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      <title>Evaluating RAG Pipelines: What Actually Helped</title>
      <link>https://tengma137.github.io/posts/2026-4-26-agentsystem3/</link>
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      <description>&lt;p&gt;In the previous posts, I wrote about agent systems from the architecture side: how to choose frameworks, how to structure agent loops, how to think about context, and how my local research agent uses a shared RAG layer.&lt;/p&gt;&#xA;&lt;p&gt;This post is about the next step: evaluation.&lt;/p&gt;&#xA;&lt;p&gt;I wanted to answer a simple question:&lt;/p&gt;&#xA;&lt;p&gt;&lt;strong&gt;Which retrieval pipeline actually works better for paper question answering?&lt;/strong&gt;&lt;/p&gt;&#xA;&lt;p&gt;Not which one feels more elegant. Not which one is more fashionable. Not which one gives a nice demo on a single document. I wanted a comparison across lexical retrieval, vector retrieval, hybrid retrieval, and my hierarchical Zoom retrieval pipeline.&lt;/p&gt;</description>
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