Integrity report for Learning Higher-Order Structure from Incomplete Spatiotemporal Data: Multi-Scale Hypergraph Laplacians with Neural Refinement

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

arXiv:2605.17316 · pith:2026:FOMGBNXFYP5GIHC3Q3XB5NQ3LK

0Critical

0Advisory

4Detectors run

2026-05-22Last checked

Paper page arXiv integrity.json bundle.json

Detector runs

doi_compliance completed v1.0.0 · findings 0 · 2026-05-22 15:26:40.034099+00:00

doi_title_agreement completed v1.0.0 · findings 0 · 2026-05-22 15:01:57.371138+00:00

claim_evidence completed v1.0.0 · findings 0 · 2026-05-21 22:22:36.463746+00:00

ai_meta_artifact skipped v1.0.0 · findings 0 · 2026-05-19 21:33:23.751476+00:00

Findings

No public integrity findings for this paper.

Signed record

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