<?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>Rope on Chi's Blog</title><link>https://zhangchitc.github.io/tags/rope/</link><description>Recent content in Rope 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/rope/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><item><title>How RoPE Improves on Sinusoidal Positional Encoding</title><link>https://zhangchitc.github.io/posts/rope/</link><pubDate>Sun, 13 Sep 2026 16:34:00 +0800</pubDate><guid>https://zhangchitc.github.io/posts/rope/</guid><description>Sinusoidal encoding has a neat rotation property, but it breaks once the encoding goes through attention&amp;rsquo;s projection matrices. We expand the dot product to see why, then put RoPE through the same expansion and watch the absolute positions cancel out.</description></item></channel></rss>