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Prompt to GPT-3: Step-by-Step Thinking Instructions for Humor Generation (2306.13195v1)

Published 22 Jun 2023 in cs.CL and cs.AI

Abstract: Artificial intelligence has made significant progress in natural language processing, with models like GPT-3 demonstrating impressive capabilities. However, these models still have limitations when it comes to complex tasks that require an understanding of the user, such as mastering human comedy writing strategies. This paper explores humor generation using GPT-3 by modeling human comedy writing theory and leveraging step-by-step thinking instructions. In addition, we explore the role of cognitive distance in creating humor.

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References (8)
  1. 2021. Deep learning of a pre-trained language model’s joke classifier using gpt-2. Journal of Hunan University Natural Sciences 48(8).
  2. 2020. Language models are few-shot learners.
  3. 2016. Is this a joke? detecting humor in spanish tweets. In Advances in Artificial Intelligence-IBERAMIA 2016: 15th Ibero-American Conference on AI, San José, Costa Rica, November 23-25, 2016, Proceedings 15, 139–150. Springer.
  4. 2019. Pun generation with surprise. arXiv preprint arXiv:1904.06828.
  5. Toplyn, J. 2014. Comedy Writing for Late-Night TV: How to Write Monologue Jokes, Desk Pieces, Sketches, Parodies, Audience Pieces, Remotes, and Other Short-Form Comedy.
  6. Toplyn, J. 2023. Witscript 3: A hybrid ai system for improvising jokes in a conversation. arXiv preprint arXiv:2301.02695.
  7. 2023. Chain-of-thought prompting elicits reasoning in large language models.
  8. 2020. Let’s be humorous: Knowledge enhanced humor generation. arXiv preprint arXiv:2004.13317.
Citations (2)
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