{"as_of":"2026-08-17T15:55:00Z","caps":{"database_statements":6,"inbound":100,"outbound":100},"context_digest":"sha256:a79801a6f7d53ce162f50b5f86982c0730d9891f0e4f7bd4fbb2df8b5aba8dcf","coverage":[{"denominator":42,"lane":"reference_resolution","note":"Typed states for the displayed outbound observations.","records_observed":42,"source":"paper_references, paper_reference_links","source_observed_at":"2026-08-15T18:08:25.114202Z","state":"measured"},{"denominator":42,"lane":"standing_notices","note":"One-hop event checks from named stored sources.","records_observed":42,"source":"scholarly_work_events, retraction_status_cache","source_observed_at":"2026-08-17T06:30:58.91139+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/2507.18996/citation-record","integrity":"/paper/2507.18996/integrity","json":"/paper/2507.18996/citation-record.json","paper":"/paper/2507.18996"},"outbound":[{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-15T18:08:27.971012Z","title":"Improving predictive inference under covariate shift by weighting the log-likelihood function.Journal of statistical planning and inference, 90(2):227–244, 2000","venue":null,"work_id":"93cbe683-9fbc-4a1a-a385-736120ca165f","year":2000},"citing_paper":{"arxiv_id":"2507.18996","last_updated":"2025-07-25T06:50:09Z","snapshot_observed_at":"2026-08-16T19:50:54.291617Z","submitted_at":"2025-07-25T06:50:09Z","title":"Adapting to Fragmented and Evolving Data: A Fisher Information Perspective","version":1},"reference_index":1,"source":"pdf_text","source_observed_at":"2026-08-15T18:08:23.868917Z"},"links":{"citing_paper":"/paper/2507.18996"},"observation_digest":"sha256:a748b43347a3725285fa443f38fd5b81c55f82e3289ca177bd3023c37820f1f5","observation_id":"a5f8635a-9def-4297-b95e-9c8e98b71b59","resolution":{"observed_at":"2026-08-15T18:08:27.976941Z","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":"2026-08-15T18:08:27.918400Z","title":"Covariate shift adaptation by importance weighted cross validation.Journal of Machine Learning Research, 8(5), 2007","venue":null,"work_id":"0e0b457b-d6e2-42b3-a8a8-868be9806d9f","year":2007},"citing_paper":{"arxiv_id":"2507.18996","last_updated":"2025-07-25T06:50:09Z","snapshot_observed_at":"2026-08-16T19:50:54.291617Z","submitted_at":"2025-07-25T06:50:09Z","title":"Adapting to Fragmented and Evolving Data: A Fisher Information Perspective","version":1},"reference_index":2,"source":"pdf_text","source_observed_at":"2026-08-15T18:08:23.896315Z"},"links":{"citing_paper":"/paper/2507.18996"},"observation_digest":"sha256:d7816537c4840ef9412b22a513c34e21522f6ac716f737141bf5582610143cb3","observation_id":"f3944cc4-f53b-408e-a110-e040ee629284","resolution":{"observed_at":"2026-08-15T18:08:27.938476Z","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":"2026-08-15T18:08:27.697333Z","title":"Causal covariate shift correction using fisher information penalty","venue":null,"work_id":"5ed8da95-7404-4209-b3ef-82247e5b39ea","year":2024},"citing_paper":{"arxiv_id":"2507.18996","last_updated":"2025-07-25T06:50:09Z","snapshot_observed_at":"2026-08-16T19:50:54.291617Z","submitted_at":"2025-07-25T06:50:09Z","title":"Adapting to Fragmented and Evolving Data: A Fisher Information Perspective","version":1},"reference_index":3,"source":"pdf_text","source_observed_at":"2026-08-15T18:08:23.930406Z"},"links":{"citing_paper":"/paper/2507.18996"},"observation_digest":"sha256:32bf3e4c0bd3098ec87972e47b259d05eb9e9f1044460598742669f44f837504","observation_id":"5dd5da09-50f2-4dee-bdb3-8530a64a2108","resolution":{"observed_at":"2026-08-15T18:08:27.798494Z","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":"2205.11101","last_updated":"2022-05-23T07:51:45Z","snapshot_observed_at":"2026-08-16T16:58:29.789455Z","submitted_at":"2022-05-23T07:51:45Z","title":"FL Games: A