<?xml version="1.0" encoding="utf-8" standalone="yes"?><rss version="2.0" xmlns:atom="http://www.w3.org/2005/Atom"><channel><title>Generative AI | Julia Kim</title><link>https://juliavekim.github.io/tags/generative-ai/</link><atom:link href="https://juliavekim.github.io/tags/generative-ai/index.xml" rel="self" type="application/rss+xml"/><description>Generative AI</description><generator>Hugo Blox Builder (https://hugoblox.com)</generator><language>en-us</language><lastBuildDate>Wed, 23 Sep 2026 00:00:00 +0000</lastBuildDate><image><url>https://juliavekim.github.io/media/icon_hu_532fa307128e7fe8.png</url><title>Generative AI</title><link>https://juliavekim.github.io/tags/generative-ai/</link></image><item><title>An Offline Architecture for Assessment-Driven Remediation Videos</title><link>https://juliavekim.github.io/publication/personalised-instruction/</link><pubDate>Wed, 23 Sep 2026 00:00:00 +0000</pubDate><guid>https://juliavekim.github.io/publication/personalised-instruction/</guid><description>&lt;p>&lt;strong>Manuscript in preparation (2026).&lt;/strong> This work studies how reusable instructional content and precomputed learner-specific videos can support automated remediation at scale. The system is designed for offline preparation; learning effectiveness has not yet been evaluated.&lt;/p></description></item></channel></rss>