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A Survey on Large Language Model Hallucination via a Creativity Perspective

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arxiv 2402.06647 v1 pith:HBHDLESR submitted 2024-02-02 cs.AI cs.HC

A Survey on Large Language Model Hallucination via a Creativity Perspective

classification cs.AI cs.HC
keywords hallucinationssurveycreativityllmsapplicationcreativeexploreslanguage
verification ladder T0 review T1 audit T2 compute T3 formal T4 reserved
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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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Cited by 4 Pith papers

Reviewed papers in the Pith corpus that reference this work. Sorted by Pith novelty score.

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  3. A Survey on the Memory Mechanism of Large Language Model based Agents

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  4. Position: Multimodal Large Language Models Can Significantly Advance Scientific Reasoning

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