{"bundle_type":"pith_open_graph_bundle","bundle_version":"1.0","pith_number":"pith:2026:QQOZKIIK7JDYU56SK3UVWY34DT","short_pith_number":"pith:QQOZKIIK","canonical_record":{"source":{"id":"2604.23683","kind":"arxiv","version":2},"metadata":{"license":"http://creativecommons.org/licenses/by-nc-sa/4.0/","primary_cat":"cs.CV","submitted_at":"2026-04-26T12:51:41Z","cross_cats_sorted":[],"title_canon_sha256":"c8f48e2892aa00d40c95b83d207193cd35c094aa12d5821eeffccb8844969631","abstract_canon_sha256":"8fa5512eb77bf00e2f7a6b1ee414c9a9515539c76298d2f2f0c5959c80df7168"},"schema_version":"1.0"},"canonical_sha256":"841d95210afa478a77d256e95b637c1cebf67fde69e84c34aac6a9fb88dce98c","source":{"kind":"arxiv","id":"2604.23683","version":2},"source_aliases":[{"alias_kind":"arxiv","alias_value":"2604.23683","created_at":"2026-07-01T01:17:51Z"},{"alias_kind":"arxiv_version","alias_value":"2604.23683v2","created_at":"2026-07-01T01:17:51Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2604.23683","created_at":"2026-07-01T01:17:51Z"},{"alias_kind":"pith_short_12","alias_value":"QQOZKIIK7JDY","created_at":"2026-07-01T01:17:51Z"},{"alias_kind":"pith_short_16","alias_value":"QQOZKIIK7JDYU56S","created_at":"2026-07-01T01:17:51Z"},{"alias_kind":"pith_short_8","alias_value":"QQOZKIIK","created_at":"2026-07-01T01:17:51Z"}],"events":[{"event_type":"record_created","subject_pith_number":"pith:2026:QQOZKIIK7JDYU56SK3UVWY34DT","target":"record","payload":{"canonical_record":{"source":{"id":"2604.23683","kind":"arxiv","version":2},"metadata":{"license":"http://creativecommons.org/licenses/by-nc-sa/4.0/","primary_cat":"cs.CV","submitted_at":"2026-04-26T12:51:41Z","cross_cats_sorted":[],"title_canon_sha256":"c8f48e2892aa00d40c95b83d207193cd35c094aa12d5821eeffccb8844969631","abstract_canon_sha256":"8fa5512eb77bf00e2f7a6b1ee414c9a9515539c76298d2f2f0c5959c80df7168"},"schema_version":"1.0"},"canonical_sha256":"841d95210afa478a77d256e95b637c1cebf67fde69e84c34aac6a9fb88dce98c","receipt":{"kind":"pith_receipt","key_id":"pith-v1-2026-05","algorithm":"ed25519","signed_at":"2026-07-01T01:17:51.322009Z","signature_b64":"N4k2TunlTw8FiK0kKDI6Yp9HcJtDuGEBpoGPS1LZ129Oh9i2TDopvsi176KvXTjj2skgFOrIKTpH1t3FEeqeBQ==","signed_message":"canonical_sha256_bytes","builder_version":"pith-number-builder-2026-05-17-v1","receipt_version":"0.3","canonical_sha256":"841d95210afa478a77d256e95b637c1cebf67fde69e84c34aac6a9fb88dce98c","last_reissued_at":"2026-07-01T01:17:51.321613Z","signature_status":"signed_v1","first_computed_at":"2026-07-01T01:17:51.321613Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"source_kind":"arxiv","source_id":"2604.23683","source_version":2,"attestation_state":"computed"},"signer":{"signer_id":"pith.science","signer_type":"pith_registry","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"created_at":"2026-07-01T01:17:51Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"I5jgAw2P5EZ41+o4BqOA9LGS/HfKoe3gulNnNdXg3QUeXhUIUqZwObucnhQQ5H2IVysRvLcYbSYGA4pKo+33BA==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-07-01T16:56:41.669262Z"},"content_sha256":"09b21e7a6c551cb70422e63ef922a3071bb0e4100e5ebcad50962b0a55c2c342","schema_version":"1.0","event_id":"sha256:09b21e7a6c551cb70422e63ef922a3071bb0e4100e5ebcad50962b0a55c2c342"},{"event_type":"graph_snapshot","subject_pith_number":"pith:2026:QQOZKIIK7JDYU56SK3UVWY34DT","target":"graph","payload":{"graph_snapshot":{"paper":{"title":"Learning to Decipher from Pixels: A Case Study of Copiale","license":"http://creativecommons.org/licenses/by-nc-sa/4.0/","headline":"A neural model can map handwritten cipher images directly to plaintext without first transcribing the symbols.","cross_cats":[],"primary_cat":"cs.CV","authors_text":"Alicia Forn\\'es, Be\\'ata Megyesi, Giuseppe De Gregorio, Lei Kang, Raphaela Heil","submitted_at":"2026-04-26T12:51:41Z","abstract_excerpt":"Historical encrypted manuscripts require both paleographic interpretation of cipher symbols and cryptanalytic recovery of plaintext. Most existing computational workflows rely on a transcription-first paradigm, in which handwritten symbols are transcribed prior