{"as_of":"2026-08-15T21:17:00Z","caps":{"database_statements":6,"inbound":100,"outbound":100},"context_digest":"sha256:437d3b8a136736315327dce1e19e79b1f16b008a10ba56dfbdbc7d7dba09ef0c","coverage":[{"denominator":53,"lane":"reference_resolution","note":"Typed states for the displayed outbound observations.","records_observed":53,"source":"paper_references, paper_reference_links","source_observed_at":"2026-08-06T10:58:06.107943Z","state":"measured"},{"denominator":54,"lane":"standing_notices","note":"One-hop event checks from named stored sources.","records_observed":54,"source":"scholarly_work_events, retraction_status_cache","source_observed_at":"2026-08-15T06:32:42.880941+00:00","state":"measured"},{"denominator":1,"lane":"inbound_itemization","note":"Pith citing papers itemized under the disclosed page cap.","records_observed":1,"source":"paper_references, paper_reference_links","source_observed_at":"2026-08-04T11:23:10.478201Z","state":"measured"},{"denominator":1,"lane":"external_citation_measurements","note":"A source-named dated measurement, never combined with another source.","records_observed":0,"source":"cited_works","source_observed_at":null,"state":"measured"}],"external_citation_measurements":[],"inbound":[{"citation":{"cited_paper":{"arxiv_id":"2507.23291","last_updated":"2025-08-03T23:23:03Z","snapshot_observed_at":"2026-08-15T20:46:11.551277Z","submitted_at":"2025-07-31T07:09:52Z","title":"Evaluating the Dynamics of Membership Privacy in Deep Learning","version":2},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2507.23291","snapshot_observed_at":"2026-08-04T11:23:10.478201Z","title":"Evaluating the dynamics of membership privacy in deep learning","venue":null,"work_id":null,"year":2025},"citing_paper":{"arxiv_id":"2510.05699","last_updated":"2026-05-25T05:56:04Z","snapshot_observed_at":"2026-08-09T08:50:47.672362Z","submitted_at":"2025-10-07T09:05:40Z","title":"Membership Inference Attacks on Tokenizers of Large Language Models","version":4},"reference_index":14,"source":"pdf_text","source_observed_at":"2026-08-04T11:23:10.478201Z"},"links":{"cited_paper":"/paper/2507.23291","citing_paper":"/paper/2510.05699"},"observation_digest":"sha256:56515ae62a818542a1f6ad35b5b644b728416dc5ac6a44c856846b2f3f4ab13b","observation_id":"ec55dba2-a01f-4865-bf65-1683e959af23","resolution":{"observed_at":"2026-08-04T11:23:10.478201Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}}],"links":{"evidence":"/evidence","html":"/paper/2507.23291/citation-record","integrity":"/paper/2507.23291/integrity","json":"/paper/2507.23291/citation-record.json","paper":"/paper/2507.23291"},"outbound":[{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-06T10:58:06.863291Z","title":null,"venue":null,"work_id":"655fbbbd-4c96-4c56-b4ff-d88bd0a23313","year":2019},"citing_paper":{"arxiv_id":"2507.23291","last_updated":"2025-08-03T23:23:03Z","snapshot_observed_at":"2026-08-15T20:46:11.551277Z","submitted_at":"2025-07-31T07:09:52Z","title":"Evaluating the Dynamics of Membership Privacy in Deep Learning","version":2},"reference_index":1,"source":"arxiv_source","source_observed_at":"2026-08-06T10:58:05.870657Z"},"links":{"citing_paper":"/paper/2507.23291"},"observation_digest":"sha256:709cb60e916e7c4999558bfa2eda4742f1273b597f33d1e9e64dcd43c3131585","observation_id":"923392b3-fa7c-453e-b322-b27889bb53c9","resolution":{"observed_at":"2026-08-06T10:58:06.867874Z","resolver_source":"raw_fallback","status":"unresolved"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-15T06:32:42.880941+00:00","source":"crossref"},{"observed_at":"2026-08-15T06:32:39.529945+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"1912.03817","last_updated":"2020-12-15T05:39:28Z","snapshot_observed_at":"2026-08-10T23:56:48.730910Z","submitted_at":"2019-12-09T02:16:53Z","title":"Machine Unlearning","version":3},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"1912.03817","snapshot_observed_at":"2026-08-06T10:58:05.875438Z","title":"A.; Jia, H.; Travers, A.; Zhang, B.; Lie, D.; and Papernot, N","venue":null,"work_id":null,"year":2020},"citing_paper":{"arxiv_id":"2507.23291","last_updated":"2025-08-03T23:23:03Z","snapshot_observed_at":"2026-08-15T20:46:11.551277Z","submitted_at":"2025-07-31T07:09:52Z","title":"Evaluating the Dynamics of Membership Privacy in Deep Learning","version":2},"reference_index":2,"source":"arxiv_source","source_observed_at":"2026-08-06T10:58:05.875438Z"},"links":{"cited_paper":"/paper/1912.03817","citing_paper":"/paper/2507.23291"},"observation_digest":"sha256:b30c1b7e8cb9245cde155ffa37833ca6e21c1b11ed5fdb23e80dd7697727add9","observation_id":"4545da31-bbf2-4054-b581-0bf7c3ee89b8","resolution":{"observed_at":"2026-08-06T10:58:05.875438Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-06T10:58:06.848123Z","title":null,"venue":null,"work_id":"3ff9c6cf-01f6-4b93-a20f-d14120260980","year":2022},"citing_paper":{"arxiv_id":"2507.23291","last_updated":"2025-08-03T23:23:03Z","snapshot_observed_at":"2026-08-15T20:46:11.551277Z","submitted_at":"2025-07-31T07:09:52Z","title":"Evaluating the Dynamics of Membership Privacy in Deep Learning","version":2},"reference_index":3,"source":"arxiv_source","source_observed_at":"2026-08-06T10:58:05.880468Z"},"links":{"citing_paper":"/paper/2507.23291"},"observation_digest":"sha256:22dade4d5fa1ca3426270edf7e5dfa44038e71c8a8846209233f31dc49a4ddd1","observation_id":"69b6bcc6-4c7c-477f-ab16-f2dd075c0d04","resolution":{"observed_at":"2026-08-06T10:58:06.852631Z","resolver_source":"raw_fallback","status":"unresolved"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-15T06:32:42.880941+00:00","source":"crossref"},{"observed_at":"2026-08-15T06:32:39.529945+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":null,"snapshot_observed_at":"2026-08-06T10:58:05.885478Z","title":null,"venue":null,"work_id":null,"year":2021},"citing_paper":{"arxiv_id":"2507.23291","last_updated":"2025-08-03T23:23:03Z","snapshot_observed_at":"2026-08-15T20:46:11.551277Z","submitted_at":"2025-07-31T07:09:52Z","title":"Evaluating the Dynamics of Membership Privacy in Deep Learning","version":2},"reference_index":4,"source":"arxiv_source","source_observed_at":"2026-08-06T10:58:05.885478Z"},"links":{"citing_paper":"/paper/2507.23291"},"observation_digest":"sha256:4d9f7ea17d8de527b46a88d9eb78227b54b8b761311c79b0ca230f3db95035f1","observation_id":"9b28eba7-c13a-4bee-9d4f-f2ec909bf8a1","resolution":{"observed_at":"2026-08-06T10:58:05.885478Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-06T10:58:06.824100Z","title":null,"venue":null,"work_id":"72b09ecc-3590-4610-9040-f31aef7f3531","year":2021},"citing_paper":{"arxiv_id":"2507.23291","last_updated":"2025-08-03T23:23:03Z","snapshot_observed_at":"2026-08-15T20:46:11.551277Z","submitted_at":"2025-07-31T07:09:52Z","title":"Evaluating the Dynamics of Membership Privacy in Deep