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Integrity report for Coarse-to-Fine Domain Incremental Learning with Attentive Distillation for Mining Footprint Segmentation in Multispectral Imagery

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

arXiv:2605.24460 · pith:2026:5CSMBK3AL5FRLYZB27NLDS2PVY

0Critical
0Advisory
4Detectors run
2026-06-05Last checked

Paper page arXiv integrity.json bundle.json

Detector runs

ai_meta_artifact skipped v1.0.0 · findings 0 · 2026-06-05 20:35:58.718043+00:00
cited_work_retraction completed v1.0.0 · findings 0 · 2026-05-30 01:54:55.259031+00:00
claim_evidence completed v1.0.0 · findings 0 · 2026-05-28 09:44:48.148449+00:00
ai_meta_artifact skipped v1.0.0 · findings 0 · 2026-05-26 04:34:05.813728+00:00

Findings

No public integrity findings for this paper.

Signed record

The machine-readable record for this paper lives at /pith/5CSMBK3AL5FRLYZB27NLDS2PVY/integrity.json. Pith Number bundles also include signed pith.integrity.v1 events where a Pith Number exists.