<?xml version="1.0" encoding="utf-8" standalone="yes"?><rss version="2.0" xmlns:atom="http://www.w3.org/2005/Atom" xmlns:content="http://purl.org/rss/1.0/modules/content/"><channel><title>Evaluation on YanlunAI</title><link>https://yanlunai.com/en/tags/evaluation/</link><description>Recent content in Evaluation on YanlunAI</description><generator>Hugo -- 0.152.2</generator><language>en</language><lastBuildDate>Sat, 22 Aug 2026 09:00:00 +0800</lastBuildDate><atom:link href="https://yanlunai.com/en/tags/evaluation/index.xml" rel="self" type="application/rss+xml"/><item><title>A minimum model-routing lab: quality, latency, and cost together</title><link>https://yanlunai.com/en/labs/model-routing-lab/</link><pubDate>Sat, 22 Aug 2026 09:00:00 +0800</pubDate><guid>https://yanlunai.com/en/labs/model-routing-lab/</guid><description>A reproducible routing skeleton that records task success, time to first token, total latency, and cost per successful task.</description></item><item><title>The RAG toolchain: a minimum loop from data to evaluation</title><link>https://yanlunai.com/en/posts/tools/2025-12-16-rag-toolchain-overview/</link><pubDate>Tue, 16 Dec 2025 09:30:00 +0800</pubDate><guid>https://yanlunai.com/en/posts/tools/2025-12-16-rag-toolchain-overview/</guid><description>Treat RAG as a pipeline: data, chunking, indexing, retrieval, reranking, generation, and evaluation. Any stage can become the bottleneck.</description></item></channel></rss>