Prompt to GPT-3: Step-by-Step Thinking Instructions for Humor Generation
Yuetian Chen Bowen Shi Mei Si
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.