{"as_of":"2026-08-14T23:53:00Z","caps":{"database_statements":6,"inbound":100,"outbound":100},"context_digest":"sha256:2342dd0088b72699062fb8880d43f4af5de6d5b0d478b5c3bc8822432648971b","coverage":[{"denominator":22,"lane":"reference_resolution","note":"Typed states for the displayed outbound observations.","records_observed":22,"source":"paper_references, paper_reference_links","source_observed_at":"2026-08-09T14:50:58.751231Z","state":"measured"},{"denominator":22,"lane":"standing_notices","note":"One-hop event checks from named stored sources.","records_observed":22,"source":"scholarly_work_events, retraction_status_cache","source_observed_at":"2026-08-14T06:32:32.682623+00:00","state":"measured"},{"denominator":0,"lane":"inbound_itemization","note":"Pith citing papers itemized under the disclosed page cap.","records_observed":0,"source":"paper_references, paper_reference_links","source_observed_at":null,"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":[],"links":{"evidence":"/evidence","html":"/paper/2502.01634/citation-record","integrity":"/paper/2502.01634/integrity","json":"/paper/2502.01634/citation-record.json","paper":"/paper/2502.01634"},"outbound":[{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-09T14:50:59.374519Z","title":"and Yang, J","venue":null,"work_id":"f965eaa0-c6d4-45dd-8404-5e37a8a44065","year":2015},"citing_paper":{"arxiv_id":"2502.01634","last_updated":"2025-02-03T18:59:04Z","snapshot_observed_at":"2026-08-13T16:51:45.788684Z","submitted_at":"2025-02-03T18:59:04Z","title":"Online Gradient Boosting Decision Tree: In-Place Updates for Efficient Adding/Deleting Data","version":1},"reference_index":3,"source":"pdf_text","source_observed_at":"2026-08-09T14:50:58.676462Z"},"links":{"citing_paper":"/paper/2502.01634"},"observation_digest":"sha256:7dc0d504aa488e22665dc022e600926a9501a72715690c66135ce75e81be2dc9","observation_id":"2feedd6e-67ba-4c13-9430-339491316e69","resolution":{"observed_at":"2026-08-09T14:50:59.378064Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-14T06:32:32.682623+00:00","source":"crossref"},{"observed_at":"2026-08-14T06:32:18.44784+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"1706.02677","last_updated":"2018-04-30T21:53:41Z","snapshot_observed_at":"2026-08-09T05:23:26.365677Z","submitted_at":"2017-06-08T16:51:53Z","title":"Accurate, Large Minibatch SGD: Training ImageNet in 1 Hour","version":2},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"1706.02677","snapshot_observed_at":"2026-08-09T14:50:58.692315Z","title":"B., Noordhuis, P., Wesolowski, L., Kyrola, A., Tulloch, A., Jia, Y ., and He, K","venue":null,"work_id":null,"year":null},"citing_paper":{"arxiv_id":"2502.01634","last_updated":"2025-02-03T18:59:04Z","snapshot_observed_at":"2026-08-13T16:51:45.788684Z","submitted_at":"2025-02-03T18:59:04Z","title":"Online Gradient Boosting Decision Tree: In-Place Updates for Efficient Adding/Deleting Data","version":1},"reference_index":7,"source":"pdf_text","source_observed_at":"2026-08-09T14:50:58.692315Z"},"links":{"cited_paper":"/paper/1706.02677","citing_paper":"/paper/2502.01634"},"observation_digest":"sha256:a17616b0e666b805acc3c3238b100f1926669507be2d5b306cd9f27e711421aa","observation_id":"459b2d11-8987-4c4c-b144-50eca9059ffe","resolution":{"observed_at":"2026-08-09T14:50:58.692315Z","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":"2026-08-09T14:50:59.297043Z","title":"Similarly, W2C represents the testing instances that are wrongly predicted