add Reverse RAG landing page with abstract and PDF link, redirect old slug
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<html lang="en">
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<head>
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<meta charset="UTF-8">
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<meta http-equiv="refresh" content="0;url=/reverse-rag.pdf">
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<title>Reverse RAG Whitepaper | uncloseai.com</title>
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<meta http-equiv="refresh" content="0;url=/reverse-retrieval-augmented-generations-rag">
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<title>Reverse RAG | uncloseai.com</title>
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</head>
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<body>
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<p>Opening PDF... <a href="/reverse-rag.pdf" target="_blank">Click here if it does not open automatically.</a></p>
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<script>window.location.replace("/reverse-rag.pdf");</script>
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<p>Redirecting... <a href="/reverse-retrieval-augmented-generations-rag">Click here.</a></p>
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<script>window.location.replace("/reverse-retrieval-augmented-generations-rag");</script>
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</html>
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<!DOCTYPE html>
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<!--
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AGPL-3.0-only
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Copyright 2025-2026 TimeHexOn & foxhop & cthegray & russell@unturf
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https://www.permacomputer.com
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-->
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<html lang="en">
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<head>
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<meta charset="UTF-8">
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<meta name="viewport" content="width=device-width, initial-scale=1.0">
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<meta name="theme-color" content="#43a047">
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<meta name="color-scheme" content="light dark">
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<title>Reverse Retrieval Augmented Generation | uncloseai.com</title>
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<meta name="description" content="Whitepaper: Reverse RAG, a client-side context injection technique that makes small language models punch above their weight by extracting live page content and injecting it directly into the conversation.">
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document.documentElement.setAttribute('data-theme', theme);
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// Disable custom styling for uncloseai.js - use PicoCSS instead
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window.UNCLOSEAI_CUSTOM_STYLING = false;
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<script src="https://uncloseai.com/uncloseai.js" type="module"></script>
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<div class="table-of-contents">
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<nav>
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<li><a href="/">Home</a></li>
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<li><a href="/c-examples.html">C Examples</a></li>
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<li><a href="/crawler.html">Our Crawler</a></li>
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<li><a href="/reverse-retrieval-augmented-generations-rag" class="active">Reverse RAG</a></li>
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<li><a href="/languages" target="_blank">All Languages</a></li>
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<li><a href="https://shop.unturf.com/p/8486f492-a93e-11f0-b477-02dfe05770ee/uncloseai-machine-learning-reference-guide-to-inference-clients" target="_blank">Book</a></li>
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<!-- Main content -->
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<main>
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<header>
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<hgroup>
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<a href="https://uncloseai.com"><h1 class="unturf" style="font-family: 'ChunkFiveRegular';">uncloseai.</h1></a>
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<p>Reverse Retrieval Augmented Generation</p>
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</hgroup>
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</header>
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<h2>Client-Side Context Injection for Small Language Models</h2>
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<p><em>How live DOM extraction makes 8B models punch above their weight class.</em></p>
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<p><em>russell@unturf, cthegray, TimeHexOn, foxhop</em></p>
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<h3>Abstract</h3>
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<p>Traditional Retrieval Augmented Generation (RAG) requires a server-side pipeline: chunk documents, embed them into vectors, store them in a database, and retrieve by similarity search at query time. This architecture demands infrastructure, indexing latency, and maintenance of embedding models and vector stores.</p>
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<p><strong>Reverse Retrieval Augmented Generation (Reverse RAG)</strong> inverts this entirely. Instead of the server fetching documents to augment the prompt, the client extracts live content from the page the user currently views and injects it directly into the conversation context. The data comes to the model. No vector database. No embeddings. No indexing pipeline. No server-side retrieval.</p>
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<p><a href="/uncloseai-js.html">uncloseai.js</a> implements this technique as an AGPL-3.0-only algorithm in a single-file JavaScript library that adds a machine learning chat interface to any webpage. By feeding the model the full, fresh content of whatever page the user visits, small 8B-parameter models produce answers that rival much larger models on page-specific questions.</p>
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<p><a href="/reverse-rag.pdf" target="_blank" role="button">Read the full whitepaper (PDF)</a></p>
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<h3>Citation</h3>
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<pre><code>russell@unturf, cthegray, TimeHexOn, foxhop. "Reverse Retrieval Augmented
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Generation: Client-Side Context Injection for Small Language Models."
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uncloseai.com, 2026. https://uncloseai.com/reverse-retrieval-augmented-generations-rag</code></pre>
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<small>© uncloseai. 2026</small>
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