{"as_of":"2026-08-16T05:04:00Z","caps":{"database_statements":6,"inbound":100,"outbound":100},"context_digest":"sha256:dc4cb8bcd697ecf631c1eeef3c4ee84a63f8c57b6542cb173e910d5566fbbc92","coverage":[{"denominator":0,"lane":"reference_resolution","note":"Typed states for the displayed outbound observations.","records_observed":0,"source":"paper_references, paper_reference_links","source_observed_at":null,"state":"measured"},{"denominator":3,"lane":"standing_notices","note":"One-hop event checks from named stored sources.","records_observed":3,"source":"scholarly_work_events, retraction_status_cache","source_observed_at":"2026-08-15T06:32:42.880941+00:00","state":"measured"},{"denominator":3,"lane":"inbound_itemization","note":"Pith citing papers itemized under the disclosed page cap.","records_observed":3,"source":"paper_references, paper_reference_links","source_observed_at":"2026-08-15T19:52:52.188564Z","state":"measured"},{"denominator":1,"lane":"external_citation_measurements","note":"A source-named dated measurement, never combined with another source.","records_observed":0,"source":"pith","source_observed_at":"2026-08-05T21:08:54.488621Z","state":"measured"}],"external_citation_measurements":[],"inbound":[{"citation":{"cited_paper":{"arxiv_id":"2203.00274","last_updated":"2022-05-03T14:53:29Z","snapshot_observed_at":"2026-08-15T14:25:38.666924Z","submitted_at":"2022-03-01T07:23:06Z","title":"TableFormer: Robust Transformer Modeling for Table-Text Encoding","version":2},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2203.00274","snapshot_observed_at":"2026-08-08T16:11:43.250067Z","title":null,"venue":null,"work_id":null,"year":2022},"citing_paper":{"arxiv_id":"2502.08662","last_updated":"2025-06-02T04:54:00Z","snapshot_observed_at":"2026-08-09T07:57:07.000139Z","submitted_at":"2025-02-10T09:34:15Z","title":"RoToR: Towards More Reliable Responses for Order-Invariant Inputs","version":3},"reference_index":37,"source":"arxiv_source","source_observed_at":"2026-08-08T16:11:43.250067Z"},"links":{"cited_paper":"/paper/2203.00274","citing_paper":"/paper/2502.08662"},"observation_digest":"sha256:049129763c4ff488e57bd8fab3eace8000e41eb9eb2d5e447b5bf814d0ac3439","observation_id":"f04a5292-11e3-4358-8bea-9ab0a1a3549c","resolution":{"observed_at":"2026-08-08T16:11:43.250067Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2203.00274","last_updated":"2022-05-03T14:53:29Z","snapshot_observed_at":"2026-08-15T14:25:38.666924Z","submitted_at":"2022-03-01T07:23:06Z","title":"TableFormer: Robust Transformer Modeling for Table-Text Encoding","version":2},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2203.00274","snapshot_observed_at":"2026-08-15T19:52:52.188564Z","title":"Available: https://arxiv.org/abs/2203.00274","venue":null,"work_id":null,"year":null},"citing_paper":{"arxiv_id":"2506.14583","last_updated":"2025-06-17T14:41:31Z","snapshot_observed_at":"2026-08-15T19:48:53.535103Z","submitted_at":"2025-06-17T14:41:31Z","title":"Synthetic Data Augmentation for Table Detection: Re-evaluating TableNet's Performance with Automatically Generated Document Images","version":1},"reference_index":2022,"source":"pdf_text","source_observed_at":"2026-08-15T19:52:52.188564Z"},"links":{"cited_paper":"/paper/2203.00274","citing_paper":"/paper/2506.14583"},"observation_digest":"sha256:f8ee27e7bbb8da10ca94aa432ac3909230d5327dd32c26b62c7322b1ee2dde49","observation_id":"4f449286-002a-47b8-81c3-2408965cb78e","resolution":{"observed_at":"2026-08-15T19:52:52.188564Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2203.00274","last_updated":"2022-05-03T14:53:29Z","snapshot_observed_at":"2026-08-15T14:25:38.666924Z","submitted_at":"2022-03-01T07:23:06Z","title":"TableFormer: Robust Transformer Modeling for Table-Text Encoding","version":2},"cited_work":{"arxiv_id":"2203.00274","doi":null,"metadata_source":"pith","pith_arxiv_id":"2203.00274","snapshot_observed_at":"2026-08-05T21:08:54.488621Z","title":"TableFormer: Robust Transformer Modeling for Table-Text Encoding","venue":"cs.CL","work_id":"5e39966d-37f6-440a-a149-3af8a110ba1b","year":2022},"citing_paper":{"arxiv_id":"2508.09324","last_updated":"2025-08-12T20:16:41Z","snapshot_observed_at":"2026-08-14T11:04:25.188871Z","submitted_at":"2025-08-12T20:16:41Z","title":"TEN: Table Explicitization, Neurosymbolically","version":1},"reference_index":43,"source":"arxiv_source","source_observed_at":"2026-08-05T21:08:52.855955Z"},"links":{"cited_paper":"/paper/2203.00274","citing_paper":"/paper/2508.09324"},"observation_digest":"sha256:afb38e80e535ec5b8f045d3565f89e49bd5862859d5ccc7d943ad97e4ded8a42","observation_id":"345a5212-b708-4ef5-9117-eb403b39c478","resolution":{"observed_at":"2026-08-05T21:08:54.629764Z","resolver_source":"local_arxiv","status":"verified_exact"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-15T06:32:42.880941+00:00","source":"crossref"},{"observed_at":"2026-08-15T06:32:39.529945+00:00","source":"retraction_watch"}],"state":"measured"}}],"links":{"evidence":"/evidence","html":"/paper/2203.00274/citation-record","integrity":"/paper/2203.00274/integrity","json":"/paper/2203.00274/citation-record.json","paper":"/paper/2203.00274"},"outbound":[],"paper":{"arxiv_id":"2203.00274","last_updated":"2022-05-03T14:53:29Z","latest_version":2,"primary_category":"cs.CL","snapshot_observed_at":"2026-08-15T14:25:38.666924Z","submitted_at":"2022-03-01T07:23:06Z","title":"TableFormer: Robust Transformer Modeling for Table-Text Encoding"},"reference_resolution":{"displayed":0,"state_counts":{"malformed_identifier":0,"metadata_mismatch":0,"parse_uncertain":0,"unresolved":0,"verified_exact":0,"verified_fuzzy":0},"total_outbound_references":0},"refusal":"A citation records a reference. It does not transfer a finding from one paper to another.","schema":"pith.paper-citation-record.v1","standing_sources":[{"observed_at":"2026-08-15T06:32:42.880941+00:00","source":"crossref"},{"observed_at":"2026-08-15T06:32:39.529945+00:00","source":"retraction_watch"}],"thesis":"As of 16 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 3 inbound Pith citation observations for arXiv:2203.00274."}