<?xml version="1.0" encoding="utf-8" standalone="yes"?><rss version="2.0" xmlns:atom="http://www.w3.org/2005/Atom"><channel><title>AI for Science | Wenlong Zhang</title><link>https://wenlongzhang0517.github.io/tags/ai-for-science/</link><atom:link href="https://wenlongzhang0517.github.io/tags/ai-for-science/index.xml" rel="self" type="application/rss+xml"/><description>AI for Science</description><generator>HugoBlox Kit (https://hugoblox.com)</generator><language>en-us</language><lastBuildDate>Thu, 12 Jun 2025 00:00:00 +0000</lastBuildDate><image><url>https://wenlongzhang0517.github.io/media/icon_hu_1c0e9cb08cfb822a.png</url><title>AI for Science</title><link>https://wenlongzhang0517.github.io/tags/ai-for-science/</link></image><item><title>SciPrismax</title><link>https://wenlongzhang0517.github.io/projects/sciprismax/</link><pubDate>Thu, 12 Jun 2025 00:00:00 +0000</pubDate><guid>https://wenlongzhang0517.github.io/projects/sciprismax/</guid><description>&lt;p&gt;SciPrismax studies how to measure scientific understanding, reasoning, and discovery capabilities in multimodal foundation models. The platform brings together scientist-aligned benchmarks, reproducible evaluation workflows, and open resources for the research community.&lt;/p&gt;</description></item></channel></rss>