{
  "id": 12080189,
  "title": "Depth as Time in One-Step Generative Models",
  "url": "https://urgent.news/2026/10/02/depth-as-time-in-one-step-generative-models",
  "topic": "ai",
  "section": "AI",
  "published": "2026-10-02T17:20:08.000Z",
  "source": {
    "name": "arXiv cs.AI",
    "slug": "arxiv-cs-ai",
    "url": "https://arxiv.org/abs/2610.03626v1"
  },
  "original_language": "en",
  "account": null,
  "summary": "The recent wave of one-step generative models, which compress the multi-step trajectory of diffusion via either distillation or learned flow maps, has reached an inflection point where they can generate high-quality images. Here, we ask a natural question that follows from these advances: what happens to the denoising trajectory of multi-step diffusion when generation is compressed into a single…",
  "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."
}