{
  "id": "2610.14456",
  "title": "Learning to Extrapolate in Depth with Looped Transformers",
  "authors": "Huitao Yang, Jianhao Huang, Zixuan Wang, Baharan Mirzasoleiman",
  "first_public": "2026-10-10",
  "added_at": "2026-10-18",
  "venue": "arXiv",
  "arxiv": "2610.14456",
  "paper_url": "https://arxiv.org/abs/2610.14456",
  "summary": "Analyzes how many extra loops a model trained on graph connectivity can safely run. Derives a finite range where added depth solves harder graphs before further loops create false connections.",
  "lens": [
    "analysis",
    "recurrent"
  ],
  "representation": [
    "hidden-state"
  ],
  "computation": [
    "recurrent",
    "depth-wise"
  ],
  "training": [
    "supervised",
    "analysis-only"
  ],
  "questions": [
    "theory",
    "generalization",
    "limitations"
  ],
  "evidence": [
    "formal",
    "empirical",
    "boundary"
  ],
  "modality": [
    "symbolic"
  ],
  "provenance": "Primary-source literature search, 2026-10-18",
  "author_names": [
    "Huitao Yang",
    "Jianhao Huang",
    "Zixuan Wang",
    "Baharan Mirzasoleiman"
  ],
  "record_url": "https://latent-implicit-thinking.github.io/papers/2610.14456/",
  "legacy_record_url": "https://latent-implicit-thinking.github.io/papers/#paper-2610-14456",
  "citation_date": "2026-10-10",
  "json_url": "https://latent-implicit-thinking.github.io/papers/2610.14456/record.json",
  "markdown_url": "https://latent-implicit-thinking.github.io/papers/2610.14456/index.md",
  "bibtex_url": "https://latent-implicit-thinking.github.io/papers/2610.14456/citation.bib",
  "csl_url": "https://latent-implicit-thinking.github.io/papers/2610.14456/citation.csl.json"
}