Recoverable Identifier

arXiv:2605.08044 · detector doi_compliance · incontrovertible · 2026-05-19 11:16:45.818717+00:00

advisory doi_compliance recoverable_identifier

DOI in the printed bibliography is fragmented by whitespace or line breaks. A longer candidate (10.1162/tacl_a_00474.https://aclanthology.org/2022.tacl-1.30/.Ishaan) 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

doi: 10.1162/tacl_a_00474.https://aclanthology.org/2022.tacl-1.30/. Ishaan Gulrajani and Tatsunori Hashimoto. Likelihood-based diffusion language models. InThirty-seventh Conference on Neural Information Processing Systems, 2023.https://openreview.net/forum?id=e2MCL6hObn. Dan Hendrycks, Collin Burns, Steven Basart, Andy Zou, Mantas Mazeika, Dawn Song, and Jacob Steinhardt. Measuring massive multitask language understanding. InInternational Conference on Learning Representations, 2021.https://openreview.net/forum?id=d7KBjmI3GmQ. Jing Huang, Zhengxuan Wu, Kyle Mahowald, and Christopher Potts. Inducing character-level structure in subword- based language models with type-level interchange intervention training. In Anna Rogers, Jordan Boyd-Graber, and Naoaki Okazaki, editors,Findings of the Association for Computational Linguistics: ACL 2023, pages 12163–12180, Toronto, Canada, July

Evidence payload

{
  "printed_excerpt": "doi: 10.1162/tacl_a_00474.https://aclanthology.org/2022.tacl-1.30/. Ishaan Gulrajani and Tatsunori Hashimoto. Likelihood-based diffusion language models. InThirty-seventh Conference on Neural Information Processing Systems, 2023.https://ope",
  "reconstructed_doi": "10.1162/tacl_a_00474.https://aclanthology.org/2022.tacl-1.30/.Ishaan",
  "ref_index": 13,
  "resolved_title": null,
  "verdict_class": "incontrovertible"
}