用《2001太空漫游》经典台词警示：LLM进入汽车环境面临哪些安全风险？这篇论文系统性评估并给出框架。
arXiv:2606.14327v1 Announce Type: cross Abstract: This paper appraises recent frameworks within AI development to integrate LLMs into control tasks in…
ICML 2026新作，精准量化大模型输出分布中的尾部风险，为模型安全与可靠性提供理论工具
arXiv:2604.22167v2 Announce Type: replace-cross Abstract: Language models are increasingly capable and are being rapidly deployed on a population-leve…
结合随机最优控制理论，为稀有事件分析提供新视角，交叉领域前沿方法值得关注。
arXiv:2604.13213v2 Announce Type: replace-cross Abstract: Rare events such as conformational changes in biomolecules, phase transitions, and chemical …
基于呼吸音和临床信号，用可审计的LLM提示链工作流实现急性哮喘风险评估，医疗AI新突破。
arXiv:2606.08247v1 Announce Type: cross Abstract: Acute asthma risk assessment requires rapid interpretation of respiratory sounds, oxygenation, airfl…
Anthropic披露Claude产品中从零信任到高权限的工程实践，平衡效率与安全。
Article URL: https://www.anthropic.com/engineering/how-we-contain-claude Comments URL: https://news.ycombinator.com/item?id=48392082 Points: 223 # Com…
从风险分类到行动计划修复，提出基于护栏反馈驱动的LLM Agent安全框架，解决行动前的风险评估与防御。
arXiv:2606.05805v1 Announce Type: new Abstract: LLM-based guardrails typically safeguard agents by evaluating proposed actions or inputs before execut…
专用护栏系统的威胁分类新框架，为AI安全防护提供系统性风险评估方法
arXiv:2605.30693v1 Announce Type: cross Abstract: Building robust safety guardrails is essential for deploying Large Language Models across diverse re…
最新研究揭示，LLM多智能体系统存在严重隐私漏洞，智能体无法保守秘密，需警惕协作中的信息泄露风险。
arXiv:2605.27766v1 Announce Type: new Abstract: LLM safety evaluations predominantly test models in isolation, yet deployed AI agents increasingly ope…
用检索增强大模型读取直播间的“似曾相识”线索，跨会话证据让风险预判更聪明
arXiv:2601.16027v2 Announce Type: replace Abstract: The rise of live streaming has transformed online interaction, enabling massive real-time engageme…
重新审视AI机器人带来的实际风险，发现它们可能并不像想象中那么可怕
Article URL: https://blawg.nochan.net/b/Internet-Crap/20260522-Maybe-AI-Bots-Are-Harmless/ Comments URL: https://news.ycombinator.com/item?id=48240859…
从企业视角解析AI评估如何成为提升性能、降低风险的关键工具，OpenAI官方深度解读。
Learn how evals help businesses define, measure, and improve AI performance—reducing risk, boosting productivity, and driving strategic advantage.