{"as_of":"2026-08-08T09:04:00Z","caps":{"database_statements":6,"inbound":100,"outbound":100},"context_digest":"sha256:a22aea414a66883e80f4be4c3bff01a66c0542914b2becc8d9ae414b41d38272","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":18,"lane":"standing_notices","note":"One-hop event checks from named stored sources.","records_observed":18,"source":"scholarly_work_events, retraction_status_cache","source_observed_at":"2026-08-08T06:32:00.761636+00:00","state":"measured"},{"denominator":18,"lane":"inbound_itemization","note":"Pith citing papers itemized under the disclosed page cap.","records_observed":18,"source":"paper_references, paper_reference_links","source_observed_at":"2026-08-07T14:30:25.232341Z","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":"2026-07-01T07:35:28.970458Z","state":"measured"}],"external_citation_measurements":[],"inbound":[{"citation":{"cited_paper":{"arxiv_id":"2201.06640","last_updated":"2023-02-22T12:33:14Z","snapshot_observed_at":"2026-07-06T12:28:07.214555Z","submitted_at":"2022-01-17T21:49:21Z","title":"Towards Adversarial Evaluations for Inexact Machine Unlearning","version":3},"cited_work":{"arxiv_id":"2201.06640","doi":null,"metadata_source":"arxiv_reference","pith_arxiv_id":"2201.06640","snapshot_observed_at":"2026-07-01T07:35:28.970458Z","title":"Towards adversarial evaluations for inexact machine unlearning","venue":null,"work_id":"9bed8423-4ac5-4297-9d61-6f4a4c4bd9e2","year":2022},"citing_paper":{"arxiv_id":"2310.12508","last_updated":"2024-04-04T07:45:38Z","snapshot_observed_at":"2026-08-03T17:30:25.153454Z","submitted_at":"2023-10-19T06:17:17Z","title":"SalUn: Empowering Machine Unlearning via Gradient-based Weight Saliency in Both Image Classification and Generation","version":5},"reference_index":114,"source":"arxiv_source","source_observed_at":"2026-05-16T17:56:23.281678Z"},"links":{"cited_paper":"/paper/2201.06640","citing_paper":"/paper/2310.12508"},"observation_digest":"sha256:9a09d1b2be2aa59d3d9bf127d707e1b99e55fdc3887dd0427948d46bd1e11344","observation_id":"5c9a2b8b-06a5-4119-bcd4-e9b1cd691fed","resolution":{"observed_at":"2026-05-16T17:56:23.437217Z","resolver_source":"arxiv_id","status":"metadata_mismatch"},"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":"2201.06640","last_updated":"2023-02-22T12:33:14Z","snapshot_observed_at":"2026-07-06T12:28:07.214555Z","submitted_at":"2022-01-17T21:49:21Z","title":"Towards Adversarial Evaluations for Inexact Machine Unlearning","version":3},"cited_work":{"arxiv_id":"2201.06640","doi":null,"metadata_source":"arxiv_reference","pith_arxiv_id":"2201.06640","snapshot_observed_at":"2026-07-01T07:35:28.970458Z","title":"Towards adversarial evaluations for inexact machine unlearning","venue":null,"work_id":"9bed8423-4ac5-4297-9d61-6f4a4c4bd9e2","year":2022},"citing_paper":{"arxiv_id":"2401.06121","last_updated":"2024-01-11T18:57:12Z","snapshot_observed_at":"2026-07-06T02:11:23.670680Z","submitted_at":"2024-01-11T18:57:12Z","title":"TOFU: A Task of Fictitious Unlearning for LLMs","version":1},"reference_index":8,"source":"arxiv_source","source_observed_at":"2026-05-16T11:07:39.215164Z"},"links":{"cited_paper":"/paper/2201.06640","citing_paper":"/paper/2401.06121"},"observation_digest":"sha256:678e46ce4315c3c621e80e42bceb8831c34ef197dbb452809961c03bf4eba88c","observation_id":"49f5169c-34d7-4002-a7b1-e77d0d16bb49","resolution":{"observed_at":"2026-05-16T11:07:39.262545Z","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":"2201.06640","last_updated":"2023-02-22T12:33:14Z","snapshot_observed_at":"2026-07-06T12:28:07.214555Z","submitted_at":"2022-01-17T21:49:21Z","title":"Towards