{"as_of":"2026-08-08T07:35:00Z","caps":{"database_statements":6,"inbound":100,"outbound":100},"context_digest":"sha256:81240899f9286a0b9b16423b51ab736d8e9f4b8a26043a6ac1aeac05dd7f5017","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":"2026-08-08T06:32:00.761636+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":"2026-08-07T05:38:36.204486Z","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":"2026-05-24T01:03:41.489771Z","state":"measured"}],"external_citation_measurements":[],"inbound":[{"citation":{"cited_paper":{"arxiv_id":"2004.04676","last_updated":"2020-04-01T12:41:45Z","snapshot_observed_at":"2026-08-04T13:39:39.727961Z","submitted_at":"2020-04-01T12:41:45Z","title":"An Overview of Federated Deep Learning Privacy Attacks and Defensive Strategies","version":1},"cited_work":{"arxiv_id":"2004.04676","doi":null,"metadata_source":"arxiv_reference","pith_arxiv_id":"2004.04676","snapshot_observed_at":"2026-06-05T21:23:00.469572Z","title":"arXiv preprint arXiv:2004.04676 (2020) https://doi.org/10","venue":null,"work_id":"b12fbe11-af3c-40ab-b314-8781a2bef21d","year":2004},"citing_paper":{"arxiv_id":"2405.09806","last_updated":"2026-04-21T06:47:31Z","snapshot_observed_at":"2026-08-05T00:03:49.090547Z","submitted_at":"2024-05-16T04:28:44Z","title":"A Generalist Model for Diverse Text-Guided Medical Image Synthesis","version":7},"reference_index":13,"source":"pdf_text","source_observed_at":"2026-05-24T00:59:10.949395Z"},"links":{"cited_paper":"/paper/2004.04676","citing_paper":"/paper/2405.09806"},"observation_digest":"sha256:752694c7fda8e667fc0354dfb552829324fcc5d00c99321a52458e654b93fa1f","observation_id":"fef1e07c-428b-45f2-98bc-a801e4685c76","resolution":{"observed_at":"2026-05-24T01:03:41.492580Z","resolver_source":"arxiv_id","status":"verified_exact"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-08T06:32:00.761636+00:00","source":"crossref"},{"observed_at":"2026-08-08T06:31:55.24221+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"2004.04676","last_updated":"2020-04-01T12:41:45Z","snapshot_observed_at":"2026-08-04T13:39:39.727961Z","submitted_at":"2020-04-01T12:41:45Z","title":"An Overview of Federated Deep Learning Privacy Attacks and Defensive Strategies","version":1},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2004.04676","snapshot_observed_at":"2026-08-07T05:38:36.204486Z","title":null,"venue":null,"work_id":null,"year":2020},"citing_paper":{"arxiv_id":"2506.07605","last_updated":"2025-07-13T17:21:43Z","snapshot_observed_at":"2026-08-07T09:31:00.241304Z","submitted_at":"2025-06-09T10:06:03Z","title":"TimberStrike: Dataset Reconstruction Attack Revealing Privacy Leakage in Federated Tree-Based Systems","version":3},"reference_index":18,"source":"pdf_text","source_observed_at":"2026-08-07T05:38:36.204486Z"},"links":{"cited_paper":"/paper/2004.04676","citing_paper":"/paper/2506.07605"},"observation_digest":"sha256:50788c77acda1cb514264288c71c7fce15a8d5e308c6fafcc4cf76520d2b2d27","observation_id":"7e7fec91-c82a-497e-a3ee-912611a8c758","resolution":{"observed_at":"2026-08-07T05:38:36.204486Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}}],"links":{"evidence":"/evidence","html":"/paper/2004.04676/citation-record","integrity":"/paper/2004.04676/integrity","json":"/paper/2004.04676/citation-record.json","paper":"/paper/2004.04676"},"outbound":[],"paper":{"arxiv_id":"2004.04676","last_updated":"2020-04-01T12:41:45Z","latest_version":1,"primary_category":"cs.CR","snapshot_observed_at":"2026-08-04T13:39:39.727961Z","submitted_at":"2020-04-01T12:41:45Z","title":"An Overview of Federated Deep Learning Privacy Attacks and Defensive Strategies"},"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":"2026-08-08T06:32:00.761636+00:00","source":"crossref"},{"observed_at":"2026-08-08T06:31:55.24221+00:00","source":"retraction_watch"}],"thesis":"As of 8 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 2 inbound Pith citation observations for arXiv:2004.04676."}