{
  "id": 11083803,
  "title": "Scaling Laws for Looped Mixture of Experts",
  "url": "https://urgent.news/2026/09/30/scaling-laws-for-looped-mixture-of-experts",
  "topic": "ai",
  "section": "AI",
  "published": "2026-09-30T17:53:47.000Z",
  "source": {
    "name": "arXiv cs.AI",
    "slug": "arxiv-cs-ai",
    "url": "https://arxiv.org/abs/2609.40316v1"
  },
  "original_language": "en",
  "account": null,
  "summary": "Looped transformers and Mixture-of-Experts (MoE) offer complementary routes to efficient scaling: recurrence increases computational depth at fixed parameters, while MoE sparsity expands total capacity at fixed active compute. Yet existing scaling laws model recurrence or sparsity in isolation. In this work, we introduce Loop Scaling Laws, the first scaling law to jointly model recurrence and…",
  "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."
}