用大模型生成界面，能快速出原型但难保可用性。
Qualitative Evaluation of LLM-Designed GUI
- 用GPT-o3-mini-high等三模型生成三种界面原型。
- 生成布局合理但无障碍和交互能力不足。
- 适合快速原型设计，需人工完善体验。
随着生成式AI发展，大型语言模型（LLMs）正被探索用于自动化图形用户界面（GUI）设计。本研究通过分析LLM生成界面满足多样化用户需求的能力，评估其可用性和适应性。实验采用2025年1月的三款先进模型（OpenAI GPT o3-mini-high、DeepSeek R1、Anthropic Claude 3.5 Sonnet），为聊天系统、技术团队面板和经理仪表盘生成原型。专家评估显示，尽管模型能有效构建结构化布局，但在符合无障碍标准和提供交互功能方面存在挑战。进一步测试表明，模型可部分适配不同用户角色，但缺乏深层上下文理解。结果表明，虽然LLMs在早期界面原型阶段具有潜力，但确保可用性、可访问性和用户满意度仍需人工干预。
原文摘要 · Abstract (English)
As generative artificial intelligence advances, Large Language Models (LLMs) are being explored for automated graphical user interface (GUI) design. This study investigates the usability and adaptability of LLM-generated interfaces by analysing their ability to meet diverse user needs. The experiments included utilization of three state-of-the-art models from January 2025 (OpenAI GPT o3-mini-high, DeepSeek R1, and Anthropic Claude 3.5 Sonnet) generating mockups for three interface types: a chat system, a technical team panel, and a manager dashboard. Expert evaluations revealed that while LLMs are effective at creating structured layouts, they face challenges in meeting accessibility standards and providing interactive functionality. Further testing showed that LLMs could partially tailor interfaces for different user personas but lacked deeper contextual understanding. The results suggest that while LLMs are promising tools for early-stage UI prototyping, human intervention remains critical to ensure usability, accessibility, and user satisfaction.
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