{"as_of":"2026-08-20T09:10:00Z","caps":{"database_statements":6,"inbound":100,"outbound":100},"context_digest":"sha256:e8ea65d445efdd3c726aaf6c593fecace6fb50f7341251c34388a070000be2e3","coverage":[{"denominator":2,"lane":"reference_resolution","note":"Typed states for the displayed outbound observations.","records_observed":2,"source":"paper_references, paper_reference_links","source_observed_at":"2026-08-12T17:33:09.891289Z","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":"2026-08-20T06:33:59.587034+00:00","state":"measured"},{"denominator":1,"lane":"inbound_itemization","note":"Pith citing papers itemized under the disclosed page cap.","records_observed":1,"source":"paper_references, paper_reference_links","source_observed_at":"2026-06-27T16:11:36.483820Z","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":"2026-07-03T02:07:33.278279Z","state":"measured"}],"external_citation_measurements":[],"inbound":[{"citation":{"cited_paper":{"arxiv_id":"2411.12451","last_updated":"2024-11-19T12:19:28Z","snapshot_observed_at":"2026-08-18T02:00:01.480978Z","submitted_at":"2024-11-19T12:19:28Z","title":"Empirical Privacy Evaluations of Generative and Predictive Machine Learning Models -- A review and challenges for practice","version":1},"cited_work":{"arxiv_id":"2411.12451","doi":null,"metadata_source":"arxiv_reference","pith_arxiv_id":"2411.12451","snapshot_observed_at":"2026-07-03T02:07:33.278279Z","title":"Empirical privacy evaluations of generative and predictive machine learning models – a review and challenges for practice, 2024","venue":null,"work_id":"6f5f7673-5602-4e21-a8da-4508604baec4","year":2024},"citing_paper":{"arxiv_id":"2606.09809","last_updated":"2026-06-08T17:55:02Z","snapshot_observed_at":"2026-08-13T06:18:06.017895Z","submitted_at":"2026-06-08T17:55:02Z","title":"Evaluation Cards: An Interpretive Layer for AI Evaluation Reporting","version":1},"reference_index":50,"source":"pdf_text","source_observed_at":"2026-06-27T16:11:36.483820Z"},"links":{"cited_paper":"/paper/2411.12451","citing_paper":"/paper/2606.09809"},"observation_digest":"sha256:7d746e380f4ab660bf8385a0fce125a9632931e6c10ae818616beb6eeeb6bfe6","observation_id":"f6cabc94-c87a-4c08-90a0-e8c0dc6df617","resolution":{"observed_at":"2026-07-03T02:07:33.280148Z","resolver_source":"arxiv_id","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/2411.12451/citation-record","integrity":"/paper/2411.12451/integrity","json":"/paper/2411.12451/citation-record.json","paper":"/paper/2411.12451"},"outbound":[{"citation":{"cited_paper":{"arxiv_id":"1705.07663","last_updated":"2018-08-21T13:24:17Z","snapshot_observed_at":"2026-08-16T22:35:56.125619Z","submitted_at":"2017-05-22T11:05:06Z","title":"LOGAN: Membership Inference Attacks Against Generative Models","version":4},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"1705.07663","snapshot_observed_at":"2026-08-12T17:33:09.885570Z","title":"Logan: Membership inference attacks against genera tive models","venue":null,"work_id":null,"year":2022},"citing_paper":{"arxiv_id":"2411.12451","last_updated":"2024-11-19T12:19:28Z","snapshot_observed_at":"2026-08-18T02:00:01.480978Z","submitted_at":"2024-11-19T12:19:28Z","title":"Empirical Privacy Evaluations of Generative and Predictive Machine Learning Models -- A review and challenges for practice","version":1},"reference_index":2017,"source":"pdf_text","source_observed_at":"2026-08-12T17:33:09.885570Z"},"links":{"cited_paper":"/paper/1705.07663","citing_paper":"/paper/2411.12451"},"observation_digest":"sha256:af6f214410c7da40b7c7d4d0358ece304b563a391bf7d544c7b8a1e9e192c2bc","observation_id":"e7764b18-bd08-47dc-a382-8232fbb57859","resolution":{"observed_at":"2026-08-12T17:33:09.885570Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"1806.03384","last_updated":"2018-07-02T19:20:02Z","snapshot_observed_at":"2026-08-18T01:59:04.304460Z","submitted_at":"2018-06-09T00:23:15Z","title":"Data Synthesis based on Generative Adversarial Networks","version":5},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"1806.03384","snapshot_observed_at":"2026-08-12T17:33:09.891289Z","title":"Privacy Assessment of Synthetic Patient Data","venue":null,"work_id":null,"year":2018},"citing_paper":{"arxiv_id":"2411.12451","last_updated":"2024-11-19T12:19:28Z","snapshot_observed_at":"2026-08-18T02:00:01.480978Z","submitted_at":"2024-11-19T12:19:28Z","title":"Empirical Privacy Evaluations of Generative and Predictive Machine Learning Models -- A review and challenges for practice","version":1},"reference_index":2023,"source":"pdf_text","source_observed_at":"2026-08-12T17:33:09.891289Z"},"links":{"cited_paper":"/paper/1806.03384","citing_paper":"/paper/2411.12451"},"observation_digest":"sha256:c89c7289dcfe0008e7fbdba406f25b8a04446f0e6d53b7808d9f86c8cd5153d3","observation_id":"dc465a47-5e9e-4eb3-b01f-fad4570306a2","resolution":{"observed_at":"2026-08-12T17:33:09.891289Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}}],"paper":{"arxiv_id":"2411.12451","last_updated":"2024-11-19T12:19:28Z","latest_version":1,"primary_category":"cs.LG","snapshot_observed_at":"2026-08-18T02:00:01.480978Z","submitted_at":"2024-11-19T12:19:28Z","title":"Empirical Privacy Evaluations of Generative and Predictive Machine Learning Models -- A review and challenges for practice"},"reference_resolution":{"displayed":2,"state_counts":{"malformed_identifier":0,"metadata_mismatch":0,"parse_uncertain":0,"unresolved":2,"verified_exact":0,"verified_fuzzy":0},"total_outbound_references":2},"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 2 of 2 outbound references and 1 inbound Pith citation observation for arXiv:2411.12451."}