Learning","version":2},"reference_index":5,"source":"arxiv_source","source_observed_at":"2026-08-06T10:58:05.890158Z"},"links":{"citing_paper":"/paper/2507.23291"},"observation_digest":"sha256:948cd0843f53a3addf47d138b02ee436258ae24a017583d7435c8a2f4b846e27","observation_id":"8c9aec1a-fef6-434c-9e4c-17f00d607e53","resolution":{"observed_at":"2026-08-06T10:58:06.828480Z","resolver_source":"raw_fallback","status":"unresolved"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-15T06:32:42.880941+00:00","source":"crossref"},{"observed_at":"2026-08-15T06:32:39.529945+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"2411.16763","last_updated":"2024-11-24T20:56:18Z","snapshot_observed_at":"2026-08-13T14:34:04.216836Z","submitted_at":"2024-11-24T20:56:18Z","title":"Hide in Plain Sight: Clean-Label Backdoor for Auditing Membership Inference","version":1},"cited_work":{"arxiv_id":"2411.16763","doi":null,"metadata_source":"pith","pith_arxiv_id":"2411.16763","snapshot_observed_at":"2026-08-06T10:58:06.431658Z","title":"Hide in Plain Sight: Clean-Label Backdoor for Auditing Membership Inference","venue":"cs.CR","work_id":"31da02dc-a2cd-4654-bb2c-6106ddb88d57","year":2024},"citing_paper":{"arxiv_id":"2507.23291","last_updated":"2025-08-03T23:23:03Z","snapshot_observed_at":"2026-08-15T20:46:11.551277Z","submitted_at":"2025-07-31T07:09:52Z","title":"Evaluating the Dynamics of Membership Privacy in Deep Learning","version":2},"reference_index":6,"source":"arxiv_source","source_observed_at":"2026-08-06T10:58:05.894582Z"},"links":{"cited_paper":"/paper/2411.16763","citing_paper":"/paper/2507.23291"},"observation_digest":"sha256:37faf8272f89ffa2c5f7f0e1848567b7ef3311b3b900ce3f49db73d73dbb65c2","observation_id":"d3bfa3d4-66e8-477b-91b6-2df6f82b63e2","resolution":{"observed_at":"2026-08-06T10:58:06.438577Z","resolver_source":"local_arxiv","status":"verified_exact"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-15T06:32:42.880941+00:00","source":"crossref"},{"observed_at":"2026-08-15T06:32:39.529945+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-06T10:58:06.810283Z","title":null,"venue":null,"work_id":"ef125673-ee1f-4ad7-bdf6-91efac51fb52","year":2021},"citing_paper":{"arxiv_id":"2507.23291","last_updated":"2025-08-03T23:23:03Z","snapshot_observed_at":"2026-08-15T20:46:11.551277Z","submitted_at":"2025-07-31T07:09:52Z","title":"Evaluating the Dynamics of Membership Privacy in Deep Learning","version":2},"reference_index":7,"source":"arxiv_source","source_observed_at":"2026-08-06T10:58:05.899939Z"},"links":{"citing_paper":"/paper/2507.23291"},"observation_digest":"sha256:462fe27685cac548704185a291559045b64d3c55e550391541d10813e2aee327","observation_id":"69042674-d7b6-4287-b09f-1bb0972829de","resolution":{"observed_at":"2026-08-06T10:58:06.814916Z","resolver_source":"raw_fallback","status":"unresolved"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-15T06:32:42.880941+00:00","source":"crossref"},{"observed_at":"2026-08-15T06:32:39.529945+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"1711.02257","last_updated":"2018-06-12T06:45:49Z","snapshot_observed_at":"2026-08-14T20:16:18.909353Z","submitted_at":"2017-11-07T02:08:12Z","title":"GradNorm: Gradient Normalization for Adaptive Loss Balancing in Deep Multitask Networks","version":4},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"1711.02257","snapshot_observed_at":"2026-08-06T10:58:05.904245Z","title":null,"venue":null,"work_id":null,"year":2018},"citing_paper":{"arxiv_id":"2507.23291","last_updated":"2025-08-03T23:23:03Z","snapshot_observed_at":"2026-08-15T20:46:11.551277Z","submitted_at":"2025-07-31T07:09:52Z","title":"Evaluating the Dynamics of Membership Privacy in Deep Learning","version":2},"reference_index":8,"source":"arxiv_source","source_observed_at":"2026-08-06T10:58:05.904245Z"},"links":{"cited_paper":"/paper/1711.02257","citing_paper":"/paper/2507.23291"},"observation_digest":"sha256:c187834c6c1e860b6677daedf69d829d39be61cc2bfd6fc7dab00dd03b2a40eb","observation_id":"8f6be4d6-4185-4b70-8131-1a17d9d2ab15","resolution":{"observed_at":"2026-08-06T10:58:05.904245Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-06T10:58:06.796862Z","title":"A.; Tramer, F.; Carlini, N.; and Papernot, N","venue":null,"work_id":"3c3becf9-c017-4daa-8788-11e07cb5c5dc","year":2021},"citing_paper":{"arxiv_id":"2507.23291","last_updated":"2025-08-03T23:23:03Z","snapshot_observed_at":"2026-08-15T20:46:11.551277Z","submitted_at":"2025-07-31T07:09:52Z","title":"Evaluating the Dynamics of Membership Privacy in Deep Learning","version":2},"reference_index":9,"source":"arxiv_source","source_observed_at":"2026-08-06T10:58:05.909020Z"},"links":{"citing_paper":"/paper/2507.23291"},"observation_digest":"sha256:9569d3375455ed7fc221d40ebed8392caabd17a89b62ff3d33f0a3c3d3f73be9","observation_id":"f6ec42d6-a169-46f9-b683-cba377cf9ab5","resolution":{"observed_at":"2026-08-06T10:58:06.801092Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-15T06:32:42.880941+00:00","source":"crossref"},{"observed_at":"2026-08-15T06:32:39.529945+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"2007.14321","last_updated":"2021-12-05T22:45:19Z","snapshot_observed_at":"2026-08-14T18:37:21.990922Z","submitted_at":"2020-07-28T15:44:31Z","title":"Label-Only Membership Inference Attacks","version":3},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2007.14321","snapshot_observed_at":"2026-08-06T10:58:05.913401Z","title":"A.; Tramer, F.; Carlini, N.; and Papernot, N","venue":null,"work_id":null,"year":2021},"citing_paper":{"arxiv_id":"2507.23291","last_updated":"2025-08-03T23:23:03Z","snapshot_observed_at":"2026-08-15T20:46:11.551277Z","submitted_at":"2025-07-31T07:09:52Z","title":"Evaluating the Dynamics of Membership Privacy in Deep Learning","version":2},"reference_index":10,"source":"arxiv_source","source_observed_at":"2026-08-06T10:58:05.913401Z"},"links":{"cited_paper":"/paper/2007.14321","citing_paper":"/paper/2507.23291"},"observation_digest":"sha256:1c2e030e6c192119604d9ab2a6d8c5d3198f0d58788fd35f825bf06d8b426c91","observation_id":"002a90e4-1c5b-4cfd-870f-b279f4bf1f8f","resolution":{"observed_at":"2026-08-06T10:58:05.913401Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"1810.03505","last_updated":"2018-10-02T21:20:09Z","snapshot_observed_at":"2026-08-15T08:58:58.432989Z","submitted_at":"2018-10-02T21:20:09Z","title":"CINIC-10 is not ImageNet or CIFAR-10","version":1},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"1810.03505","snapshot_observed_at":"2026-08-06T10:58:05.918214Z","title":"N.; Crowley, E","venue":null,"work_id":null,"year":2018},"citing_paper":{"arxiv_id":"2507.23291","last_updated":"2025-08-03T23:23:03Z","snapshot_observed_at":"2026-08-15T20:46:11.551277Z","submitted_at":"2025-07-31T07:09:52Z","title":"Evaluating the Dynamics of Membership Privacy in Deep Learning","version":2},"reference_index":11,"source":"arxiv_source","source_observed_at":"2026-08-06T10:58:05.918214Z"},"links":{"cited_paper":"/paper/1810.03505","citing_paper":"/paper/2507.23291"},"observation_digest":"sha256:f7b3faa9f0608f25ccbf7ec261e6ce8011e0827fb9bd5dffe8ff74125b557556","observation_id":"45290094-4c4d-4abe-ad71-223b88965310","resolution":{"observed_at":"2026-08-06T10:58:05.918214Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-06T10:58:06.783629Z","title":null,"venue":null,"work_id":"05f97871-2753-4bf2-8bd1-676090832ce8","year":2020},"citing_paper":{"arxiv_id":"2507.23291","last_updated":"2025-08-03T23:23:03Z","snapshot_observed_at":"2026-08-15T20:46:11.551277Z","submitted_at":"2025-07-31T07:09:52Z","title":"Evaluating