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

5Detectors run

2026-05-26Last checked

Paper page arXiv integrity.json bundle.json

Detector runs

ai_meta_artifact completed v1.0.0 · findings 0 · 2026-05-26 21:44:03.430949+00:00

doi_title_agreement completed v1.0.0 · findings 0 · 2026-05-25 16:02:46.988808+00:00

claim_evidence completed v1.0.0 · findings 0 · 2026-05-24 16:23:29.423849+00:00

doi_compliance completed v1.0.0 · findings 0 · 2026-05-24 15:51:05.474806+00:00

cited_work_retraction completed v1.0.0 · findings 0 · 2026-05-23 13:53:08.163372+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.