一位研究人员对错误地将自己提交的arXiv论文标记为自我剽窃的审稿人表示沮丧。该研究人员建议使用AI根据诸如长度、负面语言或审稿内容等标准来识别和标记有问题的审稿。 AI
影响 建议AI在学术审稿过程中具有潜在应用，例如标记有偏见或低质量的审稿。
排序理由 该条目是研究人员关于常见学术出版问题的个人观点文章，而不是主要公告或发展。
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研究人员谴责arXiv论文提交中的自我剽窃指控
本文如何被排名
- Signal score
- 0 / 100
- Composite score across the factors below. Higher = stronger signal that this story matters right now.
- Newsworthiness bucket
- Commentary
- 该条目是研究人员关于常见学术出版问题的个人观点文章，而不是主要公告或发展。
- Source corroboration
- Single-source cluster
- Only one publisher covered this so far. Single-source stories can still rank when the publisher is high-authority, but they lack cross-source corroboration.
- Topics
- paper, opinion
- Editorial topic classification. Feeds into how the story surfaces on /topic/<slug> hub pages and into the per-entity coverage mix.
- AI-industry relevance
- Standard
- On-topic for AI-industry coverage; kept in the public index.
- Story freshness
- 96 days old
- Aged out of breaking-news scoring windows; ranking reflects the durable signal from the full source set.
完整方法见我们的编辑标准。
报道来源 [1]
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我需要多少次向我们亲爱的#审稿人2解释，将我的#arxiv论文提交给会议不算#自我剽窃 🤔🤷 有很多di
How many times I'll need to explain to our dear # Reviewer2 that submitting my own # arxiv paper to a conference is not # selfplagiarism 🤔🤷 There is a lot of discussion on the use of # AI for # reviewing but, for sure, I'd use # AI to automatically # flag bad reviews (according t…