<?xml version="1.0" encoding="utf-8" standalone="yes"?><rss version="2.0" xmlns:atom="http://www.w3.org/2005/Atom"><channel><title>Muvera on Neat Guy Coding</title><link>https://neatguycoding.com/tags/muvera/</link><description>Recent content in Muvera on Neat Guy Coding</description><generator>Hugo -- gohugo.io</generator><language>en</language><copyright>© 2026 NeatGuyCoding</copyright><lastBuildDate>Mon, 18 May 2026 00:00:00 +0000</lastBuildDate><atom:link href="https://neatguycoding.com/tags/muvera/index.xml" rel="self" type="application/rss+xml"/><item><title>The Multi-Vector Retrieval Index Paradox: How MUVERA Approximates Chamfer with Single-Vector ANN</title><link>https://neatguycoding.com/posts/2026-05-18-weaviate-podcast-muvera-with-rajesh-jayaram-and-roberto-esposito-weaviate-podcast-123/</link><pubDate>Mon, 18 May 2026 00:00:00 +0000</pubDate><guid>https://neatguycoding.com/posts/2026-05-18-weaviate-podcast-muvera-with-rajesh-jayaram-and-roberto-esposito-weaviate-podcast-123/</guid><description>Models like ColBERT and ColPali represent documents as token-level vector sets and pay for finer alignment with late interaction (MaxSim/Chamfer)—but index entries explode from one per document to hundreds. Google Research&amp;rsquo;s MUVERA compresses each set into a single fixed-dimensional encoding for one ANN pass, then reranks with true Chamfer; this article separates paper facts from podcast opinion for engineers shipping multi-vector search.</description><media:content xmlns:media="http://search.yahoo.com/mrss/" url="https://neatguycoding.com/posts/2026-05-18-weaviate-podcast-muvera-with-rajesh-jayaram-and-roberto-esposito-weaviate-podcast-123/cover.png"/></item></channel></rss>