Integrity report for A New Framework to Analyse the Distributional Robustness of Deep Neural Networks

A machine-verified record of the checks Pith has run against this paper: detector runs, findings, signed bundle events, and canonical identifiers.

arXiv:2605.21313 · pith:2026:HBX2JJ6WPL7VSXQTRHJSBE5BJP

0Critical

0Advisory

8Detectors run

2026-05-30Last checked

Paper page arXiv integrity.json bundle.json

Detector runs

doi_title_agreement completed v1.0.0 · findings 0 · 2026-05-30 10:04:04.190431+00:00

doi_compliance completed v1.0.0 · findings 0 · 2026-05-28 08:25:57.568517+00:00

ai_meta_artifact completed v1.0.0 · findings 0 · 2026-05-28 03:37:47.361464+00:00

claim_evidence completed v1.0.0 · findings 0 · 2026-05-26 10:04:06.514675+00:00

external_links completed v1.0.0 · findings 0 · 2026-05-21 23:35:41.635231+00:00

shingle_duplication completed v0.1.0 · findings 0 · 2026-05-21 17:50:11.378372+00:00

citation_quote_validity completed v0.1.0 · findings 0 · 2026-05-21 07:50:02.858713+00:00

cited_work_retraction completed v1.0.0 · findings 0 · 2026-05-21 04:55:09.100772+00:00

Findings

No public integrity findings for this paper.

Signed record

The machine-readable record for this paper lives at /pith/HBX2JJ6WPL7VSXQTRHJSBE5BJP/integrity.json. Pith Number bundles also include signed pith.integrity.v1 events where a Pith Number exists.