{
  "id": 5485333,
  "title": "ESPO: Error-Structured Prompt Optimization via Diagnose, Diversify, and Stabilize",
  "url": "https://urgent.news/2026/09/03/espo-error-structured-prompt-optimization-via-diagnose-diversify-and",
  "topic": "health",
  "section": "Health & Medicine",
  "published": "2026-09-03T17:59:37.000Z",
  "source": {
    "name": "arXiv cs.AI",
    "slug": "arxiv-cs-ai",
    "url": "https://arxiv.org/abs/2609.04197v1"
  },
  "original_language": "en",
  "account": null,
  "summary": "Evolutionary prompt optimizers such as GEPA suffer from prompt bloat: each iteration appends rules and caveats, producing prompts up to 3$\\times$ longer yet no more accurate. We trace this to three deficiencies - incomplete error observation, limited search diversity, and unreliable selection - and propose ESPO (Error-Structured Prompt Optimization), which decomposes prompt optimization into…",
  "key_points": [],
  "editors_take": null,
  "illustration": null,
  "coverage": {
    "outlets": 1,
    "also_reported_by": []
  },
  "ai_generated": true,
  "disclaimer": "Summaries, key points and the editor’s take are written by software from other outlets’ reporting and may contain errors — always check the linked original."
}