{"as_of":"2026-08-17T12:19:00Z","caps":{"database_statements":6,"inbound":100,"outbound":100},"context_digest":"sha256:298662d197ed0f6ec839c08c5a2f93458d210b2b1e013470e291937d52f0337b","coverage":[{"denominator":32,"lane":"reference_resolution","note":"Typed states for the displayed outbound observations.","records_observed":32,"source":"paper_references, paper_reference_links","source_observed_at":"2026-08-15T22:00:43.200520Z","state":"measured"},{"denominator":33,"lane":"standing_notices","note":"One-hop event checks from named stored sources.","records_observed":33,"source":"scholarly_work_events, retraction_status_cache","source_observed_at":"2026-08-17T06:30:58.91139+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":"2026-05-09T20:24:59.721421Z","state":"measured"},{"denominator":1,"lane":"external_citation_measurements","note":"A source-named dated measurement, never combined with another source.","records_observed":0,"source":"arxiv_reference","source_observed_at":"2026-05-11T15:16:08.326759Z","state":"measured"}],"external_citation_measurements":[],"inbound":[{"citation":{"cited_paper":{"arxiv_id":"2505.08557","last_updated":"2025-05-13T13:33:36Z","snapshot_observed_at":"2026-08-15T21:49:35.191126Z","submitted_at":"2025-05-13T13:33:36Z","title":"Online Learning and Unlearning","version":1},"cited_work":{"arxiv_id":"2505.08557","doi":null,"metadata_source":"arxiv_reference","pith_arxiv_id":"2505.08557","snapshot_observed_at":"2026-06-05T21:23:00.469572Z","title":"arXiv preprint arXiv:2505.08557 , year=","venue":null,"work_id":"ba5d935a-675d-4557-b2af-b29c8ff537ef","year":null},"citing_paper":{"arxiv_id":"2605.00638","last_updated":"2026-05-01T13:20:13Z","snapshot_observed_at":"2026-08-11T10:36:38.695068Z","submitted_at":"2026-05-01T13:20:13Z","title":"Unlearning Offline Stochastic Multi-Armed Bandits","version":1},"reference_index":17,"source":"arxiv_source","source_observed_at":"2026-05-09T20:24:59.721421Z"},"links":{"cited_paper":"/paper/2505.08557","citing_paper":"/paper/2605.00638"},"observation_digest":"sha256:cc7dd2f15a0cd7205bade9dec1d88686e92fcdd48d107751055e7d8980834d7e","observation_id":"b00b54c2-ad7c-463a-ad9e-a94e93625a64","resolution":{"observed_at":"2026-05-11T15:16:08.340890Z","resolver_source":"arxiv_id","status":"verified_exact"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-17T06:30:58.91139+00:00","source":"crossref"},{"observed_at":"2026-08-17T06:30:54.323127+00:00","source":"retraction_watch"}],"state":"measured"}}],"links":{"evidence":"/evidence","html":"/paper/2505.08557/citation-record","integrity":"/paper/2505.08557/integrity","json":"/paper/2505.08557/citation-record.json","paper":"/paper/2505.08557"},"outbound":[{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-15T22:00:43.804922Z","title":"Membership inference attacks against machine learning models","venue":null,"work_id":"87827764-2fee-44f3-85b7-d8f005a483fa","year":2017},"citing_paper":{"arxiv_id":"2505.08557","last_updated":"2025-05-13T13:33:36Z","snapshot_observed_at":"2026-08-15T21:49:35.191126Z","submitted_at":"2025-05-13T13:33:36Z","title":"Online Learning and Unlearning","version":1},"reference_index":1,"source":"pdf_text","source_observed_at":"2026-08-15T22:00:43.070985Z"},"links":{"citing_paper":"/paper/2505.08557"},"observation_digest":"sha256:48b83e268802fc96f9dce8f81b2e98ba277f0b68511207688035fc06a8e02c48","observation_id":"f965bb14-20e6-43c4-b4ef-96674b8abbd8","resolution":{"observed_at":"2026-08-15T22:00:43.809406Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-17T06:30:58.91139+00:00","source":"crossref"},{"observed_at":"2026-08-17T06:30:54.323127+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-15T22:00:43.790613Z","title":"Reconstructing traini ng data from model gradient, provably","venue":null,"work_id":"ebf1477d-9aa9-46a2-b05d-4de7cc6b2001","year":2023},"citing_paper":{"arxiv_id":"2505.08557","last_updated":"2025-05-13T13:33:36Z","snapshot_observed_at":"2026-08-15T21:49:35.191126Z","submitted_at":"2025-05-13T13:33:36Z","title":"Online Learning and