to decipherment. This intermediate step is labor-intensive, error-prone, and not always aligned with the goal of direct plaintext recovery. We propose an end-to-end, transcription-free approach that directly maps handwritten cipher images to plaintext. Using the Copiale cipher as a case study, we introduce the first text-line-level data"},"claims":{"count":4,"items":[{"kind":"strongest_claim","text":"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.","source":"verdict.strongest_claim","status":"machine_extracted","claim_id":"C1","attestation":"unclaimed"},{"kind":"weakest_assumption","text":"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.","source":"verdict.weakest_assumption","status":"machine_extracted","claim_id":"C2","attestation":"unclaimed"},{"kind":"one_line_summary","text":"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.","source":"verdict.one_line_summary","status":"machine_extracted","claim_id":"C3","attestation":"unclaimed"},{"kind":"headline","text":"A neural model can map handwritten cipher images directly to plaintext without first transcribing the symbols.","source":"verdict.pith_extraction.headline","status":"machine_extracted","claim_id":"C4","attestation":"unclaimed"}],"snapshot_sha256":"9f2f6102cebd35b53c97f9ebfe2183c39b470183429e86e60a10fe78b32fd9a5"},"source":{"id":"2604.23683","kind":"arxiv","version":2},"verdict":{"id":"4b147998-f964-478a-86a9-75ca48ed0e3e","model_set":{"reader":"grok-4.3"},"created_at":"2026-05-08T06:48:31.559552Z","strongest_claim":"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.","one_line_summary":"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.","pipeline_version":"pith-pipeline@v0.9.0","weakest_assumption":"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.","pith_extraction_headline":"A neural model can map handwritten cipher images directly to plaintext without first transcribing the symbols."},"integrity":{"clean":true,"summary":{"advisory":0,"critical":0,"by_detector":{},"informational":0},"endpoint":"/pith/2604.23683/integrity.json","findings":[],"available":true,"detectors_run":[{"name":"ai_meta_artifact","ran_at":"2026-05-21T08:37:07.124891Z","status":"completed","version":"1.0.0","findings_count":0},{"name":"doi_compliance","ran_at":"2026-05-19T22:53:53.094087Z","status":"completed","version":"1.0.0","findings_count":0}],"snapshot_sha256":"3fefd370b6dd974c1bb41fe620a8538e703e4ff5455e0938ff6d7b69cee917bc"},"references":{"count":0,"sample":[],"resolved_work":0,"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57","internal_anchors":0},"formal_canon":{"evidence_count":0,"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"author_claims":{"count":0,"strong_count":0,"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"builder_version":"pith-number-builder-2026-05-17-v1"},"verdict_id":"4b147998-f964-478a-86a9-75ca48ed0e3e"},"signer":{"signer_id":"pith.science","signer_type":"pith_registry","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"created_at":"2026-07-01T01:17:51Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"NgtAUkPrOFE13tgzn6ScBcy9bx3S6qBtG8DxvM5rd5IciTOuUAhmyOX4aQ1Vk+GkbdhH9J51m6XIMxF8JeipBQ==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-07-01T16:56:41.669778Z"},"content_sha256":"733ab8b83d351fd4197103e7a8c9fb461883c7606b92dbb72f322ed8dd70b4f2","schema_version":"1.0","event_id":"sha256:733ab8b83d351fd4197103e7a8c9fb461883c7606b92dbb72f322ed8dd70b4f2"}],"timestamp_proofs":[],"mirror_hints":[{"mirror_type":"https","name":"Pith Resolver","base_url":"https://pith.science","bundle_url":"https://pith.science/pith/QQOZKIIK7JDYU56SK3UVWY34DT/bundle.json","state_url":"https://pith.science/pith/QQOZKIIK7JDYU56SK3UVWY34DT/state.json","well_known_bundle_url":"https://pith.science/.well-known/pith/QQOZKIIK7JDYU56SK3UVWY34DT/bundle.json","status":"primary"}],"public_keys":[{"key_id":"pith-v1-2026-05","algorithm":"ed25519","format":"raw","public_key_b64":"stVStoiQhXFxp4s2pdzPNoqVNBMojDU/fJ2db5S3CbM=","public_key_hex":"b2d552b68890857171a78b36a5dccf368a953413288c353f7c9d9d6f94b709b3","fingerprint_sha256_b32_first128bits":"RVFV5Z2OI2J3ZUO7ERDEBCYNKS","fingerprint_sha256_hex":"8d4b5ee74e4693bcd1df2446408b0d54","rotates_at":null,"url":"https://pith.science/pith-signing-key.json","notes":"Pith uses this Ed25519 key to sign canonical record SHA-256 digests. Verify with: ed25519_verify(public_key, message=canonical_sha256_bytes, signature=base64decode(signature_b64))."