during retraining but are correctly predicted after decremental learning","venue":null,"work_id":"90bef466-9d5d-477a-92da-e3687de12dac","year":2018},"citing_paper":{"arxiv_id":"2502.01634","last_updated":"2025-02-03T18:59:04Z","snapshot_observed_at":"2026-08-13T16:51:45.788684Z","submitted_at":"2025-02-03T18:59:04Z","title":"Online Gradient Boosting Decision Tree: In-Place Updates for Efficient Adding/Deleting Data","version":1},"reference_index":8,"source":"pdf_text","source_observed_at":"2026-08-09T14:50:58.746977Z"},"links":{"citing_paper":"/paper/2502.01634"},"observation_digest":"sha256:8e364513c60f7384c7fe415044b25c8b54df28da20fbdb78f879590d7e916e28","observation_id":"bd195104-fc5b-4ac6-a45a-92dffcb39781","resolution":{"observed_at":"2026-08-09T14:50:59.300736Z","resolver_source":"raw_fallback","status":"malformed_identifier"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-14T06:32:32.682623+00:00","source":"crossref"},{"observed_at":"2026-08-14T06:32:18.44784+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"2108.08233","last_updated":"2022-04-18T04:31:02Z","snapshot_observed_at":"2026-08-13T18:26:57.170070Z","submitted_at":"2021-08-18T16:54:34Z","title":"Research on Gender-related Fingerprint Features","version":2},"cited_work":{"arxiv_id":"2108.08233","doi":null,"metadata_source":"pith","pith_arxiv_id":"2108.08233","snapshot_observed_at":"2026-08-09T14:50:59.181408Z","title":"Research on Gender-related Fingerprint Features","venue":"cs.CV","work_id":"bb2e4793-4453-4163-a1ac-502cee0eb9c5","year":2021},"citing_paper":{"arxiv_id":"2502.01634","last_updated":"2025-02-03T18:59:04Z","snapshot_observed_at":"2026-08-13T16:51:45.788684Z","submitted_at":"2025-02-03T18:59:04Z","title":"Online Gradient Boosting Decision Tree: In-Place Updates for Efficient Adding/Deleting Data","version":1},"reference_index":14,"source":"pdf_text","source_observed_at":"2026-08-09T14:50:58.720399Z"},"links":{"cited_paper":"/paper/2108.08233","citing_paper":"/paper/2502.01634"},"observation_digest":"sha256:7a938916e6ea30f57fcbe25735bc35f8f6a79d077d8e6f622537b9207b5063ba","observation_id":"4e73fa1f-65e8-4aa1-a6b3-6d95dd614f28","resolution":{"observed_at":"2026-08-09T14:50:59.185483Z","resolver_source":"local_arxiv","status":"verified_exact"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-14T06:32:32.682623+00:00","source":"crossref"},{"observed_at":"2026-08-14T06:32:18.44784+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"1609.04747","last_updated":"2017-06-15T13:21:04Z","snapshot_observed_at":"2026-08-14T21:39:40.545291Z","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":"2026-08-09T14:50:58.724319Z","title":"An overview of gradient descent optimization algorithms","venue":null,"work_id":null,"year":null},"citing_paper":{"arxiv_id":"2502.01634","last_updated":"2025-02-03T18:59:04Z","snapshot_observed_at":"2026-08-13T16:51:45.788684Z","submitted_at":"2025-02-03T18:59:04Z","title":"Online Gradient Boosting Decision Tree: In-Place Updates for Efficient Adding/Deleting Data","version":1},"reference_index":15,"source":"pdf_text","source_observed_at":"2026-08-09T14:50:58.724319Z"},"links":{"cited_paper":"/paper/1609.04747","citing_paper":"/paper/2502.01634"},"observation_digest":"sha256:2e463cd4102738959b7adad348bd2731ef8631c249678ee24bbfa1e946cfd6dc","observation_id":"b4d840a8-93af-4040-9557-c44a928eb086","resolution":{"observed_at":"2026-08-09T14:50:58.724319Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2111.08947","last_updated":"2023-05-31T17:42:15Z","snapshot_observed_at":"2026-07-06T12:09:23.278166Z","submitted_at":"2021-11-17T07:29:24Z","title":"Fast