<?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>Deepseek on Chi's Blog</title><link>https://zhangchitc.github.io/tags/deepseek/</link><description>Recent content in Deepseek on Chi's Blog</description><generator>Hugo</generator><language>en-us</language><lastBuildDate>Tue, 27 Oct 2026 01:44:00 +0800</lastBuildDate><atom:link href="https://zhangchitc.github.io/tags/deepseek/index.xml" rel="self" type="application/rss+xml"/><item><title>How DeepSeek's Multi-Head Latent Attention Works</title><link>https://zhangchitc.github.io/posts/multi-head-latent-attention/</link><pubDate>Tue, 27 Oct 2026 01:44:00 +0800</pubDate><guid>https://zhangchitc.github.io/posts/multi-head-latent-attention/</guid><description>MLA caches one 512-dimensional latent per token instead of 128 heads&amp;rsquo; worth of keys and values, and matrix absorption means it never has to decompress them. We derive it step by step: joint compression, absorption, why RoPE breaks it, and the decoupled RoPE branch that fixes it.</description></item></channel></rss>