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Major changes (per partner red-pen + user decision): - Delete entire accountant-level analysis (III.J, IV.E, Tables VI/VII/VIII, Fig 4) -- cross-year pooling assumption unjustified, removes the implicit "habitually stamps = always stamps" reading. - Renumber sections III.J/K/L (was K/L/M) and IV.E/F/G/H/I (was F/G/H/I/J). - Title: "Three-Method Convergent Thresholding" -> "Replication-Dominated Calibration" (the three diagnostics do NOT converge at signature level). - Operational cosine cut anchored on whole-sample Firm A P7.5 (cos > 0.95). - Three statistical diagnostics (Hartigan/Beta/BD-McCrary) reframed as descriptive characterisation, not threshold estimators. - Firm A replication-dominated framing: 3 evidence strands -> 2. - Discussion limitation list: drop accountant-level cross-year pooling and BD/McCrary diagnostic; add auditor-year longitudinal tracking as future work. - Tone-shift: "we do not claim / do not derive" -> "we find / motivates". Reference verification (independent web-search audit of all 41 refs): - Fix [5] author hallucination: Hadjadj et al. -> Kao & Wen (real authors of Appl. Sci. 10:11:3716; report at paper/reference_verification_v3.md). - Polish [16] [21] [22] [25] (year/volume/page-range/model-name). Gemini 2.5 Pro peer review (Minor Revision verdict, A-F all positive): - Neutralize script-path references in tables/appendix -> "supplementary materials". - Move conflict-of-interest declaration from III-L to new Declarations section before References (paper_a_declarations_v3.md). Co-Authored-By: Claude Opus 4.7 (1M context) <noreply@anthropic.com>
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Abstract
Regulations require Certified Public Accountants (CPAs) to attest to each audit report by affixing a signature, but digitization makes reusing a stored signature image across reports---through administrative stamping or firm-level electronic signing---technically trivial and visually invisible to report users, undermining individualized attestation. We build an end-to-end pipeline that detects such non-hand-signed signatures at scale: a Vision-Language Model identifies signature pages, a YOLOv11 detector localizes signature regions, ResNet-50 supplies deep features, and a dual-descriptor verification layer combines deep-feature cosine similarity with perceptual hashing (difference hash, dHash) to separate style consistency (high cosine, divergent dHash) from image reproduction (high cosine, low dHash). The operational classifier outputs a five-way verdict per signature with a worst-case document-level aggregation; the cosine cut is anchored on a transparent whole-sample Firm A P7.5 percentile (cos > 0.95), and the dHash cuts on the same reference. Applied to 90,282 audit reports filed in Taiwan over 2013-2023 (182,328 signatures from 758 CPAs), the operational dual rule cos > 0.95 AND \text{dHash}_\text{indep} \leq 8 captures 89.95% of Firm A and yields FAR \leq 0.001 against a $\sim$50,000-pair inter-CPA negative anchor; intra-report agreement is 89.9% at Firm A versus 62-67% at the other Big-4 firms (a 23-28 percentage-point cross-firm gap). Validation uses three annotation-free anchors (310 byte-identical positives, $\sim$50,000 inter-CPA negatives, and a 70/30 held-out Firm A fold) reported with Wilson 95% intervals. Three statistical diagnostics applied to the per-signature similarity distribution (Hartigan dip test, EM-fitted Beta mixture with logit-Gaussian robustness check, Burgstahler-Dichev / McCrary density-smoothness procedure) jointly characterise the distribution as a continuous quality spectrum, which motivates the percentile-based anchor and is itself a substantive finding for similarity-threshold selection in document forensics.