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Wireframing is a critical step in the UI design process. Mid-fidelitywireframes offer more impactful and engaging visuals compared to low-fidelityversions. However, their creation can be time-consuming and labor-intensive,requiring the addition of actual content and semantic icons. In this paper, weintroduce a novel solution WireGen, to automatically generate mid-fidelitywireframes with just a brief design intent description using the generativeLarge Language Models (LLMs). Our experiments demonstrate the effectiveness ofWireGen in producing 77.5% significantly better wireframes, outperforming twowidely-used in-context learning baselines. A user study with 5 designersfurther validates its real-world usefulness, highlighting its potential valueto enhance UI design process.

Designing with Language: Wireframing UI Design Intent with Generative Large Language Models