federated learning framework for distribution shifts","version":1},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2205.11101","snapshot_observed_at":"2026-08-15T18:08:23.942050Z","title":"Fl games: A federated learning framework for distribution shifts.arXiv preprint arXiv:2205.11101, 2022","venue":null,"work_id":null,"year":2022},"citing_paper":{"arxiv_id":"2507.18996","last_updated":"2025-07-25T06:50:09Z","snapshot_observed_at":"2026-08-16T19:50:54.291617Z","submitted_at":"2025-07-25T06:50:09Z","title":"Adapting to Fragmented and Evolving Data: A Fisher Information Perspective","version":1},"reference_index":4,"source":"pdf_text","source_observed_at":"2026-08-15T18:08:23.942050Z"},"links":{"cited_paper":"/paper/2205.11101","citing_paper":"/paper/2507.18996"},"observation_digest":"sha256:499dd625576354f781b2174b6c1081373dea348a9de1a66f372e83f7c8fd1773","observation_id":"1b175552-e71a-4c54-aa09-43622282ac28","resolution":{"observed_at":"2026-08-15T18:08:23.942050Z","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":"2026-08-15T18:08:27.662458Z","title":"Oxford university press, 1995","venue":null,"work_id":"9767de98-f5f2-4f4a-8e16-838a0c4b2b8a","year":1995},"citing_paper":{"arxiv_id":"2507.18996","last_updated":"2025-07-25T06:50:09Z","snapshot_observed_at":"2026-08-16T19:50:54.291617Z","submitted_at":"2025-07-25T06:50:09Z","title":"Adapting to Fragmented and Evolving Data: A Fisher Information Perspective","version":1},"reference_index":5,"source":"pdf_text","source_observed_at":"2026-08-15T18:08:23.947966Z"},"links":{"citing_paper":"/paper/2507.18996"},"observation_digest":"sha256:d6ba4a45ae0a165c7d4f8face99b05c7b364906f1be7942006042205d030b84b","observation_id":"85d177d7-8d9f-4ba1-ac89-3961f6f70e97","resolution":{"observed_at":"2026-08-15T18:08:27.681238Z","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":"2026-08-15T18:08:27.569050Z","title":"Fast algorithm selection using learning curves","venue":null,"work_id":"658822c3-5337-4203-9b74-badf4505a7a7","year":2015},"citing_paper":{"arxiv_id":"2507.18996","last_updated":"2025-07-25T06:50:09Z","snapshot_observed_at":"2026-08-16T19:50:54.291617Z","submitted_at":"2025-07-25T06:50:09Z","title":"Adapting to Fragmented and Evolving Data: A Fisher Information Perspective","version":1},"reference_index":6,"source":"pdf_text","source_observed_at":"2026-08-15T18:08:24.015480Z"},"links":{"citing_paper":"/paper/2507.18996"},"observation_digest":"sha256:b07654fc345a1175f05ee7ee85619f21f7af66fa8420635d75fcc90d7b03c93d","observation_id":"6299ee10-1246-46a8-9cad-9da3b9d65948","resolution":{"observed_at":"2026-08-15T18:08:27.607468Z","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":"2026-08-15T18:08:27.486614Z","title":"Sample selection bias correction theory","venue":null,"work_id":"bbf0c75f-a202-4a63-be85-3ec70fc92848","year":2008},"citing_paper":{"arxiv_id":"2507.18996","last_updated":"2025-07-25T06:50:09Z","snapshot_observed_at":"2026-08-16T19:50:54.291617Z","submitted_at":"2025-07-25T06:50:09Z","title":"Adapting to Fragmented and Evolving Data: A Fisher Information Perspective","version":1},"reference_index":7,"source":"pdf_text","source_observed_at":"2026-08-15T18:08:24.029341Z"},"links":{"citing_paper":"/paper/2507.18996"},"observation_digest":"sha256:920d918ee7b878bf0963f96dac40dcd46c9ae30c420f15f736e0122dd797a9c6","observation_id":"a7d4f761-5dd6-45d5-a5aa-fc7015e91548","resolution":{"observed_at":"2026-08-15T18:08:27.494179Z","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":"2026-08-15T18:08:27.342707Z","title":"The impact of changing populations on classifier performance","venue":null,"work_id":"460a4454-5121-4d08-808e-aa63913afc41","year":1999},"citing_paper":{"arxiv_id":"2507.18996","last_updated":"2025-07-25T06:50:09Z","snapshot_observed_at":"2026-08-16T19:50:54.291617Z","submitted_at":"2025-07-25T06:50:09Z","title":"Adapting