}],"merge_version":"pith-open-graph-merge-v1","built_at":"2026-07-01T16:56:41Z","links":{"resolver":"https://pith.science/pith/QQOZKIIK7JDYU56SK3UVWY34DT","bundle":"https://pith.science/pith/QQOZKIIK7JDYU56SK3UVWY34DT/bundle.json","state":"https://pith.science/pith/QQOZKIIK7JDYU56SK3UVWY34DT/state.json","well_known_bundle":"https://pith.science/.well-known/pith/QQOZKIIK7JDYU56SK3UVWY34DT/bundle.json"},"state":{"state_type":"pith_open_graph_state","state_version":"1.0","pith_number":"pith:2026:QQOZKIIK7JDYU56SK3UVWY34DT","merge_version":"pith-open-graph-merge-v1","event_count":2,"valid_event_count":2,"invalid_event_count":0,"equivocation_count":0,"current":{"canonical_record":{"metadata":{"abstract_canon_sha256":"8fa5512eb77bf00e2f7a6b1ee414c9a9515539c76298d2f2f0c5959c80df7168","cross_cats_sorted":[],"license":"http://creativecommons.org/licenses/by-nc-sa/4.0/","primary_cat":"cs.CV","submitted_at":"2026-04-26T12:51:41Z","title_canon_sha256":"c8f48e2892aa00d40c95b83d207193cd35c094aa12d5821eeffccb8844969631"},"schema_version":"1.0","source":{"id":"2604.23683","kind":"arxiv","version":2}},"source_aliases":[{"alias_kind":"arxiv","alias_value":"2604.23683","created_at":"2026-07-01T01:17:51Z"},{"alias_kind":"arxiv_version","alias_value":"2604.23683v2","created_at":"2026-07-01T01:17:51Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2604.23683","created_at":"2026-07-01T01:17:51Z"},{"alias_kind":"pith_short_12","alias_value":"QQOZKIIK7JDY","created_at":"2026-07-01T01:17:51Z"},{"alias_kind":"pith_short_16","alias_value":"QQOZKIIK7JDYU56S","created_at":"2026-07-01T01:17:51Z"},{"alias_kind":"pith_short_8","alias_value":"QQOZKIIK","created_at":"2026-07-01T01:17:51Z"}],"graph_snapshots":[{"event_id":"sha256:733ab8b83d351fd4197103e7a8c9fb461883c7606b92dbb72f322ed8dd70b4f2","target":"graph","created_at":"2026-07-01T01:17:51Z","signer":{"key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signer_id":"pith.science","signer_type":"pith_registry"},"payload":{"graph_snapshot":{"author_claims":{"count":0,"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57","strong_count":0},"builder_version":"pith-number-builder-2026-05-17-v1","claims":{"count":4,"items":[{"attestation":"unclaimed","claim_id":"C1","kind":"strongest_claim","source":"verdict.strongest_claim","status":"machine_extracted","text":"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."},{"attestation":"unclaimed","claim_id":"C2","kind":"weakest_assumption","source":"verdict.weakest_assumption","status":"machine_extracted","text":"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."},{"attestation":"unclaimed","claim_id":"C3","kind":"one_line_summary","source":"verdict.one_line_summary","status":"machine_extracted","text":"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."},{"attestation":"unclaimed","claim_id":"C4","kind":"headline","source":"verdict.pith_extraction.headline","status":"machine_extracted","text":"A neural model can map handwritten cipher images directly to plaintext without first transcribing the symbols."}],"snapshot_sha256":"9f2f6102cebd35b53c97f9ebfe2183c39b470183429e86e60a10fe78b32fd9a5"},"formal_canon":{"evidence_count":0,"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"integrity":{"available":true,"clean":true,"detectors_run":[{"findings_count":0,"name":"ai_meta_artifact","ran_at":"2026-05-21T08:37:07.124891Z","status":"completed","version":"1.0.0"},{"findings_count":0,"name":"doi_compliance","ran_at":"2026-05-19T22:53:53.094087Z","status":"completed","version":"1.0.0"}],"endpoint":"/pith/2604.23683/integrity.json","findings":[],"snapshot_sha256":"3fefd370b6dd974c1bb41fe620a8538e703e4ff5455e0938ff6d7b69cee917bc","summary":{"advisory":0,"by_detector":{},"critical":0,"informational":0}},"paper":{"abstract_excerpt":"Historical