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Integrity report for Training ML Models with Predictable Failures

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

arXiv:2605.15134 · pith:2026:TZBVH2UCH57UFKYOX24RCL4VK2

0Critical
1Advisory
8Detectors run
2026-05-20Last checked

Paper page arXiv integrity.json bundle.json

Detector runs

claim_evidence completed v1.0.0 · findings 0 · 2026-05-20 23:02:15.938123+00:00
doi_compliance completed v1.0.0 · findings 1 · 2026-05-20 20:34:47.281837+00:00
doi_title_agreement completed v1.0.0 · findings 0 · 2026-05-20 20:31:29.635812+00:00
claim_evidence completed v1.0.0 · findings 0 · 2026-05-19 14:41:54.368282+00:00
external_links completed v1.0.0 · findings 0 · 2026-05-19 11:34:11.933963+00:00
shingle_duplication skipped v0.1.0 · findings 0 · 2026-05-19 09:50:02.248597+00:00
citation_quote_validity skipped v0.1.0 · findings 0 · 2026-05-19 05:51:07.253963+00:00
ai_meta_artifact skipped v1.0.0 · findings 0 · 2026-05-19 05:34:19.505612+00:00

Findings

No public integrity findings for this paper.

Signed record

The machine-readable record for this paper lives at /pith/2605.15134/integrity.json. Pith Number bundles also include signed pith.integrity.v1 events where a Pith Number exists.