Unlearning","version":1},"reference_index":2,"source":"pdf_text","source_observed_at":"2026-08-15T22:00:43.076628Z"},"links":{"citing_paper":"/paper/2505.08557"},"observation_digest":"sha256:b0bd98a699e40a8a209ba426467a474bb0ff433f8744e60577988915e84a46d0","observation_id":"2f9e60a1-b996-4da8-b5fc-a44e2982a72d","resolution":{"observed_at":"2026-08-15T22:00:43.795314Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-17T06:30:58.91139+00:00","source":"crossref"},{"observed_at":"2026-08-17T06:30:54.323127+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-15T22:00:43.770336Z","title":"Corrective machine unlearning","venue":null,"work_id":"31c34538-756d-48e3-a91a-eb91f3b5f2a9","year":2024},"citing_paper":{"arxiv_id":"2505.08557","last_updated":"2025-05-13T13:33:36Z","snapshot_observed_at":"2026-08-15T21:49:35.191126Z","submitted_at":"2025-05-13T13:33:36Z","title":"Online Learning and Unlearning","version":1},"reference_index":3,"source":"pdf_text","source_observed_at":"2026-08-15T22:00:43.080880Z"},"links":{"citing_paper":"/paper/2505.08557"},"observation_digest":"sha256:c57aa85399490cd2fe79c24b9fd5fb4e329a09da79e71f31f19d91b76b929ed7","observation_id":"fdb8780e-f03c-41eb-b78f-dc1880e05826","resolution":{"observed_at":"2026-08-15T22:00:43.775815Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-17T06:30:58.91139+00:00","source":"crossref"},{"observed_at":"2026-08-17T06:30:54.323127+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-15T22:00:43.748131Z","title":"Des cent-to-delete: Gradient-based methods for ma- chine unlearning","venue":null,"work_id":"2b1af34d-d42d-47d1-946b-a4ba8fb46c45","year":2021},"citing_paper":{"arxiv_id":"2505.08557","last_updated":"2025-05-13T13:33:36Z","snapshot_observed_at":"2026-08-15T21:49:35.191126Z","submitted_at":"2025-05-13T13:33:36Z","title":"Online Learning and Unlearning","version":1},"reference_index":4,"source":"pdf_text","source_observed_at":"2026-08-15T22:00:43.085816Z"},"links":{"citing_paper":"/paper/2505.08557"},"observation_digest":"sha256:14c34199108b8418087eb9b14ce3874fb09a7f03295ff20e7818253aa2e07f5c","observation_id":"eeb8f3f2-a3d7-42fc-a195-9afbb2d31749","resolution":{"observed_at":"2026-08-15T22:00:43.755614Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-17T06:30:58.91139+00:00","source":"crossref"},{"observed_at":"2026-08-17T06:30:54.323127+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-15T22:00:43.734100Z","title":"Choquette-Choo, Hengrui Jia, Adelin Travers, Baiwu Zhang, David Lie, and Nicolas Papernot","venue":null,"work_id":"aa5e903f-710a-4f0c-826e-a97d0cbe06f5","year":2021},"citing_paper":{"arxiv_id":"2505.08557","last_updated":"2025-05-13T13:33:36Z","snapshot_observed_at":"2026-08-15T21:49:35.191126Z","submitted_at":"2025-05-13T13:33:36Z","title":"Online Learning and Unlearning","version":1},"reference_index":5,"source":"pdf_text","source_observed_at":"2026-08-15T22:00:43.090434Z"},"links":{"citing_paper":"/paper/2505.08557"},"observation_digest":"sha256:b88c9aa49aaa20cfbf1ff420c433254e5f20248d5dda2d356d6b13d0a769901d","observation_id":"4d26d671-28c7-4d87-81a2-f7c98be1d66e","resolution":{"observed_at":"2026-08-15T22:00:43.738650Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-17T06:30:58.91139+00:00","source":"crossref"},{"observed_at":"2026-08-17T06:30:54.323127+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-15T22:00:43.720970Z","title":"Remember what you want to forget: algorithms for machine unlearning","venue":null,"work_id":"5116209e-ba13-42d0-afed-6535b9086c48","year":2021},"citing_paper":{"arxiv_id":"2505.08557","last_updated":"2025-05-13T13:33:36Z","snapshot_observed_at":"2026-08-15T21:49:35.191126Z","submitted_at":"2025-05-13T13:33:36Z","title":"Online Learning and Unlearning","version":1},"reference_index":6,"source":"pdf_text","source_observed_at":"2026-08-15T22:00:43.095177Z"},"links":{"citing_paper":"/paper/2505.08557"},"observation_digest":"sha256:7b63519ad2ed31759de2305c6452c90e4aeea93da572355bc296f271f7dc303a","observation_id":"7a5db523-a0d3-40e9-a76b-d09161170a8b","resolution":{"observed_at":"2026-08-15T22:00:43.725572Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-17T06:30:58.91139+00:00","source":"crossref"},{"observed_at":"2026-08-17T06:30:54.323127+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":null,"snapshot_observed_at":"2026-08-15T22:00:43.099738Z","title":"Rewind-to-delete: Certiﬁe d machine unlearning for nonconvex