to Fragmented and Evolving Data: A Fisher Information Perspective","version":1},"reference_index":8,"source":"pdf_text","source_observed_at":"2026-08-15T18:08:24.042424Z"},"links":{"citing_paper":"/paper/2507.18996"},"observation_digest":"sha256:b3e8d116c54804ea5cbcc26f5139b35e01e7d05987d62638345737cc22049418","observation_id":"07d0f213-446b-4eca-b231-8048dd89ab3e","resolution":{"observed_at":"2026-08-15T18:08:27.417482Z","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":"2026-08-15T18:08:24.056968Z","title":"Classifier technology and the illusion of progress","venue":null,"work_id":null,"year":2006},"citing_paper":{"arxiv_id":"2507.18996","last_updated":"2025-07-25T06:50:09Z","snapshot_observed_at":"2026-08-16T19:50:54.291617Z","submitted_at":"2025-07-25T06:50:09Z","title":"Adapting to Fragmented and Evolving Data: A Fisher Information Perspective","version":1},"reference_index":9,"source":"pdf_text","source_observed_at":"2026-08-15T18:08:24.056968Z"},"links":{"citing_paper":"/paper/2507.18996"},"observation_digest":"sha256:994f9a9ee47115311cda792892a3679b7e303501a539e073e6d34134981c9b39","observation_id":"e78fe16d-ff8a-4875-943b-57743fed7872","resolution":{"observed_at":"2026-08-15T18:08:24.056968Z","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":"2026-08-15T18:08:27.217720Z","title":"A framework for monitoring classifiers’ performance: when and why failure occurs?Knowledge and Information Systems, 18(1):83–108, 2009","venue":null,"work_id":"d6a62be9-ec9f-425a-b427-907ee8546826","year":2009},"citing_paper":{"arxiv_id":"2507.18996","last_updated":"2025-07-25T06:50:09Z","snapshot_observed_at":"2026-08-16T19:50:54.291617Z","submitted_at":"2025-07-25T06:50:09Z","title":"Adapting to Fragmented and Evolving Data: A Fisher Information Perspective","version":1},"reference_index":10,"source":"pdf_text","source_observed_at":"2026-08-15T18:08:24.068200Z"},"links":{"citing_paper":"/paper/2507.18996"},"observation_digest":"sha256:5f6ff443787881003bf602a7c56532eb04610e2f8c1e96f3e29580ba65466b0e","observation_id":"178ef772-e6ac-44c5-ad1b-8b9e34c0e474","resolution":{"observed_at":"2026-08-15T18:08:27.225304Z","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":"2026-08-15T18:08:27.199007Z","title":"A unifying view on dataset shift in classification.Pattern recognition, 45(1):521–530, 2012","venue":null,"work_id":"db696895-bcd5-4402-9874-f4fa013ec807","year":2012},"citing_paper":{"arxiv_id":"2507.18996","last_updated":"2025-07-25T06:50:09Z","snapshot_observed_at":"2026-08-16T19:50:54.291617Z","submitted_at":"2025-07-25T06:50:09Z","title":"Adapting to Fragmented and Evolving Data: A Fisher Information Perspective","version":1},"reference_index":11,"source":"pdf_text","source_observed_at":"2026-08-15T18:08:24.075343Z"},"links":{"citing_paper":"/paper/2507.18996"},"observation_digest":"sha256:4df5abacbc1ca078f2fe77f7eb37717a4993294ceb1012925d32f0eebccece80","observation_id":"0aadadc2-23d0-4a55-946a-b267f7580e95","resolution":{"observed_at":"2026-08-15T18:08:27.204136Z","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":"2026-08-15T18:08:27.108097Z","title":"Mit Press, 2009","venue":null,"work_id":"c49a8ffd-6910-46d4-854a-989bf61f732d","year":2009},"citing_paper":{"arxiv_id":"2507.18996","last_updated":"2025-07-25T06:50:09Z","snapshot_observed_at":"2026-08-16T19:50:54.291617Z","submitted_at":"2025-07-25T06:50:09Z","title":"Adapting to Fragmented and Evolving Data: A Fisher Information Perspective","version":1},"reference_index":12,"source":"pdf_text","source_observed_at":"2026-08-15T18:08:24.081851Z"},"links":{"citing_paper":"/paper/2507.18996"},"observation_digest":"sha256:b687712efbf6b835b8e600b06621828071d31f3f5a5f582a3474962bdf4093b3","observation_id":"499f5b59-bc34-4157-830d-1fb5cb0f96ec","resolution":{"observed_at":"2026-08-15T18:08:27.166252Z","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":"2026-08-15T18:08:27.034357Z","title":"Eeg-based