{
  "id": "2610.02193",
  "title": "Hierarchical Continuous Diffusion Language Models",
  "authors": "Hui Ren, Zihan Li, Chang Liu, Huidong Liu, Alexander Schwing",
  "first_public": "2026-10-01",
  "lens": [
    "continuous",
    "beyond-sequential"
  ],
  "representation": [
    "continuous-state",
    "discrete-token"
  ],
  "training": [
    "supervised"
  ],
  "questions": [
    "architecture",
    "capability"
  ],
  "evidence": [
    "formal",
    "empirical"
  ],
  "modality": [
    "language",
    "symbolic"
  ],
  "summary": "Keeps a continuous state throughout denoising while reading out tokens at each step and feeding them back into the next state update. Tests whether this coupling preserves dependencies during parallel generation on Sudoku, Countdown, and language modeling.",
  "computation": [
    "diffusion",
    "parallel"
  ],
  "venue": "arXiv",
  "arxiv": "2610.02193",
  "paper_url": "https://arxiv.org/abs/2610.02193",
  "provenance": "Primary-source literature search, 2026-10-18",
  "added_at": "2026-10-18",
  "author_names": [
    "Hui Ren",
    "Zihan Li",
    "Chang Liu",
    "Huidong Liu",
    "Alexander Schwing"
  ],
  "record_url": "https://latent-implicit-thinking.github.io/papers/2610.02193/",
  "legacy_record_url": "https://latent-implicit-thinking.github.io/papers/#paper-2610-02193",
  "citation_date": "2026-10-01",
  "json_url": "https://latent-implicit-thinking.github.io/papers/2610.02193/record.json",
  "markdown_url": "https://latent-implicit-thinking.github.io/papers/2610.02193/index.md",
  "bibtex_url": "https://latent-implicit-thinking.github.io/papers/2610.02193/citation.bib",
  "csl_url": "https://latent-implicit-thinking.github.io/papers/2610.02193/citation.csl.json"
}