functions","venue":null,"work_id":null,"year":2024},"citing_paper":{"arxiv_id":"2505.08557","last_updated":"2025-05-13T13:33:36Z","snapshot_observed_at":"2026-08-15T21:49:35.191126Z","submitted_at":"2025-05-13T13:33:36Z","title":"Online Learning and Unlearning","version":1},"reference_index":7,"source":"pdf_text","source_observed_at":"2026-08-15T22:00:43.099738Z"},"links":{"citing_paper":"/paper/2505.08557"},"observation_digest":"sha256:278aba86d72179ef041b6583a1ea82b099404ba6e5238bc747ca35972cfcf085","observation_id":"6e12a855-4c9a-4681-8e48-c2df6b9b3ef2","resolution":{"observed_at":"2026-08-15T22:00:43.099738Z","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":"2026-08-15T22:00:43.707736Z","title":"Algor ithms that approximate data removal: New results and limitations","venue":null,"work_id":"4e353ee6-5be2-4265-afaa-a211706413da","year":2022},"citing_paper":{"arxiv_id":"2505.08557","last_updated":"2025-05-13T13:33:36Z","snapshot_observed_at":"2026-08-15T21:49:35.191126Z","submitted_at":"2025-05-13T13:33:36Z","title":"Online Learning and Unlearning","version":1},"reference_index":8,"source":"pdf_text","source_observed_at":"2026-08-15T22:00:43.103636Z"},"links":{"citing_paper":"/paper/2505.08557"},"observation_digest":"sha256:d6c188d534b9ca826522d158fb88f9a28a555670be3aa0a499a1537c75955b98","observation_id":"84220bbb-0cfc-4dd6-a0ba-f3fef55ac619","resolution":{"observed_at":"2026-08-15T22:00:43.712513Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-17T06:30:58.91139+00:00","source":"crossref"},{"observed_at":"2026-08-17T06:30:54.323127+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-15T22:00:43.693246Z","title":"Control, conﬁdentiality, and the right to be forgotten","venue":null,"work_id":"36de40d5-5e22-4bac-bbfc-56daec38e5bb","year":2023},"citing_paper":{"arxiv_id":"2505.08557","last_updated":"2025-05-13T13:33:36Z","snapshot_observed_at":"2026-08-15T21:49:35.191126Z","submitted_at":"2025-05-13T13:33:36Z","title":"Online Learning and Unlearning","version":1},"reference_index":9,"source":"pdf_text","source_observed_at":"2026-08-15T22:00:43.107674Z"},"links":{"citing_paper":"/paper/2505.08557"},"observation_digest":"sha256:7bd4b7b50a068a4cf1261dd44415b5424d30a7bc3417eed65eab9930acab40d2","observation_id":"cc7872d6-49be-4643-87d0-425fa4d48221","resolution":{"observed_at":"2026-08-15T22:00:43.698458Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-17T06:30:58.91139+00:00","source":"crossref"},{"observed_at":"2026-08-17T06:30:54.323127+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"1909.05207","last_updated":"2023-08-06T14:24:26Z","snapshot_observed_at":"2026-08-14T19:15:36.367708Z","submitted_at":"2019-09-07T19:06:23Z","title":"Introduction to Online Convex Optimization","version":3},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"1909.05207","snapshot_observed_at":"2026-08-15T22:00:43.112037Z","title":"Introduction to online convex optimizatio n","venue":null,"work_id":null,"year":1909},"citing_paper":{"arxiv_id":"2505.08557","last_updated":"2025-05-13T13:33:36Z","snapshot_observed_at":"2026-08-15T21:49:35.191126Z","submitted_at":"2025-05-13T13:33:36Z","title":"Online Learning and Unlearning","version":1},"reference_index":10,"source":"pdf_text","source_observed_at":"2026-08-15T22:00:43.112037Z"},"links":{"cited_paper":"/paper/1909.05207","citing_paper":"/paper/2505.08557"},"observation_digest":"sha256:3cbb61d7d0aa2d36593613a9c163c651f4aa1b7059b94f95ab2e21c39296b72c","observation_id":"6db6cb89-adc8-420c-ba42-c6dc1fe2bf0f","resolution":{"observed_at":"2026-08-15T22:00:43.112037Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"1912.13213","last_updated":"2026-06-21T08:13:27Z","snapshot_observed_at":"2026-08-15T05:32:55.984958Z","submitted_at":"2019-12-31T08:16:31Z","title":"Online Learning: A Modern Introduction Using Convex Optimization","version":10},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"1912.13213","snapshot_observed_at":"2026-08-15T22:00:43.116221Z","title":"A modern introduction to online lea rning","venue":null,"work_id":null,"year":1912},"citing_paper":{"arxiv_id":"2505.08557","last_updated":"2025-05-13T13:33:36Z","snapshot_observed_at":"2026-08-15T21:49:35.191126Z","submitted_at":"2025-05-13T13:33:36Z","title":"Online Learning and