Unresolvable Identifier

arXiv:2605.09089 · detector doi_compliance · cross_source · 2026-05-19 10:31:44.409213+00:00

critical doi_compliance unresolvable_identifier

Identifier '10.1109/cvpr52734.2025.014152' is syntactically valid but the DOI registry (doi.org) returned 404, and Crossref / OpenAlex / internal corpus also have no record. The cited work could not be located through any authoritative source.

Paper page Integrity report arXiv Try DOI

Evidence text

Gu, Z., Zhu, B., Zhu, G., Chen, Y., Tang, M., Wang, J.: Univad: A training- free unified model for few-shot visual anomaly detection. In: 2025 IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR). pp. 15194– 15203 (2025).https://doi.org/10.1109/CVPR52734.2025.014152, 4

Evidence payload

{
  "arxiv_id": null,
  "checked_sources": [
    "crossref_by_doi",
    "openalex_by_doi",
    "doi_org_head"
  ],
  "doi": "10.1109/cvpr52734.2025.014152",
  "raw_excerpt": "Gu, Z., Zhu, B., Zhu, G., Chen, Y., Tang, M., Wang, J.: Univad: A training- free unified model for few-shot visual anomaly detection. In: 2025 IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR). pp. 15194\u2013 15203 (2025).https://doi.org/10.1109/CVPR52734.2025.014152, 4",
  "ref_index": 9,
  "verdict_class": "cross_source"
}