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Integrity report for HGQ-LUT: Fast LUT-Aware Training and Efficient Architectures for DNN Inference

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

arXiv:2604.22293

0Critical
0Advisory
2Detectors run
2026-05-21Last checked

Paper page arXiv integrity.json

Detector runs

ai_meta_artifact completed v1.0.0 · findings 0 · 2026-05-21 10:42:54.139570+00:00
doi_compliance completed v1.0.0 · findings 0 · 2026-05-20 00:06:46.855666+00:00

Findings

No public integrity findings for this paper.

Signed record

The machine-readable record for this paper lives at /pith/2604.22293/integrity.json. Pith Number bundles also include signed pith.integrity.v1 events where a Pith Number exists.