{"as_of":"2026-08-23T04:52:00Z","caps":{"database_statements":6,"inbound":100,"outbound":100},"context_digest":"sha256:2b8b7e0011fb3fe9da179ce823e654925ae3d3eac43acad94af378f63e16a71d","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":4,"lane":"standing_notices","note":"One-hop event checks from named stored sources.","records_observed":4,"source":"scholarly_work_events, retraction_status_cache","source_observed_at":"2026-08-22T06:32:14.747728+00:00","state":"measured"},{"denominator":4,"lane":"inbound_itemization","note":"Pith citing papers itemized under the disclosed page cap.","records_observed":4,"source":"paper_references, paper_reference_links","source_observed_at":"2026-08-12T19:04:58.597182Z","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":"2026-08-10T15:46:20.437511Z","state":"measured"}],"external_citation_measurements":[],"inbound":[{"citation":{"cited_paper":{"arxiv_id":"2302.12448","last_updated":"2023-02-24T04:29:44Z","snapshot_observed_at":"2026-08-20T00:18:36.790535Z","submitted_at":"2023-02-24T04:29:44Z","title":"Subspace based Federated Unlearning","version":1},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2302.12448","snapshot_observed_at":"2026-08-12T19:04:58.597182Z","title":"Subspace b ased federated unlearning,","venue":null,"work_id":null,"year":2023},"citing_paper":{"arxiv_id":"2411.11044","last_updated":"2024-11-17T11:45:15Z","snapshot_observed_at":"2026-08-15T22:34:56.656025Z","submitted_at":"2024-11-17T11:45:15Z","title":"Efficient Federated Unlearning with Adaptive Differential Privacy Preservation","version":1},"reference_index":18,"source":"pdf_text","source_observed_at":"2026-08-12T19:04:58.597182Z"},"links":{"cited_paper":"/paper/2302.12448","citing_paper":"/paper/2411.11044"},"observation_digest":"sha256:e4e93cc1631c6a8862beaf9daa7916d3f9123b3be279c93a0dee9594dbc2442c","observation_id":"a931c4fb-c3b9-480e-8aea-3be81fffce08","resolution":{"observed_at":"2026-08-12T19:04:58.597182Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2302.12448","last_updated":"2023-02-24T04:29:44Z","snapshot_observed_at":"2026-08-20T00:18:36.790535Z","submitted_at":"2023-02-24T04:29:44Z","title":"Subspace based Federated Unlearning","version":1},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2302.12448","snapshot_observed_at":"2026-08-12T10:35:58.286521Z","title":"Subspace based federated unlearning,","venue":null,"work_id":null,"year":2023},"citing_paper":{"arxiv_id":"2412.00126","last_updated":"2025-03-10T00:54:33Z","snapshot_observed_at":"2026-08-20T00:19:10.833199Z","submitted_at":"2024-11-28T12:52:48Z","title":"Streamlined Federated Unlearning: Unite as One to Be Highly Efficient","version":2},"reference_index":38,"source":"pdf_text","source_observed_at":"2026-08-12T10:35:58.286521Z"},"links":{"cited_paper":"/paper/2302.12448","citing_paper":"/paper/2412.00126"},"observation_digest":"sha256:5e79006ac6f307f477bad4f1c02fa9491eabc007c3be54a34f005e0335d2b6c0","observation_id":"71738d2e-bcdb-4e7f-8714-6d7847c922f7","resolution":{"observed_at":"2026-08-12T10:35:58.286521Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2302.12448","last_updated":"2023-02-24T04:29:44Z","snapshot_observed_at":"2026-08-20T00:18:36.790535Z","submitted_at":"2023-02-24T04:29:44Z","title":"Subspace based Federated Unlearning","version":1},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2302.12448","snapshot_observed_at":"2026-08-10T23:33:35.502502Z","title":null,"venue":null,"work_id":null,"year":2023},"citing_paper":{"arxiv_id":"2412.20200","last_updated":"2024-12-28T16:23:10Z","snapshot_observed_at":"2026-08-20T00:16:35.782096Z","submitted_at":"2024-12-28T16:23:10Z","title":"Federated Unlearning with Gradient Descent and Conflict Mitigation","version":1},"reference_index":9,"source":"arxiv_source","source_observed_at":"2026-08-10T23:33:35.502502Z"},"links":{"cited_paper":"/paper/2302.12448","citing_paper":"/paper/2412.20200"},"observation_digest":"sha256:567d715406d1f459af435a1cfa0b2534bc9cd8958741f7de016e5222c2abd185","observation_id":"7a0160db-bb5d-47ea-928e-7bdb62350342","resolution":{"observed_at":"2026-08-10T23:33:35.502502Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2302.12448","last_updated":"2023-02-24T04:29:44Z","snapshot_observed_at":"2026-08-20T00:18:36.790535Z","submitted_at":"2023-02-24T04:29:44Z","title":"Subspace based Federated Unlearning","version":1},"cited_work":{"arxiv_id":"2302.12448","doi":null,"metadata_source":"pith","pith_arxiv_id":"2302.12448","snapshot_observed_at":"2026-08-10T15:46:20.437511Z","title":"Subspace based Federated Unlearning","venue":"cs.LG","work_id":"294ef403-ca0f-4ad6-8b77-cb174dfbafb9","year":2023},"citing_paper":{"arxiv_id":"2501.13683","last_updated":"2025-01-23T14:10:02Z","snapshot_observed_at":"2026-08-18T18:04:10.799214Z","submitted_at":"2025-01-23T14:10:02Z","title":"Unlearning Clients, Features and Samples in Vertical Federated Learning","version":1},"reference_index":18,"source":"pdf_text","source_observed_at":"2026-08-10T15:46:20.128053Z"},"links":{"cited_paper":"/paper/2302.12448","citing_paper":"/paper/2501.13683"},"observation_digest":"sha256:b5676572f93cb3950ae80d3c6dfe2c11a2d30ac731b3b1eda9b9d362c4546ec3","observation_id":"5c9e5e89-7c9f-47db-9551-7709b25a63e1","resolution":{"observed_at":"2026-08-10T15:46:20.442780Z","resolver_source":"local_arxiv","status":"verified_exact"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-22T06:32:14.747728+00:00","source":"crossref"},{"observed_at":"2026-08-22T06:32:06.552537+00:00","source":"retraction_watch"}],"state":"measured"}}],"links":{"evidence":"/evidence","html":"/paper/2302.12448/citation-record","integrity":"/paper/2302.12448/integrity","json":"/paper/2302.12448/citation-record.json","paper":"/paper/2302.12448"},"outbound":[],"paper":{"arxiv_id":"2302.12448","last_updated":"2023-02-24T04:29:44Z","latest_version":1,"primary_category":"cs.LG","snapshot_observed_at":"2026-08-20T00:18:36.790535Z","submitted_at":"2023-02-24T04:29:44Z","title":"Subspace based Federated Unlearning"},"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":"2026-08-22T06:32:14.747728+00:00","source":"crossref"},{"observed_at":"2026-08-22T06:32:06.552537+00:00","source":"retraction_watch"}],"thesis":"As of 23 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 4 inbound Pith citation observations for arXiv:2302.12448."}