两篇最新的arXiv论文探讨了人工智能在科学同行评审过程中的整合，强调了其潜在益处和重大风险。一篇调查报告综合了当前AI辅助同行评审生成、申诉协助和评估方法的技巧，旨在指导实际应用。另一篇论文则侧重于AI审稿人的安全性和可靠性，详细介绍了各种攻击向量和实验结果，揭示了诸如易受提示注入和偏见等漏洞，从而对AI在科学评估中的可信度提出了质疑。 AI
影响 人工智能在科学同行评审中的作用正受到审视，新研究详细介绍了AI审稿人的漏洞和潜在的缓解措施。
排序理由 两篇发表在arXiv上的学术论文讨论了人工智能在科学同行评审中的使用。
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arXiv:2604.27924v1 Announce Type: cross Abstract: Peer review is a multi-stage process involving reviews, rebuttals, meta-reviews, final decisions, and subsequent manuscript revisions. Recent advances in large language models (LLMs) have motivated methods that assist or automate …
Peer review is a multi-stage process involving reviews, rebuttals, meta-reviews, final decisions, and subsequent manuscript revisions. Recent advances in large language models (LLMs) have motivated methods that assist or automate different stages of this pipeline. In this survey,…
arXiv:2604.23593v1 Announce Type: new Abstract: The volume of scientific submissions continues to climb, outpacing the capacity of qualified human referees and stretching editorial timelines. At the same time, modern large language models (LLMs) offer impressive capabilities in s…