Integrity report for Towards Family-Grouped Hierarchical Federated Learning on Sub-5KB Models: A Feasibility Study of Privacy-Preserving ECG Monitoring for Ultra-Resource-Constrained Wearables

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

arXiv:2605.18862 · pith:2026:SGAX56VZ3VLPSAGLCWFUQWDWBF

0Critical

0Advisory

5Detectors run

2026-05-27Last checked

Paper page arXiv integrity.json bundle.json

Detector runs

ai_meta_artifact completed v1.0.0 · findings 0 · 2026-05-27 07:42:03.992699+00:00

doi_title_agreement completed v1.0.0 · findings 0 · 2026-05-24 15:32:35.675335+00:00

cited_work_retraction completed v1.0.0 · findings 0 · 2026-05-24 12:24:26.232343+00:00

doi_compliance completed v1.0.0 · findings 0 · 2026-05-21 21:06:53.990784+00:00

claim_evidence completed v1.0.0 · findings 0 · 2026-05-21 05:42:22.213781+00:00

Findings

No public integrity findings for this paper.

Signed record

The machine-readable record for this paper lives at /pith/SGAX56VZ3VLPSAGLCWFUQWDWBF/integrity.json. Pith Number bundles also include signed pith.integrity.v1 events where a Pith Number exists.