Communicating design implications is common within the HCI community when publishing academic papers, yet these papers are rarely read and used by designers. One solution is to use design cards as a form of translational resource that communicates valuable insights from papers in a more digestible and accessible format to assist in design processes. However, creating design cards can be time-consuming, and authors may lack the resources/know-how to produce cards. Through an iterative design process, we built a system that helps create design cards from academic papers using an LLM and text-to-image model. Our evaluation with designers (N=21) and authors of selected papers (N=12) revealed that designers perceived the design implications from our design cards as more inspiring and generative, compared to reading original paper texts, and the authors viewed our system as an effective way of communicating their design implications. We also propose future enhancements for AI-generated design cards.

翻译：在人机交互（HCI）领域，发表学术论文时传达设计启示是常见做法，但这些论文很少被设计师阅读和使用。一种解决方案是采用设计卡片作为转化资源，以更易消化和可获取的形式传递论文中的宝贵见解，辅助设计流程。然而，制作设计卡片耗时费力，且作者可能缺乏制作卡片的资源或专业知识。通过迭代设计流程，我们构建了一个系统，利用大语言模型（LLM）和文本到图像模型从学术论文中自动生成设计卡片。针对设计师（N=21）及选定论文作者（N=12）的评估显示：设计师认为我们的设计卡片中的设计启示比直接阅读论文原文更具启发性和生成性，而作者则认为我们的系统是传达其设计启示的有效方式。我们还提出了针对AI生成设计卡片的未来改进方向。