Integrity report for AcOrch: Accelerating Sampling-based GNN Training under CPU-NPU Heterogeneous Environments

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

arXiv:2606.01161 · pith:2026:WAO5AXBZXRDFK6TBLUTOSLNIYV

0Critical

0Advisory

3Detectors run

2026-06-05Last checked

Paper page arXiv integrity.json bundle.json

Detector runs

claim_evidence completed v1.0.0 · findings 0 · 2026-06-05 16:29:28.253698+00:00

cited_work_retraction completed v1.0.0 · findings 0 · 2026-06-04 20:57:36.302137+00:00

ai_meta_artifact skipped v1.0.0 · findings 0 · 2026-06-02 04:35:16.286773+00:00

Findings

No public integrity findings for this paper.

Signed record

The machine-readable record for this paper lives at /pith/WAO5AXBZ/integrity.json. Pith Number bundles also include signed pith.integrity.v1 events where a Pith Number exists.