一篇新发布的arXiv调查论文详细介绍了大型语言模型（LLM）中基于推理的后门攻击。该论文引入了一种新颖的分类法，将这些攻击分为关联型、被动型和主动型。它还概述了现有的防御策略，并强调了为创建更安全、更值得信赖的LLM社区所面临的挑战和未来的研究方向。 AI
影响 突出了LLM潜在的安全漏洞，指导未来研究朝着更强大的防御方向发展。
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调查详细介绍了LLM中基于推理的后门攻击
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报道来源 [1]
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重新思考推理：LLM中基于推理的后门的调查
arXiv:2510.07697v2 Announce Type: replace-cross Abstract: With the rise of advanced reasoning capabilities, large language models (LLMs) are receiving increasing attention. However, although reasoning improves LLMs' performance on downstream tasks, it also introduces new security…