{
  "id": "2610.35544",
  "title": "StateLoop: Persistent State for Looped Transformers",
  "authors": "Feichen Song, Boyi Zeng, He Li, Shixiang Song, Yiqin Hao, Zitong Wang, Yizhou Yang, Yifan Liu, Ziwei He, Zhouhan Lin",
  "first_public": "2026-10-26",
  "added_at": "2026-11-02",
  "venue": "arXiv",
  "arxiv": "2610.35544",
  "paper_url": "https://arxiv.org/abs/2610.35544",
  "html_url": "https://arxiv.org/html/2610.35544v1",
  "lens": [
    "recurrent"
  ],
  "representation": [
    "hidden-state"
  ],
  "computation": [
    "recurrent",
    "depth-wise",
    "stateful"
  ],
  "training": [
    "pretraining"
  ],
  "questions": [
    "architecture",
    "capability",
    "scaling"
  ],
  "evidence": [
    "empirical"
  ],
  "modality": [
    "language"
  ],
  "summary": "Gives each token a persistent state alongside the output of a shared transformer backbone. Learned gates control what the state retains across loops, and separate readouts feed it into later loops and the final prediction.",
  "provenance": "Primary-source literature review, 2026-11-02",
  "author_names": [
    "Feichen Song",
    "Boyi Zeng",
    "He Li",
    "Shixiang Song",
    "Yiqin Hao",
    "Zitong Wang",
    "Yizhou Yang",
    "Yifan Liu",
    "Ziwei He",
    "Zhouhan Lin"
  ],
  "record_url": "https://latent-implicit-thinking.github.io/papers/2610.35544/",
  "legacy_record_url": "https://latent-implicit-thinking.github.io/papers/#paper-2610-35544",
  "citation_date": "2026-10-26",
  "json_url": "https://latent-implicit-thinking.github.io/papers/2610.35544/record.json",
  "markdown_url": "https://latent-implicit-thinking.github.io/papers/2610.35544/index.md",
  "bibtex_url": "https://latent-implicit-thinking.github.io/papers/2610.35544/citation.bib",
  "csl_url": "https://latent-implicit-thinking.github.io/papers/2610.35544/citation.csl.json",
  "pdf_url": "https://arxiv.org/pdf/2610.35544"
}