  This paper explores the enhancement of creativity in Large Language Models
(LLMs) like vGPT-4 through associative thinking, a cognitive process where
creative ideas emerge from linking seemingly unrelated concepts. Associative
thinking strategies have been found to effectively help humans boost
creativity. However, whether the same strategies can help LLMs become more
creative remains under-explored. In this work, we investigate whether prompting
LLMs to connect disparate concepts can augment their creative outputs. Focusing
on three domains -- Product Design, Storytelling, and Marketing -- we introduce
creativity tasks designed to assess vGPT-4's ability to generate original and
useful content. By challenging the models to form novel associations, we
evaluate the potential of associative thinking to enhance the creative
capabilities of LLMs. Our findings show that leveraging associative thinking
techniques can significantly improve the originality of vGPT-4's responses.
