Recoverable Identifier

arXiv:2604.25779 · detector doi_compliance · incontrovertible · 2026-05-19 20:46:50.338518+00:00

advisory doi_compliance recoverable_identifier

DOI in the printed bibliography is fragmented by whitespace or line breaks. A longer candidate (10.18653/v1/2023.acl-short.157.URLhttps://aclanthology.org/2023.acl-short.157/.Atsushi) was visible in the surrounding text but could not be confirmed against doi.org as printed.

Paper page Integrity report arXiv Try DOI

Evidence text

Association for Computational Linguistics. doi: 10.18653/v1/2023. acl-short.157. URLhttps://aclanthology.org/2023.acl-short.157/. Atsushi Yanagisawa, Akbarzaib Khan, Thanjeetraaj Kaur Balraj Singh, Yunjong Na, Kevin Zhu, and Antonio Mari. Liminal training: Characterizing and mitigating subliminal learning in large language models. InSocially Responsible and Trustworthy F oundation Models at NeurIPS 2025,

Evidence payload

{
  "printed_excerpt": "Association for Computational Linguistics. doi: 10.18653/v1/2023. acl-short.157. URLhttps://aclanthology.org/2023.acl-short.157/. Atsushi Yanagisawa, Akbarzaib Khan, Thanjeetraaj Kaur Balraj Singh, Yunjong Na, Kevin Zhu, and Antonio Mari. L",
  "reconstructed_doi": "10.18653/v1/2023.acl-short.157.URLhttps://aclanthology.org/2023.acl-short.157/.Atsushi",
  "ref_index": 5,
  "resolved_title": null,
  "verdict_class": "incontrovertible"
}