<?xml version="1.0" encoding="utf-8" standalone="yes"?><rss version="2.0" xmlns:atom="http://www.w3.org/2005/Atom"><channel><title>Daniel T. Levin | Fanjie Li</title><link>https://fanjie-li.netlify.app/author/daniel-t.-levin/</link><atom:link href="https://fanjie-li.netlify.app/author/daniel-t.-levin/index.xml" rel="self" type="application/rss+xml"/><description>Daniel T. Levin</description><generator>Wowchemy (https://wowchemy.com)</generator><language>en-us</language><lastBuildDate>Sat, 27 Jun 2026 00:00:00 +0000</lastBuildDate><image><url>https://fanjie-li.netlify.app/images/icon_hu21f2f3c66189db8c92168094004333f9_4740_512x512_fill_lanczos_center_2.png</url><title>Daniel T. Levin</title><link>https://fanjie-li.netlify.app/author/daniel-t.-levin/</link></image><item><title>When Can We Trust AI Coding of Student-Generated Text? A Committee-Based Approach to Diagnosing Agreement and Uncertainty at Scale</title><link>https://fanjie-li.netlify.app/publication/aied26/</link><pubDate>Sat, 27 Jun 2026 00:00:00 +0000</pubDate><guid>https://fanjie-li.netlify.app/publication/aied26/</guid><description/></item><item><title>Using RE-LLM Coding Uncertainty to Resolve Codebook Ambiguities: An Example of the CLARIFY Toolset and Workflow in Action</title><link>https://fanjie-li.netlify.app/publication/lak26_workshop/</link><pubDate>Mon, 27 Apr 2026 00:00:00 +0000</pubDate><guid>https://fanjie-li.netlify.app/publication/lak26_workshop/</guid><description/></item></channel></rss>