the Dynamics of Membership Privacy in Deep Learning","version":2},"reference_index":12,"source":"arxiv_source","source_observed_at":"2026-08-06T10:58:05.923229Z"},"links":{"citing_paper":"/paper/2507.23291"},"observation_digest":"sha256:1cd76a837258e3fbc40b41100093cea654f69d44c900c3d12ebb52bdc731e0ac","observation_id":"b8ee3dbd-f8b0-4897-8643-639d400e7941","resolution":{"observed_at":"2026-08-06T10:58:06.787884Z","resolver_source":"raw_fallback","status":"unresolved"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-15T06:32:42.880941+00:00","source":"crossref"},{"observed_at":"2026-08-15T06:32:39.529945+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"2010.01412","last_updated":"2021-04-29T16:44:25Z","snapshot_observed_at":"2026-08-15T12:34:14.131778Z","submitted_at":"2020-10-03T19:02:10Z","title":"Sharpness-Aware Minimization for Efficiently Improving Generalization","version":3},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2010.01412","snapshot_observed_at":"2026-08-06T10:58:05.927587Z","title":null,"venue":null,"work_id":null,"year":2021},"citing_paper":{"arxiv_id":"2507.23291","last_updated":"2025-08-03T23:23:03Z","snapshot_observed_at":"2026-08-15T20:46:11.551277Z","submitted_at":"2025-07-31T07:09:52Z","title":"Evaluating the Dynamics of Membership Privacy in Deep Learning","version":2},"reference_index":13,"source":"arxiv_source","source_observed_at":"2026-08-06T10:58:05.927587Z"},"links":{"cited_paper":"/paper/2010.01412","citing_paper":"/paper/2507.23291"},"observation_digest":"sha256:62a0758fe324192bca0d14b839df659b6d07dbcce6534b5ea1d68ee0fa734593","observation_id":"ccf77055-ced0-4adc-a341-6c75e2fbf36d","resolution":{"observed_at":"2026-08-06T10:58:05.927587Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-06T10:58:06.769498Z","title":null,"venue":null,"work_id":"c2c7ccee-697f-4e85-9c6b-599defe729cb","year":2020},"citing_paper":{"arxiv_id":"2507.23291","last_updated":"2025-08-03T23:23:03Z","snapshot_observed_at":"2026-08-15T20:46:11.551277Z","submitted_at":"2025-07-31T07:09:52Z","title":"Evaluating the Dynamics of Membership Privacy in Deep Learning","version":2},"reference_index":14,"source":"arxiv_source","source_observed_at":"2026-08-06T10:58:05.932193Z"},"links":{"citing_paper":"/paper/2507.23291"},"observation_digest":"sha256:adeb57520898c2eb6c8a1c3e25523b9701b3b7eabe72c04b1044c10070119fd1","observation_id":"7e6dae47-4038-4cd0-9f6b-0fdc27a4c9ed","resolution":{"observed_at":"2026-08-06T10:58:06.774079Z","resolver_source":"raw_fallback","status":"unresolved"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-15T06:32:42.880941+00:00","source":"crossref"},{"observed_at":"2026-08-15T06:32:39.529945+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"1705.07663","last_updated":"2018-08-21T13:24:17Z","snapshot_observed_at":"2026-08-14T20:59:08.335203Z","submitted_at":"2017-05-22T11:05:06Z","title":"LOGAN: Membership Inference Attacks Against Generative Models","version":4},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"1705.07663","snapshot_observed_at":"2026-08-06T10:58:05.936500Z","title":null,"venue":null,"work_id":null,"year":2017},"citing_paper":{"arxiv_id":"2507.23291","last_updated":"2025-08-03T23:23:03Z","snapshot_observed_at":"2026-08-15T20:46:11.551277Z","submitted_at":"2025-07-31T07:09:52Z","title":"Evaluating the Dynamics of Membership Privacy in Deep Learning","version":2},"reference_index":15,"source":"arxiv_source","source_observed_at":"2026-08-06T10:58:05.936500Z"},"links":{"cited_paper":"/paper/1705.07663","citing_paper":"/paper/2507.23291"},"observation_digest":"sha256:e2d6396a44396dbe06f27be85f04bec23e36cf6b92b24fdc178e007995e0ed27","observation_id":"c8bcc295-e283-4dd9-a661-d9dfd683ef60","resolution":{"observed_at":"2026-08-06T10:58:05.936500Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-06T10:58:06.755902Z","title":null,"venue":null,"work_id":"c8d3f528-287a-4641-bb33-1ad130c811bb","year":2017},"citing_paper":{"arxiv_id":"2507.23291","last_updated":"2025-08-03T23:23:03Z","snapshot_observed_at":"2026-08-15T20:46:11.551277Z","submitted_at":"2025-07-31T07:09:52Z","title":"Evaluating the Dynamics of Membership Privacy in Deep Learning","version":2},"reference_index":16,"source":"arxiv_source","source_observed_at":"2026-08-06T10:58:05.941053Z"},"links":{"citing_paper":"/paper/2507.23291"},"observation_digest":"sha256:38a6b0672a8a22b50cdf6966fe6b9ceed39aa82d1336e45707b6731cf78c809c","observation_id":"8ff8fedd-201f-414f-b253-5dc0720d5bab","resolution":{"observed_at":"2026-08-06T10:58:06.760247Z","resolver_source":"raw_fallback","status":"unresolved"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-15T06:32:42.880941+00:00","source":"crossref"},{"observed_at":"2026-08-15T06:32:39.529945+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-06T10:58:06.742109Z","title":"S.; and Zhang, X","venue":null,"work_id":"88ca1586-112f-4817-a07f-333430c1b935","year":2022},"citing_paper":{"arxiv_id":"2507.23291","last_updated":"2025-08-03T23:23:03Z","snapshot_observed_at":"2026-08-15T20:46:11.551277Z","submitted_at":"2025-07-31T07:09:52Z","title":"Evaluating the Dynamics of Membership Privacy in Deep Learning","version":2},"reference_index":17,"source":"arxiv_source","source_observed_at":"2026-08-06T10:58:05.945223Z"},"links":{"citing_paper":"/paper/2507.23291"},"observation_digest":"sha256:675a07da48a78561e4254ca83f679f830df2836031013847caf263430046aa76","observation_id":"9e9e1838-5ab6-4e36-ac04-f4f064b3f62b","resolution":{"observed_at":"2026-08-06T10:58:06.746671Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-15T06:32:42.880941+00:00","source":"crossref"},{"observed_at":"2026-08-15T06:32:39.529945+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-06T10:58:06.728521Z","title":null,"venue":null,"work_id":"add9ca24-f0ec-4e04-a6a5-a45d87af1207","year":2021},"citing_paper":{"arxiv_id":"2507.23291","last_updated":"2025-08-03T23:23:03Z","snapshot_observed_at":"2026-08-15T20:46:11.551277Z","submitted_at":"2025-07-31T07:09:52Z","title":"Evaluating the Dynamics of Membership Privacy in Deep Learning","version":2},"reference_index":18,"source":"arxiv_source","source_observed_at":"2026-08-06T10:58:05.949761Z"},"links":{"citing_paper":"/paper/2507.23291"},"observation_digest":"sha256:27f1290ce3e88453e726ff8ebd54ec09503f1a474e61b109a9c6d7f65c453c85","observation_id":"37246641-0351-4c87-96f6-02498805e1a1","resolution":{"observed_at":"2026-08-06T10:58:06.732812Z","resolver_source":"raw_fallback","status":"unresolved"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-15T06:32:42.880941+00:00","source":"crossref"},{"observed_at":"2026-08-15T06:32:39.529945+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-06T10:58:06.715332Z","title":null,"venue":null,"work_id":"f4b971ca-27e3-4633-9a0d-048bb9ccee96","year":2019},"citing_paper":{"arxiv_id":"2507.23291","last_updated":"2025-08-03T23:23:03Z","snapshot_observed_at":"2026-08-15T20:46:11.551277Z","submitted_at":"2025-07-31T07:09:52Z","title":"Evaluating the Dynamics of Membership Privacy in Deep