Unlearning","version":1},"reference_index":11,"source":"pdf_text","source_observed_at":"2026-08-15T22:00:43.116221Z"},"links":{"cited_paper":"/paper/1912.13213","citing_paper":"/paper/2505.08557"},"observation_digest":"sha256:4d7e6adc25a992bc6b7301b26f2e6e2fe53478d5ea4fda0fd2eb3c37f14195d9","observation_id":"8a7242ce-0719-4326-8e37-08717824dfc8","resolution":{"observed_at":"2026-08-15T22:00:43.116221Z","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":"2026-08-15T22:00:43.679188Z","title":"Certiﬁed data removal from machine learning models","venue":null,"work_id":"7a972002-4b7f-47ee-a7ec-a4fe1eeb53cb","year":2020},"citing_paper":{"arxiv_id":"2505.08557","last_updated":"2025-05-13T13:33:36Z","snapshot_observed_at":"2026-08-15T21:49:35.191126Z","submitted_at":"2025-05-13T13:33:36Z","title":"Online Learning and Unlearning","version":1},"reference_index":12,"source":"pdf_text","source_observed_at":"2026-08-15T22:00:43.120508Z"},"links":{"citing_paper":"/paper/2505.08557"},"observation_digest":"sha256:577d04cef88ff576cb56ed15c7edb2cca0dec02a9f1e269829c73f329c5d69c1","observation_id":"9f8114e3-648a-49c7-993f-ad344f97843f","resolution":{"observed_at":"2026-08-15T22:00:43.683805Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-17T06:30:58.91139+00:00","source":"crossref"},{"observed_at":"2026-08-17T06:30:54.323127+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-15T22:00:43.663774Z","title":"Cert iﬁed machine unlearning via noisy stochastic gradient descent","venue":null,"work_id":"76124efd-812f-414c-9659-7c37c8d6f74b","year":2024},"citing_paper":{"arxiv_id":"2505.08557","last_updated":"2025-05-13T13:33:36Z","snapshot_observed_at":"2026-08-15T21:49:35.191126Z","submitted_at":"2025-05-13T13:33:36Z","title":"Online Learning and Unlearning","version":1},"reference_index":13,"source":"pdf_text","source_observed_at":"2026-08-15T22:00:43.124512Z"},"links":{"citing_paper":"/paper/2505.08557"},"observation_digest":"sha256:961d3d5dcea448de3003c2598ccb1d1af5bf8157de51b434ec760ad37c9f20b7","observation_id":"40c6f4e0-f5cc-41bc-aec3-2b98d5520c2c","resolution":{"observed_at":"2026-08-15T22:00:43.669545Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-17T06:30:58.91139+00:00","source":"crossref"},{"observed_at":"2026-08-17T06:30:54.323127+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-15T22:00:43.648193Z","title":"Differential privacy","venue":null,"work_id":"2bc1c686-a146-42e3-a0ba-2f26c39936b7","year":2006},"citing_paper":{"arxiv_id":"2505.08557","last_updated":"2025-05-13T13:33:36Z","snapshot_observed_at":"2026-08-15T21:49:35.191126Z","submitted_at":"2025-05-13T13:33:36Z","title":"Online Learning and Unlearning","version":1},"reference_index":14,"source":"pdf_text","source_observed_at":"2026-08-15T22:00:43.128607Z"},"links":{"citing_paper":"/paper/2505.08557"},"observation_digest":"sha256:73db1efe7bbc2239ada368604b1c1d54642b74b8635eed6fa9fce9b7775ef0ae","observation_id":"87e30934-8c11-47c0-82ee-a9d9c95016af","resolution":{"observed_at":"2026-08-15T22:00:43.652754Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-17T06:30:58.91139+00:00","source":"crossref"},{"observed_at":"2026-08-17T06:30:54.323127+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-15T22:00:43.632661Z","title":"Counting distinct elements in the turnstile model with differential privacy u nder continual observation","venue":null,"work_id":"bf44e354-8ae8-44c3-9b22-ac4e6f3fa419","year":2023},"citing_paper":{"arxiv_id":"2505.08557","last_updated":"2025-05-13T13:33:36Z","snapshot_observed_at":"2026-08-15T21:49:35.191126Z","submitted_at":"2025-05-13T13:33:36Z","title":"Online Learning and Unlearning","version":1},"reference_index":15,"source":"pdf_text","source_observed_at":"2026-08-15T22:00:43.132612Z"},"links":{"citing_paper":"/paper/2505.08557"},"observation_digest":"sha256:74591dda78a17a8cfbc913173a2c809ab0b41f1028ca2631e47725e3e5031b5d","observation_id":"fd90515d-10d1-4db9-854a-17426c22b400","resolution":{"observed_at":"2026-08-15T22:00:43.638631Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-17T06:30:58.91139+00:00","source":"crossref"},{"observed_at":"2026-08-17T06:30:54.323127+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-15T22:00:43.611575Z","title":"Online convex programming and gener alized