pith. sign in

Integrity report for Dyna-Style Safety Augmented Reinforcement Learning: Staying Safe in the Face of Uncertainty

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

arXiv:2604.25508

0Critical
0Advisory
2Detectors run
2026-05-21Last checked

Paper page arXiv integrity.json

Detector runs

ai_meta_artifact completed v1.0.0 · findings 0 · 2026-05-21 04:39:22.569495+00:00
doi_compliance completed v1.0.0 · findings 0 · 2026-05-19 21:05:45.788089+00:00

Findings

No public integrity findings for this paper.

Signed record

The machine-readable record for this paper lives at /pith/2604.25508/integrity.json. Pith Number bundles also include signed pith.integrity.v1 events where a Pith Number exists.