{
  "id": "2610.06833",
  "title": "Towards Looped Models Done Right, Part II: Rethinking at Fixed Points",
  "authors": "Benhao Huang, Chufan Shi, Junlin Chen, Shicheng Wen, Zhengzhong Liu, Eric Xing, Xuezhe Ma",
  "first_public": "2026-10-05",
  "added_at": "2026-10-18",
  "venue": "arXiv",
  "arxiv": "2610.06833",
  "paper_url": "https://arxiv.org/abs/2610.06833",
  "summary": "Uses near-fixed-point recurrent states to reduce the cost of training, key/value caching, and prefill. Learns how to sample loop depths and changes how the input is reintroduced on each loop.",
  "lens": [
    "recurrent"
  ],
  "representation": [
    "hidden-state",
    "cache-memory"
  ],
  "computation": [
    "recurrent",
    "depth-wise"
  ],
  "training": [
    "pretraining",
    "distillation",
    "reinforcement-learning"
  ],
  "questions": [
    "architecture",
    "efficiency",
    "scaling"
  ],
  "evidence": [
    "empirical",
    "scaling"
  ],
  "modality": [
    "language"
  ],
  "provenance": "Primary-source literature search, 2026-10-18",
  "author_names": [
    "Benhao Huang",
    "Chufan Shi",
    "Junlin Chen",
    "Shicheng Wen",
    "Zhengzhong Liu",
    "Eric Xing",
    "Xuezhe Ma"
  ],
  "record_url": "https://latent-implicit-thinking.github.io/papers/2610.06833/",
  "legacy_record_url": "https://latent-implicit-thinking.github.io/papers/#paper-2610-06833",
  "citation_date": "2026-10-05",
  "json_url": "https://latent-implicit-thinking.github.io/papers/2610.06833/record.json",
  "markdown_url": "https://latent-implicit-thinking.github.io/papers/2610.06833/index.md",
  "bibtex_url": "https://latent-implicit-thinking.github.io/papers/2610.06833/citation.bib",
  "csl_url": "https://latent-implicit-thinking.github.io/papers/2610.06833/citation.csl.json"
}