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Author-in-the-Loop Response Generation and Evaluation: Integrating Author Expertise and Intent in Responses to Peer Review

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2026-01-12

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Re3Align, a new large-scale dataset for author-in-the-loop response generation, comprising 3.4k complete paper records (review, response, paper and revised paper) with 440k sentence-level edit annotations and 15k aligned review–response–edit triplets. This dataset is a supplement to the paper: Author-in-the-Loop Response Generation and Evaluation: Integrating Author Expertise and Intent in Responses to Peer Review. Please refer to the paper for more details (https://arxiv.org/abs/2602.11173).

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Except where otherwise noted, this license is described as CC-BY-NC 4.0 - Attribution-NonCommercial 4.0 International