{"as_of":"2026-08-10T08:26:00Z","caps":{"database_statements":6,"inbound":100,"outbound":100},"context_digest":"sha256:e84b600af4526824f16e0463d0d6e94889f63f7f95893d17f123fb89c6452b46","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":4,"lane":"standing_notices","note":"One-hop event checks from named stored sources.","records_observed":4,"source":"scholarly_work_events, retraction_status_cache","source_observed_at":"2026-08-10T06:31:04.303077+00:00","state":"measured"},{"denominator":4,"lane":"inbound_itemization","note":"Pith citing papers itemized under the disclosed page cap.","records_observed":4,"source":"paper_references, paper_reference_links","source_observed_at":"2026-08-06T20:47:40.624376Z","state":"measured"},{"denominator":1,"lane":"external_citation_measurements","note":"A source-named dated measurement, never combined with another source.","records_observed":0,"source":"arxiv_reference","source_observed_at":"2026-07-04T14:49:54.600264Z","state":"measured"}],"external_citation_measurements":[],"inbound":[{"citation":{"cited_paper":{"arxiv_id":"2212.07588","last_updated":"2023-06-23T14:58:03Z","snapshot_observed_at":"2026-08-04T04:49:24.741165Z","submitted_at":"2022-12-15T02:40:57Z","title":"DeepJoin: Joinable Table Discovery with Pre-trained Language Models","version":2},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2212.07588","snapshot_observed_at":"2026-08-06T20:47:40.624376Z","title":null,"venue":null,"work_id":null,"year":2023},"citing_paper":{"arxiv_id":"2507.02020","last_updated":"2025-07-02T14:37:31Z","snapshot_observed_at":"2026-08-09T05:07:01.657907Z","submitted_at":"2025-07-02T14:37:31Z","title":"Template-Based Schema Matching of Multi-Layout Tenancy Schedules:A Comparative Study of a Template-Based Hybrid Matcher and the ALITE Full Disjunction Model","version":1},"reference_index":11,"source":"pdf_text","source_observed_at":"2026-08-06T20:47:40.624376Z"},"links":{"cited_paper":"/paper/2212.07588","citing_paper":"/paper/2507.02020"},"observation_digest":"sha256:a045fbba37388c5b29fad42292c243cde9b2410c7c181bf8868723fb6ab9a753","observation_id":"1b2e58a7-8f07-4c10-a9ec-d220fba8c75d","resolution":{"observed_at":"2026-08-06T20:47:40.624376Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2212.07588","last_updated":"2023-06-23T14:58:03Z","snapshot_observed_at":"2026-08-04T04:49:24.741165Z","submitted_at":"2022-12-15T02:40:57Z","title":"DeepJoin: Joinable Table Discovery with Pre-trained Language Models","version":2},"cited_work":{"arxiv_id":"2212.07588","doi":null,"metadata_source":"arxiv_reference","pith_arxiv_id":"2212.07588","snapshot_observed_at":"2026-07-04T14:49:54.600264Z","title":"arXiv preprint arXiv:2212.07588 , year=","venue":null,"work_id":"9b1a9531-16c1-4f1a-b4ec-2a80f4ff71ba","year":2022},"citing_paper":{"arxiv_id":"2605.18766","last_updated":"2026-04-12T14:53:56Z","snapshot_observed_at":"2026-07-06T23:29:33.702647Z","submitted_at":"2026-04-12T14:53:56Z","title":"Retrieve Only Relevant Tables Whether Few or Many: Adaptive Table Retrieval Method","version":1},"reference_index":88,"source":"arxiv_source","source_observed_at":"2026-05-21T01:07:54.061446Z"},"links":{"cited_paper":"/paper/2212.07588","citing_paper":"/paper/2605.18766"},"observation_digest":"sha256:dd1908db5c3c2f17ff09e605d38d55e947a09dd4f5d4c3b687548f6d529f5656","observation_id":"36d26114-fe93-4484-a493-e34acb46b24e","resolution":{"observed_at":"2026-05-21T01:09:20.365292Z","resolver_source":"arxiv_id","status":"verified_exact"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-10T06:31:04.303077+00:00","source":"crossref"},{"observed_at":"2026-08-10T06:30:57.382061+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"2212.07588","last_updated":"2023-06-23T14:58:03Z","snapshot_observed_at":"2026-08-04T04:49:24.741165Z","submitted_at":"2022-12-15T02:40:57Z","title":"DeepJoin: Joinable Table Discovery with Pre-trained Language Models","version":2},"cited_work":{"arxiv_id":"2212.07588","doi":null,"metadata_source":"arxiv_reference","pith_arxiv_id":"2212.07588","snapshot_observed_at":"2026-07-04T14:49:54.600264Z","title":"arXiv preprint arXiv:2212.07588 , year=","venue":null,"work_id":"9b1a9531-16c1-4f1a-b4ec-2a80f4ff71ba","year":2022},"citing_paper":{"arxiv_id":"2606.26613","last_updated":"2026-08-01T06:08:14Z","snapshot_observed_at":"2026-08-07T11:50:56.913893Z","submitted_at":"2026-06-25T05:18:20Z","title":"EcoTable: Cost-effective Table Integration in Data Lakes for Natural Language Queries","version":1},"reference_index":12,"source":"pdf_text","source_observed_at":"2026-06-26T02:38:20.300232Z"},"links":{"cited_paper":"/paper/2212.07588","citing_paper":"/paper/2606.26613"},"observation_digest":"sha256:74d752b859891665873fbfa494b97f5d963cf53295d1345151f2ca4e013a4389","observation_id":"a2b6bb17-0d62-4fd6-bd5c-c931693fee3f","resolution":{"observed_at":"2026-07-04T14:49:54.602925Z","resolver_source":"arxiv_id","status":"verified_exact"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-10T06:31:04.303077+00:00","source":"crossref"},{"observed_at":"2026-08-10T06:30:57.382061+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"2212.07588","last_updated":"2023-06-23T14:58:03Z","snapshot_observed_at":"2026-08-04T04:49:24.741165Z","submitted_at":"2022-12-15T02:40:57Z","title":"DeepJoin: Joinable Table Discovery with Pre-trained Language Models","version":2},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2212.07588","snapshot_observed_at":"2026-08-04T02:32:09.559987Z","title":null,"venue":null,"work_id":null,"year":2022},"citing_paper":{"arxiv_id":"2606.26613","last_updated":"2026-08-01T06:08:14Z","snapshot_observed_at":"2026-08-07T11:50:56.913893Z","submitted_at":"2026-06-25T05:18:20Z","title":"EcoTable: Cost-effective Table Integration in Data Lakes for Natural Language Queries","version":2},"reference_index":12,"source":"pdf_text","source_observed_at":"2026-08-04T02:32:09.559987Z"},"links":{"cited_paper":"/paper/2212.07588","citing_paper":"/paper/2606.26613"},"observation_digest":"sha256:945dc6bf2e4f6e676302b7389d2a70918c9c11df9c815ab0dddc13113bea1af4","observation_id":"8ce00963-d8c5-4b37-821a-112633b5c8ed","resolution":{"observed_at":"2026-08-04T02:32:09.559987Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}}],"links":{"evidence":"/evidence","html":"/paper/2212.07588/citation-record","integrity":"/paper/2212.07588/integrity","json":"/paper/2212.07588/citation-record.json","paper":"/paper/2212.07588"},"outbound":[],"paper":{"arxiv_id":"2212.07588","last_updated":"2023-06-23T14:58:03Z","latest_version":2,"primary_category":"cs.DB","snapshot_observed_at":"2026-08-04T04:49:24.741165Z","submitted_at":"2022-12-15T02:40:57Z","title":"DeepJoin: Joinable Table Discovery with Pre-trained Language Models"},"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":"2026-08-10T06:31:04.303077+00:00","source":"crossref"},{"observed_at":"2026-08-10T06:30:57.382061+00:00","source":"retraction_watch"}],"thesis":"As of 10 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 4 inbound Pith citation observations for arXiv:2212.07588."}