Adversarial Evaluations for Inexact Machine Unlearning","version":3},"cited_work":{"arxiv_id":"2201.06640","doi":null,"metadata_source":"arxiv_reference","pith_arxiv_id":"2201.06640","snapshot_observed_at":"2026-07-01T07:35:28.970458Z","title":"Towards adversarial evaluations for inexact machine unlearning","venue":null,"work_id":"9bed8423-4ac5-4297-9d61-6f4a4c4bd9e2","year":2022},"citing_paper":{"arxiv_id":"2411.02622","last_updated":"2026-04-09T02:59:33Z","snapshot_observed_at":"2026-07-06T19:45:13.078526Z","submitted_at":"2024-11-04T21:27:06Z","title":"AdaProb: Efficient Machine Unlearning via Adaptive Probability","version":3},"reference_index":5,"source":"pdf_text","source_observed_at":"2026-05-23T17:13:32.169844Z"},"links":{"cited_paper":"/paper/2201.06640","citing_paper":"/paper/2411.02622"},"observation_digest":"sha256:953b1ac88f48b75785704fd2c11a91cdae00f2d10b41ea744f247397edf91677","observation_id":"4cb4eae9-c913-41a2-b0dd-41f591e89fa5","resolution":{"observed_at":"2026-05-23T17:15:43.710629Z","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":"2201.06640","last_updated":"2023-02-22T12:33:14Z","snapshot_observed_at":"2026-07-06T12:28:07.214555Z","submitted_at":"2022-01-17T21:49:21Z","title":"Towards Adversarial Evaluations for Inexact Machine Unlearning","version":3},"cited_work":{"arxiv_id":"2201.06640","doi":null,"metadata_source":"arxiv_reference","pith_arxiv_id":"2201.06640","snapshot_observed_at":"2026-07-01T07:35:28.970458Z","title":"Towards adversarial evaluations for inexact machine unlearning","venue":null,"work_id":"9bed8423-4ac5-4297-9d61-6f4a4c4bd9e2","year":2022},"citing_paper":{"arxiv_id":"2503.08633","last_updated":"2026-05-19T13:33:29Z","snapshot_observed_at":"2026-07-06T20:50:51.469809Z","submitted_at":"2025-03-11T17:21:26Z","title":"How Does Overparameterization Affect Machine Unlearning of Deep Neural Networks?","version":2},"reference_index":5,"source":"pdf_text","source_observed_at":"2026-05-23T00:02:33.008566Z"},"links":{"cited_paper":"/paper/2201.06640","citing_paper":"/paper/2503.08633"},"observation_digest":"sha256:ff299fa0982721f3c72b553d29acf99d2fbe2566ee42babb70e5b91515855a8c","observation_id":"fea1e2c4-2743-483b-8006-1ebfc6448a25","resolution":{"observed_at":"2026-05-23T00:05:13.557864Z","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":"2201.06640","last_updated":"2023-02-22T12:33:14Z","snapshot_observed_at":"2026-07-06T12:28:07.214555Z","submitted_at":"2022-01-17T21:49:21Z","title":"Towards Adversarial Evaluations for Inexact Machine Unlearning","version":3},"cited_work":{"arxiv_id":"2201.06640","doi":null,"metadata_source":"arxiv_reference","pith_arxiv_id":"2201.06640","snapshot_observed_at":"2026-07-01T07:35:28.970458Z","title":"Towards adversarial evaluations for inexact machine unlearning","venue":null,"work_id":"9bed8423-4ac5-4297-9d61-6f4a4c4bd9e2","year":2022},"citing_paper":{"arxiv_id":"2505.10859","last_updated":"2026-05-12T16:17:21Z","snapshot_observed_at":"2026-07-06T21:24:49.058355Z","submitted_at":"2025-05-16T04:56:47Z","title":"Exploring Nonlinear Pathway in