{"bundle_type":"pith_open_graph_bundle","bundle_version":"1.0","pith_number":"pith:2024:KZGGJRD6NB2RI37AZJA7JO2ZQZ","short_pith_number":"pith:KZGGJRD6","canonical_record":{"source":{"id":"2404.11339","kind":"arxiv","version":1},"metadata":{"license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"cs.CV","submitted_at":"2024-04-17T13:00:05Z","cross_cats_sorted":[],"title_canon_sha256":"074c2e1ad3d8f39e8d851b7c87f96eded630d572de3aa933e0b0e7e08bea73d4","abstract_canon_sha256":"440251a066b7d0df24045721173684e56895d6afe8636d0bd40d7f0e9b7b7a53"},"schema_version":"1.0"},"canonical_sha256":"564c64c47e6875146fe0ca41f4bb598665ddae6008c79cf4f833ee193b74a683","source":{"kind":"arxiv","id":"2404.11339","version":1},"source_aliases":[{"alias_kind":"arxiv","alias_value":"2404.11339","created_at":"2026-07-05T08:09:07Z"},{"alias_kind":"arxiv_version","alias_value":"2404.11339v1","created_at":"2026-07-05T08:09:07Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2404.11339","created_at":"2026-07-05T08:09:07Z"},{"alias_kind":"pith_short_12","alias_value":"KZGGJRD6NB2R","created_at":"2026-07-05T08:09:07Z"},{"alias_kind":"pith_short_16","alias_value":"KZGGJRD6NB2RI37A","created_at":"2026-07-05T08:09:07Z"},{"alias_kind":"pith_short_8","alias_value":"KZGGJRD6","created_at":"2026-07-05T08:09:07Z"}],"events":[{"event_type":"record_created","subject_pith_number":"pith:2024:KZGGJRD6NB2RI37AZJA7JO2ZQZ","target":"record","payload":{"canonical_record":{"source":{"id":"2404.11339","kind":"arxiv","version":1},"metadata":{"license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"cs.CV","submitted_at":"2024-04-17T13:00:05Z","cross_cats_sorted":[],"title_canon_sha256":"074c2e1ad3d8f39e8d851b7c87f96eded630d572de3aa933e0b0e7e08bea73d4","abstract_canon_sha256":"440251a066b7d0df24045721173684e56895d6afe8636d0bd40d7f0e9b7b7a53"},"schema_version":"1.0"},"canonical_sha256":"564c64c47e6875146fe0ca41f4bb598665ddae6008c79cf4f833ee193b74a683","receipt":{"kind":"pith_receipt","key_id":"pith-v1-2026-05","algorithm":"ed25519","signed_at":"2026-07-05T08:09:07.794136Z","signature_b64":"RV8CyBKOYY/s96Kxk82EJSqj6yF7jWcBo3DXfM0r7LMtnkOqzqpyeKZEMVgpViDtcq1HzembTSLbixWfZNulDA==","signed_message":"canonical_sha256_bytes","builder_version":"pith-number-builder-2026-05-17-v1","receipt_version":"0.3","canonical_sha256":"564c64c47e6875146fe0ca41f4bb598665ddae6008c79cf4f833ee193b74a683","last_reissued_at":"2026-07-05T08:09:07.793739Z","signature_status":"signed_v1","first_computed_at":"2026-07-05T08:09:07.793739Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"source_kind":"arxiv","source_id":"2404.11339","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":"2026-07-05T08:09:07Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"z7H259J+cLJdKzFJZR9Yq1SBSdkgYIg1xAts03+tH3io1cV0vYWe1trhopPlfepYEOV/kXhPGLxUAK20qzKpCg==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-08-22T19:47:08.219142Z"},"content_sha256":"03c44e1b4c04de4cc591b7250be049c5bfcc7aa063b72a160d597bfc257585f8","schema_version":"1.0","event_id":"sha256:03c44e1b4c04de4cc591b7250be049c5bfcc7aa063b72a160d597bfc257585f8"},{"event_type":"graph_snapshot","subject_pith_number":"pith:2024:KZGGJRD6NB2RI37AZJA7JO2ZQZ","target":"graph","payload":{"graph_snapshot":{"paper":{"title":"Best Practices for a Handwritten Text Recognition System","license":"http://creativecommons.org/licenses/by/4.0/","headline":"","cross_cats":[],"primary_cat":"cs.CV","authors_text":"Basilis