emotion recognition using deep learning network with principal component based covariate shift adaptation.The Scientific World Journal, 2014, 2014","venue":null,"work_id":"2e84a413-e760-4891-ab55-29b03fbbebb0","year":2014},"citing_paper":{"arxiv_id":"2507.18996","last_updated":"2025-07-25T06:50:09Z","snapshot_observed_at":"2026-08-16T19:50:54.291617Z","submitted_at":"2025-07-25T06:50:09Z","title":"Adapting to Fragmented and Evolving Data: A Fisher Information Perspective","version":1},"reference_index":13,"source":"pdf_text","source_observed_at":"2026-08-15T18:08:24.090666Z"},"links":{"citing_paper":"/paper/2507.18996"},"observation_digest":"sha256:80a7d020a0b6041d32d0132d7bd415d9dfb3e04e680485cbf56d8d7530c98ad1","observation_id":"5a07ff12-2599-4021-acde-4767633766d5","resolution":{"observed_at":"2026-08-15T18:08:27.046470Z","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":"2026-08-15T18:08:26.923476Z","title":"A weighted support vector machine for data classification.International Journal of Pattern Recognition and Artificial Intelligence, 21(05):961–976, 2007","venue":null,"work_id":"735a72cf-c00b-4057-a49f-4d2a3e0a0736","year":2007},"citing_paper":{"arxiv_id":"2507.18996","last_updated":"2025-07-25T06:50:09Z","snapshot_observed_at":"2026-08-16T19:50:54.291617Z","submitted_at":"2025-07-25T06:50:09Z","title":"Adapting to Fragmented and Evolving Data: A Fisher Information Perspective","version":1},"reference_index":14,"source":"pdf_text","source_observed_at":"2026-08-15T18:08:24.163444Z"},"links":{"citing_paper":"/paper/2507.18996"},"observation_digest":"sha256:49b6ef6be33d9ce9e96ad50a57083cb9d4be81a09a651ed1cca6f76646f258b5","observation_id":"3da5b2e2-11f4-4d0d-86a0-131d00dfcac7","resolution":{"observed_at":"2026-08-15T18:08:26.980527Z","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":"2026-08-15T18:08:26.751842Z","title":"Application of covariate shift adaptation techniques in brain–computer interfaces.IEEE Transactions on Biomedical Engineering, 57(6):1318–1324, 2010","venue":null,"work_id":"07a2e1b7-431d-4893-b6c4-70e110c84bdb","year":2010},"citing_paper":{"arxiv_id":"2507.18996","last_updated":"2025-07-25T06:50:09Z","snapshot_observed_at":"2026-08-16T19:50:54.291617Z","submitted_at":"2025-07-25T06:50:09Z","title":"Adapting to Fragmented and Evolving Data: A Fisher Information Perspective","version":1},"reference_index":15,"source":"pdf_text","source_observed_at":"2026-08-15T18:08:24.237126Z"},"links":{"citing_paper":"/paper/2507.18996"},"observation_digest":"sha256:90be8c3ec1486075611f40fcfe20cf8a5ad9afec74cdab86f4f9f7ae428b8ae1","observation_id":"0204313b-6cb0-4395-85f0-678ebc67aeae","resolution":{"observed_at":"2026-08-15T18:08:26.794428Z","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":"2026-08-15T18:08:26.710401Z","title":"Dirichlet-enhanced spam filtering based on biased samples.Advances in neural information processing systems, 19, 2006","venue":null,"work_id":"9a1013c3-f275-4fea-9463-0d0dd88feaa2","year":2006},"citing_paper":{"arxiv_id":"2507.18996","last_updated":"2025-07-25T06:50:09Z","snapshot_observed_at":"2026-08-16T19:50:54.291617Z","submitted_at":"2025-07-25T06:50:09Z","title":"Adapting to Fragmented and Evolving Data: A Fisher Information Perspective","version":1},"reference_index":16,"source":"pdf_text","source_observed_at":"2026-08-15T18:08:24.280899Z"},"links":{"citing_paper":"/paper/2507.18996"},"observation_digest":"sha256:d587a47d287269e72400ea5ea322a3ff84ee246575adb9f619acad2851218633","observation_id":"d77c0c3c-9b29-4ea4-b952-9290232531fb","resolution":{"observed_at":"2026-08-15T18:08:26.716174Z","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":"2026-08-15T18:08:26.682509Z","title":"Failing