{
  "id": "2610.40283",
  "title": "Latent Path Exploration via Potential-Guided Subtrajectory Balance",
  "authors": "Xiaoling Zeng, Qi Zhang",
  "first_public": "2026-10-29",
  "added_at": "2026-11-02",
  "venue": "arXiv",
  "arxiv": "2610.40283",
  "paper_url": "https://arxiv.org/abs/2610.40283",
  "html_url": "https://arxiv.org/html/2610.40283v1",
  "lens": [
    "continuous",
    "internalized"
  ],
  "representation": [
    "continuous-state",
    "hidden-state"
  ],
  "computation": [
    "token-wise",
    "search"
  ],
  "training": [
    "supervised",
    "distillation",
    "reinforcement-learning"
  ],
  "questions": [
    "capability",
    "controllability"
  ],
  "evidence": [
    "empirical"
  ],
  "modality": [
    "language",
    "symbolic"
  ],
  "summary": "Samples continuous reasoning paths before producing an answer. Trains the paths with explicit-chain supervision, hidden-state distillation, and a balance objective that compares how much intermediate states support the correct answer.",
  "provenance": "Primary-source literature review, 2026-11-02",
  "author_names": [
    "Xiaoling Zeng",
    "Qi Zhang"
  ],
  "record_url": "https://latent-implicit-thinking.github.io/papers/2610.40283/",
  "legacy_record_url": "https://latent-implicit-thinking.github.io/papers/#paper-2610-40283",
  "citation_date": "2026-10-29",
  "json_url": "https://latent-implicit-thinking.github.io/papers/2610.40283/record.json",
  "markdown_url": "https://latent-implicit-thinking.github.io/papers/2610.40283/index.md",
  "bibtex_url": "https://latent-implicit-thinking.github.io/papers/2610.40283/citation.bib",
  "csl_url": "https://latent-implicit-thinking.github.io/papers/2610.40283/citation.csl.json",
  "pdf_url": "https://arxiv.org/pdf/2610.40283"
}