Gatos, Christophoros Nikou, George Retsinas, Giorgos Sfikas","submitted_at":"2024-04-17T13:00:05Z","abstract_excerpt":"Handwritten text recognition has been developed rapidly in the recent years, following the rise of deep learning and its applications. Though deep learning methods provide notable boost in performance concerning text recognition, non-trivial deviation in performance can be detected even when small pre-processing or architectural/optimization elements are changed. This work follows a ``best practice'' rationale; highlight simple yet effective empirical practices that can further help training and provide well-performing handwritten text recognition systems. Specifically, we considered three bas"},"claims":{"count":0,"items":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2404.11339","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/2404.11339/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":"2026-07-05T08:09:07Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"a5Kee+xS59K5TBxvUBsuDb/iNMco2gCP4VDSaLBDfV53538N03hgH0H1L0FjQ4LneBp5Wc2ZloEtf3GnhVTKBw==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-08-22T19:47:08.219629Z"},"content_sha256":"c1ca88194dedbdf87fb91eae3ca62b13956f0babd62636ed246facc31fa3b758","schema_version":"1.0","event_id":"sha256:c1ca88194dedbdf87fb91eae3ca62b13956f0babd62636ed246facc31fa3b758"}],"timestamp_proofs":[],"mirror_hints":[{"mirror_type":"https","name":"Pith Resolver","base_url":"https://pith.science","bundle_url":"https://pith.science/pith/KZGGJRD6NB2RI37AZJA7JO2ZQZ/bundle.json","state_url":"https://pith.science/pith/KZGGJRD6NB2RI37AZJA7JO2ZQZ/state.json","well_known_bundle_url":"https://pith.science/.well-known/pith/KZGGJRD6NB2RI37AZJA7JO2ZQZ/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":"2026-08-22T19:47:08Z","links":{"resolver":"https://pith.science/pith/KZGGJRD6NB2RI37AZJA7JO2ZQZ","bundle":"https://pith.science/pith/KZGGJRD6NB2RI37AZJA7JO2ZQZ/bundle.json","state":"https://pith.science/pith/KZGGJRD6NB2RI37AZJA7JO2ZQZ/state.json","well_known_bundle":"https://pith.science/.well-known/pith/KZGGJRD6NB2RI37AZJA7JO2ZQZ/bundle.json"},"state":{"state_type":"pith_open_graph_state","state_version":"1.0","pith_number":"pith:2024:KZGGJRD6NB2RI37AZJA7JO2ZQZ","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":"440251a066b7d0df24045721173684e56895d6afe8636d0bd40d7f0e9b7b7a53","cross_cats_sorted":[],"license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"cs.CV","submitted_at":"2024-04-17T13:00:05Z","title_canon_sha256":"074c2e1ad3d8f39e8d851b7c87f96eded630d572de3aa933e0b0e7e08bea73d4"},"schema_version":"1.0","source":{"id":"2404.11339","kind":"arxiv","version":1}},"source_aliases":[{"alias_kind":"arxiv","alias_value":"2404.11339","created_at":"2026-07-05T08:09:07Z"},{"alias_kind":"arxiv_version","alias_value":"2404.11339v1","created_at":"2026-07-05T08:09:07Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2404.11339","created_at":"2026-07-05T08:09:07Z"},{"alias_kind":"pith_short_12","alias_value":"KZGGJRD6NB2R","created_at":"2026-07-05T08:09:07Z"},{"alias_kind":"pith_short_16","alias_value":"KZGGJRD6NB2RI37A","created_at":"2026-07-05T08:09:07Z"},{"alias_kind":"pith_short_8","alias_value":"KZGGJRD6","created_at":"2026-07-05T08:09:07Z"}],"graph_snapshots":[{"event_id":"sha256:c1ca88194dedbdf87fb91eae3ca62b13956f0babd62636ed246facc31fa3b758","target":"graph","created_at":"2026-07-05T08:09:07Z","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/2404.11339/integrity.json","findings":[],"snapshot_sha256":"c28c3603d3b5d939e8dc4c7e95fa8dfce3d595e45f758748cecf8e644a296938","summary":{"advisory":0,"by_detector":{},"critical":0,"informational":0}},"paper":{"abstract_excerpt":"Handwritten