<?xml version="1.0" encoding="utf-8" standalone="yes"?><rss version="2.0" xmlns:atom="http://www.w3.org/2005/Atom"><channel><title>Agent Evaluation on Cunxin's Website</title><link>https://opthuang.github.io/tags/agent-evaluation/</link><description>Recent content in Agent Evaluation on Cunxin's Website</description><generator>Hugo -- gohugo.io</generator><language>en</language><lastBuildDate>Wed, 26 Aug 2026 00:00:00 +0000</lastBuildDate><atom:link href="https://opthuang.github.io/tags/agent-evaluation/index.xml" rel="self" type="application/rss+xml"/><item><title>Terminal-Bench Science: Four Accepted Tasks in v0.1</title><link>https://opthuang.github.io/posts/terminal-bench-science/</link><pubDate>Wed, 26 Aug 2026 00:00:00 +0000</pubDate><guid>https://opthuang.github.io/posts/terminal-bench-science/</guid><description>Project: Terminal-Bench Science, a benchmark for AI agents working through computational tasks in the natural sciences.
Release: v0.1.0, released in August 2026.
Contribution: I was a main contributor to Terminal-Bench Science v0.1. Four tasks I contributed to were accepted into v0.1.
Overview Link to heading Terminal-Bench Science studies whether AI systems can work through realistic scientific-computing workflows in a terminal environment. The benchmark is about more than producing code that looks plausible: an agent must understand the scientific setting, carry out the workflow, and produce a result that can be checked.</description></item></channel></rss>