{"as_of":"2026-08-20T09:33:00Z","caps":{"database_statements":6,"inbound":100,"outbound":100},"context_digest":"sha256:c233b0d9cf187db4a7f00afd52f5466cac7ceeb20da526f64c09f4091b7292db","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":"2026-08-20T06:33:59.587034+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":"2026-08-14T13:28:22.116581Z","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":"2026-08-14T10:50:12.521323Z","state":"measured"}],"external_citation_measurements":[],"inbound":[{"citation":{"cited_paper":{"arxiv_id":"1912.02938","last_updated":"2019-12-06T00:51:51Z","snapshot_observed_at":"2026-08-18T07:06:46.378194Z","submitted_at":"2019-12-06T00:51:51Z","title":"Lower Bounds for Compressed Sensing with Generative Models","version":1},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"1912.02938","snapshot_observed_at":"2026-08-14T13:28:22.116581Z","title":", Karmalkar, S","venue":null,"work_id":null,"year":2019},"citing_paper":{"arxiv_id":"1908.05368","last_updated":"2020-08-22T06:44:50Z","snapshot_observed_at":"2026-08-19T00:09:03.834141Z","submitted_at":"2019-08-14T22:56:34Z","title":"Robust One-Bit Recovery via ReLU Generative Networks: Near-Optimal Statistical Rate and Global Landscape Analysis","version":3},"reference_index":19,"source":"arxiv_source","source_observed_at":"2026-08-14T13:28:22.116581Z"},"links":{"cited_paper":"/paper/1912.02938","citing_paper":"/paper/1908.05368"},"observation_digest":"sha256:6b4de9dc56b6c7ba806472da0ddc6e7788be0b624013d7b0e117d14256cabe40","observation_id":"8eb0034e-1e53-4b07-a535-dd0eb1fc2a2a","resolution":{"observed_at":"2026-08-14T13:28:22.116581Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"1912.02938","last_updated":"2019-12-06T00:51:51Z","snapshot_observed_at":"2026-08-18T07:06:46.378194Z","submitted_at":"2019-12-06T00:51:51Z","title":"Lower Bounds for Compressed Sensing with Generative Models","version":1},"cited_work":{"arxiv_id":"1912.02938","doi":null,"metadata_source":"pith","pith_arxiv_id":"1912.02938","snapshot_observed_at":"2026-08-14T10:50:12.521323Z","title":"Lower Bounds for Compressed Sensing with Generative Models","venue":"cs.DS","work_id":"144b4046-9664-4ac4-92da-4d793e01d4e5","year":2019},"citing_paper":{"arxiv_id":"1908.10744","last_updated":"2020-03-10T06:15:58Z","snapshot_observed_at":"2026-08-19T20:51:37.020516Z","submitted_at":"2019-08-28T14:24:03Z","title":"Information-Theoretic Lower Bounds for Compressive Sensing with Generative Models","version":2},"reference_index":23,"source":"pdf_text","source_observed_at":"2026-08-14T10:50:12.348567Z"},"links":{"cited_paper":"/paper/1912.02938","citing_paper":"/paper/1908.10744"},"observation_digest":"sha256:157a047e5387b002f0dc78a2e99f45d8e694a706ced88b2d2358c39f622ee23d","observation_id":"496ec104-e718-4fb9-912e-73619374cfb0","resolution":{"observed_at":"2026-08-14T10:50:12.530292Z","resolver_source":"local_arxiv","status":"verified_exact"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-20T06:33:59.587034+00:00","source":"crossref"},{"observed_at":"2026-08-20T06:33:54.927442+00:00","source":"retraction_watch"}],"state":"measured"}}],"links":{"evidence":"/evidence","html":"/paper/1912.02938/citation-record","integrity":"/paper/1912.02938/integrity","json":"/paper/1912.02938/citation-record.json","paper":"/paper/1912.02938"},"outbound":[],"paper":{"arxiv_id":"1912.02938","last_updated":"2019-12-06T00:51:51Z","latest_version":1,"primary_category":"cs.DS","snapshot_observed_at":"2026-08-18T07:06:46.378194Z","submitted_at":"2019-12-06T00:51:51Z","title":"Lower Bounds for Compressed Sensing with Generative 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":"2026-08-20T06:33:59.587034+00:00","source":"crossref"},{"observed_at":"2026-08-20T06:33:54.927442+00:00","source":"retraction_watch"}],"thesis":"As of 20 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 2 inbound Pith citation observations for arXiv:1912.02938."}