Enhancing Creativity in Large Language Models through Associative Thinking Strategies

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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.