Parameter Space for Machine Unlearning","version":2},"reference_index":10,"source":"pdf_text","source_observed_at":"2026-05-22T15:27:28.694532Z"},"links":{"cited_paper":"/paper/2201.06640","citing_paper":"/paper/2505.10859"},"observation_digest":"sha256:af657d6dc37180ced7c32d9064ed5bd242a63607f148017ff2fba69b38302d56","observation_id":"54145ae9-bfb9-444a-af65-73281999a64e","resolution":{"observed_at":"2026-05-22T15:31:44.868200Z","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":"2201.06640","last_updated":"2023-02-22T12:33:14Z","snapshot_observed_at":"2026-07-06T12:28:07.214555Z","submitted_at":"2022-01-17T21:49:21Z","title":"Towards Adversarial Evaluations for Inexact Machine Unlearning","version":3},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2201.06640","snapshot_observed_at":"2026-08-07T14:30:25.232341Z","title":"Evaluating inexact unlearning requires revisiting forgetting.CoRR, abs/2201.06640, 2022","venue":null,"work_id":null,"year":2022},"citing_paper":{"arxiv_id":"2505.18783","last_updated":"2025-05-24T16:40:14Z","snapshot_observed_at":"2026-08-07T14:23:22.496606Z","submitted_at":"2025-05-24T16:40:14Z","title":"Soft Weighted Machine Unlearning","version":1},"reference_index":14,"source":"pdf_text","source_observed_at":"2026-08-07T14:30:25.232341Z"},"links":{"cited_paper":"/paper/2201.06640","citing_paper":"/paper/2505.18783"},"observation_digest":"sha256:e1fad1cee993631707d059391522ba69c0a242fe16f2ab1947795feb01204635","observation_id":"6160eea2-6c05-42c2-aa63-94f1e15b068d","resolution":{"observed_at":"2026-08-07T14:30:25.232341Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2201.06640","last_updated":"2023-02-22T12:33:14Z","snapshot_observed_at":"2026-07-06T12:28:07.214555Z","submitted_at":"2022-01-17T21:49:21Z","title":"Towards Adversarial Evaluations for Inexact Machine Unlearning","version":3},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2201.06640","snapshot_observed_at":"2026-08-07T14:29:49.062968Z","title":"Towards adversarial evaluations for inex- act machine unlearning","venue":null,"work_id":null,"year":null},"citing_paper":{"arxiv_id":"2505.18786","last_updated":"2025-05-24T16:55:57Z","snapshot_observed_at":"2026-08-07T14:23:20.871121Z","submitted_at":"2025-05-24T16:55:57Z","title":"Leveraging Per-Instance Privacy for Machine Unlearning","version":1},"reference_index":2019,"source":"pdf_text","source_observed_at":"2026-08-07T14:29:49.062968Z"},"links":{"cited_paper":"/paper/2201.06640","citing_paper":"/paper/2505.18786"},"observation_digest":"sha256:9504c6025da1d007dae4ae1d41fe588f434f804807c2068eba52ca3f8562bd5d","observation_id":"07fad513-a354-45bb-b525-dc59e1b8ce1c","resolution":{"observed_at":"2026-08-07T14:29:49.062968Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2201.06640","last_updated":"2023-02-22T12:33:14Z","snapshot_observed_at":"2026-07-06T12:28:07.214555Z","submitted_at":"2022-01-17T21:49:21Z","title":"Towards Adversarial Evaluations for Inexact Machine Unlearning","version":3},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2201.06640","snapshot_observed_at":"2026-08-07T06:14:43.532788Z","title":"Towards adversarial evaluations for inexact machine unlearning, 2023","venue":null,"work_id":null,"year":2023},"citing_paper":{"arxiv_id":"2506.06073","last_updated":"2025-06-06T13:30:40Z","snapshot_observed_at":"2026-08-07T05:58:30.695869Z","submitted_at":"2025-06-06T13:30:40Z","title":"System-Aware