Found in Translation: The Role of Prompt Language in Creative LLM Outputs
Found in Translation: The Role of Prompt Language in Creative LLM Outputs

Author(s): Dragana Zundanović, Dragana Božić Lenard, Krešimir Romić, Hrvoje Leventić
Subject(s): Social Sciences
Published by: Udruženje ekonomista i menadžera Balkana
Keywords: Prompt engineering; Image generation; Low-resource languages
Summary/Abstract: Artificial intelligence (AI) has rapidly become indispensable, with applications spanning natural language processing, image generation, and content creation. While large language models (LLMs) primarily process text in English as the global lingua franca, most of the world’s population communicates in other languages, raising questions about the role of low-resource languages in prompt engineering. This paper examines whether the choice of input language—English, Croatian, or a hybrid of both—affects prompt quality and creativity in downstream tasks. Croatian, with its limited digital resources and smaller speaker base, was selected as a case study. A dataset of 100 articles from a Croatian agricultural news portal was used to generate Midjourney prompts via GPT-4o under three language conditions. The prompts and resulting images were analyzed for creativity, semantic consistency, and output quality. Findings reveal subtle but meaningful differences, suggesting that linguistic variation can influence AI-driven creativity. The study underscores the importance of evaluating low-resource languages in multimodal AI systems.

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