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Integrity report for ProRL: Effective Reinforcement Learning for Proactive Recommendation via Rectified Policy Gradient Estimation

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

arXiv:2605.28293 · pith:2026:UQBBR3MVAF5G7MDW3IRXYOWWN7

0Critical
0Advisory
5Detectors run
2026-06-02Last checked

Paper page arXiv integrity.json bundle.json

Detector runs

claim_evidence completed v1.0.0 · findings 0 · 2026-06-02 00:47:32.850731+00:00
citation_quote_validity skipped v0.1.0 · findings 0 · 2026-05-28 13:50:26.762749+00:00
cited_work_retraction completed v1.0.0 · findings 0 · 2026-05-28 09:53:56.964128+00:00
ai_meta_artifact skipped v1.0.0 · findings 0 · 2026-05-28 01:34:18.843309+00:00
claim_evidence completed v1.0.0 · findings 0 · 2026-05-28 01:24:41.621215+00:00

Findings

No public integrity findings for this paper.

Signed record

The machine-readable record for this paper lives at /pith/UQBBR3MV/integrity.json. Pith Number bundles also include signed pith.integrity.v1 events where a Pith Number exists.