<?xml version="1.0" encoding="utf-8" standalone="yes"?><rss version="2.0" xmlns:atom="http://www.w3.org/2005/Atom" xmlns:content="http://purl.org/rss/1.0/modules/content/"><channel><title>HybridRetrieval on SiBlog</title><link>https://sinimite.work/en/tags/hybridretrieval/</link><description>Recent content in HybridRetrieval on SiBlog</description><image><title>SiBlog</title><url>https://sinimite.work/images/og-default.svg?v=20260525-210321</url><link>https://sinimite.work/images/og-default.svg?v=20260525-210321</link></image><generator>Hugo -- 0.156.0</generator><language>en-US</language><lastBuildDate>Wed, 29 Jul 2026 00:00:00 +0900</lastBuildDate><atom:link href="https://sinimite.work/en/tags/hybridretrieval/rss.xml" rel="self" type="application/rss+xml"/><item><title>How to Rerank RAG Retrieval Results: From Hybrid Retrieval to Cross-Encoders, Listwise Ranking, and Evidence-Set Selection</title><link>https://sinimite.work/en/posts/rag-reranking-best-practices-2026/</link><pubDate>Wed, 29 Jul 2026 00:00:00 +0900</pubDate><guid>https://sinimite.work/en/posts/rag-reranking-best-practices-2026/</guid><description>A systematic guide to RRF, Cross-Encoders, Pairwise and Listwise ranking, Late Interaction, Learning-to-Rank, MMR, and Set-wise Selection, including how to balance candidate recall, quality, latency, cost, and Token Budget in a production RAG rerank module.</description></item><item><title>RAG Retrieval Engineering: From Hybrid Retrieval to Production Governance</title><link>https://sinimite.work/en/posts/rag-retrieval-engineering-guide/</link><pubDate>Fri, 17 Jul 2026 15:40:44 +0900</pubDate><guid>https://sinimite.work/en/posts/rag-retrieval-engineering-guide/</guid><description>A technical report on designing and implementing the RAG retrieval layer, covering BM25, embeddings, ANN, RRF, reranking, query understanding, access control, evaluation, and deployment practices.</description></item><item><title>The Role of RRF in RAG: A Simple but Not Universal Retrieval-Fusion Method</title><link>https://sinimite.work/en/posts/rag-rrf-retrieval-fusion/</link><pubDate>Wed, 15 Jul 2026 17:37:44 +0900</pubDate><guid>https://sinimite.work/en/posts/rag-rrf-retrieval-fusion/</guid><description>A technical reference on the principles of Reciprocal Rank Fusion, its place in the retrieval pipeline, fusion choices, and production evaluation.</description></item><item><title>Dense + Sparse Hybrid Search in RAG</title><link>https://sinimite.work/en/posts/rag-dense-sparse-hybrid-search/</link><pubDate>Wed, 15 Jul 2026 17:25:30 +0900</pubDate><guid>https://sinimite.work/en/posts/rag-dense-sparse-hybrid-search/</guid><description>A technical reference on Dense + Sparse Hybrid Search, including its principles, fusion methods, suitable use cases, and evaluation approach.</description></item><item><title>A Guide to Building Enterprise RAG Systems</title><link>https://sinimite.work/en/posts/enterprise-rag-system-building-guide/</link><pubDate>Wed, 15 Jul 2026 16:35:23 +0900</pubDate><guid>https://sinimite.work/en/posts/enterprise-rag-system-building-guide/</guid><description>An introduction to the architecture of enterprise RAG data ingestion, hybrid retrieval, access control, generation, evaluation, and observability.</description></item><item><title>What AI Engineers Should Learn in 2026</title><link>https://sinimite.work/en/posts/ai-engineer-skill-value-map-2026/</link><pubDate>Sun, 03 May 2026 20:09:15 +0900</pubDate><guid>https://sinimite.work/en/posts/ai-engineer-skill-value-map-2026/</guid><description>A skill value map for engineers moving into AI application engineering, explaining how the value of basic RAG, prompt engineering, and framework APIs is changing, and why evaluation, governance, and agentic workflows deserve greater investment.</description></item><item><title>The Complete RAG Systems Guide: From Zero to Production</title><link>https://sinimite.work/en/posts/rag-system-complete-guide/</link><pubDate>Fri, 27 Mar 2026 15:06:20 +0900</pubDate><guid>https://sinimite.work/en/posts/rag-system-complete-guide/</guid><description>A panoramic RAG guide covering ingestion, chunking, retrieval, reranking, generation, evaluation, and production operations, with an implementation path from zero to launch.</description></item><item><title>Notes on Anthropic's Contextual Retrieval</title><link>https://sinimite.work/en/posts/anthropic-contextual-retrieval-reading-notes/</link><pubDate>Wed, 11 Mar 2026 09:00:00 +0900</pubDate><guid>https://sinimite.work/en/posts/anthropic-contextual-retrieval-reading-notes/</guid><description>Reading notes on Anthropic&amp;#39;s Contextual Retrieval, covering semantic loss after chunking, experimental benchmarks, ground-truth evaluation, and production RAG practices.</description></item></channel></rss>