<?xml version="1.0" encoding="utf-8" standalone="yes"?><rss version="2.0" xmlns:atom="http://www.w3.org/2005/Atom"><channel><title>Foundation Models | Zunzhe Zhang</title><link>https://tuagoale.github.io/tags/foundation-models/</link><atom:link href="https://tuagoale.github.io/tags/foundation-models/index.xml" rel="self" type="application/rss+xml"/><description>Foundation Models</description><generator>HugoBlox Kit (https://hugoblox.com)</generator><language>en-us</language><lastBuildDate>Mon, 30 Jun 2025 00:00:00 +0000</lastBuildDate><image><url>https://tuagoale.github.io/media/icon.svg</url><title>Foundation Models</title><link>https://tuagoale.github.io/tags/foundation-models/</link></image><item><title>Ella: Embodied Social Agents with Lifelong Memory</title><link>https://tuagoale.github.io/publications/ella/</link><pubDate>Mon, 30 Jun 2025 00:00:00 +0000</pubDate><guid>https://tuagoale.github.io/publications/ella/</guid><description>&lt;p&gt;Ella focuses on long-horizon embodied social behavior: agents must observe, remember, plan, and interact across days rather than solve isolated tasks. Its memory system organizes acquired knowledge in semantic form while preserving episodic traces of multimodal experience.&lt;/p&gt;
&lt;p&gt;The system is evaluated in a dynamic 3D open world where multiple agents participate in social activities and are later tested on controlled tasks such as influence, leadership, and cooperation. The results show how structured memory can help foundation-model agents learn from observation and interaction.&lt;/p&gt;</description></item></channel></rss>