{"bundle_type":"pith_open_graph_bundle","bundle_version":"1.0","pith_number":"pith:2023:IUUQ7WEOJMESDHYXX7I2BDSQRJ","short_pith_number":"pith:IUUQ7WEO","canonical_record":{"source":{"id":"2303.03127","kind":"arxiv","version":1},"metadata":{"license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"cs.CV","submitted_at":"2023-03-06T13:39:41Z","cross_cats_sorted":[],"title_canon_sha256":"b5d416b5b7ca1212b3d165ce834e2d5c7d0673b68045e3d14b0c6d050f989d8a","abstract_canon_sha256":"b92dcb215158206490f91afbc63f12ee55a9f5e56c49df3ad759d26bddc18505"},"schema_version":"1.0"},"canonical_sha256":"45290fd88e4b09219f17bfd1a08e508a774766668920ae0c11d43e0a26bfc40f","source":{"kind":"arxiv","id":"2303.03127","version":1},"source_aliases":[{"alias_kind":"arxiv","alias_value":"2303.03127","created_at":"2026-07-05T05:48:19Z"},{"alias_kind":"arxiv_version","alias_value":"2303.03127v1","created_at":"2026-07-05T05:48:19Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2303.03127","created_at":"2026-07-05T05:48:19Z"},{"alias_kind":"pith_short_12","alias_value":"IUUQ7WEOJMES","created_at":"2026-07-05T05:48:19Z"},{"alias_kind":"pith_short_16","alias_value":"IUUQ7WEOJMESDHYX","created_at":"2026-07-05T05:48:19Z"},{"alias_kind":"pith_short_8","alias_value":"IUUQ7WEO","created_at":"2026-07-05T05:48:19Z"}],"events":[{"event_type":"record_created","subject_pith_number":"pith:2023:IUUQ7WEOJMESDHYXX7I2BDSQRJ","target":"record","payload":{"canonical_record":{"source":{"id":"2303.03127","kind":"arxiv","version":1},"metadata":{"license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"cs.CV","submitted_at":"2023-03-06T13:39:41Z","cross_cats_sorted":[],"title_canon_sha256":"b5d416b5b7ca1212b3d165ce834e2d5c7d0673b68045e3d14b0c6d050f989d8a","abstract_canon_sha256":"b92dcb215158206490f91afbc63f12ee55a9f5e56c49df3ad759d26bddc18505"},"schema_version":"1.0"},"canonical_sha256":"45290fd88e4b09219f17bfd1a08e508a774766668920ae0c11d43e0a26bfc40f","receipt":{"kind":"pith_receipt","key_id":"pith-v1-2026-05","algorithm":"ed25519","signed_at":"2026-07-05T05:48:19.406156Z","signature_b64":"RK5Mti98aEYyV91rZ7jRm0PZHcrwWnXIyn3v4tgpnp4Nerh4T5oyO0QvEMX6r9H7zKeLvdlf8OVoCJ9H056qAA==","signed_message":"canonical_sha256_bytes","builder_version":"pith-number-builder-2026-05-17-v1","receipt_version":"0.3","canonical_sha256":"45290fd88e4b09219f17bfd1a08e508a774766668920ae0c11d43e0a26bfc40f","last_reissued_at":"2026-07-05T05:48:19.405759Z","signature_status":"signed_v1","first_computed_at":"2026-07-05T05:48:19.405759Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"source_kind":"arxiv","source_id":"2303.03127","source_version":1,"attestation_state":"computed"},"signer":{"signer_id":"pith.science","signer_type":"pith_registry","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"created_at":"2026-07-05T05:48:19Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"macI44hSJbJfbLde5WOZOoyUEjvBQ5RELKI1M1kOQqvSi+/6D38NgiEuDlXOcQS1pNYac2rwE2DsOWTAXR+wAQ==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-08-18T14:25:05.161072Z"},"content_sha256":"3e8ee3d5735606f937a010b1199946da7eee2764df73ce83e33b505e58aab3b4","schema_version":"1.0","event_id":"sha256:3e8ee3d5735606f937a010b1199946da7eee2764df73ce83e33b505e58aab3b4"},{"event_type":"graph_snapshot","subject_pith_number":"pith:2023:IUUQ7WEOJMESDHYXX7I2BDSQRJ","target":"graph","payload":{"graph_snapshot":{"paper":{"title":"ST-KeyS: Self-Supervised Transformer for Keyword Spotting in Historical Handwritten Documents","license":"http://creativecommons.org/licenses/by/4.0/","headline":"","cross_cats":[],"primary_cat":"cs.CV","authors_text":"Abbas Cheddad, Mohamed Ali Souibgui, Sana Khamekhem Jemni, Sourour Ammar, Yousri Kessentini","submitted_at":"2023-03-06T13:39:41Z","abstract_excerpt":"Keyword spotting (KWS) in historical documents is an important tool for the initial exploration of digitized