<?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>Seq2seq on Jeanphilo Blog</title><link>https://shio-chan-dev.github.io/jeanblog/zh/tags/seq2seq/</link><description>Recent content in Seq2seq on Jeanphilo Blog</description><generator>Hugo -- 0.159.2</generator><language>zh-cn</language><lastBuildDate>Sun, 25 Jan 2026 20:08:41 +0800</lastBuildDate><atom:link href="https://shio-chan-dev.github.io/jeanblog/zh/tags/seq2seq/index.xml" rel="self" type="application/rss+xml"/><item><title>Attention Is All You Need：Transformer 的核心算法与工程落地</title><link>https://shio-chan-dev.github.io/jeanblog/zh/ai/attention/attention-is-all-you-need/</link><pubDate>Sun, 25 Jan 2026 20:08:41 +0800</pubDate><guid>https://shio-chan-dev.github.io/jeanblog/zh/ai/attention/attention-is-all-you-need/</guid><description>从算法抽象、复杂度与工程约束出发，解释 Transformer 如何用注意力替代递归与卷积，并给出可运行示例与选型指南。</description></item></channel></rss>