Unlearning Algorithms: Use Lesser, Forget Faster","version":1},"reference_index":32,"source":"arxiv_source","source_observed_at":"2026-08-07T06:14:43.532788Z"},"links":{"cited_paper":"/paper/2201.06640","citing_paper":"/paper/2506.06073"},"observation_digest":"sha256:70f2d29c4699848eac7cc39ae1d2f5eb3281b6436bc06ce592af0a57c3123db0","observation_id":"537c2138-d20e-4cda-bc81-9cb4ad84a4fb","resolution":{"observed_at":"2026-08-07T06:14:43.532788Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2201.06640","last_updated":"2023-02-22T12:33:14Z","snapshot_observed_at":"2026-07-06T12:28:07.214555Z","submitted_at":"2022-01-17T21:49:21Z","title":"Towards Adversarial Evaluations for Inexact Machine Unlearning","version":3},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2201.06640","snapshot_observed_at":"2026-08-07T00:53:48.044883Z","title":"Towards adversarial evaluations for inexact machine unlearning","venue":null,"work_id":null,"year":2022},"citing_paper":{"arxiv_id":"2506.13048","last_updated":"2025-06-16T02:31:41Z","snapshot_observed_at":"2026-08-08T00:45:51.797303Z","submitted_at":"2025-06-16T02:31:41Z","title":"The Space Complexity of Learning-Unlearning Algorithms","version":1},"reference_index":43,"source":"arxiv_source","source_observed_at":"2026-08-07T00:53:48.044883Z"},"links":{"cited_paper":"/paper/2201.06640","citing_paper":"/paper/2506.13048"},"observation_digest":"sha256:72b9c6acf28c15909617a995a3b91dfc26e7b1f3915c1ee3f6a38dd602c07fa7","observation_id":"eb2a5d9c-bf22-4beb-a556-ab72719c5d11","resolution":{"observed_at":"2026-08-07T00:53:48.044883Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2201.06640","last_updated":"2023-02-22T12:33:14Z","snapshot_observed_at":"2026-07-06T12:28:07.214555Z","submitted_at":"2022-01-17T21:49:21Z","title":"Towards Adversarial Evaluations for Inexact Machine Unlearning","version":3},"cited_work":{"arxiv_id":"2201.06640","doi":null,"metadata_source":"arxiv_reference","pith_arxiv_id":"2201.06640","snapshot_observed_at":"2026-07-01T07:35:28.970458Z","title":"Towards adversarial evaluations for inexact machine unlearning","venue":null,"work_id":"9bed8423-4ac5-4297-9d61-6f4a4c4bd9e2","year":2022},"citing_paper":{"arxiv_id":"2506.15115","last_updated":"2026-04-07T04:34:06Z","snapshot_observed_at":"2026-07-06T21:43:59.163336Z","submitted_at":"2025-06-18T03:33:59Z","title":"Towards Reliable Forgetting: A Survey on Machine Unlearning Verification","version":3},"reference_index":36,"source":"pdf_text","source_observed_at":"2026-05-19T09:35:00.520860Z"},"links":{"cited_paper":"/paper/2201.06640","citing_paper":"/paper/2506.15115"},"observation_digest":"sha256:13bd92232fcdc9f60f6e91f06fc83fe2fbfb95e4873f9319855b186988fa7661","observation_id":"0cb97f72-084f-41fc-9793-8d37e779812f","resolution":{"observed_at":"2026-05-19T09:37:14.158372Z","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":"2201.06640","last_updated":"2023-02-22T12:33:14Z","snapshot_observed_at":"2026-07-06T12:28:07.214555Z","submitted_at":"2022-01-17T21:49:21Z","title":"Towards Adversarial Evaluations for Inexact Machine Unlearning","version":3},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2201.06640","snapshot_observed_at":"2026-08-06T21:54:43.704896Z","title":"Evaluating inexact unlearning requires revisiting