<?xml version="1.0" encoding="utf-8" standalone="yes"?><rss version="2.0" xmlns:atom="http://www.w3.org/2005/Atom"><channel><title>Computational-Linguistics on Marginalia</title><link>https://sguzman.github.io/marginalia/tags/computational-linguistics/</link><description>Recent content in Computational-Linguistics on Marginalia</description><generator>Hugo</generator><language>en-us</language><lastBuildDate>Sat, 22 Aug 2026 00:00:00 +0000</lastBuildDate><atom:link href="https://sguzman.github.io/marginalia/tags/computational-linguistics/index.xml" rel="self" type="application/rss+xml"/><item><title>The Learner in the Corpus: What LLMs Actually Show About Chomsky</title><link>https://sguzman.github.io/marginalia/research/how-llms-challenge-chomskyan-assumptions-analytical-report/</link><pubDate>Tue, 03 Mar 2026 00:00:00 +0000</pubDate><guid>https://sguzman.github.io/marginalia/research/how-llms-challenge-chomskyan-assumptions-analytical-report/</guid><description>A source-audited assessment of what neural language models actually establish about Chomskyan learnability claims. Specific computational results weaken some poverty-of-the-stimulus and impossible-language arguments, while child-scale data, model inductive bias, harder syntactic phenomena, and cognitive mismatch block a blanket &lt;code&gt;Chomsky refuted&lt;/code&gt; verdict.</description></item></channel></rss>