text recognition has been developed rapidly in the recent years, following the rise of deep learning and its applications. Though deep learning methods provide notable boost in performance concerning text recognition, non-trivial deviation in performance can be detected even when small pre-processing or architectural/optimization elements are changed. This work follows a ``best practice'' rationale; highlight simple yet effective empirical practices that can further help training and provide well-performing handwritten text recognition systems. Specifically, we considered three bas","authors_text":"Basilis Gatos, Christophoros Nikou, George Retsinas, Giorgos Sfikas","cross_cats":[],"headline":"","license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"cs.CV","submitted_at":"2024-04-17T13:00:05Z","title":"Best Practices for a Handwritten Text Recognition System"},"references":{"count":0,"internal_anchors":0,"resolved_work":0,"sample":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2404.11339","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":"sha256:03c44e1b4c04de4cc591b7250be049c5bfcc7aa063b72a160d597bfc257585f8","target":"record","created_at":"2026-07-05T08:09:07Z","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":"440251a066b7d0df24045721173684e56895d6afe8636d0bd40d7f0e9b7b7a53","cross_cats_sorted":[],"license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"cs.CV","submitted_at":"2024-04-17T13:00:05Z","title_canon_sha256":"074c2e1ad3d8f39e8d851b7c87f96eded630d572de3aa933e0b0e7e08bea73d4"},"schema_version":"1.0","source":{"id":"2404.11339","kind":"arxiv","version":1}},"canonical_sha256":"564c64c47e6875146fe0ca41f4bb598665ddae6008c79cf4f833ee193b74a683","receipt":{"algorithm":"ed25519","builder_version":"pith-number-builder-2026-05-17-v1","canonical_sha256":"564c64c47e6875146fe0ca41f4bb598665ddae6008c79cf4f833ee193b74a683","first_computed_at":"2026-07-05T08:09:07.793739Z","key_id":"pith-v1-2026-05","kind":"pith_receipt","last_reissued_at":"2026-07-05T08:09:07.793739Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","receipt_version":"0.3","signature_b64":"RV8CyBKOYY/s96Kxk82EJSqj6yF7jWcBo3DXfM0r7LMtnkOqzqpyeKZEMVgpViDtcq1HzembTSLbixWfZNulDA==","signature_status":"signed_v1","signed_at":"2026-07-05T08:09:07.794136Z","signed_message":"canonical_sha256_bytes"},"source_id":"2404.11339","source_kind":"arxiv","source_version":1}}},"equivocations":[],"invalid_events":[],"applied_event_ids":["sha256:03c44e1b4c04de4cc591b7250be049c5bfcc7aa063b72a160d597bfc257585f8","sha256:c1ca88194dedbdf87fb91eae3ca62b13956f0babd62636ed246facc31fa3b758"],"state_sha256":"6542779768719522023537c3db9e52ecdb400e1f5b0f8d1ec273c75d3b27ec2a"},"bundle_signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"wx9xcpuKpoohT4yWJJDQM081zmABjLWrQ5jQhaRB7hfvFKsRNCg+2j5cnM+TkE6bJUeTxTEPZGvf2y3qvOQwCw==","signed_message":"bundle_sha256_bytes","signed_at":"2026-08-22T19:47:08.224640Z","bundle_sha256":"34361e34df32389da821b91e3bf643f73464c1f711cbb199a3c1a7f3af14c418"}}