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决策变化总结

来源: twitter关注列表
作者: meng shao (@shao__meng)
发布于: 2026-06-26
收录于: 2026-06-26
AI 推荐理由
精准识别核心问题并提出改进方案
核心解读
ADE 说明优化文档层次,提升需嵌入处理的准确性
全文
meng shao (@shao__meng) 转发了 LandingAI (@LandingAI) 的帖子: The hard part of RAG isn't finding the right chunk! When you chunk a document for RAG, each chunk lands in the index on its own, disconnected from the section it came from. So two chunks with identical text, but from completely different parts of the document, look exactly the same to a flat index. That becomes a problem the moment a question needs context from more than one section. The chunks come back, but how they relate to each other gets lost. ADE Section fixes this. It reads the parsed document, builds the actual hierarchy, and figures out where every chunk falls within it. That gets attached to the chunk before it's embedded. Once that's in place, a broad question can stay at the section level. A specific one can drop into a sub-chunk. You can scope a search to one part of a document instead of the whole thing. Citations get more accurate too. The model knows exactly which section a fact came from. Run ADE Parse, then run ADE Section. ![photo](https://pbs.twimg.com/media/HLv71embwAApfKE.jpg)
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