pith. sign in

Integrity report for Plug-in Losses for Evidential Deep Learning: A Simplified Framework for Uncertainty Estimation that Includes the Softmax Classifier

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

arXiv:2605.22746 · pith:2026:IWTYM65N3UA3GUR5GOBP4N3DRL

0Critical
0Advisory
8Detectors run
2026-05-22Last checked

Paper page arXiv integrity.json bundle.json

Detector runs

external_links completed v1.0.0 · findings 0 · 2026-05-22 17:35:27.898611+00:00
shingle_duplication completed v0.1.0 · findings 0 · 2026-05-22 09:50:49.038157+00:00
doi_compliance completed v1.0.0 · findings 0 · 2026-05-22 07:09:45.696081+00:00
doi_title_agreement completed v1.0.0 · findings 0 · 2026-05-22 07:01:53.080430+00:00
citation_quote_validity skipped v0.1.0 · findings 0 · 2026-05-22 03:51:24.979699+00:00
cited_work_retraction completed v1.0.0 · findings 0 · 2026-05-22 03:22:29.411077+00:00
ai_meta_artifact skipped v1.0.0 · findings 0 · 2026-05-22 02:33:37.945223+00:00
claim_evidence completed v1.0.0 · findings 0 · 2026-05-22 02:22:39.117321+00:00

Findings

No public integrity findings for this paper.

Signed record

The machine-readable record for this paper lives at /pith/IWTYM65N/integrity.json. Pith Number bundles also include signed pith.integrity.v1 events where a Pith Number exists.