<?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>Information Theory on datafox.tw</title><link>https://datafox.tw/tags/information-theory/</link><description>Recent content in Information Theory on datafox.tw</description><image><title>datafox.tw</title><url>https://datafox.tw/images/Open_graph_image.png</url><link>https://datafox.tw/images/Open_graph_image.png</link></image><generator>Hugo -- 0.146.0</generator><language>zh-tw</language><lastBuildDate>Thu, 21 May 2026 00:00:00 +0000</lastBuildDate><atom:link href="https://datafox.tw/tags/information-theory/index.xml" rel="self" type="application/rss+xml"/><item><title>打破 Seq2Seq 迷思，從資訊理論看大模型的極致壓縮與湧現</title><link>https://datafox.tw/posts/decoder-only-vs-seq2seq-information-theory/</link><pubDate>Thu, 21 May 2026 00:00:00 +0000</pubDate><guid>https://datafox.tw/posts/decoder-only-vs-seq2seq-information-theory/</guid><description>跟上一篇相關，但是這裡從從資訊理論、KL 散度與有損壓縮的底層數學出發，拆解模型湧現能力的真實由來。</description></item></channel></rss>