{"as_of":"2026-08-18T05:09:00Z","caps":{"database_statements":6,"inbound":100,"outbound":100},"context_digest":"sha256:2c2146cc5831734946d8c87270d2213883fbcea1a8da86f745d3a0ec05a5be9e","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":"2026-08-17T06:30:58.91139+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":"2026-08-16T12:21:36.111755Z","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":"2026-07-03T00:07:28.381806Z","state":"measured"}],"external_citation_measurements":[],"inbound":[{"citation":{"cited_paper":{"arxiv_id":"2407.00866","last_updated":"2024-07-05T18:01:16Z","snapshot_observed_at":"2026-08-17T20:49:14.392934Z","submitted_at":"2024-07-01T00:20:26Z","title":"Silver Linings in the Shadows: Harnessing Membership Inference for Machine Unlearning","version":2},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2407.00866","snapshot_observed_at":"2026-08-10T21:24:10.626202Z","title":"Silver linings in the shadows: Harnessing membership inference for machine unlearning","venue":null,"work_id":null,"year":2024},"citing_paper":{"arxiv_id":"2501.04952","last_updated":"2025-01-09T03:59:10Z","snapshot_observed_at":"2026-08-15T06:27:30.398438Z","submitted_at":"2025-01-09T03:59:10Z","title":"Open Problems in Machine Unlearning for AI Safety","version":1},"reference_index":122,"source":"arxiv_source","source_observed_at":"2026-08-10T21:24:10.626202Z"},"links":{"cited_paper":"/paper/2407.00866","citing_paper":"/paper/2501.04952"},"observation_digest":"sha256:bae5abb3f771abe76eb52a943c794ba92455d4d0bb84d6453f44fc0868f1c3ff","observation_id":"1447dc08-fbb6-4beb-9e8f-2f83715f2a01","resolution":{"observed_at":"2026-08-10T21:24:10.626202Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2407.00866","last_updated":"2024-07-05T18:01:16Z","snapshot_observed_at":"2026-08-17T20:49:14.392934Z","submitted_at":"2024-07-01T00:20:26Z","title":"Silver Linings in the Shadows: Harnessing Membership Inference for Machine Unlearning","version":2},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2407.00866","snapshot_observed_at":"2026-08-16T12:21:36.111755Z","title":null,"venue":null,"work_id":null,"year":2024},"citing_paper":{"arxiv_id":"2504.12996","last_updated":"2025-04-17T15:05:40Z","snapshot_observed_at":"2026-08-16T16:00:10.394461Z","submitted_at":"2025-04-17T15:05:40Z","title":"SHA256 at SemEval-2025 Task 4: Selective Amnesia -- Constrained Unlearning for Large Language Models via Knowledge Isolation","version":1},"reference_index":25,"source":"arxiv_source","source_observed_at":"2026-08-16T12:21:36.111755Z"},"links":{"cited_paper":"/paper/2407.00866","citing_paper":"/paper/2504.12996"},"observation_digest":"sha256:384d9d8d4336c841b4a4fc1f83714a70a4750a0e48f88d41631c0f15040f2d4c","observation_id":"93525d00-f2a9-4400-a985-5352522f0c31","resolution":{"observed_at":"2026-08-16T12:21:36.111755Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2407.00866","last_updated":"2024-07-05T18:01:16Z","snapshot_observed_at":"2026-08-17T20:49:14.392934Z","submitted_at":"2024-07-01T00:20:26Z","title":"Silver Linings in the Shadows: Harnessing Membership Inference for Machine Unlearning","version":2},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2407.00866","snapshot_observed_at":"2026-08-07T00:30:35.263745Z","title":null,"venue":null,"work_id":null,"year":2024},"citing_paper":{"arxiv_id":"2506.13972","last_updated":"2025-07-03T17:45:38Z","snapshot_observed_at":"2026-08-16T22:50:40.168604Z","submitted_at":"2025-06-16T20:22:07Z","title":"Membership Inference Attacks as Privacy Tools: Reliability, Disparity and Ensemble","version":2},"reference_index":47,"source":"pdf_text","source_observed_at":"2026-08-07T00:30:35.263745Z"},"links":{"cited_paper":"/paper/2407.00866","citing_paper":"/paper/2506.13972"},"observation_digest":"sha256:c0eb0fb18e1765b805c9c798451968a1c5dc9b0946a4ee4ba0eabf128a6acb34","observation_id":"84c8d8cb-a656-4a29-8177-064814869248","resolution":{"observed_at":"2026-08-07T00:30:35.263745Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2407.00866","last_updated":"2024-07-05T18:01:16Z","snapshot_observed_at":"2026-08-17T20:49:14.392934Z","submitted_at":"2024-07-01T00:20:26Z","title":"Silver Linings in the Shadows: Harnessing Membership Inference for Machine Unlearning","version":2},"cited_work":{"arxiv_id":"2407.00866","doi":null,"metadata_source":"arxiv_reference","pith_arxiv_id":"2407.00866","snapshot_observed_at":"2026-07-03T00:07:28.381806Z","title":null,"venue":null,"work_id":"3004c530-1bc5-40a7-bf98-6f099b3324b0","year":2024},"citing_paper":{"arxiv_id":"2606.09559","last_updated":"2026-06-08T14:33:40Z","snapshot_observed_at":"2026-08-13T21:51:16.078818Z","submitted_at":"2026-06-08T14:33:40Z","title":"Safe-RULE: Safe Reinforcement UnLEarning","version":1},"reference_index":19,"source":"pdf_text","source_observed_at":"2026-06-27T17:28:09.686163Z"},"links":{"cited_paper":"/paper/2407.00866","citing_paper":"/paper/2606.09559"},"observation_digest":"sha256:19220da8cda27b6dbd26b803d32916f18ebf3ca7d4ad4c843371aa322f626a3b","observation_id":"e078956d-d57d-4a9f-83e1-ff9ebe834dc5","resolution":{"observed_at":"2026-07-03T00:07:28.383157Z","resolver_source":"arxiv_id","status":"verified_exact"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-17T06:30:58.91139+00:00","source":"crossref"},{"observed_at":"2026-08-17T06:30:54.323127+00:00","source":"retraction_watch"}],"state":"measured"}}],"links":{"evidence":"/evidence","html":"/paper/2407.00866/citation-record","integrity":"/paper/2407.00866/integrity","json":"/paper/2407.00866/citation-record.json","paper":"/paper/2407.00866"},"outbound":[],"paper":{"arxiv_id":"2407.00866","last_updated":"2024-07-05T18:01:16Z","latest_version":2,"primary_category":"cs.LG","snapshot_observed_at":"2026-08-17T20:49:14.392934Z","submitted_at":"2024-07-01T00:20:26Z","title":"Silver Linings in the Shadows: Harnessing Membership Inference for Machine 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":"2026-08-17T06:30:58.91139+00:00","source":"crossref"},{"observed_at":"2026-08-17T06:30:54.323127+00:00","source":"retraction_watch"}],"thesis":"As of 18 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 4 inbound Pith citation observations for arXiv:2407.00866."}