{"as_of":"2026-08-15T17:29:00Z","caps":{"database_statements":6,"inbound":100,"outbound":100},"context_digest":"sha256:37c99e354ed47b9cf55d3959012536c7ba172545b604e9e177fee1a5d75c2da6","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":2,"lane":"standing_notices","note":"One-hop event checks from named stored sources.","records_observed":2,"source":"scholarly_work_events, retraction_status_cache","source_observed_at":"2026-08-15T06:32:42.880941+00:00","state":"measured"},{"denominator":2,"lane":"inbound_itemization","note":"Pith citing papers itemized under the disclosed page cap.","records_observed":2,"source":"paper_references, paper_reference_links","source_observed_at":"2026-08-14T14:09:59.916447Z","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":"2026-05-25T12:25:48.162204Z","state":"measured"}],"external_citation_measurements":[],"inbound":[{"citation":{"cited_paper":{"arxiv_id":"1901.02220","last_updated":"2021-03-12T13:59:26Z","snapshot_observed_at":"2026-08-15T13:21:09.122493Z","submitted_at":"2019-01-08T09:41:27Z","title":"Deep Neural Network Approximation Theory","version":4},"cited_work":{"arxiv_id":"1901.02220","doi":null,"metadata_source":"arxiv_reference","pith_arxiv_id":"1901.02220","snapshot_observed_at":"2026-06-05T21:23:00.469572Z","title":"Grohs, D","venue":null,"work_id":"c1ffc248-d86b-421f-b5f8-fde1f899b89d","year":1901},"citing_paper":{"arxiv_id":"1907.00485","last_updated":"2019-06-30T22:27:13Z","snapshot_observed_at":"2026-08-03T03:23:50.494089Z","submitted_at":"2019-06-30T22:27:13Z","title":"Robust and Resource Efficient Identification of Two Hidden Layer Neural Networks","version":1},"reference_index":27,"source":"pdf_text","source_observed_at":"2026-05-25T12:22:47.849439Z"},"links":{"cited_paper":"/paper/1901.02220","citing_paper":"/paper/1907.00485"},"observation_digest":"sha256:73fb5cecec4f6405eb833e8746a9e8bc756cd0b0a595419bdbf722527423209f","observation_id":"630b2daa-5b08-413a-b580-cd4c3c018127","resolution":{"observed_at":"2026-05-25T12:25:48.165298Z","resolver_source":"arxiv_id","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"}},{"citation":{"cited_paper":{"arxiv_id":"1901.02220","last_updated":"2021-03-12T13:59:26Z","snapshot_observed_at":"2026-08-15T13:21:09.122493Z","submitted_at":"2019-01-08T09:41:27Z","title":"Deep Neural Network Approximation Theory","version":4},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"1901.02220","snapshot_observed_at":"2026-08-14T14:09:59.916447Z","title":"Deep Neural Network Approximation Theory","venue":null,"work_id":null,"year":2019},"citing_paper":{"arxiv_id":"1908.03833","last_updated":"2019-08-11T00:40:43Z","snapshot_observed_at":"2026-08-15T03:21:22.751656Z","submitted_at":"2019-08-11T00:40:43Z","title":"Space-time error estimates for deep neural network approximations for differential equations","version":1},"reference_index":17,"source":"pdf_text","source_observed_at":"2026-08-14T14:09:59.916447Z"},"links":{"cited_paper":"/paper/1901.02220","citing_paper":"/paper/1908.03833"},"observation_digest":"sha256:b407af3efde801f220aeb6a7dc09d783b592dd7f72c7cfc3e764a98950c84ce7","observation_id":"b16a480f-bc18-4651-b627-d42ba730c92b","resolution":{"observed_at":"2026-08-14T14:09:59.916447Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}}],"links":{"evidence":"/evidence","html":"/paper/1901.02220/citation-record","integrity":"/paper/1901.02220/integrity","json":"/paper/1901.02220/citation-record.json","paper":"/paper/1901.02220"},"outbound":[],"paper":{"arxiv_id":"1901.02220","last_updated":"2021-03-12T13:59:26Z","latest_version":4,"primary_category":"cs.LG","snapshot_observed_at":"2026-08-15T13:21:09.122493Z","submitted_at":"2019-01-08T09:41:27Z","title":"Deep Neural Network Approximation Theory"},"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 15 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 2 inbound Pith citation observations for arXiv:1901.02220."}