{
  "id": "2608.13570",
  "title": "Think in Latent, Explain in Language: Self-Explainable Latent Reasoning",
  "authors": "Dayuan Zhao, Shengcao Cao, Yu-Xiong Wang, Liang-Yan Gui",
  "first_public": "2026-07-01",
  "venue": "arXiv",
  "arxiv": "2608.13570",
  "paper_url": "https://arxiv.org/abs/2608.13570",
  "code_url": "https://jasondayuan.github.io/SELR/",
  "lens": [
    "continuous",
    "analysis"
  ],
  "representation": [
    "continuous-state",
    "text-latent-hybrid"
  ],
  "computation": [
    "token-wise"
  ],
  "training": [
    "supervised"
  ],
  "questions": [
    "capability",
    "efficiency",
    "interpretability"
  ],
  "evidence": [
    "empirical"
  ],
  "modality": [
    "language",
    "multimodal",
    "vision"
  ],
  "summary": "Jointly trains latent states for answer prediction and for decoding back into readable reasoning, using one model rather than a separate post-hoc explanation decoder.",
  "provenance": "Primary-source literature search, 2026-09-05",
  "author_names": [
    "Dayuan Zhao",
    "Shengcao Cao",
    "Yu-Xiong Wang",
    "Liang-Yan Gui"
  ],
  "record_url": "https://latent-implicit-thinking.github.io/papers/2608.13570/",
  "legacy_record_url": "https://latent-implicit-thinking.github.io/papers/#paper-2608-13570",
  "citation_date": "2026-07-01",
  "json_url": "https://latent-implicit-thinking.github.io/papers/2608.13570/record.json",
  "markdown_url": "https://latent-implicit-thinking.github.io/papers/2608.13570/index.md",
  "bibtex_url": "https://latent-implicit-thinking.github.io/papers/2608.13570/citation.bib",
  "csl_url": "https://latent-implicit-thinking.github.io/papers/2608.13570/citation.csl.json"
}