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We're different, we're the same: Creative homogeneity across LLMs

Emily Wenger

cs.CY, computer science - artificial intelligence, computer science - computation and language, computer science - machine learning

Abstract

Numerous powerful large language models (LLMs) are now available for use as writing support tools, idea generators, and beyond. Although these LLMs are marketed as helpful creative assistants, several works have shown that using an LLM as a creative partner results in a narrower set of creative outputs. However, these studies only consider the effects of interacting with a single LLM, begging the question of whether such narrowed creativity stems from using a particular LLM – which arguably has

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creativity frameworks › psychological/cognitiverelated to creativity › mentions creativity as a human abilitymodel used › ChatGPTmodel used › Large (>32B)model used › Medium (8-24)model used › Small (<3B)evaluation › automatic metricsevaluation › creativity evaluationevaluation › human evalscope › prompt engineeringscope › technical research

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Paper ID: 97971a0a-a7bc-4be9-abd1-bae0e945e295Added: 10/26/2025