{"as_of":"2026-08-12T08:40:00Z","caps":{"database_statements":6,"inbound":100,"outbound":100},"context_digest":"sha256:ce0eb3e3e1229b13060873f817ecb55ce3a73f7445fd7813816534aa5cc7cdad","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":"2026-08-12T06:34:41.77262+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":"2026-08-10T18:12:46.771953Z","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":"2026-07-04T12:39:50.039430Z","state":"measured"}],"external_citation_measurements":[],"inbound":[{"citation":{"cited_paper":{"arxiv_id":"1712.09136","last_updated":"2017-12-25T22:23:28Z","snapshot_observed_at":"2026-07-06T06:16:02.079103Z","submitted_at":"2017-12-25T22:23:28Z","title":"Towards Measuring Membership Privacy","version":1},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"1712.09136","snapshot_observed_at":"2026-08-10T18:12:46.771953Z","title":"Towards measuring membership privacy,","venue":null,"work_id":null,"year":2017},"citing_paper":{"arxiv_id":"2501.11577","last_updated":"2025-01-20T16:28:04Z","snapshot_observed_at":"2026-08-12T07:41:01.944350Z","submitted_at":"2025-01-20T16:28:04Z","title":"Rethinking Membership Inference Attacks Against Transfer Learning","version":1},"reference_index":27,"source":"pdf_text","source_observed_at":"2026-08-10T18:12:46.771953Z"},"links":{"cited_paper":"/paper/1712.09136","citing_paper":"/paper/2501.11577"},"observation_digest":"sha256:089b105502ec9a8c5c76f9c0ca45e3f2ba922301d72ef2b33113c5f24bade0c2","observation_id":"34e2c038-8672-4aaf-80b7-e3af579b4694","resolution":{"observed_at":"2026-08-10T18:12:46.771953Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"1712.09136","last_updated":"2017-12-25T22:23:28Z","snapshot_observed_at":"2026-07-06T06:16:02.079103Z","submitted_at":"2017-12-25T22:23:28Z","title":"Towards Measuring Membership Privacy","version":1},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"1712.09136","snapshot_observed_at":"2026-08-10T14:01:10.985169Z","title":"Towards measuring membership privacy.arXiv preprint arXiv:1712.09136, 2017","venue":null,"work_id":null,"year":2017},"citing_paper":{"arxiv_id":"2501.18624","last_updated":"2025-02-07T05:11:54Z","snapshot_observed_at":"2026-08-12T08:20:53.652418Z","submitted_at":"2025-01-27T05:44:58Z","title":"Membership Inference Attacks Against Vision-Language Models","version":2},"reference_index":54,"source":"pdf_text","source_observed_at":"2026-08-10T14:01:10.985169Z"},"links":{"cited_paper":"/paper/1712.09136","citing_paper":"/paper/2501.18624"},"observation_digest":"sha256:d932537dbf123aab8065fdb954ed314c578cb3707b36fb96518f24ed56f1665c","observation_id":"d1ad026e-c021-4e8f-a5c5-5c23720162f5","resolution":{"observed_at":"2026-08-10T14:01:10.985169Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"1712.09136","last_updated":"2017-12-25T22:23:28Z","snapshot_observed_at":"2026-07-06T06:16:02.079103Z","submitted_at":"2017-12-25T22:23:28Z","title":"Towards Measuring Membership Privacy","version":1},"cited_work":{"arxiv_id":"1712.09136","doi":null,"metadata_source":"pith","pith_arxiv_id":"1712.09136","snapshot_observed_at":"2026-07-04T12:39:50.039430Z","title":"Towards Measuring Membership Privacy","venue":"cs.CR","work_id":"20709f94-745d-4371-ab6b-bf0759f81b4b","year":2017},"citing_paper":{"arxiv_id":"2606.23477","last_updated":"2026-06-22T15:24:53Z","snapshot_observed_at":"2026-08-08T22:57:23.345561Z","submitted_at":"2026-06-22T15:24:53Z","title":"Sublinearly Structured Deep Neural Networks Achieve Feature Learning Consistency for Compositional Functions","version":1},"reference_index":230,"source":"arxiv_source","source_observed_at":"2026-06-26T06:11:13.051639Z"},"links":{"cited_paper":"/paper/1712.09136","citing_paper":"/paper/2606.23477"},"observation_digest":"sha256:da10c78f76d5f5cd9d0203c1e2c63c0ebdf8b7f997134f237e8de31c9f484a25","observation_id":"fb8b895f-19b3-4ed5-9689-4144383c8788","resolution":{"observed_at":"2026-07-04T12:39:50.040587Z","resolver_source":"local_arxiv","status":"metadata_mismatch"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-12T06:34:41.77262+00:00","source":"crossref"},{"observed_at":"2026-08-12T06:34:36.333875+00:00","source":"retraction_watch"}],"state":"measured"}}],"links":{"evidence":"/evidence","html":"/paper/1712.09136/citation-record","integrity":"/paper/1712.09136/integrity","json":"/paper/1712.09136/citation-record.json","paper":"/paper/1712.09136"},"outbound":[],"paper":{"arxiv_id":"1712.09136","last_updated":"2017-12-25T22:23:28Z","latest_version":1,"primary_category":"cs.CR","snapshot_observed_at":"2026-07-06T06:16:02.079103Z","submitted_at":"2017-12-25T22:23:28Z","title":"Towards Measuring Membership Privacy"},"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":"2026-08-12T06:34:41.77262+00:00","source":"crossref"},{"observed_at":"2026-08-12T06:34:36.333875+00:00","source":"retraction_watch"}],"thesis":"As of 12 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 3 inbound Pith citation observations for arXiv:1712.09136."}