mlsanityData to 14 Oct 2026

Creating User Interface Mock-ups from High-Level Text Descriptions with Deep-Learning Models

arXiv 2110.07775 ↗First posted 14 Oct 2021cs.HC cs.AI cs.LGcited by 8

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Abstract (arXiv)

The design process of user interfaces (UIs) often begins with articulating high-level design goals. Translating these high-level design goals into concrete design mock-ups, however, requires extensive effort and UI design expertise. To facilitate this process for app designers and developers, we introduce three deep-learning techniques to create low-fidelity UI mock-ups from a natural language phrase that describes the high-level design goal (e.g. "pop up displaying an image and other options"). In particular, we contribute two retrieval-based methods and one generative method, as well as pre-processing and post-processing techniques to ensure the quality of the created UI mock-ups. We quantitatively and qualitatively compare and contrast each method's ability in suggesting coherent, diverse and relevant UI design mock-ups. We further evaluate these methods with 15 professional UI designers and practitioners to understand each method's advantages and disadvantages. The designers responded positively to the potential of these methods for assisting the design process.

Key facts. Cited by 8 papers in the map (data through 14 Oct 2026). Builds on 15 of its 27 references that are in the map. First posted on arXiv 14 Oct 2021.

Builds on

15 of 27 references.

References · 15

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3 more
  1. 2020Crisscrossed Captions: Extended Intramodal and Intermodal Semantic Similarity Judgments for MS-COCOcited by 46
  2. 2021Screen2Vec: Semantic Embedding of GUI Screens and GUI Componentscited by 41
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Cited by year (2026 to 14 Oct)

Citing papers per year: 2023: 3; 2024: 1; 2025: 3; 2026: 1.

8 papers.