{"state_type":"pith_open_graph_state","state_version":"1.0","pith_number":"pith:2019:ZA67IL5QHPVZZT5CQPPDLQBG7U","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":"193dd73a917e30845361a96e85edc2ee89f0e28e499f245d86ee2b2e0523f9a3","cross_cats_sorted":[],"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.CV","submitted_at":"2019-03-05T17:34:21Z","title_canon_sha256":"9209ae0fabe61ee56949deec8d5f171d4048bdc32272b6b3c7c7596ec87d838c"},"schema_version":"1.0","source":{"id":"1903.01949","kind":"arxiv","version":2}},"source_aliases":[{"alias_kind":"arxiv","alias_value":"1903.01949","created_at":"2026-07-05T01:16:08Z"},{"alias_kind":"arxiv_version","alias_value":"1903.01949v2","created_at":"2026-07-05T01:16:08Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.1903.01949","created_at":"2026-07-05T01:16:08Z"},{"alias_kind":"pith_short_12","alias_value":"ZA67IL5QHPVZ","created_at":"2026-07-05T01:16:08Z"},{"alias_kind":"pith_short_16","alias_value":"ZA67IL5QHPVZZT5C","created_at":"2026-07-05T01:16:08Z"},{"alias_kind":"pith_short_8","alias_value":"ZA67IL5Q","created_at":"2026-07-05T01:16:08Z"}],"graph_snapshots":[{"event_id":"sha256:2db05eeb5f6e2c006af7366b43205b35a4ff603261a906ce506eef21aa507292","target":"graph","created_at":"2026-07-05T01:16:08Z","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/1903.01949/integrity.json","findings":[],"snapshot_sha256":"c28c3603d3b5d939e8dc4c7e95fa8dfce3d595e45f758748cecf8e644a296938","summary":{"advisory":0,"by_detector":{},"critical":0,"informational":0}},"paper":{"abstract_excerpt":"We present TableBank, a new image-based table detection and recognition dataset built with novel weak supervision from Word and Latex documents on the internet. Existing research for image-based table detection and recognition usually fine-tunes pre-trained models on out-of-domain data with a few thousand human-labeled examples, which is difficult to generalize on real-world applications. With TableBank that contains 417K high quality labeled tables, we build several strong baselines using state-of-the-art models with deep neural networks. We make TableBank publicly available and hope it will ","authors_text":"Furu Wei, Lei Cui, Minghao Li, Ming Zhou, Shaohan Huang, Zhoujun Li","cross_cats":[],"headline":"","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.CV","submitted_at":"2019-03-05T17:34:21Z","title":"TableBank: A Benchmark Dataset for Table Detection and Recognition"},"references":{"count":0,"internal_anchors":0,"resolved_work":0,"sample":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"1903.01949","kind":"arxiv","version":2},"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:ca72ba3cf5761f6c02b8bf472546e3d01411d4eb138bf5bf80308b16b6c39232","target":"record","created_at":"2026-07-05T01:16:08Z","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":"193dd73a917e30845361a96e85edc2ee89f0e28e499f245d86ee2b2e0523f9a3","cross_cats_sorted":[],"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.CV","submitted_at":"2019-03-05T17:34:21Z","title_canon_sha256":"9209ae0fabe61ee56949deec8d5f171d4048bdc32272b6b3c7c7596ec87d838c"},"schema_version":"1.0","source":{"id":"1903.01949","kind":"arxiv","version":2}},"canonical_sha256":"c83df42fb03beb9ccfa283de35c026fd1d1a20317c48fd0b17322d15af5edc0b","receipt":{"algorithm":"ed25519","builder_version":"pith-number-builder-2026-05-17-v1","canonical_sha256":"c83df42fb03beb9ccfa283de35c026fd1d1a20317c48fd0b17322d15af5edc0b","first_computed_at":"2026-07-05T01:16:08.226228Z","key_id":"pith-v1-2026-05","kind":"pith_receipt","last_reissued_at":"2026-07-05T01:16:08.226228Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","receipt_version":"0.3","signature_b64":"e+Hq5JsHs80QDCAhQ2XztxbxQ64DXhjwvZOqosf3hvYP6LWPB8aDjrpZQ72LaEeKBHM7qpEcAtaAMyY8rKaoCg==","signature_status":"signed_v1","signed_at":"2026-07-05T01:16:08.226740Z","signed_message":"canonical_sha256_bytes"},"source_id":"1903.01949","source_kind":"arxiv","source_version":2}}},"equivocations":[],"invalid_events":[],"applied_event_ids":["sha256:ca72ba3cf5761f6c02b8bf472546e3d01411d4eb138bf5bf80308b16b6c39232","sha256:2db05eeb5f6e2c006af7366b43205b35a4ff603261a906ce506eef21aa507292"],"state_sha256":"058f120d08e32d654e1ec53998144f3fd3235b224f21954bb1f019b84b7e980b"}