Yet Effective Machine Unlearning","version":5},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2111.08947","snapshot_observed_at":"2026-08-09T14:50:58.731524Z","title":"K., Chundawat, V","venue":null,"work_id":null,"year":null},"citing_paper":{"arxiv_id":"2502.01634","last_updated":"2025-02-03T18:59:04Z","snapshot_observed_at":"2026-08-13T16:51:45.788684Z","submitted_at":"2025-02-03T18:59:04Z","title":"Online Gradient Boosting Decision Tree: In-Place Updates for Efficient Adding/Deleting Data","version":1},"reference_index":17,"source":"pdf_text","source_observed_at":"2026-08-09T14:50:58.731524Z"},"links":{"cited_paper":"/paper/2111.08947","citing_paper":"/paper/2502.01634"},"observation_digest":"sha256:92abdb823c984ff8c80b488336a4ff69e731d7930d7fe10ef41683823b88c379","observation_id":"43cef25a-1741-4b12-bedb-f4ea2b39657c","resolution":{"observed_at":"2026-08-09T14:50:58.731524Z","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":"2026-08-09T14:50:59.307912Z","title":"Structure aware incremental learning with personalized imitation weights for recommender sys- tems","venue":null,"work_id":"45fb4b7d-88f0-4107-84ac-c4be40658a13","year":2023},"citing_paper":{"arxiv_id":"2502.01634","last_updated":"2025-02-03T18:59:04Z","snapshot_observed_at":"2026-08-13T16:51:45.788684Z","submitted_at":"2025-02-03T18:59:04Z","title":"Online Gradient Boosting Decision Tree: In-Place Updates for Efficient Adding/Deleting Data","version":1},"reference_index":18,"source":"pdf_text","source_observed_at":"2026-08-09T14:50:58.735157Z"},"links":{"citing_paper":"/paper/2502.01634"},"observation_digest":"sha256:ceaf7efd8b29a7902f726ca65dcf78618d64614fad64a66c356158d3783293b2","observation_id":"bd041f1e-d9bd-4b57-bc61-495d0e8b1f15","resolution":{"observed_at":"2026-08-09T14:50:59.311653Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-14T06:32:32.682623+00:00","source":"crossref"},{"observed_at":"2026-08-14T06:32:18.44784+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"2311.13174","last_updated":"2023-11-22T05:38:53Z","snapshot_observed_at":"2026-08-13T05:19:55.474385Z","submitted_at":"2023-11-22T05:38:53Z","title":"SecureCut: Federated Gradient Boosting Decision Trees with Efficient Machine Unlearning","version":1},"cited_work":{"arxiv_id":"2311.13174","doi":null,"metadata_source":"pith","pith_arxiv_id":"2311.13174","snapshot_observed_at":"2026-08-09T14:50:59.143539Z","title":"SecureCut: Federated Gradient Boosting Decision Trees with Efficient Machine Unlearning","venue":"cs.LG","work_id":"5ca789f2-e075-4788-81a4-8355ea4c3773","year":2023},"citing_paper":{"arxiv_id":"2502.01634","last_updated":"2025-02-03T18:59:04Z","snapshot_observed_at":"2026-08-13T16:51:45.788684Z","submitted_at":"2025-02-03T18:59:04Z","title":"Online Gradient Boosting Decision Tree: In-Place Updates for Efficient Adding/Deleting Data","version":1},"reference_index":19,"source":"pdf_text","source_observed_at":"2026-08-09T14:50:58.738918Z"},"links":{"cited_paper":"/paper/2311.13174","citing_paper":"/paper/2502.01634"},"observation_digest":"sha256:72659fcd7518aaa10ab209d1254209b86530916490307b37074146dc2638403c","observation_id":"d8ed46a2-5bd1-4490-90d5-a6592d6d27be","resolution":{"observed_at":"2026-08-09T14:50:59.147861Z","resolver_source":"local_arxiv","status":"verified_exact"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-14T06:32:32.682623+00:00","source":"crossref"},{"observed_at":"2026-08-14T06:32:18.44784+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"arxiv_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-09T14:50:59.127397Z","title":"Table 