{
  "id": "2610.01153",
  "title": "Looping Beyond Twice: A Scalable Recipe for Looped Mixture-of-Experts",
  "authors": "Di He, Pengxiang Li, Da Chang, Qingyan Meng, Lu Yin, Shiwei Liu",
  "first_public": "2026-10-01",
  "added_at": "2026-10-18",
  "venue": "arXiv",
  "arxiv": "2610.01153",
  "paper_url": "https://arxiv.org/abs/2610.01153",
  "lens": [
    "recurrent"
  ],
  "representation": [
    "hidden-state"
  ],
  "computation": [
    "recurrent",
    "depth-wise"
  ],
  "training": [
    "pretraining"
  ],
  "questions": [
    "architecture",
    "scaling",
    "efficiency"
  ],
  "evidence": [
    "empirical",
    "scaling"
  ],
  "modality": [
    "language"
  ],
  "summary": "Studies how to train mixture-of-experts transformers with more than two recurrent passes. Combines stabilized residual updates, reintroduced input information, and loop-specific routing to support deeper reuse of the shared model.",
  "provenance": "Primary-source literature search, 2026-10-18",
  "author_names": [
    "Di He",
    "Pengxiang Li",
    "Da Chang",
    "Qingyan Meng",
    "Lu Yin",
    "Shiwei Liu"
  ],
  "record_url": "https://latent-implicit-thinking.github.io/papers/2610.01153/",
  "legacy_record_url": "https://latent-implicit-thinking.github.io/papers/#paper-2610-01153",
  "citation_date": "2026-10-01",
  "json_url": "https://latent-implicit-thinking.github.io/papers/2610.01153/record.json",
  "markdown_url": "https://latent-implicit-thinking.github.io/papers/2610.01153/index.md",
  "bibtex_url": "https://latent-implicit-thinking.github.io/papers/2610.01153/citation.bib",
  "csl_url": "https://latent-implicit-thinking.github.io/papers/2610.01153/citation.csl.json"
}