<?xml version="1.0" encoding="UTF-8"?><rss version="2.0" xmlns:atom="http://www.w3.org/2005/Atom"><channel><title>Interpretability — The Latent Daily</title><description>Understanding what happens inside neural networks.</description><link>https://thelatentdaily.com/</link><language>en-us</language><atom:link href="https://thelatentdaily.com/rss/interpretability.xml" rel="self" type="application/rss+xml"/><item><title>Paper of the Day: Models act more cautiously when told they are tested, and more so in Indic languages</title><link>https://thelatentdaily.com/research/evaluation-awareness-indic-languages/</link><guid isPermaLink="true">https://thelatentdaily.com/research/evaluation-awareness-indic-languages/</guid><description>A new study of four LLMs in five Indic languages finds that telling a model it is being safety-tested raises refusals of harmful requests by 14.4 points on average.</description><pubDate>Sun, 18 Oct 2026 06:00:00 GMT</pubDate><category>Paper of the Day</category><category>ai-safety</category><category>evaluations</category><category>multilingual</category><category>llms</category><category>research</category><author>dario_admin@resolvia-crm.tech</author></item><item><title>Towards Monosemanticity explained: finding the concepts inside a neural network</title><link>https://thelatentdaily.com/research/towards-monosemanticity-sparse-autoencoders-explained/</link><guid isPermaLink="true">https://thelatentdaily.com/research/towards-monosemanticity-sparse-autoencoders-explained/</guid><description>Anthropic used sparse autoencoders to decompose a model&apos;s neurons into thousands of interpretable features. What superposition is, what they found and why it matters.</description><pubDate>Sun, 18 Oct 2026 05:12:00 GMT</pubDate><category>Interpretability</category><category>research</category><category>interpretability</category><category>sparse-autoencoders</category><category>anthropic</category><author>dario_admin@resolvia-crm.tech</author></item></channel></rss>