SOURCE-LINKED INTELLIGENCE
ActReview: Rebuttal-Guided Training Data and Rubric Rewards for Actionable Peer Review Generation
As LLMs are increasingly used for pre-submission self-review, there is growing demand for feedback that not only identifies weaknesses but also guides authors toward concrete revisions. We study this as Actionable Peer-review Generation and decompose it into two subtasks: diagnostic claim generation and revision suggestion generation. We introduce ActReview, a rebuttal-guided post-training framework that connects paper-specific diagnoses to concrete, grounded revision plans. Our central insight is that author rebuttals reveal plausible actions for addressing reviewer concerns and can therefore
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Evidence & attribution
- arXiv · AI, language, vision and robotics · 2026-09-08T17:30:16.000Z
First collected: 2026-09-20T20:02:11.508Z. This is not the publication date.