PageIndex：无需向量基于推理的RAG框架

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PageIndex是一种创新的基于推理的检索增强生成（RAG）框架，旨在解决传统向量检索的局限性。传统的向量化方法往往只依赖语义相似度，这在处理复杂、长篇或专业性强的文档时，容易出现上下文断裂和信息不匹配的问题。PageIndex 通过构建一种树状目录结构（ToC），模拟人类查阅资料的过程，引导大语言模型进行动态迭代推理。这种方法使模型能够理解文档的逻辑层级并追踪内部引用，从而精准定位真正相关的信息而非表面的文字匹配。总之，该技术通过将检索过程代理化，显著提升了模型对长文档进行深度理解和准确问答的能力。

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PageIndex：无需向量基于推理的RAG框架

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