encrypted manuscripts require both paleographic interpretation of cipher symbols and cryptanalytic recovery of plaintext. Most existing computational workflows rely on a transcription-first paradigm, in which handwritten symbols are transcribed prior to decipherment. This intermediate step is labor-intensive, error-prone, and not always aligned with the goal of direct plaintext recovery. We propose an end-to-end, transcription-free approach that directly maps handwritten cipher images to plaintext. Using the Copiale cipher as a case study, we introduce the first text-line-level data","authors_text":"Alicia Forn\\'es, Be\\'ata Megyesi, Giuseppe De Gregorio, Lei Kang, Raphaela Heil","cross_cats":[],"headline":"A neural model can map handwritten cipher images directly to plaintext without first transcribing the symbols.","license":"http://creativecommons.org/licenses/by-nc-sa/4.0/","primary_cat":"cs.CV","submitted_at":"2026-04-26T12:51:41Z","title":"Learning to Decipher from Pixels: A Case Study of Copiale"},"references":{"count":0,"internal_anchors":0,"resolved_work":0,"sample":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2604.23683","kind":"arxiv","version":2},"verdict":{"created_at":"2026-05-08T06:48:31.559552Z","id":"4b147998-f964-478a-86a9-75ca48ed0e3e","model_set":{"reader":"grok-4.3"},"one_line_summary":"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.","pipeline_version":"pith-pipeline@v0.9.0","pith_extraction_headline":"A neural model can map handwritten cipher images directly to plaintext without first transcribing the symbols.","strongest_claim":"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.","weakest_assumption":"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."}},"verdict_id":"4b147998-f964-478a-86a9-75ca48ed0e3e"}}],"author_attestations":[],"timestamp_anchors":[],"storage_attestations":[],"citation_signatures":[],"replication_records":[],"corrections":[],"mirror_hints":[],"record_created":{"event_id":"sha256:09b21e7a6c551cb70422e63ef922a3071bb0e4100e5ebcad50962b0a55c2c342","target":"record","created_at":"2026-07-01T01:17:51Z","signer":{"key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signer_id":"pith.science","signer_type":"pith_registry"},"payload":{"attestation_state":"computed","canonical_record":{"metadata":{"abstract_canon_sha256":"8fa5512eb77bf00e2f7a6b1ee414c9a9515539c76298d2f2f0c5959c80df7168","cross_cats_sorted":[],"license":"http://creativecommons.org/licenses/by-nc-sa/4.0/","primary_cat":"cs.CV","submitted_at":"2026-04-26T12:51:41Z","title_canon_sha256":"c8f48e2892aa00d40c95b83d207193cd35c094aa12d5821eeffccb8844969631"},"schema_version":"1.0","source":{"id":"2604.23683","kind":"arxiv","version":2}},"canonical_sha256":"841d95210afa478a77d256e95b637c1cebf67fde69e84c34aac6a9fb88dce98c","receipt":{"algorithm":"ed25519","builder_version":"pith-number-builder-2026-05-17-v1","canonical_sha256":"841d95210afa478a77d256e95b637c1cebf67fde69e84c34aac6a9fb88dce98c","first_computed_at":"2026-07-01T01:17:51.321613Z","key_id":"pith-v1-2026-05","kind":"pith_receipt","last_reissued_at":"2026-07-01T01:17:51.321613Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","receipt_version":"0.3","signature_b64":"N4k2TunlTw8FiK0kKDI6Yp9HcJtDuGEBpoGPS1LZ129Oh9i2TDopvsi176KvXTjj2skgFOrIKTpH1t3FEeqeBQ==","signature_status":"signed_v1","signed_at":"2026-07-01T01:17:51.322009Z","signed_message":"canonical_sha256_bytes"},"source_id":"2604.23683","source_kind":"arxiv","source_version":2}}},"equivocations":[],"invalid_events":[],"applied_event_ids":["sha256:09b21e7a6c551cb70422e63ef922a3071bb0e4100e5ebcad50962b0a55c2c342","sha256:733ab8b83d351fd4197103e7a8c9fb461883c7606b92dbb72f322ed8dd70b4f2"],"state_sha256":"d2dbabd2254e3ff805f3e8ad6d78ec4b0cc050eccb129ee1ff16e63445e544d9"},"bundle_signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"S6ZQXcmplt/GpZBwyOr3TR/dccPf6CBG6eIwwH0mzMrGEJfOU/GN9b7cWHYMJi4+oxiCHcH+vok32BvoE6m5CA==","signed_message":"bundle_sha256_bytes","signed_at":"2026-07-01T16:56:41.672007Z","bundle_sha256":"e13788c257d6bb823eb2baa20c866ef12365b3165934e4c1f0d3d322b5061d5b"}}