<?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>Multi-Objective Optimization on 兜忆轩 | Cedric's Compiler Notes</title><link>https://douyixuan.github.io/tags/multi-objective-optimization/</link><description>Recent content in Multi-Objective Optimization on 兜忆轩 | Cedric's Compiler Notes</description><image><title>兜忆轩 | Cedric's Compiler Notes</title><url>https://douyixuan.github.io/images/papermod-cover.png</url><link>https://douyixuan.github.io/images/papermod-cover.png</link></image><generator>Hugo -- 0.146.0</generator><language>en-us</language><lastBuildDate>Wed, 28 Oct 2026 12:00:00 +0800</lastBuildDate><atom:link href="https://douyixuan.github.io/tags/multi-objective-optimization/index.xml" rel="self" type="application/rss+xml"/><item><title>043 · 最好的下一份 RTL，为什么取决于已经生成了什么？</title><link>https://douyixuan.github.io/posts/ai-silicon-papers/2026-10-28/</link><pubDate>Wed, 28 Oct 2026 12:00:00 +0800</pubDate><guid>https://douyixuan.github.io/posts/ai-silicon-papers/2026-10-28/</guid><description>把评价对象从单个电路换成候选集合，奖励也随历史改变。这篇多目标强化学习论文追问：生成器应该反复找到高分答案，还是补上尚未覆盖的设计取舍？</description></item></channel></rss>