inﬁnitesimal gradient ascent","venue":null,"work_id":"2acaf46c-aac0-43f3-a3c9-61f9f0bc36f9","year":2003},"citing_paper":{"arxiv_id":"2505.08557","last_updated":"2025-05-13T13:33:36Z","snapshot_observed_at":"2026-08-15T21:49:35.191126Z","submitted_at":"2025-05-13T13:33:36Z","title":"Online Learning and Unlearning","version":1},"reference_index":16,"source":"pdf_text","source_observed_at":"2026-08-15T22:00:43.136306Z"},"links":{"citing_paper":"/paper/2505.08557"},"observation_digest":"sha256:494f19c9b4e4fef06895c837ed2c8a379b5dd3e7029153a3569542e0a6f4743f","observation_id":"099260f8-340e-47d6-bd8b-49e46768e5bf","resolution":{"observed_at":"2026-08-15T22:00:43.616838Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-17T06:30:58.91139+00:00","source":"crossref"},{"observed_at":"2026-08-17T06:30:54.323127+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-15T22:00:43.596722Z","title":"Dynamic regret of convex and smooth functions","venue":null,"work_id":"eb18c0f5-4918-4088-9589-37c63b5efee1","year":2020},"citing_paper":{"arxiv_id":"2505.08557","last_updated":"2025-05-13T13:33:36Z","snapshot_observed_at":"2026-08-15T21:49:35.191126Z","submitted_at":"2025-05-13T13:33:36Z","title":"Online Learning and Unlearning","version":1},"reference_index":17,"source":"pdf_text","source_observed_at":"2026-08-15T22:00:43.140103Z"},"links":{"citing_paper":"/paper/2505.08557"},"observation_digest":"sha256:1a0486bc37497d52425db43a010080cad52c7307dfb4c409a25838e8296789a4","observation_id":"28ef3035-736e-4e72-a816-979fc535656d","resolution":{"observed_at":"2026-08-15T22:00:43.601988Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-17T06:30:58.91139+00:00","source":"crossref"},{"observed_at":"2026-08-17T06:30:54.323127+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-15T22:00:43.578793Z","title":"(Nearly) optim al algorithms for private online learning in full-information and bandit settings","venue":null,"work_id":"5a731f27-414e-4d63-836d-dd3852c1e435","year":2013},"citing_paper":{"arxiv_id":"2505.08557","last_updated":"2025-05-13T13:33:36Z","snapshot_observed_at":"2026-08-15T21:49:35.191126Z","submitted_at":"2025-05-13T13:33:36Z","title":"Online Learning and Unlearning","version":1},"reference_index":18,"source":"pdf_text","source_observed_at":"2026-08-15T22:00:43.143736Z"},"links":{"citing_paper":"/paper/2505.08557"},"observation_digest":"sha256:31c439d05db36023957369b5431954c70b05c756a5fc77574f92503c7369b767","observation_id":"7960c4f4-fff8-44f2-9741-ed8dd4c36ebc","resolution":{"observed_at":"2026-08-15T22:00:43.583642Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-17T06:30:58.91139+00:00","source":"crossref"},{"observed_at":"2026-08-17T06:30:54.323127+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-15T22:00:43.561192Z","title":"Differentially private online learning","venue":null,"work_id":"0f79164a-3793-4b34-bd01-bd5ea0cffc21","year":2012},"citing_paper":{"arxiv_id":"2505.08557","last_updated":"2025-05-13T13:33:36Z","snapshot_observed_at":"2026-08-15T21:49:35.191126Z","submitted_at":"2025-05-13T13:33:36Z","title":"Online Learning and Unlearning","version":1},"reference_index":19,"source":"pdf_text","source_observed_at":"2026-08-15T22:00:43.147553Z"},"links":{"citing_paper":"/paper/2505.08557"},"observation_digest":"sha256:7b3f8b1923357aef3ce1aed84d287705b024152e5edc887ec961ee15088d3a21","observation_id":"8933d302-3875-41b2-bf22-04831a09178f","resolution":{"observed_at":"2026-08-15T22:00:43.566865Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-17T06:30:58.91139+00:00","source":"crossref"},{"observed_at":"2026-08-17T06:30:54.323127+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-15T22:00:43.546191Z","title":"Privacy Ampliﬁcation by Iteration","venue":null,"work_id":"8d4b8a96-90db-446d-8d73-4cdac74d2f69","year":2018},"citing_paper":{"arxiv_id":"2505.08557","last_updated":"2025-05-13T13:33:36Z","snapshot_observed_at":"2026-08-15T21:49:35.191126Z","submitted_at":"2025-05-13T13:33:36Z","title":"Online Learning and