7: Error rate after every on- line learning step","venue":null,"work_id":"33a9c791-c792-478d-886d-de1f3c220811","year":1934},"citing_paper":{"arxiv_id":"2502.01634","last_updated":"2025-02-03T18:59:04Z","snapshot_observed_at":"2026-08-13T16:51:45.788684Z","submitted_at":"2025-02-03T18:59:04Z","title":"Online Gradient Boosting Decision Tree: In-Place Updates for Efficient Adding/Deleting Data","version":1},"reference_index":20,"source":"pdf_text","source_observed_at":"2026-08-09T14:50:58.743049Z"},"links":{"citing_paper":"/paper/2502.01634"},"observation_digest":"sha256:65c63f0966e5e52b3e29045eea70357aed42fc1a719a875d5e76510d9bbe14ae","observation_id":"5d54a46a-7831-4a36-8812-bed71efb60c2","resolution":{"observed_at":"2026-08-09T14:50:59.132413Z","resolver_source":"arxiv_id_nonexistent","status":"verified_exact"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-14T06:32:32.682623+00:00","source":"crossref"},{"observed_at":"2026-08-14T06:32:18.44784+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"arxiv_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-09T14:50:58.940498Z","title":null,"venue":null,"work_id":"304fc81f-ece2-4682-9b2e-b6bb0b7adeb7","year":2000},"citing_paper":{"arxiv_id":"2502.01634","last_updated":"2025-02-03T18:59:04Z","snapshot_observed_at":"2026-08-13T16:51:45.788684Z","submitted_at":"2025-02-03T18:59:04Z","title":"Online Gradient Boosting Decision Tree: In-Place Updates for Efficient Adding/Deleting Data","version":1},"reference_index":22,"source":"pdf_text","source_observed_at":"2026-08-09T14:50:58.751231Z"},"links":{"citing_paper":"/paper/2502.01634"},"observation_digest":"sha256:335275af36c94d0eb934ca50e0dc9dc45c009273af1954b281289ed7a767dc4e","observation_id":"3cbb4fcd-234a-4864-a708-73d1168063cc","resolution":{"observed_at":"2026-08-09T14:50:58.946895Z","resolver_source":"arxiv_id_nonexistent","status":"malformed_identifier"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-14T06:32:32.682623+00:00","source":"crossref"},{"observed_at":"2026-08-14T06:32:18.44784+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"2304.02049","last_updated":"2024-06-08T10:56:27Z","snapshot_observed_at":"2026-08-13T12:09:13.596971Z","submitted_at":"2023-04-04T18:01:59Z","title":"Multi-Class Unlearning for Image Classification via Weight Filtering","version":2},"cited_work":{"arxiv_id":"2304.02049","doi":null,"metadata_source":"pith","pith_arxiv_id":"2304.02049","snapshot_observed_at":"2026-08-09T14:50:59.196688Z","title":"Multi-Class Unlearning for Image Classification via Weight Filtering","venue":"cs.CV","work_id":"c733e766-94f7-485a-b754-f358d33ee483","year":2023},"citing_paper":{"arxiv_id":"2502.01634","last_updated":"2025-02-03T18:59:04Z","snapshot_observed_at":"2026-08-13T16:51:45.788684Z","submitted_at":"2025-02-03T18:59:04Z","title":"Online Gradient Boosting Decision Tree: In-Place Updates for Efficient Adding/Deleting Data","version":1},"reference_index":2001,"source":"pdf_text","source_observed_at":"2026-08-09T14:50:58.716428Z"},"links":{"cited_paper":"/paper/2304.02049","citing_paper":"/paper/2502.01634"},"observation_digest":"sha256:fac3a1ec8b332011252c7f183e1bc4976ffc54bae801e62ee7f088c1843fe9ef","observation_id":"b12ddae7-2c16-47de-ab35-e3f4ea3bc281","resolution":{"observed_at":"2026-08-09T14:50:59.200890Z","resolver_source":"local_arxiv","status":"verified_exact"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-14T06:32:32.682623+00:00","source":"crossref"},{"observed_at":"2026-08-14T06:32:18.44784+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":"2026-08-09T14:50:59.319021Z","title":"Mem- bership