<?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>Word2Vec on s-ai-unix's Blog</title><link>https://s-ai-unix.github.io/tags/word2vec/</link><description>Recent content in Word2Vec on s-ai-unix's Blog</description><generator>Hugo -- 0.161.1</generator><language>zh-cn</language><lastBuildDate>Fri, 30 Jan 2026 09:00:00 +0800</lastBuildDate><atom:link href="https://s-ai-unix.github.io/tags/word2vec/index.xml" rel="self" type="application/rss+xml"/><item><title>AI 论文解读系列：Word2Vec - 词向量的革命</title><link>https://s-ai-unix.github.io/posts/2026-01-30-word2vec-paper-explained/</link><pubDate>Fri, 30 Jan 2026 09:00:00 +0800</pubDate><guid>https://s-ai-unix.github.io/posts/2026-01-30-word2vec-paper-explained/</guid><description>深入浅出解读 Mikolov 等人的 Word2Vec 论文，从词袋模型到神经语言模型，完整推导 CBOW 和 Skip-gram 的数学原理与应用。</description></item></channel></rss>