  Recent years have seen impressive progress in AI-assisted writing, yet the
developments in AI-assisted reading are lacking. We propose inline commentary
as a natural vehicle for AI-based reading assistance, and present CARE: the
first open integrated platform for the study of inline commentary and reading.
CARE facilitates data collection for inline commentaries in a commonplace
collaborative reading environment, and provides a framework for enhancing
reading with NLP-based assistance, such as text classification, generation or
question answering. The extensible behavioral logging allows unique insights
into the reading and commenting behavior, and flexible configuration makes the
platform easy to deploy in new scenarios. To evaluate CARE in action, we apply
the platform in a user study dedicated to scholarly peer review. CARE
facilitates the data collection and study of inline commentary in NLP,
extrinsic evaluation of NLP assistance, and application prototyping. We invite
the community to explore and build upon the open source implementation of CARE.