inference attacks against machine learning mod- els","venue":null,"work_id":"29067a32-f29b-46ab-8547-8174dd2e39a7","year":2017},"citing_paper":{"arxiv_id":"2502.01634","last_updated":"2025-02-03T18:59:04Z","snapshot_observed_at":"2026-08-13T16:51:45.788684Z","submitted_at":"2025-02-03T18:59:04Z","title":"Online Gradient Boosting Decision Tree: In-Place Updates for Efficient Adding/Deleting Data","version":1},"reference_index":2005,"source":"pdf_text","source_observed_at":"2026-08-09T14:50:58.728026Z"},"links":{"citing_paper":"/paper/2502.01634"},"observation_digest":"sha256:207d7924377a15ad8fe465288682e8eeeb7e1fbaca01b0e97f7c7da4dc53dd4b","observation_id":"b1c004a5-c4d8-47ab-8dbf-52d33f1e0675","resolution":{"observed_at":"2026-08-09T14:50:59.322761Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-14T06:32:32.682623+00:00","source":"crossref"},{"observed_at":"2026-08-14T06:32:18.44784+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"2209.02299","last_updated":"2024-09-17T11:55:58Z","snapshot_observed_at":"2026-08-13T14:32:32.333600Z","submitted_at":"2022-09-06T08:51:53Z","title":"A Survey of Machine Unlearning","version":6},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2209.02299","snapshot_observed_at":"2026-08-09T14:50:58.712354Z","title":"T., Huynh, T","venue":null,"work_id":null,"year":null},"citing_paper":{"arxiv_id":"2502.01634","last_updated":"2025-02-03T18:59:04Z","snapshot_observed_at":"2026-08-13T16:51:45.788684Z","submitted_at":"2025-02-03T18:59:04Z","title":"Online Gradient Boosting Decision Tree: In-Place Updates for Efficient Adding/Deleting Data","version":1},"reference_index":2007,"source":"pdf_text","source_observed_at":"2026-08-09T14:50:58.712354Z"},"links":{"cited_paper":"/paper/2209.02299","citing_paper":"/paper/2502.01634"},"observation_digest":"sha256:0607d20c9b6883d54446e4e47e313bb08057774ceb82fd1b686455f3fc3244bc","observation_id":"08cbefa3-84cd-47cb-97ea-d8755d0f4773","resolution":{"observed_at":"2026-08-09T14:50:58.712354Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"1507.01030","last_updated":"2017-12-19T20:11:29Z","snapshot_observed_at":"2026-08-14T22:41:48.769610Z","submitted_at":"2015-07-03T21:20:51Z","title":"Incremental Gradient, Subgradient, and Proximal Methods for Convex Optimization: A Survey","version":2},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"1507.01030","snapshot_observed_at":"2026-08-09T14:50:58.667569Z","title":null,"venue":null,"work_id":null,"year":null},"citing_paper":{"arxiv_id":"2502.01634","last_updated":"2025-02-03T18:59:04Z","snapshot_observed_at":"2026-08-13T16:51:45.788684Z","submitted_at":"2025-02-03T18:59:04Z","title":"Online Gradient Boosting Decision Tree: In-Place Updates for Efficient Adding/Deleting Data","version":1},"reference_index":2009,"source":"pdf_text","source_observed_at":"2026-08-09T14:50:58.667569Z"},"links":{"cited_paper":"/paper/1507.01030","citing_paper":"/paper/2502.01634"},"observation_digest":"sha256:5fb5f216aae1db073363b19a023c224aadabc8c77f76185070f9dbb1c66747d2","observation_id":"bf8bca4d-c99d-4fd4-8b4b-92258d52c330","resolution":{"observed_at":"2026-08-09T14:50:58.667569Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2205.10927","last_updated":"2022-06-26T16:25:20Z","snapshot_observed_at":"2026-08-13T15:39:17.443011Z","submitted_at":"2022-05-22T20:42:26Z","title":"Fast