<rss xmlns:atom="http://www.w3.org/2005/Atom" version="2.0"><channel><title>Sampling - Tag - lilfry's library</title><link>https://lilfry09.github.io/en/tags/sampling/</link><description>Sampling - Tag - lilfry's library</description><generator>Hugo -- gohugo.io</generator><language>en</language><managingEditor>lilfry@sjtu.edu.cn (lilfry)</managingEditor><webMaster>lilfry@sjtu.edu.cn (lilfry)</webMaster><copyright>All rights reserved.</copyright><lastBuildDate>Tue, 07 Apr 2026 20:55:00 +0800</lastBuildDate><atom:link href="https://lilfry09.github.io/en/tags/sampling/" rel="self" type="application/rss+xml"/><item><title>Read "Reasoning with Sampling": RL does not make the model smarter, it just redistributes reasoning capabilities</title><link>https://lilfry09.github.io/en/ai/reasoning-with-sampling-rl-redistribution/</link><pubDate>Tue, 07 Apr 2026 20:55:00 +0800</pubDate><author>fry</author><guid>https://lilfry09.github.io/en/ai/reasoning-with-sampling-rl-redistribution/</guid><description><![CDATA[<p>The really dangerous thing about this paper is not that it proposes a new sampler, but that it asks a deeper interpretive question:</p>
<p>**The progress of reasoning model, is it that the model has learned new capabilities, or have we finally learned how to sample from old capabilities? **</p>
<p>If this question were asked correctly, much of the narrative about <code>RL for reasoning</code> would have to be rewritten.</p>]]></description></item></channel></rss>