forgetting.CoRR, abs/2201.06640, 2022","venue":null,"work_id":null,"year":2022},"citing_paper":{"arxiv_id":"2506.23145","last_updated":"2025-06-29T08:53:23Z","snapshot_observed_at":"2026-08-07T22:56:50.813411Z","submitted_at":"2025-06-29T08:53:23Z","title":"Forget-MI: Machine Unlearning for Forgetting Multimodal Information in Healthcare Settings","version":1},"reference_index":11,"source":"pdf_text","source_observed_at":"2026-08-06T21:54:43.704896Z"},"links":{"cited_paper":"/paper/2201.06640","citing_paper":"/paper/2506.23145"},"observation_digest":"sha256:bf2827598a7995f9415ae0c7bd39fd90d7b65dd6332382718ba67f5fcd04c4e5","observation_id":"df6a8472-27ce-451d-9f12-3e37fa7c3372","resolution":{"observed_at":"2026-08-06T21:54:43.704896Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2201.06640","last_updated":"2023-02-22T12:33:14Z","snapshot_observed_at":"2026-07-06T12:28:07.214555Z","submitted_at":"2022-01-17T21:49:21Z","title":"Towards Adversarial Evaluations for Inexact Machine Unlearning","version":3},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2201.06640","snapshot_observed_at":"2026-08-06T05:02:45.753783Z","title":null,"venue":null,"work_id":null,"year":2023},"citing_paper":{"arxiv_id":"2508.02422","last_updated":"2025-08-04T13:43:47Z","snapshot_observed_at":"2026-08-08T05:36:07.413553Z","submitted_at":"2025-08-04T13:43:47Z","title":"Superior resilience to poisoning and amenability to unlearning in quantum machine learning","version":1},"reference_index":64,"source":"pdf_text","source_observed_at":"2026-08-06T05:02:45.753783Z"},"links":{"cited_paper":"/paper/2201.06640","citing_paper":"/paper/2508.02422"},"observation_digest":"sha256:dba2072dbfd742f8148eb691a59904b97d26cbe72cd6882f883ec860d87066a8","observation_id":"05eb4748-003e-46da-8742-d0595e000b57","resolution":{"observed_at":"2026-08-06T05:02:45.753783Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2201.06640","last_updated":"2023-02-22T12:33:14Z","snapshot_observed_at":"2026-07-06T12:28:07.214555Z","submitted_at":"2022-01-17T21:49:21Z","title":"Towards Adversarial Evaluations for Inexact Machine Unlearning","version":3},"cited_work":{"arxiv_id":"2201.06640","doi":null,"metadata_source":"arxiv_reference","pith_arxiv_id":"2201.06640","snapshot_observed_at":"2026-07-01T07:35:28.970458Z","title":"Towards adversarial evaluations for inexact machine unlearning","venue":null,"work_id":"9bed8423-4ac5-4297-9d61-6f4a4c4bd9e2","year":2022},"citing_paper":{"arxiv_id":"2604.07962","last_updated":"2026-04-09T08:24:52Z","snapshot_observed_at":"2026-07-06T22:57:09.435331Z","submitted_at":"2026-04-09T08:24:52Z","title":"Is your algorithm unlearning or untraining?","version":1},"reference_index":11,"source":"pdf_text","source_observed_at":"2026-05-10T18:06:08.962042Z"},"links":{"cited_paper":"/paper/2201.06640","citing_paper":"/paper/2604.07962"},"observation_digest":"sha256:adfd9dea187af8fd0a755f8588ad4e321448742119caa4fd0379956f44cf360c","observation_id":"a0ec3f1f-c00a-4141-bea8-7dfd077ce3e3","resolution":{"observed_at":"2026-05-11T05:30:59.046471Z","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":"2201.06640","last_updated":"2023-02-22T12:33:14Z","snapshot_observed_at":"2026-07-06T12:28:07.214555Z","submitted_at":"2022-01-17T21:49:21Z","title":"Towards Adversarial Evaluations for Inexact Machine