ABC-Boost: A Unified Framework for Selecting the Base Class in Multi-Class Classification","version":2},"cited_work":{"arxiv_id":"2205.10927","doi":null,"metadata_source":"pith","pith_arxiv_id":"2205.10927","snapshot_observed_at":"2026-08-09T14:50:59.239622Z","title":"Fast ABC-Boost: A Unified Framework for Selecting the Base Class in Multi-Class Classification","venue":"cs.LG","work_id":"1d4b19d4-2c96-42fe-8f45-5fa9d236b824","year":2022},"citing_paper":{"arxiv_id":"2502.01634","last_updated":"2025-02-03T18:59:04Z","snapshot_observed_at":"2026-08-13T16:51:45.788684Z","submitted_at":"2025-02-03T18:59:04Z","title":"Online Gradient Boosting Decision Tree: In-Place Updates for Efficient Adding/Deleting Data","version":1},"reference_index":2010,"source":"pdf_text","source_observed_at":"2026-08-09T14:50:58.704181Z"},"links":{"cited_paper":"/paper/2205.10927","citing_paper":"/paper/2502.01634"},"observation_digest":"sha256:fb1b7d80d34983025c43b4b6ea5183b1ef5404edf742d6d0fc94bfe50d33eba2","observation_id":"4e8f93ec-50b2-4907-8971-37d513034c78","resolution":{"observed_at":"2026-08-09T14:50:59.243635Z","resolver_source":"local_arxiv","status":"verified_exact"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-14T06:32:32.682623+00:00","source":"crossref"},{"observed_at":"2026-08-14T06:32:18.44784+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":"2026-08-09T14:50:59.329654Z","title":"Incremental support vector learning: Analysis, implementation and applications","venue":null,"work_id":"1696f4f1-5bf5-4099-b5db-166a7451604f","year":1909},"citing_paper":{"arxiv_id":"2502.01634","last_updated":"2025-02-03T18:59:04Z","snapshot_observed_at":"2026-08-13T16:51:45.788684Z","submitted_at":"2025-02-03T18:59:04Z","title":"Online Gradient Boosting Decision Tree: In-Place Updates for Efficient Adding/Deleting Data","version":1},"reference_index":2013,"source":"pdf_text","source_observed_at":"2026-08-09T14:50:58.700314Z"},"links":{"citing_paper":"/paper/2502.01634"},"observation_digest":"sha256:b8abf27f95c6b8c744db9f62c0a00aec7afddeefac9a3da87c22547e115d895c","observation_id":"eac2f027-aee1-4993-9341-5c291cc98d0b","resolution":{"observed_at":"2026-08-09T14:50:59.333712Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-14T06:32:32.682623+00:00","source":"crossref"},{"observed_at":"2026-08-14T06:32:18.44784+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":"2026-08-09T14:50:59.363386Z","title":"Membership inference attacks from first prin- ciples","venue":null,"work_id":"d6a4ede6-030a-4c66-8e51-98a2088f3c3e","year":1914},"citing_paper":{"arxiv_id":"2502.01634","last_updated":"2025-02-03T18:59:04Z","snapshot_observed_at":"2026-08-13T16:51:45.788684Z","submitted_at":"2025-02-03T18:59:04Z","title":"Online Gradient Boosting Decision Tree: In-Place Updates for Efficient Adding/Deleting Data","version":1},"reference_index":2015,"source":"pdf_text","source_observed_at":"2026-08-09T14:50:58.680334Z"},"links":{"citing_paper":"/paper/2502.01634"},"observation_digest":"sha256:8ebdb89304f84df43bcd17461594f38c9c905cd5fbfb43dc9839cd6760759761","observation_id":"e1cbcef6-1858-4e13-a6c5-777fbc6eb17b","resolution":{"observed_at":"2026-08-09T14:50:59.367276Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-14T06:32:32.682623+00:00","source":"crossref"},{"observed_at":"2026-08-14T06:32:18.44784+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":"2026-08-09T14:50:59.340781Z","title":"From