<?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>论文解读 on s-ai-unix's Blog</title><link>https://s-ai-unix.github.io/tags/%E8%AE%BA%E6%96%87%E8%A7%A3%E8%AF%BB/</link><description>Recent content in 论文解读 on s-ai-unix's Blog</description><generator>Hugo -- 0.161.1</generator><language>zh-cn</language><lastBuildDate>Fri, 30 Jan 2026 13:00:00 +0800</lastBuildDate><atom:link href="https://s-ai-unix.github.io/tags/%E8%AE%BA%E6%96%87%E8%A7%A3%E8%AF%BB/index.xml" rel="self" type="application/rss+xml"/><item><title>AI 论文解读系列：AlphaZero - 从零开始的自我博弈通用算法</title><link>https://s-ai-unix.github.io/posts/2026-01-30-alphazero-paper-interpretation/</link><pubDate>Fri, 30 Jan 2026 13:00:00 +0800</pubDate><guid>https://s-ai-unix.github.io/posts/2026-01-30-alphazero-paper-interpretation/</guid><description>深入解读 DeepMind 发表于 Science 2018 的里程碑论文，剖析 AlphaZero 如何从零开始，通过纯自我博弈掌握国际象棋、将棋和围棋</description></item><item><title>AI 论文解读系列：AlphaGo - 深度学习与树搜索征服围棋</title><link>https://s-ai-unix.github.io/posts/2026-01-30-alphago-paper-interpretation/</link><pubDate>Fri, 30 Jan 2026 12:30:00 +0800</pubDate><guid>https://s-ai-unix.github.io/posts/2026-01-30-alphago-paper-interpretation/</guid><description>深入解读 DeepMind 发表于 Nature 的里程碑论文，剖析 AlphaGo 如何结合深度神经网络与蒙特卡洛树搜索，首次在围棋领域击败人类职业棋手</description></item><item><title>AI 论文解读系列：BERT - 预训练深度双向 Transformer 的革命</title><link>https://s-ai-unix.github.io/posts/2026-01-30-bert-paper-interpretation/</link><pubDate>Fri, 30 Jan 2026 12:00:00 +0800</pubDate><guid>https://s-ai-unix.github.io/posts/2026-01-30-bert-paper-interpretation/</guid><description>深入解读 Google 发表于 NAACL 2019 的里程碑论文，剖析 BERT 如何通过双向预训练革命性地提升自然语言理解能力</description></item></channel></rss>