June 11, 2024, 4:41 a.m. | Cheng Tan, Dongxin Lyu, Siyuan Li, Zhangyang Gao, Jingxuan Wei, Siqi Ma, Zicheng Liu, Stan Z. Li

cs.CL updates on arXiv.org arxiv.org

arXiv:2406.05688v1 Announce Type: new
Abstract: Large Language Models (LLMs) have demonstrated wide-ranging applications across various fields and have shown significant potential in the academic peer-review process. However, existing applications are primarily limited to static review generation based on submitted papers, which fail to capture the dynamic and iterative nature of real-world peer reviews. In this paper, we reformulate the peer-review process as a multi-turn, long-context dialogue, incorporating distinct roles for authors, reviewers, and decision makers. We construct a comprehensive dataset …

arxiv context cs.ai cs.cl cs.lg dialogue interactions peer review role type

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