一句话：提出 SeePrivacy 多模态框架，从移动截图检测隐私上下文并检索展示对应政策片段。
隐私政策是移动应用告知数据实践的主要机制，但冗长且法律语言晦涩，用户难以查阅。上下文隐私政策（CPP）通过在相关 GUI 元素旁展示简短政策片段来缓解该问题。本文提出 SeePrivacy：一个多模态框架，从移动截图中检测隐私上下文，检索相关隐私政策片段，并在界面上下文中呈现。为评估，作者构建 CPP4APP 基准，含 1,200 多个隐私相关上下文及匹配政策片段。SeePrivacy 检测上下文达到 0.88 精确率、0.90 召回率；提取对应片段达到 0.98 精确率、0.96 召回率。人工评估中 77% 的回答认为片段有助于解释上下文；Android SDK 实现平均 9.15 秒执行流水线，表明在移动应用中交付 CPP 的可行性。
Privacy policies are the predominant mechanism for notifying mobile application users about data practices, yet their length and legal language make them difficult to consult. Contextual Privacy Policies (CPPs) address this problem by presenting short policy segments beside the graphical user interface (GUI) elements to which they apply. This paper presents SeePrivacy, a multimodal framework that detects privacy contexts in mobile screenshots, retrieves related policy segments, and presents them in context. To evaluate SeePrivacy, we establish our benchmark dataset, named CPP4APP, which covers more than 1,200 privacy-related contexts along with matched privacy policy segments. SeePrivacy achieves 0.88 precision and 0.90 recall to detect contexts, as well as 0.98 precision and 0.96 recall in extracting corresponding policy segments. A human evaluation shows that 77% of responses agreed that the segment helps explain the detected context. An Android SDK implementation executes the pipeline in 9.15 seconds on average, demonstrating the feasibility of delivering CPPs in mobile applications. The introductory video, examples, and code are available at our website: https://cpp4app.github.io/SeePrivacy.