{
  "id": 18227,
  "title": "APO: Unsupervised Atomic Policy Optimization for 3D Structure Prediction of Atomic Systems",
  "url": "https://urgent.news/2026/07/30/apo-unsupervised-atomic-policy-optimization-for-3d-structure",
  "topic": "world",
  "section": "World",
  "published": "2026-07-30T17:21:58.000Z",
  "source": {
    "name": "arXiv cs.AI",
    "slug": "arxiv-cs-ai",
    "url": "https://arxiv.org/abs/2607.28553v1"
  },
  "original_language": "en",
  "account": null,
  "summary": "Predicting the 3D structures of atomic systems is fundamental to advancing material science and drug discovery. While flow-matching models (, FlowDPO) have recently shown promise in this domain, their performance relies heavily on alignment with ground-truth coordinates via supervised preference learning. However, obtaining experimental labels for novel crystal phases or de novo proteins is…",
  "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."
}