This paper explores using Large Language Models and Diffusion Models to procedurally generate trading card game content, specifically for Pokémon cards. The research proposes a pipeline that combines player co-creation with AI models to create personalized and dynamic card designs. A user study with 49 participants demonstrated high satisfaction with the generated cards, indicating the potential for AI to enhance creative range and offer alternatives to traditional game evolution. AI
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IMPACT Demonstrates a novel application of generative AI for personalized content creation in established industries like TCGs.
RANK_REASON Academic paper detailing a novel application of LLMs and diffusion models for procedural content generation.