{
  "abstract": "Embedding-based verification often calibrates a false-accept threshold from all impostor pairs among $m$ identities, although these pairs share identities. We characterize a worst-case limit: when hub identities score highly against a fraction $ρ$ of the population, a calibration-only threshold with marginal false-accept rate (FAR) at most $α$ under every identity-exchangeable law reaches the hub score on hub-free calibration sets with probability at most $(m+2)α/(2ρ)$. Uniformly accepting near that score at levels well below $ρ/m$ therefore requires trial information. We propose COVE, which ranks the trial pair among all $N=\\binom{m+2}{2}$ pairs formed by augmenting the calibration units with the probe and reference. Under identity exchangeability, its marginal FAR is at most $\\lfloorαN\\rfloor/N$, with first possible acceptance at $1/N=O(1/m^2)$. The rule also retains this guarantee with a fixed symmetric cohort-normalized score using an independent cohort. On 6 benchmarks and 8 frozen encoders, realised FAR was consistent with the exact bound. Where both valid calibration-only baselines accepted nothing, COVE retained a median $100\\%$ of the sampled oracle's true-accept rate over reliable comparisons. In contrast, an empirical quantile over dependent pairs reached 2.87$\\,α$ FAR, and a binomial upper confidence bound over pairs missed its nominal 95\\% conditional-FAR target in up to 55\\% of calibration draws. Symmetric CSLS raised COVE's true-accept rate by up to 4.3-fold in the tested settings. The code is available in https://github.com/salimkhazem/Cove.git",
  "abstract_shown": true,
  "affiliations": [],
  "article_type": null,
  "arxiv": "2610.35277",
  "author_total": 1,
  "authors": [
    {
      "name": "Salim Khazem"
    }
  ],
  "bibtex": "https://research.draconitic.com/paper/5p7dgt0m8ng7m.bib",
  "cited_by": 0,
  "doi": "10.48550/arxiv.2610.35277",
  "fulltext_url": null,
  "id": "5p7dgt0m8ng7m",
  "issns": [],
  "landing_url": "https://arxiv.org/abs/2610.35277",
  "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.LG"
    ],
    [
      "arxiv",
      "stat.ML"
    ]
  ],
  "openalex": null,
  "pdf_url": "https://arxiv.org/pdf/2610.35277",
  "pmcid": null,
  "pmid": null,
  "published": "2026-10-26",
  "publisher": null,
  "ris": "https://research.draconitic.com/paper/5p7dgt0m8ng7m.ris",
  "sources": [
    {
      "first_seen": "2026-10-30T12:35:49Z",
      "native_id": "2610.35277",
      "source": "arxiv",
      "url": "https://arxiv.org/abs/2610.35277"
    }
  ],
  "subjects": [
    {
      "field": "mathematics",
      "origin": "arxiv:stat.ML",
      "subfield": "statistics"
    }
  ],
  "title": "Identities, Not Pairs: Distribution-Free False-Accept Control for Embedding-Based Verification",
  "title_text": "Identities, Not Pairs: Distribution-Free False-Accept Control for Embedding-Based Verification",
  "type": "preprint",
  "updated_at": "2026-10-30T12:35:49Z",
  "url": "https://research.draconitic.com/paper/5p7dgt0m8ng7m",
  "venue": "arXiv",
  "versions": []
}