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Integrity report for Characterizing Learning in Deep Neural Networks using Tractable Algorithmic Complexity Analysis

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

arXiv:2605.15551 · pith:2026:UAUIGELU6SO3IT7AC6NOKJKAU6

0Critical
0Advisory
4Detectors run
2026-05-20Last checked

Paper page arXiv integrity.json bundle.json

Detector runs

doi_compliance completed v1.0.0 · findings 0 · 2026-05-20 20:34:39.110288+00:00
doi_title_agreement completed v1.0.0 · findings 0 · 2026-05-20 20:31:29.504165+00:00
claim_evidence completed v1.0.0 · findings 0 · 2026-05-20 17:42:09.497470+00:00
ai_meta_artifact skipped v1.0.0 · findings 0 · 2026-05-19 19:34:36.247527+00:00

Findings

No public integrity findings for this paper.

Signed record

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