{
  "id": "codd2026",
  "title": "Breaking the Factorization Barrier in Diffusion Language Models",
  "authors": [
    {
      "given": "Ian",
      "family": "Li"
    },
    {
      "given": "Zilei",
      "family": "Shao"
    },
    {
      "given": "Benjie",
      "family": "Wang"
    },
    {
      "given": "Rose",
      "family": "Yu"
    },
    {
      "given": "Guy",
      "family": "Van den Broeck"
    },
    {
      "given": "Anji",
      "family": "Liu"
    }
  ],
  "year": 2026,
  "venue": "ICML 2026",
  "paper_url": "https://proceedings.mlr.press/v306/li26fd.html",
  "summary": "CoDD composes factorized diffusion predictions with a tractable probabilistic-circuit prior to model joint token dependencies.",
  "connection": "Shares structured generation’s separation of parallel neural scoring from joint probabilistic inference.",
  "bibtex_type": "inproceedings",
  "citation_key": "li2026factorization",
  "source_urls": [
    "https://proceedings.mlr.press/v306/li26fd.html",
    "https://arxiv.org/abs/2603.00045",
    "https://arxiv.org/html/2603.00045v3"
  ],
  "arxiv_id": "2603.00045",
  "arxiv_first_posted": "2026-02-09",
  "updated_at": "2026-11-10",
  "record_url": "https://yuntiandeng.com/research/papers/codd2026/"
}