collections. Nowadays, the most efficient KWS methods are relying on machine learning techniques that require a large amount of annotated training data. However, in the case of historical manuscripts, there is a lack of annotated corpus for training. To handle the data scarcity issue, we investigate the merits of the self-supervised learning to extract useful representations of the input data without relying on human annotations and then using these representations in the downstream tas"},"claims":{"count":0,"items":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2303.03127","kind":"arxiv","version":1},"verdict":{"id":null,"model_set":{},"created_at":null,"strongest_claim":"","one_line_summary":"","pipeline_version":null,"weakest_assumption":"","pith_extraction_headline":""},"integrity":{"clean":true,"summary":{"advisory":0,"critical":0,"by_detector":{},"informational":0},"endpoint":"/pith/2303.03127/integrity.json","findings":[],"available":true,"detectors_run":[],"snapshot_sha256":"c28c3603d3b5d939e8dc4c7e95fa8dfce3d595e45f758748cecf8e644a296938"},"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":null},"signer":{"signer_id":"pith.science","signer_type":"pith_registry","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"created_at":"2026-07-05T05:48:19Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"GskIPDd1mrkHOkBg6ZWgNkq1RuHHDckNrlqlTicYBSLocVaQYmuJRfz5rW1+wRhX3yqM2JahpihqyCYUYOylAg==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-08-18T14:25:05.162025Z"},"content_sha256":"fca3355078f910ae53f1038c0ad9cbe6a32c02236a13a2594927a00e3295e668","schema_version":"1.0","event_id":"sha256:fca3355078f910ae53f1038c0ad9cbe6a32c02236a13a2594927a00e3295e668"}],"timestamp_proofs":[],"mirror_hints":[{"mirror_type":"https","name":"Pith Resolver","base_url":"https://pith.science","bundle_url":"https://pith.science/pith/IUUQ7WEOJMESDHYXX7I2BDSQRJ/bundle.json","state_url":"https://pith.science/pith/IUUQ7WEOJMESDHYXX7I2BDSQRJ/state.json","well_known_bundle_url":"https://pith.science/.well-known/pith/IUUQ7WEOJMESDHYXX7I2BDSQRJ/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":"2026-08-18T14:25:05Z","links":{"resolver":"https://pith.science/pith/IUUQ7WEOJMESDHYXX7I2BDSQRJ","bundle":"https://pith.science/pith/IUUQ7WEOJMESDHYXX7I2BDSQRJ/bundle.json","state":"https://pith.science/pith/IUUQ7WEOJMESDHYXX7I2BDSQRJ/state.json","well_known_bundle":"https://pith.science/.well-known/pith/IUUQ7WEOJMESDHYXX7I2BDSQRJ/bundle.json"},"state":{"state_type":"pith_open_graph_state","state_version":"1.0","pith_number":"pith:2023:IUUQ7WEOJMESDHYXX7I2BDSQRJ","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":"b92dcb215158206490f91afbc63f12ee55a9f5e56c49df3ad759d26bddc18505","cross_cats_sorted":[],"license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"cs.CV","submitted_at":"2023-03-06T13:39:41Z","title_canon_sha256":"b5d416b5b7ca1212b3d165ce834e2d5c7d0673b68045e3d14b0c6d050f989d8a"},"schema_version":"1.0","source":{"id":"2303.03127","kind":"arxiv","version":1}},"source_aliases":[{"alias_kind":"arxiv","alias_value":"2303.03127","created_at":"2026-07-05T05:48:19Z"},{"alias_kind":"arxiv_version","alias_value":"2303.03127v1","created_at":"2026-07-05T05:48:19Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2303.03127","created_at":"2026-07-05T05:48:19Z"},{"alias_kind":"pith_short_12","alias_value":"IUUQ7WEOJMES","created_at":"2026-07-05T05:48:19Z"},{"alias_kind":"pith_short_16","alias_value":"IUUQ7WEOJMESDHYX","created_at":"2026-07-05T05:48:19Z"},{"alias_kind":"pith_short_8","alias_value":"IUUQ7WEO","created_at":"2026-07-05T05:48:19Z"}],"graph_snapshots":[{"event_id":"sha256:fca3355078f910ae53f1038c0ad9cbe6a32c02236a13a2594927a00e3295e668","target":"graph","created_at":"2026-07-05T05:48:19Z","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":0,"items":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"formal_canon":{"evidence_count":0,"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"integrity":{"available":true,"clean":true,"detectors_run":[],"endpoint":"/pith/2303.03127/integrity.json","findings":[],"snapshot_sha256":"c28c3603d3b5d939e8dc4c7e95fa8dfce3d595e45f758748cecf8e644a296938","summary":{"advisory":0,"by_detector":{},"critical":0,"informational":0}},"paper":{"abstract_excerpt":"Keyword