{
  "id": 14601102,
  "title": "Scaling Discovery Requires Forgetting",
  "url": "https://urgent.news/2026/10/14/scaling-discovery-requires-forgetting",
  "topic": "ai",
  "section": "AI",
  "published": "2026-10-14T17:49:37.000Z",
  "source": {
    "name": "arXiv cs.AI",
    "slug": "arxiv-cs-ai",
    "url": "https://arxiv.org/abs/2610.20563v1"
  },
  "original_language": "en",
  "account": null,
  "summary": "Automated research with LLM agents has shown promising results in various domains. Through iterative refinement and scored verifiers, LLM agents are capable of discovering new ideas. There are different ways to scale automated research: let one agent iterate for longer, run several agents in parallel, or further let the parallel agents communicate and build on one another's candidates. However,…",
  "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."
}