ActReview: Rebuttal-Guided Training Data and Rubric Rewards for Actionable Peer Review Generation
Paper recorded by Signals 4 on 2026-09-08 in cs.CL. Abstract reproduced from arXiv; link to the original below.
Published 2026-09-08 on arXiv · recorded by Signals 4 on 2026-09-09
Category: cs.CL · 自然语言处理 · first seen 2026-09-09
Abstract
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 framewo
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Cite this page: ActReview: Rebuttal-Guided Training Data and Rubric Rewards for Actionable Peer Review Generation: the #95 most recent of 186 cs.CL papers we have recorded (as of 2026-09-08). Source: Signals 4 (Signals API) — https://data.jiangzhang.ca/signals4/t/papers/actreview-rebuttal-guided-training-data-and-rubric-rewards-for-actionable-peer-r.html
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