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Integrity report for Neural-ESO: A Dual-Pathway Architecture for Provably Robust Learning-Based Control

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

arXiv:2607.06535 · pith:2026:7SQ5J7ZXL7HLUDC4PA2JHJLRZF

0Critical
0Advisory
4Detectors run
2026-07-09Last checked

Paper page arXiv integrity.json bundle.json

Detector runs

ai_meta_artifact completed v1.0.0 · findings 0 · 2026-07-09 09:49:31.685394+00:00
claim_evidence completed v1.0.0 · findings 0 · 2026-07-09 09:01:48.583643+00:00
doi_title_agreement completed v1.0.0 · findings 0 · 2026-07-09 07:30:57.457772+00:00
doi_compliance completed v1.0.0 · findings 0 · 2026-07-09 07:19:37.163084+00:00

Findings

No public integrity findings for this paper.

Signed record

The machine-readable record for this paper lives at /pith/7SQ5J7ZX/integrity.json. Pith Number bundles also include signed pith.integrity.v1 events where a Pith Number exists.