{
  "abstract": "In shared-codebook unsourced random access (URA), a receiver must recover an unordered set of messages from simultaneous transmissions. Its outer decoder assembles ambiguous slot-wise evidence into distinct codewords while enforcing parity constraints. We propose CIDER, a learned outer decoder that combines masked-diffusion refinement with cross-row demixing and parity-aware propagation on the code's Tanner graph. At higher per-bin loads, quality-guided remasking selectively re-decodes low-confidence rows. On the evaluated GF(64) LDPC codes at $K=2$, CIDER has lower measured symbol and codeword error rates than SIC-BP and FFT-BP at all four code lengths. In same-GPU decoder-only measurements, the deployed mixed-precision implementation is $8.2\\times$ to $167\\times$ faster than our optimized FFT-BP implementation across those lengths. We also evaluate higher loads, estimated user counts, and detector mismatch. Code is available at https://github.com/jiyunyoung/CIDER/tree/neurips-2026.",
  "abstract_shown": true,
  "affiliations": [],
  "article_type": null,
  "arxiv": "2605.26580",
  "author_total": 4,
  "authors": [
    {
      "name": "Taekyun Lee"
    },
    {
      "name": "Jiyoung Yun"
    },
    {
      "name": "Jeffrey G. Andrews"
    },
    {
      "name": "Hyeji Kim"
    }
  ],
  "bibtex": "https://research.draconitic.com/paper/bedk3z3xf7byw.bib",
  "cited_by": 0,
  "doi": "10.48550/arxiv.2605.26580",
  "fulltext_url": null,
  "id": "bedk3z3xf7byw",
  "issns": [],
  "landing_url": "https://arxiv.org/abs/2605.26580",
  "language": null,
  "licence": "CC-BY-4.0",
  "licence_label": "CC BY 4.0",
  "licence_source": "article",
  "licence_url": "http://creativecommons.org/licenses/by/4.0/",
  "metadata_licence": "CC0-1.0",
  "native_subjects": [
    [
      "arxiv",
      "cs.IT"
    ],
    [
      "arxiv",
      "eess.SP"
    ],
    [
      "arxiv",
      "math.IT"
    ],
    [
      "openalex",
      "1705|Error Correcting Code Techniques"
    ]
  ],
  "openalex": "W7162547477",
  "pdf_url": "https://arxiv.org/pdf/2605.26580",
  "pmcid": null,
  "pmid": null,
  "published": "2026-10-13",
  "publisher": null,
  "ris": "https://research.draconitic.com/paper/bedk3z3xf7byw.ris",
  "sources": [
    {
      "first_seen": "2026-10-30T12:29:35Z",
      "native_id": "2605.26580",
      "source": "arxiv",
      "url": "https://arxiv.org/abs/2605.26580"
    }
  ],
  "subjects": [
    {
      "field": "mathematics",
      "origin": "arxiv:math.IT",
      "subfield": "general"
    }
  ],
  "title": "Structured Masked Diffusion for Shared-Codebook Unsourced Random Access Decoding",
  "title_text": "Structured Masked Diffusion for Shared-Codebook Unsourced Random Access Decoding",
  "type": "preprint",
  "updated_at": "2026-10-30T12:29:35Z",
  "url": "https://research.draconitic.com/paper/bedk3z3xf7byw",
  "venue": "arXiv",
  "versions": []
}