<?xml version="1.0" encoding="utf-8" standalone="yes"?>
<rss version="2.0" xmlns:atom="http://www.w3.org/2005/Atom">
  <channel>
    <title>Interpretability on Nalar</title>
    <link>https://nalar.dev/tags/interpretability/</link>
    <description>Recent content in Interpretability on Nalar</description>
    <generator>Hugo</generator>
    <language>en-us</language>
    <lastBuildDate>Sun, 06 Sep 2026 00:00:00 +0700</lastBuildDate>
    <atom:link href="https://nalar.dev/tags/interpretability/index.xml" rel="self" type="application/rss+xml" />
    <item>
      <title>Inspect Transformer Predictions with the Logit Lens</title>
      <link>https://nalar.dev/inspect-transformer-predictions-with-the-logit-lens/</link>
      <pubDate>Sun, 06 Sep 2026 00:00:00 +0700</pubDate>
      <guid>https://nalar.dev/inspect-transformer-predictions-with-the-logit-lens/</guid>
      <description>&lt;p&gt;A transformer language model produces its next-token prediction only after many layers of computation. When that prediction is wrong or surprising, developers often want a more specific question answered: &lt;strong&gt;how did the model&amp;rsquo;s candidate tokens change as the input moved through the network?&lt;/strong&gt;&lt;/p&gt;&#xA;&lt;p&gt;The &lt;strong&gt;logit lens&lt;/strong&gt; is a simple interpretability technique for exploring that question. Instead of waiting for the final layer, it takes an intermediate representation and passes it through the model&amp;rsquo;s final decoding machinery to obtain vocabulary logits. Repeating this across layers gives a rough view of how token predictions evolve with depth.&lt;/p&gt;</description>
    </item>
  </channel>
</rss>
