{
  "id": "2510.04871",
  "title": "Less is More: Recursive Reasoning with Tiny Networks",
  "first_public": "2025-10-06",
  "paper_url": "https://arxiv.org/abs/2510.04871",
  "authors": "Alexia Jolicoeur-Martineau",
  "arxiv": "2510.04871",
  "added_at": "2026-11-09",
  "venue": "arXiv",
  "provenance": "Primary-source literature review, 2026-11-09",
  "html_url": "https://arxiv.org/html/2510.04871v1",
  "lens": [
    "recurrent"
  ],
  "representation": [
    "hidden-state"
  ],
  "computation": [
    "recurrent",
    "stateful"
  ],
  "training": [
    "supervised"
  ],
  "questions": [
    "architecture",
    "capability",
    "efficiency"
  ],
  "evidence": [
    "empirical"
  ],
  "modality": [
    "symbolic"
  ],
  "summary": "Uses one small network to repeatedly update a reasoning state and a proposed answer. Trains these updates with deep supervision and a learned halting score, evaluating the approach on Sudoku, mazes, and ARC-AGI puzzles.",
  "author_names": [
    "Alexia Jolicoeur-Martineau"
  ],
  "record_url": "https://latent-implicit-thinking.github.io/papers/2510.04871/",
  "legacy_record_url": "https://latent-implicit-thinking.github.io/papers/#paper-2510-04871",
  "citation_date": "2025-10-06",
  "json_url": "https://latent-implicit-thinking.github.io/papers/2510.04871/record.json",
  "markdown_url": "https://latent-implicit-thinking.github.io/papers/2510.04871/index.md",
  "bibtex_url": "https://latent-implicit-thinking.github.io/papers/2510.04871/citation.bib",
  "csl_url": "https://latent-implicit-thinking.github.io/papers/2510.04871/citation.csl.json",
  "pdf_url": "https://arxiv.org/pdf/2510.04871"
}