pith:QQOZKIIK
Learning to Decipher from Pixels: A Case Study of Copiale
A neural model can map handwritten cipher images directly to plaintext without first transcribing the symbols.
arxiv:2604.23683 v2 · 2026-04-26 · cs.CV
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\pithnumber{QQOZKIIK7JDYU56SK3UVWY34DT}
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Claims
Our results demonstrate that transcription-free image-to-plaintext decipherment is both feasible and effective for historical substitution ciphers, offering a simplified and scalable alternative to traditional pipelines.
The method assumes that a model pretrained on generic handwriting data can be effectively fine-tuned on a limited cipher-specific dataset to learn the direct visual-to-plaintext mapping without needing explicit symbol-level transcription or additional cryptanalytic constraints.
An end-to-end neural network deciphers the Copiale cipher directly from line-level images to German plaintext without any transcription step, using pretraining on generic handwriting followed by cipher-specific fine-tuning.
Receipt and verification
| First computed | 2026-07-01T01:17:51.321613Z |
|---|---|
| Builder | pith-number-builder-2026-05-17-v1 |
| Signature | Pith Ed25519
(pith-v1-2026-05) · public key |
| Schema | pith-number/v1.0 |
Canonical hash
841d95210afa478a77d256e95b637c1cebf67fde69e84c34aac6a9fb88dce98c
Aliases
· · · · ·Agent API
Verify this Pith Number yourself
curl -sH 'Accept: application/ld+json' https://pith.science/pith/QQOZKIIK7JDYU56SK3UVWY34DT \
| jq -c '.canonical_record' \
| python3 -c "import sys,json,hashlib; b=json.dumps(json.loads(sys.stdin.read()), sort_keys=True, separators=(',',':'), ensure_ascii=False).encode(); print(hashlib.sha256(b).hexdigest())"
# expect: 841d95210afa478a77d256e95b637c1cebf67fde69e84c34aac6a9fb88dce98c
Canonical record JSON
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