Unlearning","version":3},"cited_work":{"arxiv_id":"2201.06640","doi":null,"metadata_source":"arxiv_reference","pith_arxiv_id":"2201.06640","snapshot_observed_at":"2026-07-01T07:35:28.970458Z","title":"Towards adversarial evaluations for inexact machine unlearning","venue":null,"work_id":"9bed8423-4ac5-4297-9d61-6f4a4c4bd9e2","year":2022},"citing_paper":{"arxiv_id":"2604.16536","last_updated":"2026-04-16T21:01:28Z","snapshot_observed_at":"2026-07-16T23:19:34.565929Z","submitted_at":"2026-04-16T21:01:28Z","title":"Towards Reliable Testing of Machine Unlearning","version":1},"reference_index":23,"source":"pdf_text","source_observed_at":"2026-05-10T11:24:29.533446Z"},"links":{"cited_paper":"/paper/2201.06640","citing_paper":"/paper/2604.16536"},"observation_digest":"sha256:55aa2ef3b461312825fbf663e97c8e14a02bc3582605228af677484d2733d675","observation_id":"47c199c9-b379-4786-918b-f336d1b4a93d","resolution":{"observed_at":"2026-05-10T11:25:18.313289Z","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":"2201.06640","last_updated":"2023-02-22T12:33:14Z","snapshot_observed_at":"2026-07-06T12:28:07.214555Z","submitted_at":"2022-01-17T21:49:21Z","title":"Towards Adversarial Evaluations for Inexact Machine Unlearning","version":3},"cited_work":{"arxiv_id":"2201.06640","doi":null,"metadata_source":"arxiv_reference","pith_arxiv_id":"2201.06640","snapshot_observed_at":"2026-07-01T07:35:28.970458Z","title":"Towards adversarial evaluations for inexact machine unlearning","venue":null,"work_id":"9bed8423-4ac5-4297-9d61-6f4a4c4bd9e2","year":2022},"citing_paper":{"arxiv_id":"2605.01129","last_updated":"2026-05-30T02:25:28Z","snapshot_observed_at":"2026-07-06T23:14:24.758147Z","submitted_at":"2026-05-01T21:57:09Z","title":"Revisiting Privacy Leakage in Machine Unlearning: Membership Inference Beyond the Forgotten Set","version":1},"reference_index":37,"source":"pdf_text","source_observed_at":"2026-05-09T18:36:21.189195Z"},"links":{"cited_paper":"/paper/2201.06640","citing_paper":"/paper/2605.01129"},"observation_digest":"sha256:0bbc63ab80ab563f5a134fb7acdee43a00a7850e28fff358235758445247a37a","observation_id":"e7b602cc-a05d-45e9-b53e-1e2a61da754d","resolution":{"observed_at":"2026-05-11T16:11:08.534678Z","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":"2201.06640","last_updated":"2023-02-22T12:33:14Z","snapshot_observed_at":"2026-07-06T12:28:07.214555Z","submitted_at":"2022-01-17T21:49:21Z","title":"Towards Adversarial Evaluations for Inexact Machine Unlearning","version":3},"cited_work":{"arxiv_id":"2201.06640","doi":null,"metadata_source":"arxiv_reference","pith_arxiv_id":"2201.06640","snapshot_observed_at":"2026-07-01T07:35:28.970458Z","title":"Towards adversarial evaluations for inexact machine unlearning","venue":null,"work_id":"9bed8423-4ac5-4297-9d61-6f4a4c4bd9e2","year":2022},"citing_paper":{"arxiv_id":"2605.01129","last_updated":"2026-05-30T02:25:28Z","snapshot_observed_at":"2026-07-06T23:14:24.758147Z","submitted_at":"2026-05-01T21:57:09Z","title":"Revisiting Privacy Leakage in Machine Unlearning: Membership Inference Beyond the Forgotten Set","version":2},"reference_index":37,"source":"pdf_text","source_observed_at":"2026-07-01T07:30:02.278335Z"},"links":{"cited_paper":"/paper/2201.06640","citing_paper":"/paper/2605.01129"},"observation_digest":"sha256:7f9540ab2ebb35749b46074a6fea9992cc7976ace1834ccc2e76afd970bf3154","observation_id":"4a99335e-ff20-4d78-a391-19e5ffb3c0a2","resolution":{"observed_at":"2026-07-01T07:35:28.971899Z","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":"2201.06640","last_updated":"2023-02-22T12:33:14Z","snapshot_observed_at":"2026-07-06T12:28:07.214555Z","submitted_at":"2022-01-17T21:49:21Z","title":"Towards