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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
2026-06-01Last checked

Paper page arXiv integrity.json bundle.json

Detector runs

doi_compliance completed v1.0.0 · findings 0 · 2026-06-01 07:29:02.672191+00:00
doi_title_agreement completed v1.0.0 · findings 0 · 2026-06-01 07:04:49.889802+00:00
cited_work_retraction completed v1.0.0 · findings 0 · 2026-05-30 10:56:21.739509+00:00
ai_meta_artifact completed v1.0.0 · findings 0 · 2026-05-29 03:36:52.009585+00:00
claim_evidence completed v1.0.0 · findings 0 · 2026-05-28 19:44:56.768850+00:00
external_links completed v1.0.0 · findings 0 · 2026-05-24 17:35:29.954345+00:00
citation_quote_validity completed v0.1.0 · findings 0 · 2026-05-24 07:52:07.175737+00:00
shingle_duplication completed v0.1.0 · findings 0 · 2026-05-22 09:50:49.038157+00:00

Findings

No public integrity findings for this paper.

Signed record

The machine-readable record for this paper lives at /pith/IWTYM65N3UA3GUR5GOBP4N3DRL/integrity.json. Pith Number bundles also include signed pith.integrity.v1 events where a Pith Number exists.