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A Survey on Large Language Model Hallucination via a Creativity Perspective (2402.06647v1)

Published 2 Feb 2024 in cs.AI and cs.HC

Abstract: Hallucinations in 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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Authors (6)
  1. Xuhui Jiang (16 papers)
  2. Yuxing Tian (6 papers)
  3. Fengrui Hua (5 papers)
  4. Chengjin Xu (36 papers)
  5. Yuanzhuo Wang (16 papers)
  6. Jian Guo (76 papers)
Citations (12)
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