Learning","version":2},"reference_index":19,"source":"arxiv_source","source_observed_at":"2026-08-06T10:58:05.954146Z"},"links":{"citing_paper":"/paper/2507.23291"},"observation_digest":"sha256:1e4efd8916cff97823a21c1d5bccd34bd4cb6b5cf42c8d3b07e2efa5a2b83b34","observation_id":"c92d886e-58e1-4895-a6bf-d8ad9a5ab377","resolution":{"observed_at":"2026-08-06T10:58:06.719678Z","resolver_source":"raw_fallback","status":"unresolved"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-15T06:32:42.880941+00:00","source":"crossref"},{"observed_at":"2026-08-15T06:32:39.529945+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-06T10:58:06.702019Z","title":null,"venue":null,"work_id":"9d8c3636-4e8e-485a-9814-8bc743fec225","year":2019},"citing_paper":{"arxiv_id":"2507.23291","last_updated":"2025-08-03T23:23:03Z","snapshot_observed_at":"2026-08-15T20:46:11.551277Z","submitted_at":"2025-07-31T07:09:52Z","title":"Evaluating the Dynamics of Membership Privacy in Deep Learning","version":2},"reference_index":20,"source":"arxiv_source","source_observed_at":"2026-08-06T10:58:05.958758Z"},"links":{"citing_paper":"/paper/2507.23291"},"observation_digest":"sha256:e34cbda989e21d3864c7c99981abe2039113f6bac75624db6982e889939286d7","observation_id":"7ed9addc-c50a-439c-a84e-981ad228abc5","resolution":{"observed_at":"2026-08-06T10:58:06.706230Z","resolver_source":"raw_fallback","status":"unresolved"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-15T06:32:42.880941+00:00","source":"crossref"},{"observed_at":"2026-08-15T06:32:39.529945+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"2005.10881","last_updated":"2021-01-13T20:44:44Z","snapshot_observed_at":"2026-08-15T02:51:08.759688Z","submitted_at":"2020-05-21T20:17:42Z","title":"Revisiting Membership Inference Under Realistic Assumptions","version":5},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2005.10881","snapshot_observed_at":"2026-08-06T10:58:05.962975Z","title":null,"venue":null,"work_id":null,"year":2020},"citing_paper":{"arxiv_id":"2507.23291","last_updated":"2025-08-03T23:23:03Z","snapshot_observed_at":"2026-08-15T20:46:11.551277Z","submitted_at":"2025-07-31T07:09:52Z","title":"Evaluating the Dynamics of Membership Privacy in Deep Learning","version":2},"reference_index":21,"source":"arxiv_source","source_observed_at":"2026-08-06T10:58:05.962975Z"},"links":{"cited_paper":"/paper/2005.10881","citing_paper":"/paper/2507.23291"},"observation_digest":"sha256:2d72e52d18edf64e027201778370948cf6f14f1c5b8b771538e50176f14ad349","observation_id":"a85b9404-e99b-4640-a951-f266ccb36ccb","resolution":{"observed_at":"2026-08-06T10:58:05.962975Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"1703.04730","last_updated":"2020-12-29T22:40:43Z","snapshot_observed_at":"2026-08-15T02:28:36.697260Z","submitted_at":"2017-03-14T21:07:01Z","title":"Understanding Black-box Predictions via Influence Functions","version":3},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"1703.04730","snapshot_observed_at":"2026-08-06T10:58:05.967606Z","title":"W.; and Liang, P","venue":null,"work_id":null,"year":2020},"citing_paper":{"arxiv_id":"2507.23291","last_updated":"2025-08-03T23:23:03Z","snapshot_observed_at":"2026-08-15T20:46:11.551277Z","submitted_at":"2025-07-31T07:09:52Z","title":"Evaluating the Dynamics of Membership Privacy in Deep Learning","version":2},"reference_index":22,"source":"arxiv_source","source_observed_at":"2026-08-06T10:58:05.967606Z"},"links":{"cited_paper":"/paper/1703.04730","citing_paper":"/paper/2507.23291"},"observation_digest":"sha256:c503d244af39134f96e653430187ddc246f399d5dabd7ffce322059ef5c2d092","observation_id":"fa4bdcb8-5bcc-4560-bf57-b462143da1ae","resolution":{"observed_at":"2026-08-06T10:58:05.967606Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-06T10:58:06.687967Z","title":null,"venue":null,"work_id":"357fc759-f0b8-42a6-90da-7acdc6ed3658","year":2009},"citing_paper":{"arxiv_id":"2507.23291","last_updated":"2025-08-03T23:23:03Z","snapshot_observed_at":"2026-08-15T20:46:11.551277Z","submitted_at":"2025-07-31T07:09:52Z","title":"Evaluating the Dynamics of Membership Privacy in Deep Learning","version":2},"reference_index":23,"source":"arxiv_source","source_observed_at":"2026-08-06T10:58:05.972111Z"},"links":{"citing_paper":"/paper/2507.23291"},"observation_digest":"sha256:4d5442485d85cd7c7ce043c86c1147ba3609c939a62c1a5293a355014cdcf758","observation_id":"cef647bf-8e14-4423-a46d-60c7d3acda15","resolution":{"observed_at":"2026-08-06T10:58:06.692407Z","resolver_source":"raw_fallback","status":"unresolved"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-15T06:32:42.880941+00:00","source":"crossref"},{"observed_at":"2026-08-15T06:32:39.529945+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-06T10:58:06.674485Z","title":null,"venue":null,"work_id":"2ae501b8-6726-443a-893f-fd1e0ab03362","year":1998},"citing_paper":{"arxiv_id":"2507.23291","last_updated":"2025-08-03T23:23:03Z","snapshot_observed_at":"2026-08-15T20:46:11.551277Z","submitted_at":"2025-07-31T07:09:52Z","title":"Evaluating the Dynamics of Membership Privacy in Deep Learning","version":2},"reference_index":24,"source":"arxiv_source","source_observed_at":"2026-08-06T10:58:05.976320Z"},"links":{"citing_paper":"/paper/2507.23291"},"observation_digest":"sha256:76df2cc2c402ad7f3fe707987f0291a120ac1bc517b34cee264c7e203f78c570","observation_id":"b9234480-35cc-46a7-bf5f-f6e1900036ca","resolution":{"observed_at":"2026-08-06T10:58:06.678782Z","resolver_source":"raw_fallback","status":"unresolved"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-15T06:32:42.880941+00:00","source":"crossref"},{"observed_at":"2026-08-15T06:32:39.529945+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-06T10:58:06.661129Z","title":null,"venue":null,"work_id":"cc97ed74-863c-410f-89fe-aad3b7f16586","year":1998},"citing_paper":{"arxiv_id":"2507.23291","last_updated":"2025-08-03T23:23:03Z","snapshot_observed_at":"2026-08-15T20:46:11.551277Z","submitted_at":"2025-07-31T07:09:52Z","title":"Evaluating the Dynamics of Membership Privacy in Deep Learning","version":2},"reference_index":25,"source":"arxiv_source","source_observed_at":"2026-08-06T10:58:05.980637Z"},"links":{"citing_paper":"/paper/2507.23291"},"observation_digest":"sha256:350036b37f76a8c54a2e0b2ea251c7b20140ffc7dc6941e36f0047f0ff8e8213","observation_id":"3b27be6b-699c-406d-ab92-f0b840df0812","resolution":{"observed_at":"2026-08-06T10:58:06.665453Z","resolver_source":"raw_fallback","status":"unresolved"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-15T06:32:42.880941+00:00","source":"crossref"},{"observed_at":"2026-08-15T06:32:39.529945+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-06T10:58:06.647885Z","title":null,"venue":null,"work_id":"788309c2-d056-46dc-abf6-59647791befd","year":2020},"citing_paper":{"arxiv_id":"2507.23291","last_updated":"2025-08-03T23:23:03Z","snapshot_observed_at":"2026-08-15T20:46:11.551277Z","submitted_at":"2025-07-31T07:09:52Z","title":"Evaluating the Dynamics of Membership Privacy in Deep