Unlearning","version":1},"reference_index":20,"source":"pdf_text","source_observed_at":"2026-08-15T22:00:43.151214Z"},"links":{"citing_paper":"/paper/2505.08557"},"observation_digest":"sha256:af6f4c603dfd64eaba6f59b6ef432f0ee96ea30be55ac2c84c57836151c572eb","observation_id":"9e671a12-f53b-458a-9cfc-ed925ff28693","resolution":{"observed_at":"2026-08-15T22:00:43.550547Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-17T06:30:58.91139+00:00","source":"crossref"},{"observed_at":"2026-08-17T06:30:54.323127+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-15T22:00:43.531038Z","title":"Privacy of noisy sto chastic gradient descent: More iterations without more privacy loss","venue":null,"work_id":"1b0bbf50-7210-462f-bfa1-762dde4573e7","year":2022},"citing_paper":{"arxiv_id":"2505.08557","last_updated":"2025-05-13T13:33:36Z","snapshot_observed_at":"2026-08-15T21:49:35.191126Z","submitted_at":"2025-05-13T13:33:36Z","title":"Online Learning and Unlearning","version":1},"reference_index":21,"source":"pdf_text","source_observed_at":"2026-08-15T22:00:43.155145Z"},"links":{"citing_paper":"/paper/2505.08557"},"observation_digest":"sha256:c90b46afa7df1b1d8961085af5df33d40a32b355c818618e6a3b314ac431a9ca","observation_id":"5d780770-17f9-44e2-9f23-483f6d9c9632","resolution":{"observed_at":"2026-08-15T22:00:43.535896Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-17T06:30:58.91139+00:00","source":"crossref"},{"observed_at":"2026-08-17T06:30:54.323127+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-15T22:00:43.514520Z","title":"Resolving the mixin g time of the langevin algorithm to its stationary distribution for log-concave sampling","venue":null,"work_id":"c899665c-5d85-4675-a822-2d2b2611fb07","year":2023},"citing_paper":{"arxiv_id":"2505.08557","last_updated":"2025-05-13T13:33:36Z","snapshot_observed_at":"2026-08-15T21:49:35.191126Z","submitted_at":"2025-05-13T13:33:36Z","title":"Online Learning and Unlearning","version":1},"reference_index":22,"source":"pdf_text","source_observed_at":"2026-08-15T22:00:43.159419Z"},"links":{"citing_paper":"/paper/2505.08557"},"observation_digest":"sha256:d00bd0e5fa0a77097ac6bc8e92bf693c5f9a00e33efefa70a2ecdce9783f22b5","observation_id":"2989ff60-76f7-40a8-bdcb-e9b514517804","resolution":{"observed_at":"2026-08-15T22:00:43.519106Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-17T06:30:58.91139+00:00","source":"crossref"},{"observed_at":"2026-08-17T06:30:54.323127+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-15T22:00:43.501177Z","title":"Train faster , generalize better: Stability of stochastic gradient descent","venue":null,"work_id":"eb110a96-a0f9-42df-9377-4f12a5dc1191","year":2016},"citing_paper":{"arxiv_id":"2505.08557","last_updated":"2025-05-13T13:33:36Z","snapshot_observed_at":"2026-08-15T21:49:35.191126Z","submitted_at":"2025-05-13T13:33:36Z","title":"Online Learning and Unlearning","version":1},"reference_index":23,"source":"pdf_text","source_observed_at":"2026-08-15T22:00:43.163228Z"},"links":{"citing_paper":"/paper/2505.08557"},"observation_digest":"sha256:ae30072f4abfe9c443507bc8558b4d5183d0e7e182412009801faa17aa22e3db","observation_id":"1f101f95-5d8e-411b-9bd7-e6856fde5b40","resolution":{"observed_at":"2026-08-15T22:00:43.506032Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-17T06:30:58.91139+00:00","source":"crossref"},{"observed_at":"2026-08-17T06:30:54.323127+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-15T22:00:43.485922Z","title":"On the gene ralization ability of online gradient descent algorithm under the quadratic growth condition","venue":null,"work_id":"0ef1aec3-c1f6-4836-96b5-f4717977de44","year":2018},"citing_paper":{"arxiv_id":"2505.08557","last_updated":"2025-05-13T13:33:36Z","snapshot_observed_at":"2026-08-15T21:49:35.191126Z","submitted_at":"2025-05-13T13:33:36Z","title":"Online Learning and Unlearning","version":1},"reference_index":24,"source":"pdf_text","source_observed_at":"2026-08-15T22:00:43.167279Z"},"links":{"citing_paper":"/paper/2505.08557"},"observation_digest":"sha256:601feef671e985d71fdc04fff9b409f85cde2489d96c4404e1a01cdbe9093a86","observation_id":"d3531e70-7df1-42ed-98a8-a15235753afe","resolution":{"observed_at":"2026-08-15T22:00:43.491198Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-17T06:30:58.91139+00:00","source":"crossref"},{"observed_at":"2026-08-17T06:30:54.323127+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-15T22:00:43.472138Z","title":"Logarithmi c regret algorithms for online convex