spotting (KWS) in historical documents is an important tool for the initial exploration of digitized collections. Nowadays, the most efficient KWS methods are relying on machine learning techniques that require a large amount of annotated training data. However, in the case of historical manuscripts, there is a lack of annotated corpus for training. To handle the data scarcity issue, we investigate the merits of the self-supervised learning to extract useful representations of the input data without relying on human annotations and then using these representations in the downstream tas","authors_text":"Abbas Cheddad, Mohamed Ali Souibgui, Sana Khamekhem Jemni, Sourour Ammar, Yousri Kessentini","cross_cats":[],"headline":"","license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"cs.CV","submitted_at":"2023-03-06T13:39:41Z","title":"ST-KeyS: Self-Supervised Transformer for Keyword Spotting in Historical Handwritten Documents"},"references":{"count":0,"internal_anchors":0,"resolved_work":0,"sample":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2303.03127","kind":"arxiv","version":1},"verdict":{"created_at":null,"id":null,"model_set":{},"one_line_summary":"","pipeline_version":null,"pith_extraction_headline":"","strongest_claim":"","weakest_assumption":""}},"verdict_id":null}}],"author_attestations":[],"timestamp_anchors":[],"storage_attestations":[],"citation_signatures":[],"replication_records":[],"corrections":[],"mirror_hints":[],"record_created":{"event_id":"sha256:3e8ee3d5735606f937a010b1199946da7eee2764df73ce83e33b505e58aab3b4","target":"record","created_at":"2026-07-05T05:48:19Z","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":"b92dcb215158206490f91afbc63f12ee55a9f5e56c49df3ad759d26bddc18505","cross_cats_sorted":[],"license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"cs.CV","submitted_at":"2023-03-06T13:39:41Z","title_canon_sha256":"b5d416b5b7ca1212b3d165ce834e2d5c7d0673b68045e3d14b0c6d050f989d8a"},"schema_version":"1.0","source":{"id":"2303.03127","kind":"arxiv","version":1}},"canonical_sha256":"45290fd88e4b09219f17bfd1a08e508a774766668920ae0c11d43e0a26bfc40f","receipt":{"algorithm":"ed25519","builder_version":"pith-number-builder-2026-05-17-v1","canonical_sha256":"45290fd88e4b09219f17bfd1a08e508a774766668920ae0c11d43e0a26bfc40f","first_computed_at":"2026-07-05T05:48:19.405759Z","key_id":"pith-v1-2026-05","kind":"pith_receipt","last_reissued_at":"2026-07-05T05:48:19.405759Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","receipt_version":"0.3","signature_b64":"RK5Mti98aEYyV91rZ7jRm0PZHcrwWnXIyn3v4tgpnp4Nerh4T5oyO0QvEMX6r9H7zKeLvdlf8OVoCJ9H056qAA==","signature_status":"signed_v1","signed_at":"2026-07-05T05:48:19.406156Z","signed_message":"canonical_sha256_bytes"},"source_id":"2303.03127","source_kind":"arxiv","source_version":1}}},"equivocations":[],"invalid_events":[],"applied_event_ids":["sha256:3e8ee3d5735606f937a010b1199946da7eee2764df73ce83e33b505e58aab3b4","sha256:fca3355078f910ae53f1038c0ad9cbe6a32c02236a13a2594927a00e3295e668"],"state_sha256":"e167a334cdcde9021208c5c263efafdc40d4364f304a3bc164b43f4b554f6394"},"bundle_signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"tPNgA/p6+5/z//dkSWz4AbHyJmwG4DLn2ijE4mA8KznV7hAlAxl6vZ6dnHpLhadAJzDEsjTC5dpdvDdPLg76Dw==","signed_message":"bundle_sha256_bytes","signed_at":"2026-08-18T14:25:05.178745Z","bundle_sha256":"746727ba0a886b73b1565d6b0468ce12bb2c8665b6ce832b67b3ffd03fb9b4b7"}}