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

新框架助力作者生成AI辅助的同行评审回复

研究人员开发了一个名为REspGen的新框架,以协助作者生成对同行评审的回复,整合作者的专业知识和意图。该框架附带了Re3Align,这是一个包含评审-回复-修订三元组的大型数据集,以及REspEval,一套包含20多个用于评估回复质量的全面指标。使用最先进的大型语言模型的实验证明了作者输入和评估指导的改进在提高回复生成方面的有效性。 AI

影响 引入了用于改进AI辅助科学交流和同行评审过程的新工具和数据集。

排序理由 该集群包含两篇学术论文,讨论了用于科学同行评审中AI辅助响应生成的新型数据集、框架和评估方法。

在 arXiv cs.CL 阅读 →

AI 生成摘要 · Google Gemini · 来自 2 个来源。 我们如何撰写摘要 →

报道来源 [2]

  1. arXiv cs.CL TIER_1 English(EN) · Qian Ruan, Iryna Gurevych ·

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

    arXiv:2602.11173v3 Announce Type: replace Abstract: 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 …

  2. arXiv cs.LG TIER_1 English(EN) · Buxin Su, Jiayao Zhang, Natalie Collina, Yuling Yan, Didong Li, Kyunghyun Cho, Jianqing Fan, Aaron Roth, Weijie Su ·

    Rejoinder: The ICML 2023 Ranking Experiment: Examining Author Self-Assessment in ML/AI Peer Review

    arXiv:2605.25172v1 Announce Type: cross Abstract: This article is the rejoinder to ``The ICML 2023 Ranking Experiment: Examining Author Self-Assessment in ML/AI Peer Review,'' to appear in the Journal of the American Statistical Association with discussion. To address the practic…