{
  "id": "2609.36636",
  "title": "What Makes Recurrence Effective in Looped Language Models?",
  "authors": "Xinlin Zhuang, Siyuan Wang, Imran Razzak, Weiyang Liu",
  "first_public": "2026-09-29",
  "added_at": "2026-10-18",
  "venue": "arXiv",
  "arxiv": "2609.36636",
  "paper_url": "https://arxiv.org/abs/2609.36636",
  "lens": [
    "recurrent",
    "analysis"
  ],
  "representation": [
    "hidden-state"
  ],
  "computation": [
    "recurrent",
    "depth-wise"
  ],
  "training": [
    "pretraining",
    "analysis-only"
  ],
  "questions": [
    "architecture",
    "scaling",
    "limitations"
  ],
  "evidence": [
    "empirical"
  ],
  "modality": [
    "language"
  ],
  "summary": "Compares loop layouts and ways of passing information between loops in language models. Examines when recurrence helps reasoning and when it helps less on knowledge-dependent tasks.",
  "provenance": "Primary-source literature search, 2026-10-18",
  "author_names": [
    "Xinlin Zhuang",
    "Siyuan Wang",
    "Imran Razzak",
    "Weiyang Liu"
  ],
  "record_url": "https://latent-implicit-thinking.github.io/papers/2609.36636/",
  "legacy_record_url": "https://latent-implicit-thinking.github.io/papers/#paper-2609-36636",
  "citation_date": "2026-09-29",
  "json_url": "https://latent-implicit-thinking.github.io/papers/2609.36636/record.json",
  "markdown_url": "https://latent-implicit-thinking.github.io/papers/2609.36636/index.md",
  "bibtex_url": "https://latent-implicit-thinking.github.io/papers/2609.36636/citation.bib",
  "csl_url": "https://latent-implicit-thinking.github.io/papers/2609.36636/citation.csl.json"
}