  Collaborative review and revision of textual documents is the core of
knowledge work and a promising target for empirical analysis and NLP
assistance. Yet, a holistic framework that would allow modeling complex
relationships between document revisions, reviews and author responses is
lacking. To address this gap, we introduce Re3, a framework for joint analysis
of collaborative document revision. We instantiate this framework in the
scholarly domain, and present Re3-Sci, a large corpus of aligned scientific
paper revisions manually labeled according to their action and intent, and
supplemented with the respective peer reviews and human-written edit summaries.
We use the new data to provide first empirical insights into collaborative
document revision in the academic domain, and to assess the capabilities of
state-of-the-art LLMs at automating edit analysis and facilitating text-based
collaboration. We make our annotation environment and protocols, the resulting
data and experimental code publicly available.
