{
  "id": 16834705,
  "title": "What Improves During Pretraining? Tracking Knowledge Acquisition with Point-in-Time Models",
  "url": "https://urgent.news/2026/10/27/what-improves-during-pretraining-tracking-knowledge-acquisition-with",
  "topic": "ai",
  "section": "AI",
  "published": "2026-10-27T17:52:38.000Z",
  "source": {
    "name": "arXiv cs.AI",
    "slug": "arxiv-cs-ai",
    "url": "https://arxiv.org/abs/2610.37631v1"
  },
  "original_language": "en",
  "account": null,
  "summary": "Language models pretrained on web corpora collected over multiple years learn both general and domain-specific knowledge. How these different kinds of knowledge are learned as pretraining progresses remains unclear. Recent point-in-time models trained on web snapshots from different years provide a way to probe how knowledge prevalence varies over time. Using these models, we propose a temporal…",
  "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."
}