N to N+1: multiclass transfer incremental learning","venue":null,"work_id":"be81e53a-8858-489c-a71a-82d318310b86","year":2013},"citing_paper":{"arxiv_id":"2502.01634","last_updated":"2025-02-03T18:59:04Z","snapshot_observed_at":"2026-08-13T16:51:45.788684Z","submitted_at":"2025-02-03T18:59:04Z","title":"Online Gradient Boosting Decision Tree: In-Place Updates for Efficient Adding/Deleting Data","version":1},"reference_index":2017,"source":"pdf_text","source_observed_at":"2026-08-09T14:50:58.696538Z"},"links":{"citing_paper":"/paper/2502.01634"},"observation_digest":"sha256:7b6089f0a67a0246960429b02b2f1bed6ecb8d9f267f5c5a1d87cdee9d6caf4f","observation_id":"4affdd6b-9f04-406c-9b26-5851c9a81aa5","resolution":{"observed_at":"2026-08-09T14:50:59.344572Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-14T06:32:32.682623+00:00","source":"crossref"},{"observed_at":"2026-08-14T06:32:18.44784+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":"2026-08-09T14:50:59.351942Z","title":"A., Tram `er, F., Carlini, N., and Pa- pernot, N","venue":null,"work_id":"8966f50e-05e5-4fdc-82df-eb798fa93fa7","year":1964},"citing_paper":{"arxiv_id":"2502.01634","last_updated":"2025-02-03T18:59:04Z","snapshot_observed_at":"2026-08-13T16:51:45.788684Z","submitted_at":"2025-02-03T18:59:04Z","title":"Online Gradient Boosting Decision Tree: In-Place Updates for Efficient Adding/Deleting Data","version":1},"reference_index":2019,"source":"pdf_text","source_observed_at":"2026-08-09T14:50:58.684523Z"},"links":{"citing_paper":"/paper/2502.01634"},"observation_digest":"sha256:36928dee7e63dfcd7dd84c628d186fdb01d24a103c59a5b9536a0c49c11157f3","observation_id":"9565f500-39a6-4672-8e05-bdb5cf611e31","resolution":{"observed_at":"2026-08-09T14:50:59.355777Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-14T06:32:32.682623+00:00","source":"crossref"},{"observed_at":"2026-08-14T06:32:18.44784+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"2009.05567","last_updated":"2021-06-11T22:04:44Z","snapshot_observed_at":"2026-08-11T12:43:02.916370Z","submitted_at":"2020-09-11T17:53:20Z","title":"Machine Unlearning for Random Forests","version":2},"cited_work":{"arxiv_id":"2009.05567","doi":null,"metadata_source":"pith","pith_arxiv_id":"2009.05567","snapshot_observed_at":"2026-08-09T14:50:59.274490Z","title":"Machine Unlearning for Random Forests","venue":"cs.LG","work_id":"fd67a118-3d5f-4066-b974-bb7029139105","year":2020},"citing_paper":{"arxiv_id":"2502.01634","last_updated":"2025-02-03T18:59:04Z","snapshot_observed_at":"2026-08-13T16:51:45.788684Z","submitted_at":"2025-02-03T18:59:04Z","title":"Online Gradient Boosting Decision Tree: In-Place Updates for Efficient Adding/Deleting Data","version":1},"reference_index":2021,"source":"pdf_text","source_observed_at":"2026-08-09T14:50:58.672354Z"},"links":{"cited_paper":"/paper/2009.05567","citing_paper":"/paper/2502.01634"},"observation_digest":"sha256:c764518da745f95182dcd7d6dff841b1caa1be7233667360726e54e9520c3f4b","observation_id":"49f1d81f-94eb-4b03-85da-b742bd2dd242","resolution":{"observed_at":"2026-08-09T14:50:59.279299Z","resolver_source":"local_arxiv","status":"verified_exact"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-14T06:32:32.682623+00:00","source":"crossref"},{"observed_at":"2026-08-14T06:32:18.44784+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"2412.08637","last_updated":"2026-04-09T06:53:44Z","snapshot_observed_at":"2026-08-12T15:49:04.743422Z","submitted_at":"2024-12-11T18:58:40Z","title":"DMin: