{"ID":2877806,"CreatedAt":"2026-06-01T04:54:23.091178241Z","UpdatedAt":"2026-06-01T04:54:23.091178241Z","DeletedAt":null,"paper_url":"https://arxiv.org/abs/2508.20263","arxiv_id":"2508.20263","title":"Athena: Intermediate Representations for Iterative Scaffolded App Generation with an LLM","abstract":"It is challenging to generate the code for a complete user interface using a Large Language Model (LLM). User interfaces are complex and their implementations often consist of multiple, inter-related files that together specify the contents of each screen, the navigation flows between the screens, and the data model used throughout the application. It is challenging to craft a single prompt for an LLM that contains enough detail to generate a complete user interface, and even then the result is frequently a single large and difficult to understand file that contains all of the generated screens. In this paper, we introduce Athena, a prototype application generation environment that demonstrates how the use of shared intermediate representations, including an app storyboard, data model, and GUI skeletons, can help a developer work with an LLM in an iterative fashion to craft a complete user interface. These intermediate representations also scaffold the LLM's code generation process, producing organized and structured code in multiple files while limiting errors. We evaluated Athena with a user study that found 75% of participants preferred our prototype over a typical chatbot-style baseline for prototyping apps.","short_abstract":"It is challenging to generate the code for a complete user interface using a Large Language Model (LLM). User interfaces are complex and their implementations often consist of multiple, inter-related files that together specify the contents of each screen, the navigation flows between the screens, and the data model us...","url_abs":"https://arxiv.org/abs/2508.20263","url_pdf":"https://arxiv.org/pdf/2508.20263v1","authors":"[\"Jazbo Beason\",\"Ruijia Cheng\",\"Eldon Schoop\",\"Jeffrey Nichols\"]","published":"2025-08-27T20:42:10Z","proceeding":"cs.HC","tasks":"[\"cs.HC\"]","methods":"[\"Large Language Model\",\"Language Model\",\"Generative Adversarial Network\"]","has_code":false}