{
  "id": 3634518,
  "title": "Unfolding Scientific Papers into Multi-Turn Generation Trajectories for Continued Pre-Training",
  "url": "https://urgent.news/2026/08/26/unfolding-scientific-papers-into-multi-turn-generation-trajectories",
  "topic": "ai",
  "section": "AI",
  "published": "2026-08-26T14:06:29.000Z",
  "source": {
    "name": "arXiv cs.AI",
    "slug": "arxiv-cs-ai",
    "url": "https://arxiv.org/abs/2608.25826v1"
  },
  "original_language": "en",
  "account": null,
  "summary": "A recent line of synthetic-data work reconstructs the thinking behind existing text rather than rewriting the text itself, but it operates on short web passages, recovers only local thoughts, and leaves the structure of whole documents untouched. Scientific papers are written to a clear and largely uniform structure and make a natural substrate for lifting this paradigm to the document level. We…",
  "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."
}