{
  "id": "2507.07996",
  "title": "Skip a Layer or Loop it? Test-Time Depth Adaptation of Pretrained LLMs",
  "authors": "Ziyue Li, Yang Li, Tianyi Zhou",
  "first_public": "2025-07-10",
  "venue": "arXiv",
  "arxiv": "2507.07996",
  "paper_url": "https://arxiv.org/abs/2507.07996",
  "lens": [
    "recurrent"
  ],
  "representation": [
    "hidden-state"
  ],
  "computation": [
    "depth-wise",
    "recurrent"
  ],
  "training": [
    "inference-only"
  ],
  "questions": [
    "capability",
    "efficiency",
    "architecture"
  ],
  "evidence": [
    "empirical"
  ],
  "modality": [
    "language"
  ],
  "summary": "Adapts the depth of pretrained language models at test time by selectively skipping or repeating layers.",
  "provenance": "Primary-source literature search, 2026-09-04",
  "author_names": [
    "Ziyue Li",
    "Yang Li",
    "Tianyi Zhou"
  ],
  "record_url": "https://latent-implicit-thinking.github.io/papers/2507.07996/",
  "legacy_record_url": "https://latent-implicit-thinking.github.io/papers/#paper-2507-07996",
  "citation_date": "2025-07-10",
  "json_url": "https://latent-implicit-thinking.github.io/papers/2507.07996/record.json",
  "markdown_url": "https://latent-implicit-thinking.github.io/papers/2507.07996/index.md",
  "bibtex_url": "https://latent-implicit-thinking.github.io/papers/2507.07996/citation.bib",
  "csl_url": "https://latent-implicit-thinking.github.io/papers/2507.07996/citation.csl.json"
}