Integrity report for H-Flow: Self-supervised Human Scene Flow via Physics-inspired Joint Multi-modal Learning

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

arXiv:2605.22629 · pith:2026:OCGJIYG6THOSVTBCTTRUC7UC7X

0Critical

0Advisory

8Detectors run

2026-05-25Last checked

Paper page arXiv integrity.json bundle.json

Detector runs

doi_title_agreement completed v1.0.0 · findings 0 · 2026-05-25 07:02:40.148922+00:00

doi_compliance completed v1.0.0 · findings 0 · 2026-05-25 06:48:32.160747+00:00

claim_evidence completed v1.0.0 · findings 0 · 2026-05-25 03:43:40.643330+00:00

external_links completed v1.0.0 · findings 0 · 2026-05-24 23:36:44.899398+00:00

citation_quote_validity completed v0.1.0 · findings 0 · 2026-05-24 11:50:41.068066+00:00

shingle_duplication completed v0.1.0 · findings 0 · 2026-05-22 17:50:52.154813+00:00

cited_work_retraction completed v1.0.0 · findings 0 · 2026-05-22 05:23:12.200451+00:00

ai_meta_artifact skipped v1.0.0 · findings 0 · 2026-05-22 02:33:38.051169+00:00

Findings

No public integrity findings for this paper.

Signed record

The machine-readable record for this paper lives at /pith/OCGJIYG6/integrity.json. Pith Number bundles also include signed pith.integrity.v1 events where a Pith Number exists.