arXiv:2603.04245cs.SEcs.AI2026-03中稿 · 2026 IEEE/ACM 48th…

用AI把用户抱怨变成可执行的界面改进建议。

LikeThis! Empowering App Users to Submit UI Improvement Suggestions Instead of Complaints

  • 输入用户评论和截图,AI自动生成多个具体改进方案供选择。
  • 在10个真实应用上测试,开发者认为带生成建议的反馈更易懂、可操作。
  • 先生成方案说明再绘图,确保改进有效且不引入新问题。

用户反馈对移动应用演进至关重要,但现有反馈常模糊或破坏性。本文提出LikeThis!,一种基于生成式AI的方法,将用户评论与截图结合,即时生成多个具体的界面改进建议,帮助用户提交更具建设性的反馈。首先,在公开的精细评审界面设计数据集上进行模型对比,结果显示GPT-Image-1在修复界面问题的同时保持设计保真度,且未引入新问题,显著优于其他三个顶尖图像生成模型。LikeThis!的关键步骤是先生成解决方案说明,再绘制设计草图,以确保改进有效性。其次,我们在10个上线应用中开展用户研究,15名用户使用LikeThis!提交反馈,开发团队评估了有无生成建议的反馈在可理解性和可操作性上的差异。结果表明,该方法从用户和开发者双重视角提升了反馈质量,为AI辅助的用户-开发者协作铺平道路。

原文摘要 · Abstract (English)

User feedback is crucial for the evolution of mobile apps. However, research suggests that users tend to submit uninformative, vague, or destructive feedback. Unlike recent AI4SE approaches that focus on generating code and other development artifacts, our work aims at empowering users to submit better and more constructive UI feedback with concrete suggestions on how to improve the app. We propose LikeThis!, a GenAI-based approach that takes a user comment with the corresponding screenshot to immediately generate multiple improvement alternatives, from which the user can easily choose their preferred option. To evaluate LikeThis!, we first conducted a model benchmarking study based on a public dataset of carefully critiqued UI designs. The results show that GPT-Image-1 significantly outperformed three other state-of-the-art image generation models in improving the designs to address UI issues while keeping the fidelity and without introducing new issues. An intermediate step in LikeThis! is to generate a solution specification before sketching the design as a key to achieving effective improvement. Second, we conducted a user study with 10 production apps, where 15 users used LikeThis! to submit their feedback on encountered issues. Later, the developers of the apps assessed the understandability and actionability of the feedback with and without generated improvements. The results show that our approach helps generate better feedback from both user and developer perspectives, paving the way for AI-assisted user-developer collaboration.

人机协作UI改进生成式AI

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