Learning","version":2},"reference_index":26,"source":"arxiv_source","source_observed_at":"2026-08-06T10:58:05.984913Z"},"links":{"citing_paper":"/paper/2507.23291"},"observation_digest":"sha256:f58b74ce20a4c59371bfaad0136789abb8df02021927da41ffee9ba405b66e06","observation_id":"f634c7e4-3e30-468a-880f-6b27a84e6f89","resolution":{"observed_at":"2026-08-06T10:58:06.652027Z","resolver_source":"raw_fallback","status":"unresolved"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-15T06:32:42.880941+00:00","source":"crossref"},{"observed_at":"2026-08-15T06:32:39.529945+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"2007.15528","last_updated":"2021-09-17T17:40:37Z","snapshot_observed_at":"2026-08-15T02:51:23.898296Z","submitted_at":"2020-07-30T15:27:55Z","title":"Membership Leakage in Label-Only Exposures","version":3},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2007.15528","snapshot_observed_at":"2026-08-06T10:58:05.989078Z","title":null,"venue":null,"work_id":null,"year":2021},"citing_paper":{"arxiv_id":"2507.23291","last_updated":"2025-08-03T23:23:03Z","snapshot_observed_at":"2026-08-15T20:46:11.551277Z","submitted_at":"2025-07-31T07:09:52Z","title":"Evaluating the Dynamics of Membership Privacy in Deep Learning","version":2},"reference_index":27,"source":"arxiv_source","source_observed_at":"2026-08-06T10:58:05.989078Z"},"links":{"cited_paper":"/paper/2007.15528","citing_paper":"/paper/2507.23291"},"observation_digest":"sha256:9cfeaa21c3fd7f160fd2c3cffb733eabea12752aa8e7157a1541e87285af460e","observation_id":"aa666abe-a35d-40e8-84bf-a130c53fef45","resolution":{"observed_at":"2026-08-06T10:58:05.989078Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"1802.04889","last_updated":"2018-02-13T23:05:05Z","snapshot_observed_at":"2026-08-14T19:46:08.923996Z","submitted_at":"2018-02-13T23:05:05Z","title":"Understanding Membership Inferences on Well-Generalized Learning Models","version":1},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"1802.04889","snapshot_observed_at":"2026-08-06T10:58:05.993667Z","title":"A.; and Chen, K","venue":null,"work_id":null,"year":2018},"citing_paper":{"arxiv_id":"2507.23291","last_updated":"2025-08-03T23:23:03Z","snapshot_observed_at":"2026-08-15T20:46:11.551277Z","submitted_at":"2025-07-31T07:09:52Z","title":"Evaluating the Dynamics of Membership Privacy in Deep Learning","version":2},"reference_index":28,"source":"arxiv_source","source_observed_at":"2026-08-06T10:58:05.993667Z"},"links":{"cited_paper":"/paper/1802.04889","citing_paper":"/paper/2507.23291"},"observation_digest":"sha256:5832b3f8c60bf4bdf1e56f022c43c4605ee11431e0221327a4684232ece8ecd3","observation_id":"0fd8fc14-88ee-4cdb-b76e-4ea8a2c1643f","resolution":{"observed_at":"2026-08-06T10:58:05.993667Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"1711.05101","last_updated":"2019-01-04T21:01:49Z","snapshot_observed_at":"2026-08-14T20:13:52.872565Z","submitted_at":"2017-11-14T14:24:06Z","title":"Decoupled Weight Decay Regularization","version":3},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"1711.05101","snapshot_observed_at":"2026-08-06T10:58:05.998036Z","title":null,"venue":null,"work_id":null,"year":2017},"citing_paper":{"arxiv_id":"2507.23291","last_updated":"2025-08-03T23:23:03Z","snapshot_observed_at":"2026-08-15T20:46:11.551277Z","submitted_at":"2025-07-31T07:09:52Z","title":"Evaluating the Dynamics of Membership Privacy in Deep Learning","version":2},"reference_index":29,"source":"arxiv_source","source_observed_at":"2026-08-06T10:58:05.998036Z"},"links":{"cited_paper":"/paper/1711.05101","citing_paper":"/paper/2507.23291"},"observation_digest":"sha256:57179b64cead92090aed3acdd79dfcf19d9e49e4f98205460259681e6cfc8ee0","observation_id":"073c8e11-53a1-4e43-884b-7793ca6d990a","resolution":{"observed_at":"2026-08-06T10:58:05.998036Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2203.03929","last_updated":"2022-11-04T02:47:37Z","snapshot_observed_at":"2026-08-15T02:51:07.077488Z","submitted_at":"2022-03-08T08:50:34Z","title":"Quantifying Privacy Risks of Masked Language Models Using Membership Inference Attacks","version":2},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2203.03929","snapshot_observed_at":"2026-08-06T10:58:06.002264Z","title":null,"venue":null,"work_id":null,"year":2022},"citing_paper":{"arxiv_id":"2507.23291","last_updated":"2025-08-03T23:23:03Z","snapshot_observed_at":"2026-08-15T20:46:11.551277Z","submitted_at":"2025-07-31T07:09:52Z","title":"Evaluating the Dynamics of Membership Privacy in Deep Learning","version":2},"reference_index":30,"source":"arxiv_source","source_observed_at":"2026-08-06T10:58:06.002264Z"},"links":{"cited_paper":"/paper/2203.03929","citing_paper":"/paper/2507.23291"},"observation_digest":"sha256:02c5d9204c3c8297847161d65ec39ce6013df4ed13ab25fbc7fe97cdd7774445","observation_id":"56dba173-eb39-4954-a8e3-e28425bb8b11","resolution":{"observed_at":"2026-08-06T10:58:06.002264Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-06T10:58:06.634989Z","title":null,"venue":null,"work_id":"a5ca1235-c01d-4caa-bcc4-ae6ff2526311","year":2019},"citing_paper":{"arxiv_id":"2507.23291","last_updated":"2025-08-03T23:23:03Z","snapshot_observed_at":"2026-08-15T20:46:11.551277Z","submitted_at":"2025-07-31T07:09:52Z","title":"Evaluating the Dynamics of Membership Privacy in Deep Learning","version":2},"reference_index":31,"source":"arxiv_source","source_observed_at":"2026-08-06T10:58:06.006595Z"},"links":{"citing_paper":"/paper/2507.23291"},"observation_digest":"sha256:864b22d65c0da8800ef9824cff160060184696cac84eed8066e2f7983cd2134a","observation_id":"ff729686-e114-45ca-8276-58faf8f6dd09","resolution":{"observed_at":"2026-08-06T10:58:06.639262Z","resolver_source":"raw_fallback","status":"unresolved"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-15T06:32:42.880941+00:00","source":"crossref"},{"observed_at":"2026-08-15T06:32:39.529945+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-06T10:58:06.621516Z","title":null,"venue":null,"work_id":"1271fb9f-0048-4c4d-9c89-0b437a68128e","year":2021},"citing_paper":{"arxiv_id":"2507.23291","last_updated":"2025-08-03T23:23:03Z","snapshot_observed_at":"2026-08-15T20:46:11.551277Z","submitted_at":"2025-07-31T07:09:52Z","title":"Evaluating the Dynamics of Membership Privacy in Deep Learning","version":2},"reference_index":32,"source":"arxiv_source","source_observed_at":"2026-08-06T10:58:06.010647Z"},"links":{"citing_paper":"/paper/2507.23291"},"observation_digest":"sha256:cfa4be481d8428478ec8e944d819d8f878169012ca48665f825b628c77cf061d","observation_id":"c8576813-8144-408c-b821-3ab884ac88a0","resolution":{"observed_at":"2026-08-06T10:58:06.625908Z","resolver_source":"raw_fallback","status":"unresolved"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-15T06:32:42.880941+00:00","source":"crossref"},{"observed_at":"2026-08-15T06:32:39.529945+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-06T10:58:06.607957Z","title":null,"venue":null,"work_id":"915c171b-4eb6-45c3-933d-bcafe3dcbddb","year":2023},"citing_paper":{"arxiv_id":"2507.23291","last_updated":"2025-08-03T23:23:03Z","snapshot_observed_at":"2026-08-15T20:46:11.551277Z","submitted_at":"2025-07-31T07:09:52Z","title":"Evaluating the Dynamics of Membership Privacy in Deep