Adversarial Evaluations for Inexact Machine Unlearning","version":3},"cited_work":{"arxiv_id":"2201.06640","doi":null,"metadata_source":"arxiv_reference","pith_arxiv_id":"2201.06640","snapshot_observed_at":"2026-07-01T07:35:28.970458Z","title":"Towards adversarial evaluations for inexact machine unlearning","venue":null,"work_id":"9bed8423-4ac5-4297-9d61-6f4a4c4bd9e2","year":2022},"citing_paper":{"arxiv_id":"2605.10680","last_updated":"2026-05-11T14:57:31Z","snapshot_observed_at":"2026-07-06T23:22:37.355450Z","submitted_at":"2026-05-11T14:57:31Z","title":"Exact Unlearning from Proxies Induces Closeness Guarantees on Approximate Unlearning","version":1},"reference_index":71,"source":"arxiv_source","source_observed_at":"2026-05-12T03:33:03.867735Z"},"links":{"cited_paper":"/paper/2201.06640","citing_paper":"/paper/2605.10680"},"observation_digest":"sha256:be35e4ee56a661a5b7e4abbfb45d46b4915669eaa6bdbbe41b83938be825693a","observation_id":"0b4e17ed-941f-4650-a9cc-70527b9c8554","resolution":{"observed_at":"2026-05-12T07:16:29.645163Z","resolver_source":"arxiv_id","status":"metadata_mismatch"},"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":"2201.06640","last_updated":"2023-02-22T12:33:14Z","snapshot_observed_at":"2026-07-06T12:28:07.214555Z","submitted_at":"2022-01-17T21:49:21Z","title":"Towards Adversarial Evaluations for Inexact Machine Unlearning","version":3},"cited_work":{"arxiv_id":"2201.06640","doi":null,"metadata_source":"arxiv_reference","pith_arxiv_id":"2201.06640","snapshot_observed_at":"2026-07-01T07:35:28.970458Z","title":"Towards adversarial evaluations for inexact machine unlearning","venue":null,"work_id":"9bed8423-4ac5-4297-9d61-6f4a4c4bd9e2","year":2022},"citing_paper":{"arxiv_id":"2605.27569","last_updated":"2026-05-31T21:06:35Z","snapshot_observed_at":"2026-07-29T14:17:44.011772Z","submitted_at":"2026-05-26T18:41:48Z","title":"RULER: Representation-Level Verification of Machine Unlearning","version":2},"reference_index":4,"source":"pdf_text","source_observed_at":"2026-06-29T17:24:14.599565Z"},"links":{"cited_paper":"/paper/2201.06640","citing_paper":"/paper/2605.27569"},"observation_digest":"sha256:ec900f4504c5050ea8656bd8b53b83e195cc8d989129ee0eea19455b626702f9","observation_id":"7c2866bd-ada0-4489-b514-6aabba126149","resolution":{"observed_at":"2026-06-29T17:33:45.596286Z","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"}}],"links":{"evidence":"/evidence","html":"/paper/2201.06640/citation-record","integrity":"/paper/2201.06640/integrity","json":"/paper/2201.06640/citation-record.json","paper":"/paper/2201.06640"},"outbound":[],"paper":{"arxiv_id":"2201.06640","last_updated":"2023-02-22T12:33:14Z","latest_version":3,"primary_category":"cs.LG","snapshot_observed_at":"2026-07-06T12:28:07.214555Z","submitted_at":"2022-01-17T21:49:21Z","title":"Towards Adversarial Evaluations for Inexact 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":"2026-08-08T06:32:00.761636+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 18 inbound Pith citation observations for arXiv:2201.06640."}