arXiv:2607. 18665v1 Announce Type: new Abstract: Large language models (LLMs) increasingly support science, but they can also convert hazardous scientific knowledge into actionable misuse guidance.
By Chunxiao Li, Yuan Xiong, Lijun Li, Tianyi Du, Wenlong Zhang, Lei Bai, Jing Shao
arXiv:2606. 18936v1 Announce Type: new Abstract: Large language models (LLMs) are increasingly embedded in AI for Science (AI4Science) workflows, from scientific question answering and literature analysis to laboratory planning and autonomous discovery.
By Linghao Feng, Yinqian Sun, Dongqi Liang, Sicheng Shen, Chenfei Yan, Yuxuan Peng, Yilin Zhao, Haibo Tong, Kai Li, FeiFei Zhao, Yi Zeng
Large language models (LLMs) are increasingly embedded in AI for Science (AI4Science) workflows, from scientific question answering and literature analysis to laboratory planning and autonomous discovery. This progress creates an urgent need for safety benchmarks that evaluate not only scientific competence, but also whether models recognize and avoid risks in high-stakes scientific contexts.
arXiv:2508. 00923v3 Announce Type: replace Abstract: Large language models (LLMs) are increasingly used to answer health-related questions and support healthcare workflows, yet evidence for their safety still relies heavily on static benchmarks that can rapidly become obsolete or be optimized against.
By Jiazhen Pan (Cherise), Bailiang Jian (Cherise), Paul Hager (Cherise), Yundi Zhang (Cherise), Che Liu (Cherise), Friederike Jungmann (Cherise), Hongwei Bran Li (Cherise), Julian Canisius (Cherise), Chenyu You (Cherise), Junde Wu (Cherise), Jiayuan Zhu (Cherise), Fenglin Liu (Cherise), Yuyuan Liu (Cherise), Niklas Bubeck (Cherise), Moritz Knolle (Cherise), Chen (Cherise), Chen (Cherise), Christian Wachinger, Zhenyu Gong, Cheng Ouyang, Georgios Kaissis, Benedikt Wiestler, Daniel Rueckert
arXiv:2609.01210v1 Announce Type: cross
Abstract: Safety benchmarks for large language models often assess the risk of a user query, although the outcome of question answering depends on whether the...
By Rui Yang, Shuang Huang, Junhua Liu, Ziqi Zhao, Qingzhong Yan, Yuhang Sun, Cong Liu, Guoping Hu, Rui Mei, Jing Shao
Safety benchmarks for large language models often assess the risk of a user query, although the outcome of question answering depends on whether the response violates a policy. This distinction is cri...