Learning","version":2},"reference_index":33,"source":"arxiv_source","source_observed_at":"2026-08-06T10:58:06.014898Z"},"links":{"citing_paper":"/paper/2507.23291"},"observation_digest":"sha256:c801dca7293d839f258d044cc5d7f7bfc030f5eda945dc95a2ac4e53c16a9dd3","observation_id":"1e1dabde-cac8-46d9-8586-e52c43998157","resolution":{"observed_at":"2026-08-06T10:58:06.612241Z","resolver_source":"raw_fallback","status":"unresolved"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-15T06:32:42.880941+00:00","source":"crossref"},{"observed_at":"2026-08-15T06:32:39.529945+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"1609.04747","last_updated":"2017-06-15T13:21:04Z","snapshot_observed_at":"2026-08-15T03:49:17.013617Z","submitted_at":"2016-09-15T17:32:34Z","title":"An overview of gradient descent optimization algorithms","version":2},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"1609.04747","snapshot_observed_at":"2026-08-06T10:58:06.019008Z","title":null,"venue":null,"work_id":null,"year":2016},"citing_paper":{"arxiv_id":"2507.23291","last_updated":"2025-08-03T23:23:03Z","snapshot_observed_at":"2026-08-15T20:46:11.551277Z","submitted_at":"2025-07-31T07:09:52Z","title":"Evaluating the Dynamics of Membership Privacy in Deep Learning","version":2},"reference_index":34,"source":"arxiv_source","source_observed_at":"2026-08-06T10:58:06.019008Z"},"links":{"cited_paper":"/paper/1609.04747","citing_paper":"/paper/2507.23291"},"observation_digest":"sha256:ed037c4c2be4373d021104e1be0c297b1d1022a78a21113d39674b753340dba6","observation_id":"06f20047-2f6d-4890-ad5c-13d1dd5f0872","resolution":{"observed_at":"2026-08-06T10:58:06.019008Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-06T10:58:06.594240Z","title":null,"venue":null,"work_id":"096de592-51bf-4c03-a5a8-f0a441cc9fb5","year":2019},"citing_paper":{"arxiv_id":"2507.23291","last_updated":"2025-08-03T23:23:03Z","snapshot_observed_at":"2026-08-15T20:46:11.551277Z","submitted_at":"2025-07-31T07:09:52Z","title":"Evaluating the Dynamics of Membership Privacy in Deep Learning","version":2},"reference_index":35,"source":"arxiv_source","source_observed_at":"2026-08-06T10:58:06.023482Z"},"links":{"citing_paper":"/paper/2507.23291"},"observation_digest":"sha256:c7e8b447f1a29bbde483dd46a340e7c7871fd493f3776eb9fb851cbfee61244a","observation_id":"3f890b50-4312-407f-b371-0378502c2cc8","resolution":{"observed_at":"2026-08-06T10:58:06.598558Z","resolver_source":"raw_fallback","status":"unresolved"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-15T06:32:42.880941+00:00","source":"crossref"},{"observed_at":"2026-08-15T06:32:39.529945+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"1806.01246","last_updated":"2018-12-14T19:39:43Z","snapshot_observed_at":"2026-08-14T19:07:42.874279Z","submitted_at":"2018-06-04T17:38:42Z","title":"ML-Leaks: Model and Data Independent Membership Inference Attacks and Defenses on Machine Learning Models","version":2},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"1806.01246","snapshot_observed_at":"2026-08-06T10:58:06.028928Z","title":null,"venue":null,"work_id":null,"year":2018},"citing_paper":{"arxiv_id":"2507.23291","last_updated":"2025-08-03T23:23:03Z","snapshot_observed_at":"2026-08-15T20:46:11.551277Z","submitted_at":"2025-07-31T07:09:52Z","title":"Evaluating the Dynamics of Membership Privacy in Deep Learning","version":2},"reference_index":36,"source":"arxiv_source","source_observed_at":"2026-08-06T10:58:06.028928Z"},"links":{"cited_paper":"/paper/1806.01246","citing_paper":"/paper/2507.23291"},"observation_digest":"sha256:f1ff2b623fa5cc1d86b8cfe13f963681438e02839d640016fc2593eddbe7daa2","observation_id":"c8d0b5e2-f529-4993-9223-e26406ac1963","resolution":{"observed_at":"2026-08-06T10:58:06.028928Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-06T10:58:06.580913Z","title":null,"venue":null,"work_id":"d81e0f15-33ad-48c5-8bf2-0be957eb1d41","year":2022},"citing_paper":{"arxiv_id":"2507.23291","last_updated":"2025-08-03T23:23:03Z","snapshot_observed_at":"2026-08-15T20:46:11.551277Z","submitted_at":"2025-07-31T07:09:52Z","title":"Evaluating the Dynamics of Membership Privacy in Deep Learning","version":2},"reference_index":37,"source":"arxiv_source","source_observed_at":"2026-08-06T10:58:06.033575Z"},"links":{"citing_paper":"/paper/2507.23291"},"observation_digest":"sha256:f7cdaad34c33894ac1e133de941672f9685f0c9f033aa8ec540368cedce8e643","observation_id":"2df12a90-01e1-4ed4-8370-6702d1c429a4","resolution":{"observed_at":"2026-08-06T10:58:06.585167Z","resolver_source":"raw_fallback","status":"unresolved"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-15T06:32:42.880941+00:00","source":"crossref"},{"observed_at":"2026-08-15T06:32:39.529945+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"1610.05820","last_updated":"2017-03-31T22:17:07Z","snapshot_observed_at":"2026-08-14T21:34:36.777438Z","submitted_at":"2016-10-18T22:38:33Z","title":"Membership Inference Attacks against Machine Learning Models","version":2},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"1610.05820","snapshot_observed_at":"2026-08-06T10:58:06.037996Z","title":null,"venue":null,"work_id":null,"year":2017},"citing_paper":{"arxiv_id":"2507.23291","last_updated":"2025-08-03T23:23:03Z","snapshot_observed_at":"2026-08-15T20:46:11.551277Z","submitted_at":"2025-07-31T07:09:52Z","title":"Evaluating the Dynamics of Membership Privacy in Deep Learning","version":2},"reference_index":38,"source":"arxiv_source","source_observed_at":"2026-08-06T10:58:06.037996Z"},"links":{"cited_paper":"/paper/1610.05820","citing_paper":"/paper/2507.23291"},"observation_digest":"sha256:8179069f1c3349d3c5e8a22365b65bfc4a4fa0b1921953c664de8f94de11ae8e","observation_id":"7ee740e8-4493-4a63-966c-eb424e5f697a","resolution":{"observed_at":"2026-08-06T10:58:06.037996Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-06T10:58:06.567883Z","title":null,"venue":null,"work_id":"fc7db346-6654-4023-af51-8deac23ec439","year":2021},"citing_paper":{"arxiv_id":"2507.23291","last_updated":"2025-08-03T23:23:03Z","snapshot_observed_at":"2026-08-15T20:46:11.551277Z","submitted_at":"2025-07-31T07:09:52Z","title":"Evaluating the Dynamics of Membership Privacy in Deep Learning","version":2},"reference_index":39,"source":"arxiv_source","source_observed_at":"2026-08-06T10:58:06.042336Z"},"links":{"citing_paper":"/paper/2507.23291"},"observation_digest":"sha256:f2976629a4989bf315c13041c2f22024e9bcea2b498819c182404b666614455e","observation_id":"7d354d62-cb5b-4f0e-8366-2fe15ae6a2e2","resolution":{"observed_at":"2026-08-06T10:58:06.571923Z","resolver_source":"raw_fallback","status":"unresolved"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-15T06:32:42.880941+00:00","source":"crossref"},{"observed_at":"2026-08-15T06:32:39.529945+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-06T10:58:06.553631Z","title":null,"venue":null,"work_id":"b7ab26e5-186f-4141-8ff6-7a7e92f1ea49","year":2019},"citing_paper":{"arxiv_id":"2507.23291","last_updated":"2025-08-03T23:23:03Z","snapshot_observed_at":"2026-08-15T20:46:11.551277Z","submitted_at":"2025-07-31T07:09:52Z","title":"Evaluating the Dynamics of Membership Privacy in Deep