<?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>Openevals on Sabit Shaikholla</title><link>https://sabit-shaikholla.github.io/tags/openevals/</link><description>Recent content in Openevals on Sabit Shaikholla</description><image><title>Sabit Shaikholla</title><url>https://sabit-shaikholla.github.io/images/profile.jpg</url><link>https://sabit-shaikholla.github.io/images/profile.jpg</link></image><generator>Hugo</generator><language>en-us</language><lastBuildDate>Tue, 20 May 2025 00:00:00 +0000</lastBuildDate><atom:link href="https://sabit-shaikholla.github.io/tags/openevals/index.xml" rel="self" type="application/rss+xml"/><item><title>Corrective RAG Agent: Self-Checking Answers with OpenEvals</title><link>https://sabit-shaikholla.github.io/projects/corrective-rag-openevals/</link><pubDate>Tue, 20 May 2025 00:00:00 +0000</pubDate><guid>https://sabit-shaikholla.github.io/projects/corrective-rag-openevals/</guid><description>A deep dive into building more reliable LLM agents by combining Corrective Retrieval-Augmented Generation (CRAG) with OpenEvals. Learn how self-checking retrieval, automated evaluation, and iterative refinement can dramatically reduce hallucinations and improve answer accuracy in AI-powered assistants.</description></item></channel></rss>