  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.