Learning","version":2},"reference_index":40,"source":"arxiv_source","source_observed_at":"2026-08-06T10:58:06.046621Z"},"links":{"citing_paper":"/paper/2507.23291"},"observation_digest":"sha256:aa499b4c1994ca288a3f53e818237a55ecf7f6977c2609030e5fb1522e9a2079","observation_id":"6f76d691-41dd-4f25-8e98-bb48df7876ae","resolution":{"observed_at":"2026-08-06T10:58:06.558465Z","resolver_source":"raw_fallback","status":"unresolved"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-15T06:32:42.880941+00:00","source":"crossref"},{"observed_at":"2026-08-15T06:32:39.529945+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-06T10:58:06.538682Z","title":"M.; Papernot, N.; Goldenberg, A.; and Ghassemi, M","venue":null,"work_id":"b4214694-bea9-464a-a499-ebe1ad98f310","year":2021},"citing_paper":{"arxiv_id":"2507.23291","last_updated":"2025-08-03T23:23:03Z","snapshot_observed_at":"2026-08-15T20:46:11.551277Z","submitted_at":"2025-07-31T07:09:52Z","title":"Evaluating the Dynamics of Membership Privacy in Deep Learning","version":2},"reference_index":41,"source":"arxiv_source","source_observed_at":"2026-08-06T10:58:06.050809Z"},"links":{"citing_paper":"/paper/2507.23291"},"observation_digest":"sha256:ca2f16d9c00e934f450fbf4aee7ffa676959f0d62ac0ef4421939a92d37df6a1","observation_id":"345eb6d7-68f3-4e2c-b493-bd84c80e139c","resolution":{"observed_at":"2026-08-06T10:58:06.543060Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-15T06:32:42.880941+00:00","source":"crossref"},{"observed_at":"2026-08-15T06:32:39.529945+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"1812.05159","last_updated":"2019-11-15T17:08:30Z","snapshot_observed_at":"2026-08-14T17:44:31.188487Z","submitted_at":"2018-12-12T21:24:15Z","title":"An Empirical Study of Example Forgetting during Deep Neural Network Learning","version":3},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"1812.05159","snapshot_observed_at":"2026-08-06T10:58:06.059734Z","title":"T.; Trischler, A.; Bengio, Y.; and Gordon, G","venue":null,"work_id":null,"year":2019},"citing_paper":{"arxiv_id":"2507.23291","last_updated":"2025-08-03T23:23:03Z","snapshot_observed_at":"2026-08-15T20:46:11.551277Z","submitted_at":"2025-07-31T07:09:52Z","title":"Evaluating the Dynamics of Membership Privacy in Deep Learning","version":2},"reference_index":43,"source":"arxiv_source","source_observed_at":"2026-08-06T10:58:06.059734Z"},"links":{"cited_paper":"/paper/1812.05159","citing_paper":"/paper/2507.23291"},"observation_digest":"sha256:d77ef955466652390ffbbdf84b8f13885159fb0ac9a3d4cc3f693c8d519f4021","observation_id":"24fa866d-22d7-4a59-a0af-c10dcc523423","resolution":{"observed_at":"2026-08-06T10:58:06.059734Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-06T10:58:06.524402Z","title":"E.; Yu, L.; and Wei, W","venue":null,"work_id":"64f7379f-8ac7-4147-8d84-c57437bc6ca8","year":2021},"citing_paper":{"arxiv_id":"2507.23291","last_updated":"2025-08-03T23:23:03Z","snapshot_observed_at":"2026-08-15T20:46:11.551277Z","submitted_at":"2025-07-31T07:09:52Z","title":"Evaluating the Dynamics of Membership Privacy in Deep Learning","version":2},"reference_index":44,"source":"arxiv_source","source_observed_at":"2026-08-06T10:58:06.064101Z"},"links":{"citing_paper":"/paper/2507.23291"},"observation_digest":"sha256:afa0166186a77f48b2fc827264e4e5e4018f96c6b5798bde506ebd62345caed8","observation_id":"9f8dfcd9-0d38-4c05-bad8-08d1cfc3f032","resolution":{"observed_at":"2026-08-06T10:58:06.528698Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-15T06:32:42.880941+00:00","source":"crossref"},{"observed_at":"2026-08-15T06:32:39.529945+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"2111.08440","last_updated":"2022-04-11T09:23:43Z","snapshot_observed_at":"2026-08-13T17:33:59.202979Z","submitted_at":"2021-11-15T12:32:20Z","title":"On the Importance of Difficulty Calibration in Membership Inference Attacks","version":2},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2111.08440","snapshot_observed_at":"2026-08-06T10:58:06.068483Z","title":null,"venue":null,"work_id":null,"year":2022},"citing_paper":{"arxiv_id":"2507.23291","last_updated":"2025-08-03T23:23:03Z","snapshot_observed_at":"2026-08-15T20:46:11.551277Z","submitted_at":"2025-07-31T07:09:52Z","title":"Evaluating the Dynamics of Membership Privacy in Deep Learning","version":2},"reference_index":45,"source":"arxiv_source","source_observed_at":"2026-08-06T10:58:06.068483Z"},"links":{"cited_paper":"/paper/2111.08440","citing_paper":"/paper/2507.23291"},"observation_digest":"sha256:7fa3c9c371d340ebeffbd7f4372588835a1ee258a68b481066e1e5c8b795684e","observation_id":"0d6b4a36-0a9f-46f0-aba3-08feaf8f9ade","resolution":{"observed_at":"2026-08-06T10:58:06.068483Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"1708.07747","last_updated":"2017-09-15T21:29:49Z","snapshot_observed_at":"2026-08-13T15:13:33.081929Z","submitted_at":"2017-08-25T14:01:29Z","title":"Fashion-MNIST: a Novel Image Dataset for Benchmarking Machine Learning Algorithms","version":2},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"1708.07747","snapshot_observed_at":"2026-08-06T10:58:06.072661Z","title":null,"venue":null,"work_id":null,"year":2017},"citing_paper":{"arxiv_id":"2507.23291","last_updated":"2025-08-03T23:23:03Z","snapshot_observed_at":"2026-08-15T20:46:11.551277Z","submitted_at":"2025-07-31T07:09:52Z","title":"Evaluating the Dynamics of Membership Privacy in Deep Learning","version":2},"reference_index":46,"source":"arxiv_source","source_observed_at":"2026-08-06T10:58:06.072661Z"},"links":{"cited_paper":"/paper/1708.07747","citing_paper":"/paper/2507.23291"},"observation_digest":"sha256:bc16d3dc5597be73cd5f51a5d668d771192472c86f1ed68716482fb26cdd22b3","observation_id":"426a1ec1-34d4-4c44-8f76-11b8f8afc161","resolution":{"observed_at":"2026-08-06T10:58:06.072661Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-06T10:58:06.510591Z","title":"K.; Bindschaedler, V.; and Shokri, R","venue":null,"work_id":"155088fa-eea0-4a9a-b2df-0d90bc670aac","year":2022},"citing_paper":{"arxiv_id":"2507.23291","last_updated":"2025-08-03T23:23:03Z","snapshot_observed_at":"2026-08-15T20:46:11.551277Z","submitted_at":"2025-07-31T07:09:52Z","title":"Evaluating the Dynamics of Membership Privacy in Deep Learning","version":2},"reference_index":47,"source":"arxiv_source","source_observed_at":"2026-08-06T10:58:06.077082Z"},"links":{"citing_paper":"/paper/2507.23291"},"observation_digest":"sha256:9e751b11fbf00a8eea918148bc81f875b446b4bc06e56cf0d5074172dece21d8","observation_id":"1abfc3b4-f218-4191-a7fc-9bc48bfb0b67","resolution":{"observed_at":"2026-08-06T10:58:06.514807Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-15T06:32:42.880941+00:00","source":"crossref"},{"observed_at":"2026-08-15T06:32:39.529945+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"1709.01604","last_updated":"2018-05-04T22:43:43Z","snapshot_observed_at":"2026-08-15T02:51:03.472866Z","submitted_at":"2017-09-05T21:56:24Z","title":"Privacy Risk in Machine Learning: Analyzing the Connection to Overfitting","version":5},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"1709.01604","snapshot_observed_at":"2026-08-06T10:58:06.081119Z","title":null,"venue":null,"work_id":null,"year":2018},"citing_paper":{"arxiv_id":"2507.23291","last_updated":"2025-08-03T23:23:03Z","snapshot_observed_at":"2026-08-15T20:46:11.551277Z","submitted_at":"2025-07-31T07:09:52Z","title":"Evaluating