4 Matching Annotations
  1. May 2026
    1. Results show that participants successfully customized interfaces using natural language. Users found the system intuitive and achieved good performance regardless of technical background, we report analysis of optimal prompt length, challenges in separating functional and visual instructions in structured templates, correlation between LLM experience and success, and learning effects.

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    2. By allowing users to express desired changes using their own words and harnessing the generative capabilities of LLMs, MorphGUI mitigates the limitations of predefined options and reduces the need for technical expertise. The framework translates functional and stylistic requests into either modifications of existing application components or generation of new ones.

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    3. Graphical user interface (GUI) customization relies on predefined configuration options and settings, constraining diverse individual needs and preferences within predetermined boundaries and often requiring technical expertise. To address these limitations, this work introduces MorphGUI, a framework leveraging Large Language Models (LLMs) to enable interface customization through natural language.

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