<?xml version="1.0" encoding="utf-8" standalone="yes"?><rss version="2.0" xmlns:atom="http://www.w3.org/2005/Atom"><channel><title>Agent Memory | Yiqiao Jin CS PhD @ Georgia Tech</title><link>https://ahren09.github.io/tags/agent-memory/</link><atom:link href="https://ahren09.github.io/tags/agent-memory/index.xml" rel="self" type="application/rss+xml"/><description>Agent Memory</description><generator>Hugo Blox Builder (https://hugoblox.com)</generator><language>en-us</language><lastBuildDate>Thu, 01 Oct 2026 00:00:00 +0000</lastBuildDate><image><url>https://ahren09.github.io/media/icon_hu_eee6347cbdb2cc3f.png</url><title>Agent Memory</title><link>https://ahren09.github.io/tags/agent-memory/</link></image><item><title>From Knowledge Access to Source Learning: Developing Source-Specific Competence</title><link>https://ahren09.github.io/publication/preprint26_sourcelearn/</link><pubDate>Thu, 01 Oct 2026 00:00:00 +0000</pubDate><guid>https://ahren09.github.io/publication/preprint26_sourcelearn/</guid><description>&lt;h2 id="overview">Overview&lt;/h2>
&lt;p>SourceLearn studies how an LLM agent can progressively learn from a persistent authoritative source. It maintains a source model that represents how knowledge is structured, interpreted, and applied. Self-directed learning revisits incompletely understood material, while task-guided learning identifies recurring representational needs. Both mechanisms reconstruct persistent updates from the original source.&lt;/p>
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