arXiv:2511.14101cs.AI2025-11

用大模型驱动多智能体自动设计手机页面布局,提升效率与一致性。

APD-Agents: A Large Language Model-Driven Multi-Agents Collaborative Framework for Automated Page Design

  • 基于大模型的多智能体协作框架,动态分工完成页面设计任务。
  • 在RICO数据集上达到当前最佳效果,生成布局质量高且结构合理。
  • 适合移动应用开发团队快速产出标准化页面原型,减少人工调整。

页面布局是移动应用开发中的关键步骤。然而,设计出令人满意的布局耗时耗力:设计师需决定页面展示哪些控件和内容,并反复调整其大小、位置和样式以实现更好的视觉效果与结构。尽管现有设计软件可辅助完成重复性工作,但有效使用仍需大量培训。此外,跨页面协同设计还需额外时间统一标准并保持风格一致。本文提出APD-agents,一个由大语言模型驱动的多智能体协同框架,用于自动化移动应用页面设计。该框架包含协调者(OrchestratorAgent)、语义解析器(SemanticParserAgent)、主布局生成器(PrimaryLayoutAgent)、模板检索器(TemplateRetrievalAgent)和递归组件生成器(RecursiveComponentAgent)。当接收用户对页面的描述后,协调者可动态调度其他智能体完成设计任务。其中,语义解析器将用户描述转化为结构化数据;主布局生成器创建粗粒度初始布局;模板检索器获取语义相关的少样本示例以提升布局质量;递归组件生成器则针对布局中每个元素递归生成所有细粒度子元素。本工作充分利用大模型驱动多智能体系统的自动协作能力。在RICO数据集上的实验结果表明,APD-agents实现了当前最优性能。

原文摘要 · Abstract (English)

Layout design is a crucial step in developing mobile app pages. However, crafting satisfactory designs is time-intensive for designers: they need to consider which controls and content to present on the page, and then repeatedly adjust their size, position, and style for better aesthetics and structure. Although many design software can now help to perform these repetitive tasks, extensive training is needed to use them effectively. Moreover, collaborative design across app pages demands extra time to align standards and ensure consistent styling. In this work, we propose APD-agents, a large language model (LLM) driven multi-agent framework for automated page design in mobile applications. Our framework contains OrchestratorAgent, SemanticParserAgent, PrimaryLayoutAgent, TemplateRetrievalAgent, and RecursiveComponentAgent. Upon receiving the user's description of the page, the OrchestratorAgent can dynamically can direct other agents to accomplish users' design task. To be specific, the SemanticParserAgent is responsible for converting users' descriptions of page content into structured data. The PrimaryLayoutAgent can generate an initial coarse-grained layout of this page. The TemplateRetrievalAgent can fetch semantically relevant few-shot examples and enhance the quality of layout generation. Besides, a RecursiveComponentAgent can be used to decide how to recursively generate all the fine-grained sub-elements it contains for each element in the layout. Our work fully leverages the automatic collaboration capabilities of large-model-driven multi-agent systems. Experimental results on the RICO dataset show that our APD-agents achieve state-of-the-art performance.

页面设计多智能体大模型应用自动化

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