optimization","venue":null,"work_id":"6f93eaa3-0190-44ba-ba1c-b09cc024fc8f","year":2007},"citing_paper":{"arxiv_id":"2505.08557","last_updated":"2025-05-13T13:33:36Z","snapshot_observed_at":"2026-08-15T21:49:35.191126Z","submitted_at":"2025-05-13T13:33:36Z","title":"Online Learning and Unlearning","version":1},"reference_index":25,"source":"pdf_text","source_observed_at":"2026-08-15T22:00:43.171320Z"},"links":{"citing_paper":"/paper/2505.08557"},"observation_digest":"sha256:649dc144eab90404d7fdc99ba852254882f2bec27305cf18c9083292d024e60c","observation_id":"a8020b5b-6320-417d-afbb-7e9d22aee34c","resolution":{"observed_at":"2026-08-15T22:00:43.476778Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-17T06:30:58.91139+00:00","source":"crossref"},{"observed_at":"2026-08-17T06:30:54.323127+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-15T22:00:43.455217Z","title":"Adaptive subgradient methods for online learning and stochastic optimization","venue":null,"work_id":"7e56f40b-aefa-467e-ba86-063dbc7adb4c","year":2011},"citing_paper":{"arxiv_id":"2505.08557","last_updated":"2025-05-13T13:33:36Z","snapshot_observed_at":"2026-08-15T21:49:35.191126Z","submitted_at":"2025-05-13T13:33:36Z","title":"Online Learning and Unlearning","version":1},"reference_index":26,"source":"pdf_text","source_observed_at":"2026-08-15T22:00:43.175070Z"},"links":{"citing_paper":"/paper/2505.08557"},"observation_digest":"sha256:eff1fa2db0a12a49adf493ca6bcc288a56496a19c006aeaa5695b91eb52eafec","observation_id":"93004344-ac58-48bb-9e65-de260d7e7528","resolution":{"observed_at":"2026-08-15T22:00:43.460829Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-17T06:30:58.91139+00:00","source":"crossref"},{"observed_at":"2026-08-17T06:30:54.323127+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"1009.3896","last_updated":"2012-11-26T06:42:25Z","snapshot_observed_at":"2026-08-15T05:08:18.811569Z","submitted_at":"2010-09-20T17:35:35Z","title":"Optimistic Rates for Learning with a Smooth Loss","version":2},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"1009.3896","snapshot_observed_at":"2026-08-15T22:00:43.178901Z","title":"Op timistic rates for learning with a smooth loss","venue":null,"work_id":null,"year":2012},"citing_paper":{"arxiv_id":"2505.08557","last_updated":"2025-05-13T13:33:36Z","snapshot_observed_at":"2026-08-15T21:49:35.191126Z","submitted_at":"2025-05-13T13:33:36Z","title":"Online Learning and Unlearning","version":1},"reference_index":27,"source":"pdf_text","source_observed_at":"2026-08-15T22:00:43.178901Z"},"links":{"cited_paper":"/paper/1009.3896","citing_paper":"/paper/2505.08557"},"observation_digest":"sha256:ac67947ddc88242ab3530ef384743748684120745b5820a37906c44168a5de9d","observation_id":"6b2b718a-47a5-4ed8-90f4-a84d87ab8737","resolution":{"observed_at":"2026-08-15T22:00:43.178901Z","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":"2026-08-15T22:00:43.435247Z","title":"Ticketed learning-unlearning schemes","venue":null,"work_id":"ca911784-249a-4359-b83f-e7020df3214c","year":2023},"citing_paper":{"arxiv_id":"2505.08557","last_updated":"2025-05-13T13:33:36Z","snapshot_observed_at":"2026-08-15T21:49:35.191126Z","submitted_at":"2025-05-13T13:33:36Z","title":"Online Learning and Unlearning","version":1},"reference_index":28,"source":"pdf_text","source_observed_at":"2026-08-15T22:00:43.183416Z"},"links":{"citing_paper":"/paper/2505.08557"},"observation_digest":"sha256:eca5786be8a9c70f6c510544e6705190ae3f44e3ac899bf6ba56c048a2f04009","observation_id":"2303a9a2-48a8-4108-b8d4-8e42367389ec","resolution":{"observed_at":"2026-08-15T22:00:43.443842Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-17T06:30:58.91139+00:00","source":"crossref"},{"observed_at":"2026-08-17T06:30:54.323127+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-15T22:00:43.419529Z","title":"Rényi differential privacy","venue":null,"work_id":"bd688097-fc21-4601-b59a-744d7f1c0d08","year":2017},"citing_paper":{"arxiv_id":"2505.08557","last_updated":"2025-05-13T13:33:36Z","snapshot_observed_at":"2026-08-15T21:49:35.191126Z","submitted_at":"2025-05-13T13:33:36Z","title":"Online Learning and