{
  "id": "2610.14252",
  "title": "Adaptive-Depth Is a Finishing Stage",
  "authors": "Andrei Piterbarg, Sean McLeish, Dhruv Pai, Benjamin Keigwin",
  "first_public": "2026-10-09",
  "added_at": "2026-10-18",
  "venue": "arXiv",
  "arxiv": "2610.14252",
  "paper_url": "https://arxiv.org/abs/2610.14252",
  "lens": [
    "recurrent"
  ],
  "representation": [
    "hidden-state"
  ],
  "computation": [
    "recurrent",
    "depth-wise"
  ],
  "training": [
    "pretraining",
    "curriculum"
  ],
  "questions": [
    "efficiency",
    "architecture",
    "scaling"
  ],
  "evidence": [
    "empirical",
    "scaling"
  ],
  "modality": [
    "language"
  ],
  "summary": "Trains a looped language model at a fixed depth first, then introduces varying depths only near the end of training. Compares the resulting training cost and performance across inference depths with varying depth throughout training.",
  "provenance": "Primary-source literature search, 2026-10-18",
  "author_names": [
    "Andrei Piterbarg",
    "Sean McLeish",
    "Dhruv Pai",
    "Benjamin Keigwin"
  ],
  "record_url": "https://latent-implicit-thinking.github.io/papers/2610.14252/",
  "legacy_record_url": "https://latent-implicit-thinking.github.io/papers/#paper-2610-14252",
  "citation_date": "2026-10-09",
  "json_url": "https://latent-implicit-thinking.github.io/papers/2610.14252/record.json",
  "markdown_url": "https://latent-implicit-thinking.github.io/papers/2610.14252/index.md",
  "bibtex_url": "https://latent-implicit-thinking.github.io/papers/2610.14252/citation.bib",
  "csl_url": "https://latent-implicit-thinking.github.io/papers/2610.14252/citation.csl.json"
}