the Dynamics of Membership Privacy in Deep Learning","version":2},"reference_index":48,"source":"arxiv_source","source_observed_at":"2026-08-06T10:58:06.081119Z"},"links":{"cited_paper":"/paper/1709.01604","citing_paper":"/paper/2507.23291"},"observation_digest":"sha256:5618b0514730d53656ca5332574ca80691721d38019b388784189754396d8f2d","observation_id":"549d4605-75da-4cfc-9357-21ed3b43440d","resolution":{"observed_at":"2026-08-06T10:58:06.081119Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"1605.07146","last_updated":"2017-06-14T06:06:48Z","snapshot_observed_at":"2026-08-13T10:21:59.687060Z","submitted_at":"2016-05-23T19:27:13Z","title":"Wide Residual Networks","version":4},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"1605.07146","snapshot_observed_at":"2026-08-06T10:58:06.085663Z","title":null,"venue":null,"work_id":null,"year":2016},"citing_paper":{"arxiv_id":"2507.23291","last_updated":"2025-08-03T23:23:03Z","snapshot_observed_at":"2026-08-15T20:46:11.551277Z","submitted_at":"2025-07-31T07:09:52Z","title":"Evaluating the Dynamics of Membership Privacy in Deep Learning","version":2},"reference_index":49,"source":"arxiv_source","source_observed_at":"2026-08-06T10:58:06.085663Z"},"links":{"cited_paper":"/paper/1605.07146","citing_paper":"/paper/2507.23291"},"observation_digest":"sha256:1c9c50587b2e459381b2d3c327d6ede04f85234b080ebbbebbff881a9bf57145","observation_id":"9a71c8fa-275d-4f58-8623-13584e9faf4f","resolution":{"observed_at":"2026-08-06T10:58:06.085663Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-06T10:58:06.496320Z","title":"u hle, V.; Paverd, A.; Ohrimenko, O.; K \\","venue":null,"work_id":"11f3693f-9532-4cde-b92e-9e4480a21f48","year":2020},"citing_paper":{"arxiv_id":"2507.23291","last_updated":"2025-08-03T23:23:03Z","snapshot_observed_at":"2026-08-15T20:46:11.551277Z","submitted_at":"2025-07-31T07:09:52Z","title":"Evaluating the Dynamics of Membership Privacy in Deep Learning","version":2},"reference_index":50,"source":"arxiv_source","source_observed_at":"2026-08-06T10:58:06.090088Z"},"links":{"citing_paper":"/paper/2507.23291"},"observation_digest":"sha256:27f0ddec4fda955fa3d0ef07248f4a7d39050cc4a404620b2b59c34b84ed6cd4","observation_id":"e7a27174-d7b1-4576-8aac-8a3a8299a92c","resolution":{"observed_at":"2026-08-06T10:58:06.501073Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-15T06:32:42.880941+00:00","source":"crossref"},{"observed_at":"2026-08-15T06:32:39.529945+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"2001.02610","last_updated":"2020-01-08T16:45:09Z","snapshot_observed_at":"2026-08-15T12:58:25.117101Z","submitted_at":"2020-01-08T16:45:09Z","title":"iDLG: Improved Deep Leakage from Gradients","version":1},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2001.02610","snapshot_observed_at":"2026-08-06T10:58:06.094314Z","title":"R.; and Bilen, H","venue":null,"work_id":null,"year":2020},"citing_paper":{"arxiv_id":"2507.23291","last_updated":"2025-08-03T23:23:03Z","snapshot_observed_at":"2026-08-15T20:46:11.551277Z","submitted_at":"2025-07-31T07:09:52Z","title":"Evaluating the Dynamics of Membership Privacy in Deep Learning","version":2},"reference_index":51,"source":"arxiv_source","source_observed_at":"2026-08-06T10:58:06.094314Z"},"links":{"cited_paper":"/paper/2001.02610","citing_paper":"/paper/2507.23291"},"observation_digest":"sha256:3c758f8b2dd8c550668f9866b944d0c5364cd6af4dc79ee5b2fef4e8a906f535","observation_id":"cac595b2-1d42-4488-8aa0-59d57798c100","resolution":{"observed_at":"2026-08-06T10:58:06.094314Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-06T10:58:06.481893Z","title":null,"venue":null,"work_id":"8277fefd-d3b0-41de-923c-95491e2fa00e","year":2019},"citing_paper":{"arxiv_id":"2507.23291","last_updated":"2025-08-03T23:23:03Z","snapshot_observed_at":"2026-08-15T20:46:11.551277Z","submitted_at":"2025-07-31T07:09:52Z","title":"Evaluating the Dynamics of Membership Privacy in Deep Learning","version":2},"reference_index":52,"source":"arxiv_source","source_observed_at":"2026-08-06T10:58:06.098901Z"},"links":{"citing_paper":"/paper/2507.23291"},"observation_digest":"sha256:5ce9c167aace1cebdb255d6bbc7db3e741bcb64835760511cfa7da5257c39719","observation_id":"90f08c26-bdd2-42e9-90a9-7724125d0d79","resolution":{"observed_at":"2026-08-06T10:58:06.486770Z","resolver_source":"raw_fallback","status":"unresolved"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-15T06:32:42.880941+00:00","source":"crossref"},{"observed_at":"2026-08-15T06:32:39.529945+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":null,"snapshot_observed_at":"2026-08-06T10:58:06.103133Z","title":", \" * write output.state after.block = add.period write newline","venue":null,"work_id":null,"year":null},"citing_paper":{"arxiv_id":"2507.23291","last_updated":"2025-08-03T23:23:03Z","snapshot_observed_at":"2026-08-15T20:46:11.551277Z","submitted_at":"2025-07-31T07:09:52Z","title":"Evaluating the Dynamics of Membership Privacy in Deep Learning","version":2},"reference_index":53,"source":"arxiv_source","source_observed_at":"2026-08-06T10:58:06.103133Z"},"links":{"citing_paper":"/paper/2507.23291"},"observation_digest":"sha256:5b6a05bd4042aa544706b3199d307d75f3dc1b0cf834828e120d675c63ca0bff","observation_id":"ee23bfb2-0395-4448-a25e-0902d1d6c842","resolution":{"observed_at":"2026-08-06T10:58:06.103133Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":null,"snapshot_observed_at":"2026-08-06T10:58:06.107943Z","title":"write newline","venue":null,"work_id":null,"year":null},"citing_paper":{"arxiv_id":"2507.23291","last_updated":"2025-08-03T23:23:03Z","snapshot_observed_at":"2026-08-15T20:46:11.551277Z","submitted_at":"2025-07-31T07:09:52Z","title":"Evaluating the Dynamics of Membership Privacy in Deep Learning","version":2},"reference_index":54,"source":"arxiv_source","source_observed_at":"2026-08-06T10:58:06.107943Z"},"links":{"citing_paper":"/paper/2507.23291"},"observation_digest":"sha256:db8b7d7290bf46daf863998589cc050f7c214150d99e49527867dff898e16795","observation_id":"d65f2599-36c6-410c-a131-e2b8cac17d63","resolution":{"observed_at":"2026-08-06T10:58:06.107943Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}}],"paper":{"arxiv_id":"2507.23291","last_updated":"2025-08-03T23:23:03Z","latest_version":2,"primary_category":"cs.LG","snapshot_observed_at":"2026-08-15T20:46:11.551277Z","submitted_at":"2025-07-31T07:09:52Z","title":"Evaluating the Dynamics of Membership Privacy in Deep Learning"},"reference_resolution":{"displayed":53,"state_counts":{"malformed_identifier":0,"metadata_mismatch":0,"parse_uncertain":0,"unresolved":46,"verified_exact":1,"verified_fuzzy":6},"total_outbound_references":53},"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":"2026-08-15T06:32:42.880941+00:00","source":"crossref"},{"observed_at":"2026-08-15T06:32:39.529945+00:00","source":"retraction_watch"}],"thesis":"As of 15 August 2026, this Paper Citation Record lists 53 of 53 outbound references and 1 inbound Pith citation observation for arXiv:2507.23291."}