We explore the design of Marvista -- a human-AI collaborative tool that employs a suite of natural language processing models to provide end-to-end support for reading online news articles. Before reading an article, Marvista helps a user plan what to read by filtering text based on how much time one can spend and what questions one is interested to find out from the article. During reading, Marvista helps the user reflect on their understanding of each paragraph with AI-generated questions. After reading, Marvista generates an explainable human-AI summary that combines both AI's processing of the text, the user's reading behavior, and user-generated data in the reading process. In contrast to prior work that offered (content-independent) interaction techniques or devices for reading, Marvista takes a human-AI collaborative approach that contributes text-specific guidance (content-aware) to support the entire reading process.

翻译：我们探索了Marvista的设计——这是一款人机协作工具，它利用一组自然语言处理模型，为在线阅读新闻文章提供端到端支持。在阅读文章前，Marvista通过根据用户可投入的时间及感兴趣的疑问对文本进行筛选，帮助用户规划阅读内容。在阅读过程中，Marvista通过AI生成的问题帮助用户反思对每个段落的理解。阅读结束后，Marvista生成一种可解释的人机摘要，该摘要融合了AI对文本的处理、用户的阅读行为以及用户在阅读过程中生成的数据。与以往提供（内容无关的）交互技术或阅读设备的研究不同，Marvista采用人机协作方法，贡献了针对文本的特定指导（内容感知），以支持整个阅读过程。