuo Wang, Jian Guo
arXiv ID
2402.06647
Category
cs.AI: Artificial Intelligence
Cross-listed
cs.HC
Citations
56
Venue
arXiv.org
Last Checked
1 day ago
Abstract
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.
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