<?xml version="1.0" encoding="utf-8" standalone="yes"?>
<rss version="2.0" xmlns:atom="http://www.w3.org/2005/Atom">
  <channel>
    <title>GEPA on My learning and diary</title>
    <link>https://jackliusr.github.io/tags/gepa/</link>
    <description>Recent content in GEPA on My learning and diary</description>
    <generator>Hugo -- gohugo.io</generator>
    <language>en-us</language>
    <lastBuildDate>Tue, 02 Jun 2026 20:00:00 +0800</lastBuildDate><atom:link href="https://jackliusr.github.io/tags/gepa/index.xml" rel="self" type="application/rss+xml" />
    <item>
      <title>one GEPA report of DSPy</title>
      <link>https://jackliusr.github.io/posts/2026/06/one-gepa-report-of-dspy/</link>
      <pubDate>Tue, 02 Jun 2026 20:00:00 +0800</pubDate>
      
      <guid>https://jackliusr.github.io/posts/2026/06/one-gepa-report-of-dspy/</guid>
      <description>What is GEPA? GEPA stands for Graph-based Evolutionary Program Adaptation — a DSPy optimizer that automatically improves the prompts/instructions of a multi-module LLM program through evolutionary search. It iteratively mutates module instructions, evaluates the changes, and keeps the best-performing candidates on a Pareto front.
   What’s Happening in This Run This file captures a GEPA optimization run on a financial news extraction system that classifies M&amp;amp;A (merger/acquisition) articles and extracts structured data from them.</description>
    </item>
    
  </channel>
</rss>