Scalable Training Data Influence Estimation for Diffusion Models","version":4},"cited_work":{"arxiv_id":"2412.08637","doi":null,"metadata_source":"pith","pith_arxiv_id":"2412.08637","snapshot_observed_at":"2026-08-09T14:50:59.223395Z","title":"DMin: Scalable Training Data Influence Estimation for Diffusion Models","venue":"cs.CV","work_id":"f2f2d9b8-6817-4ee8-a437-6f39c8486c8e","year":2024},"citing_paper":{"arxiv_id":"2502.01634","last_updated":"2025-02-03T18:59:04Z","snapshot_observed_at":"2026-08-13T16:51:45.788684Z","submitted_at":"2025-02-03T18:59:04Z","title":"Online Gradient Boosting Decision Tree: In-Place Updates for Efficient Adding/Deleting Data","version":1},"reference_index":2022,"source":"pdf_text","source_observed_at":"2026-08-09T14:50:58.708127Z"},"links":{"cited_paper":"/paper/2412.08637","citing_paper":"/paper/2502.01634"},"observation_digest":"sha256:c2069cb861f6467ccd6ffa5c3b7fabcb87beb47aa0df2d1544255ba2a025ad09","observation_id":"d415871a-7e3a-4a04-9463-bf5325b8f1d4","resolution":{"observed_at":"2026-08-09T14:50:59.228026Z","resolver_source":"local_arxiv","status":"metadata_mismatch"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-14T06:32:32.682623+00:00","source":"crossref"},{"observed_at":"2026-08-14T06:32:18.44784+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"1810.11363","last_updated":"2018-10-24T13:08:24Z","snapshot_observed_at":"2026-08-14T18:10:01.824731Z","submitted_at":"2018-10-24T13:08:24Z","title":"CatBoost: gradient boosting with categorical features support","version":1},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"1810.11363","snapshot_observed_at":"2026-08-09T14:50:58.688271Z","title":"V ., Ershov, V ., and Gulin, A","venue":null,"work_id":null,"year":null},"citing_paper":{"arxiv_id":"2502.01634","last_updated":"2025-02-03T18:59:04Z","snapshot_observed_at":"2026-08-13T16:51:45.788684Z","submitted_at":"2025-02-03T18:59:04Z","title":"Online Gradient Boosting Decision Tree: In-Place Updates for Efficient Adding/Deleting Data","version":1},"reference_index":2023,"source":"pdf_text","source_observed_at":"2026-08-09T14:50:58.688271Z"},"links":{"cited_paper":"/paper/1810.11363","citing_paper":"/paper/2502.01634"},"observation_digest":"sha256:5353e13b4fb82c28da55817694228755057b4bf84ded12d969cc54e6e2d9f542","observation_id":"17cd8c85-1b3c-4331-96d9-4afc23b9d378","resolution":{"observed_at":"2026-08-09T14:50:58.688271Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}}],"paper":{"arxiv_id":"2502.01634","last_updated":"2025-02-03T18:59:04Z","latest_version":1,"primary_category":"cs.LG","snapshot_observed_at":"2026-08-13T16:51:45.788684Z","submitted_at":"2025-02-03T18:59:04Z","title":"Online Gradient Boosting Decision Tree: In-Place Updates for Efficient Adding/Deleting Data"},"reference_resolution":{"displayed":22,"state_counts":{"malformed_identifier":2,"metadata_mismatch":1,"parse_uncertain":0,"unresolved":6,"verified_exact":6,"verified_fuzzy":7},"total_outbound_references":22},"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":"2026-08-14T06:32:32.682623+00:00","source":"crossref"},{"observed_at":"2026-08-14T06:32:18.44784+00:00","source":"retraction_watch"}],"thesis":"As of 14 August 2026, this Paper Citation Record lists 22 of 22 outbound references and 0 inbound Pith citation observations for arXiv:2502.01634."}