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RAG存在两个漏洞：模型处理上下文时仍可能误读误用，以及检索到的上下文本身可能错误或无关

1

Sources

50%

Confidence

Long-term

Relevance

7/20/2026

First Seen

Sources

AI幻觉从何而来？为什么难以根除

Related Claims

UnverifiedRAG管线在代码场景下的问题是不可诊断性：模型无法判断检索结果错误是外部检索系统的问题还是原始数据本身的问题77% similar VerifiedRAG并非幻觉问题的万能解药，当检索到的文档片段与问题无关或内容存在歧义时，模型仍可能产生幻觉76% similar UnverifiedRAG导致的上下文污染会产生'由检索驱动的幻觉'，这类错误通常不触发异常或错误码，只能通过人工语义核验发现75% similar VerifiedRAG存在检索精度不稳定、语义匹配偏差以及消耗大量上下文窗口等缺陷75% similar UnverifiedRAG在代码场景失败的真正原因是不可诊断性、多环节误差乘法叠加、索引时效性三个深层问题，而非Embedding对代码失效75% similar

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