{
  "id": 17925878,
  "title": "Tracing the Scientific Discovery Capacity of LLMs to Their Training Data",
  "url": "https://urgent.news/2026/11/02/tracing-the-scientific-discovery-capacity-of-llms-to-their-training",
  "topic": "ai",
  "section": "AI",
  "published": "2026-11-02T18:50:54.000Z",
  "source": {
    "name": "arXiv cs.AI",
    "slug": "arxiv-cs-ai",
    "url": "https://arxiv.org/abs/2611.03617v1"
  },
  "original_language": "en",
  "account": null,
  "summary": "Large language models (LLMs) show growing promise for scientific discovery, yet basic questions remain about what enables reliable discovery. How can we trace the scientific discovery capacity of LLMs to their training data? We study this question as one of missing probability mass and develop a theoretical account in which monofacts-the facts observed once during training-set the discovery…",
  "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."
}