{"as_of":"2026-08-18T18:53:00Z","caps":{"database_statements":6,"inbound":100,"outbound":100},"context_digest":"sha256:b97a3ff5d221d291ecf5b2bdfb4a0b9fc9002f83dd4a05ca54ad2b3a48cf952e","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":"2026-08-16T00:36:02.508314Z","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":"2026-05-23T17:15:43.712708Z","state":"measured"}],"external_citation_measurements":[],"inbound":[{"citation":{"cited_paper":{"arxiv_id":"2308.07061","last_updated":"2024-03-15T02:29:24Z","snapshot_observed_at":"2026-08-16T15:08:41.224808Z","submitted_at":"2023-08-14T10:45:51Z","title":"Machine Unlearning: Solutions and Challenges","version":3},"cited_work":{"arxiv_id":"2308.07061","doi":null,"metadata_source":"arxiv_reference","pith_arxiv_id":"2308.07061","snapshot_observed_at":"2026-06-05T21:23:00.469572Z","title":"Machine unlearning: Solutions and challenges","venue":null,"work_id":"ec602329-8728-4d66-b84b-4b87480658f3","year":null},"citing_paper":{"arxiv_id":"2411.02622","last_updated":"2026-04-09T02:59:33Z","snapshot_observed_at":"2026-08-12T20:48:44.727919Z","submitted_at":"2024-11-04T21:27:06Z","title":"AdaProb: Efficient Machine Unlearning via Adaptive Probability","version":3},"reference_index":15,"source":"pdf_text","source_observed_at":"2026-05-23T17:13:32.169844Z"},"links":{"cited_paper":"/paper/2308.07061","citing_paper":"/paper/2411.02622"},"observation_digest":"sha256:02fe453eae274b9a20e20b06afcaccd69192d92bfd57552516ed8df734049401","observation_id":"3ebad8de-23f1-4d9c-94e3-2e63a3611d04","resolution":{"observed_at":"2026-05-23T17:15:43.716296Z","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"}},{"citation":{"cited_paper":{"arxiv_id":"2308.07061","last_updated":"2024-03-15T02:29:24Z","snapshot_observed_at":"2026-08-16T15:08:41.224808Z","submitted_at":"2023-08-14T10:45:51Z","title":"Machine Unlearning: Solutions and Challenges","version":3},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2308.07061","snapshot_observed_at":"2026-08-06T17:26:34.714945Z","title":null,"venue":null,"work_id":null,"year":2023},"citing_paper":{"arxiv_id":"2507.10886","last_updated":"2025-07-15T00:59:42Z","snapshot_observed_at":"2026-08-13T08:19:04.234165Z","submitted_at":"2025-07-15T00:59:42Z","title":"How to Protect Models against Adversarial Unlearning?","version":1},"reference_index":41,"source":"pdf_text","source_observed_at":"2026-08-06T17:26:34.714945Z"},"links":{"cited_paper":"/paper/2308.07061","citing_paper":"/paper/2507.10886"},"observation_digest":"sha256:33cd5049c845518725995462340c62a3f844dfdf6ed4b7bd2d1b05d5bdf92502","observation_id":"dffef6ff-b69e-4309-8da1-e4801f056805","resolution":{"observed_at":"2026-08-06T17:26:34.714945Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2308.07061","last_updated":"2024-03-15T02:29:24Z","snapshot_observed_at":"2026-08-16T15:08:41.224808Z","submitted_at":"2023-08-14T10:45:51Z","title":"Machine Unlearning: Solutions and Challenges","version":3},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2308.07061","snapshot_observed_at":"2026-08-16T00:36:02.508314Z","title":"arXiv preprint arXiv:2308.07061 , year=","venue":null,"work_id":null,"year":null},"citing_paper":{"arxiv_id":"2608.11749","last_updated":"2026-08-12T07:41:31Z","snapshot_observed_at":"2026-08-17T20:12:58.618941Z","submitted_at":"2026-08-12T07:41:31Z","title":"MOON: Multi-Objective OrthoNormalized Updates for Multitask Learning","version":1},"reference_index":168,"source":"arxiv_source","source_observed_at":"2026-08-16T00:36:02.508314Z"},"links":{"cited_paper":"/paper/2308.07061","citing_paper":"/paper/2608.11749"},"observation_digest":"sha256:fc1411b3edc0b957d1f4e603f850b980d588d67d796ca2b407a85c0f603daacb","observation_id":"a0a20fd5-41d0-499f-b555-a86e04bf5d01","resolution":{"observed_at":"2026-08-16T00:36:02.508314Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}}],"links":{"evidence":"/evidence","html":"/paper/2308.07061/citation-record","integrity":"/paper/2308.07061/integrity","json":"/paper/2308.07061/citation-record.json","paper":"/paper/2308.07061"},"outbound":[],"paper":{"arxiv_id":"2308.07061","last_updated":"2024-03-15T02:29:24Z","latest_version":3,"primary_category":"cs.LG","snapshot_observed_at":"2026-08-16T15:08:41.224808Z","submitted_at":"2023-08-14T10:45:51Z","title":"Machine Unlearning: Solutions and Challenges"},"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:2308.07061."}