首项针对多模态同行评审的对抗攻击与防御研究，揭示AI审稿的脆弱性。
arXiv:2606.12716v1 Announce Type: new Abstract: The integration of Large Language Models (LLMs) and Multimodal LLMs (MLLMs) into scientific peer-revie…
揭秘LLM在科学新颖性评估中的致命短板，颠覆对AI判别的盲目信任
arXiv:2606.12071v1 Announce Type: cross Abstract: LLMs are increasingly used to generate and judge scientific ideas. This makes novelty evaluation a c…
LLM生成论文评审正被大会试点，但存在被操纵的风险——这篇研究揭示了人机对齐与可游戏性的关键矛盾。
arXiv:2605.28897v1 Announce Type: new Abstract: LLM-generated reviews for scientific papers are gaining considerable traction and are even being offic…
首次系统评估LLM作为论文审稿人的能力、结果分歧与提示注入攻击风险，为AI辅助同行评议提供重要基准。
arXiv:2605.25415v1 Announce Type: new Abstract: Large language models (LLMs) are increasingly used in academic peer review, yet their reliability, ali…