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Oct 12 · Monday
Another 255 papers do not have category tags yet and are not included in filtered results.
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About this collection Collection in progress We are building a large AI safety paper collection to help researchers find work related to their interests. Papers are collected automatically andfiltered only for relevance to AI safety , without judging quality, novelty or reading value. The default “Annotated first” shows papers with tags or published paper analyses first. Each group is ordered by original publication date, newest first, with undated papers last. “Newest first” uses publication dates only. This order is not a quality ranking.
One-line summaries, tags and paper analyses are prepared by AI from the papers. Language models may have systematic biases and produce hallucinations.We plan to carry out human annotation and review to reduce errors in this content.
提出最小范数攻击集成,用鲁棒性曲线评测图像分类器
Published Jul 22
Evaluated models C1–C20(CIFAR-10,Table 1) , I1–I10(ImageNet,Table 1) Abstract 预算可控的最小范数集成用 AOI 逼近攻击前沿,DOI 给出不依赖单一ε的防御排序。这篇工作把对抗鲁棒评测从单一 ε、固定集成,改成可按查询预算收紧的曲线估计。
提出 ARE 框架与图像文本攻击,评测多模态网页 Agent 的对抗鲁棒性
Published Jun 19, 2024
Evaluated models GPT-4o , GPT-4V , Claude-3-Opus and others4 Abstract 系统评估多模态网页智能体的脆弱性,指出推理时计算组件被攻破会加剧系统风险。
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