{
  "id": "2610.02185",
  "title": "Decoding Looped Transformers Better for (Almost) Free",
  "authors": "Weihao Liu, Huangjie Zheng, Tianrong Chen, Rohit Dilip, Richard He Bai, Yizhu Jiao, Yuyang Wang, Ruixiang Zhang",
  "first_public": "2026-10-01",
  "added_at": "2026-10-18",
  "venue": "arXiv",
  "arxiv": "2610.02185",
  "paper_url": "https://arxiv.org/abs/2610.02185",
  "lens": [
    "recurrent"
  ],
  "representation": [
    "hidden-state"
  ],
  "computation": [
    "recurrent",
    "depth-wise"
  ],
  "training": [
    "inference-only"
  ],
  "questions": [
    "capability",
    "efficiency"
  ],
  "evidence": [
    "empirical"
  ],
  "modality": [
    "language",
    "symbolic"
  ],
  "summary": "Compares a looped model's final prediction with predictions from earlier loops to improve decoding without additional training. Tests contrastive variants using either output logits or hidden states on mathematical reasoning and code generation.",
  "provenance": "Primary-source literature search, 2026-10-18",
  "author_names": [
    "Weihao Liu",
    "Huangjie Zheng",
    "Tianrong Chen",
    "Rohit Dilip",
    "Richard He Bai",
    "Yizhu Jiao",
    "Yuyang Wang",
    "Ruixiang Zhang"
  ],
  "record_url": "https://latent-implicit-thinking.github.io/papers/2610.02185/",
  "legacy_record_url": "https://latent-implicit-thinking.github.io/papers/#paper-2610-02185",
  "citation_date": "2026-10-01",
  "json_url": "https://latent-implicit-thinking.github.io/papers/2610.02185/record.json",
  "markdown_url": "https://latent-implicit-thinking.github.io/papers/2610.02185/index.md",
  "bibtex_url": "https://latent-implicit-thinking.github.io/papers/2610.02185/citation.bib",
  "csl_url": "https://latent-implicit-thinking.github.io/papers/2610.02185/citation.csl.json"
}