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Integrity report for PAC-Bayesian Adversarially Robust Generalization for Message Passing Graph Neural Networks: A Sensitivity Analysis

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

arXiv:2606.06293 · pith:2026:LH6KYWA6FXGXZQ3MIZJTD7LZHJ

0Critical
0Advisory
5Detectors run
2026-06-05Last checked

Paper page arXiv integrity.json bundle.json

Detector runs

shingle_duplication skipped v0.1.0 · findings 0 · 2026-06-05 17:50:35.065176+00:00
citation_quote_validity skipped v0.1.0 · findings 0 · 2026-06-05 05:51:14.342893+00:00
cited_work_retraction completed v1.0.0 · findings 0 · 2026-06-05 04:27:40.150825+00:00
claim_evidence completed v1.0.0 · findings 0 · 2026-06-05 01:49:13.226642+00:00
ai_meta_artifact skipped v1.0.0 · findings 0 · 2026-06-05 01:35:49.456395+00:00

Findings

No public integrity findings for this paper.

Signed record

The machine-readable record for this paper lives at /pith/LH6KYWA6FXGXZQ3MIZJTD7LZHJ/integrity.json. Pith Number bundles also include signed pith.integrity.v1 events where a Pith Number exists.