Unlearning","version":1},"reference_index":29,"source":"pdf_text","source_observed_at":"2026-08-15T22:00:43.187808Z"},"links":{"citing_paper":"/paper/2505.08557"},"observation_digest":"sha256:cc5f9a5d6e8f82bd0fca27404e1faea401379a59974b58e0b52caddea4c3ef87","observation_id":"04ce3368-d690-4346-aa8b-1c3863187d2a","resolution":{"observed_at":"2026-08-15T22:00:43.424594Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-17T06:30:58.91139+00:00","source":"crossref"},{"observed_at":"2026-08-17T06:30:54.323127+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-15T22:00:43.401063Z","title":"Ele522: Lecutre notes for gradient methods (unconstrained), 2020","venue":null,"work_id":"eda8c83c-4bfb-4b28-91cb-960616166aed","year":2020},"citing_paper":{"arxiv_id":"2505.08557","last_updated":"2025-05-13T13:33:36Z","snapshot_observed_at":"2026-08-15T21:49:35.191126Z","submitted_at":"2025-05-13T13:33:36Z","title":"Online Learning and Unlearning","version":1},"reference_index":30,"source":"pdf_text","source_observed_at":"2026-08-15T22:00:43.191600Z"},"links":{"citing_paper":"/paper/2505.08557"},"observation_digest":"sha256:ee9c615b0e0cf18286107975f559c129584d9a689a3b25220d65be00f2ef0a46","observation_id":"a6d37f5b-9ff5-4333-bc91-14249bf72bd3","resolution":{"observed_at":"2026-08-15T22:00:43.406942Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-17T06:30:58.91139+00:00","source":"crossref"},{"observed_at":"2026-08-17T06:30:54.323127+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-15T22:00:43.384572Z","title":"Lemma C (Shift-reduction lemma [20])","venue":null,"work_id":"51a8e09f-f733-4349-9196-bd11ab2be246","year":null},"citing_paper":{"arxiv_id":"2505.08557","last_updated":"2025-05-13T13:33:36Z","snapshot_observed_at":"2026-08-15T21:49:35.191126Z","submitted_at":"2025-05-13T13:33:36Z","title":"Online Learning and Unlearning","version":1},"reference_index":31,"source":"pdf_text","source_observed_at":"2026-08-15T22:00:43.195731Z"},"links":{"citing_paper":"/paper/2505.08557"},"observation_digest":"sha256:2cb527cb3457c5b690f3e1653daa5b59a803c5a48580f0dd34c13bb4d2691077","observation_id":"949027e4-639e-4776-a98e-8c8c7b76c577","resolution":{"observed_at":"2026-08-15T22:00:43.389897Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-17T06:30:58.91139+00:00","source":"crossref"},{"observed_at":"2026-08-17T06:30:54.323127+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-15T22:00:43.367181Z","title":"The unlearning auxiliary function Uaux(ψj(z), Sτ [j], SU j ) performs these two phases: I1 GD steps on Sτ [j] (viaF0) and I2 GD steps on Sτ [j] \\ S U j (viaF1)","venue":null,"work_id":"d31524ac-31d5-4ad2-bdf9-7a7f3b18868b","year":null},"citing_paper":{"arxiv_id":"2505.08557","last_updated":"2025-05-13T13:33:36Z","snapshot_observed_at":"2026-08-15T21:49:35.191126Z","submitted_at":"2025-05-13T13:33:36Z","title":"Online Learning and Unlearning","version":1},"reference_index":32,"source":"pdf_text","source_observed_at":"2026-08-15T22:00:43.200520Z"},"links":{"citing_paper":"/paper/2505.08557"},"observation_digest":"sha256:6491c24b75b598103b10d606c72e52defc4310946706275b4b203cd6e0a8652f","observation_id":"1e6102bb-eb74-4f90-869f-08a8ab21a405","resolution":{"observed_at":"2026-08-15T22:00:43.373820Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-17T06:30:58.91139+00:00","source":"crossref"},{"observed_at":"2026-08-17T06:30:54.323127+00:00","source":"retraction_watch"}],"state":"measured"}}],"paper":{"arxiv_id":"2505.08557","last_updated":"2025-05-13T13:33:36Z","latest_version":1,"primary_category":"cs.LG","snapshot_observed_at":"2026-08-15T21:49:35.191126Z","submitted_at":"2025-05-13T13:33:36Z","title":"Online Learning and Unlearning"},"reference_resolution":{"displayed":32,"state_counts":{"malformed_identifier":0,"metadata_mismatch":0,"parse_uncertain":0,"unresolved":4,"verified_exact":0,"verified_fuzzy":28},"total_outbound_references":32},"refusal":"A citation records a reference. It does not transfer a finding from one paper to another.","schema":"pith.paper-citation-record.v1","standing_sources":[{"observed_at":"2026-08-17T06:30:58.91139+00:00","source":"crossref"},{"observed_at":"2026-08-17T06:30:54.323127+00:00","source":"retraction_watch"}],"thesis":"As of 17 August 2026, this Paper Citation Record lists 32 of 32 outbound references and 1 inbound Pith citation observation for arXiv:2505.08557."}