{"as_of":"2026-08-18T17:02:00Z","caps":{"database_statements":6,"inbound":100,"outbound":100},"context_digest":"sha256:cfdd794052f90acdd116beb8a70d2e3a773fe3e51a43cf29b8cb9b7e4c0c5453","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":"2026-08-18T06:34:40.430872+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":"2026-08-16T05:02:17.477543Z","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":"2026-05-10T00:49:48.673155Z","state":"measured"}],"external_citation_measurements":[],"inbound":[{"citation":{"cited_paper":{"arxiv_id":"1911.12704","last_updated":"2020-10-12T13:38:52Z","snapshot_observed_at":"2026-08-18T11:11:07.674985Z","submitted_at":"2019-11-28T13:38:17Z","title":"Comparative Study of Differentially Private Synthetic Data Algorithms from the NIST PSCR Differential Privacy Synthetic Data Challenge","version":3},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"1911.12704","snapshot_observed_at":"2026-08-08T19:09:03.850176Z","title":"Comparative study of differentially private synthetic data algorithms from the nist pscr differential privacy synthetic data challenge","venue":null,"work_id":null,"year":1911},"citing_paper":{"arxiv_id":"2502.05505","last_updated":"2025-05-20T04:05:24Z","snapshot_observed_at":"2026-08-17T13:26:10.786750Z","submitted_at":"2025-02-08T09:50:30Z","title":"Differentially Private Synthetic Data via APIs 3: Using Simulators Instead of Foundation Model","version":3},"reference_index":7,"source":"pdf_text","source_observed_at":"2026-08-08T19:09:03.850176Z"},"links":{"cited_paper":"/paper/1911.12704","citing_paper":"/paper/2502.05505"},"observation_digest":"sha256:d03b2bc2022f62c0e03cacf0fd5ce31d1c10ed58d1ad03a2b0dae02cc4551fda","observation_id":"c07611a7-6e23-4158-8140-49bfd6d1e244","resolution":{"observed_at":"2026-08-08T19:09:03.850176Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"1911.12704","last_updated":"2020-10-12T13:38:52Z","snapshot_observed_at":"2026-08-18T11:11:07.674985Z","submitted_at":"2019-11-28T13:38:17Z","title":"Comparative Study of Differentially Private Synthetic Data Algorithms from the NIST PSCR Differential Privacy Synthetic Data Challenge","version":3},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"1911.12704","snapshot_observed_at":"2026-08-16T05:02:17.477543Z","title":null,"venue":null,"work_id":null,"year":2019},"citing_paper":{"arxiv_id":"2504.21634","last_updated":"2025-04-30T13:36:27Z","snapshot_observed_at":"2026-08-18T16:42:46.373518Z","submitted_at":"2025-04-30T13:36:27Z","title":"Quantitative Auditing of AI Fairness with Differentially Private Synthetic Data","version":1},"reference_index":11,"source":"pdf_text","source_observed_at":"2026-08-16T05:02:17.477543Z"},"links":{"cited_paper":"/paper/1911.12704","citing_paper":"/paper/2504.21634"},"observation_digest":"sha256:c4ab2cff55c1917a9a06eee20828c27e65dd4d92f6de9c48a09471246faeec53","observation_id":"e4f18cf5-4089-44e3-90de-16916ace2e7c","resolution":{"observed_at":"2026-08-16T05:02:17.477543Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"1911.12704","last_updated":"2020-10-12T13:38:52Z","snapshot_observed_at":"2026-08-18T11:11:07.674985Z","submitted_at":"2019-11-28T13:38:17Z","title":"Comparative Study of Differentially Private Synthetic Data Algorithms from the NIST PSCR Differential Privacy Synthetic Data Challenge","version":3},"cited_work":{"arxiv_id":"1911.12704","doi":null,"metadata_source":"arxiv_reference","pith_arxiv_id":"1911.12704","snapshot_observed_at":"2026-06-05T21:23:00.469572Z","title":"arXiv preprint arXiv:1911.12704 (2019)","venue":null,"work_id":"8e863526-d013-4f39-9944-b3304725e592","year":1911},"citing_paper":{"arxiv_id":"2604.21031","last_updated":"2026-04-22T19:23:25Z","snapshot_observed_at":"2026-08-15T03:55:48.559220Z","submitted_at":"2026-04-22T19:23:25Z","title":"Synthetic Data in Education: Empirical Insights from Traditional Resampling and Deep Generative Models","version":1},"reference_index":4,"source":"pdf_text","source_observed_at":"2026-05-10T00:46:26.349406Z"},"links":{"cited_paper":"/paper/1911.12704","citing_paper":"/paper/2604.21031"},"observation_digest":"sha256:d0688dc88370a056a1a61e05915b3866c1e8cc16a1d4a52ae4fef507c0f5d2e9","observation_id":"f61516fd-4a11-4186-8b04-0f8d2d3e81a9","resolution":{"observed_at":"2026-05-10T00:49:48.674368Z","resolver_source":"arxiv_id","status":"verified_exact"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-18T06:34:40.430872+00:00","source":"crossref"},{"observed_at":"2026-08-18T06:34:34.496301+00:00","source":"retraction_watch"}],"state":"measured"}}],"links":{"evidence":"/evidence","html":"/paper/1911.12704/citation-record","integrity":"/paper/1911.12704/integrity","json":"/paper/1911.12704/citation-record.json","paper":"/paper/1911.12704"},"outbound":[],"paper":{"arxiv_id":"1911.12704","last_updated":"2020-10-12T13:38:52Z","latest_version":3,"primary_category":"stat.AP","snapshot_observed_at":"2026-08-18T11:11:07.674985Z","submitted_at":"2019-11-28T13:38:17Z","title":"Comparative Study of Differentially Private Synthetic Data Algorithms from the NIST PSCR Differential Privacy Synthetic Data Challenge"},"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":"2026-08-18T06:34:40.430872+00:00","source":"crossref"},{"observed_at":"2026-08-18T06:34:34.496301+00:00","source":"retraction_watch"}],"thesis":"As of 18 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 3 inbound Pith citation observations for arXiv:1911.12704."}