loudly: An empirical study of methods for detecting dataset shift.Advances in Neural Information Processing Systems, 32, 2019","venue":null,"work_id":"4eafadaf-6ab8-4623-aa13-e441e7752db6","year":2019},"citing_paper":{"arxiv_id":"2507.18996","last_updated":"2025-07-25T06:50:09Z","snapshot_observed_at":"2026-08-16T19:50:54.291617Z","submitted_at":"2025-07-25T06:50:09Z","title":"Adapting to Fragmented and Evolving Data: A Fisher Information Perspective","version":1},"reference_index":17,"source":"pdf_text","source_observed_at":"2026-08-15T18:08:24.297409Z"},"links":{"citing_paper":"/paper/2507.18996"},"observation_digest":"sha256:65d2672cdddcb7d90cf925c5c8a68a6ffae54e046eb3296f1eecb0945ddd5ab1","observation_id":"90248572-83e2-499e-9a0d-b87fd468ccaa","resolution":{"observed_at":"2026-08-15T18:08:26.697063Z","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":"2010.07147","last_updated":"2023-02-23T02:44:32Z","snapshot_observed_at":"2026-08-16T19:13:32.926899Z","submitted_at":"2020-10-14T15:03:29Z","title":"A Two-Sample Conditional Distribution Test Using Conformal Prediction and Weighted Rank Sum","version":2},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2010.07147","snapshot_observed_at":"2026-08-15T18:08:24.345514Z","title":"A distribution-free test of covariate shift using conformal prediction.arXiv preprint arXiv:2010.07147, 2020","venue":null,"work_id":null,"year":2010},"citing_paper":{"arxiv_id":"2507.18996","last_updated":"2025-07-25T06:50:09Z","snapshot_observed_at":"2026-08-16T19:50:54.291617Z","submitted_at":"2025-07-25T06:50:09Z","title":"Adapting to Fragmented and Evolving Data: A Fisher Information Perspective","version":1},"reference_index":18,"source":"pdf_text","source_observed_at":"2026-08-15T18:08:24.345514Z"},"links":{"cited_paper":"/paper/2010.07147","citing_paper":"/paper/2507.18996"},"observation_digest":"sha256:497fc5b8e7f84a4b5f5b05ea9711d898920c9d83db43d15075916d34d2315888","observation_id":"6027f7f2-7062-4373-bfe0-bbd9cc869ce7","resolution":{"observed_at":"2026-08-15T18:08:24.345514Z","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":"2026-08-15T18:08:26.559056Z","title":"Study on the impact of partition-induced dataset shift onk-fold cross-validation.IEEE Transactions on Neural Networks and Learning Systems, 23(8):1304–1312, 2012","venue":null,"work_id":"a1d06153-26e3-49f9-ac84-89e3f5b78be0","year":2012},"citing_paper":{"arxiv_id":"2507.18996","last_updated":"2025-07-25T06:50:09Z","snapshot_observed_at":"2026-08-16T19:50:54.291617Z","submitted_at":"2025-07-25T06:50:09Z","title":"Adapting to Fragmented and Evolving Data: A Fisher Information Perspective","version":1},"reference_index":19,"source":"pdf_text","source_observed_at":"2026-08-15T18:08:24.352813Z"},"links":{"citing_paper":"/paper/2507.18996"},"observation_digest":"sha256:534b35a280789aae19f3f46695ee7ccd238724dd7f6924b33ef2ed8805ecb9a3","observation_id":"aa032fb5-9e27-4b58-ab48-50360d6017b4","resolution":{"observed_at":"2026-08-15T18:08:26.614027Z","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":"2012.14246","last_updated":"2020-12-28T14:33:03Z","snapshot_observed_at":"2026-08-16T18:55:41.143962Z","submitted_at":"2020-12-28T14:33:03Z","title":"Testing for concept shift online","version":1},"cited_work":{"arxiv_id":"2012.14246","doi":null,"metadata_source":"pith","pith_arxiv_id":"2012.14246","snapshot_observed_at":"2026-08-15T18:08:25.236551Z","title":"Testing for concept shift online","venue":"cs.LG","work_id":"32e04a72-1748-4feb-9bda-9872f5610d78","year":2020},"citing_paper":{"arxiv_id":"2507.18996","last_updated":"2025-07-25T06:50:09Z","snapshot_observed_at":"2026-08-16T19:50:54.291617Z","submitted_at":"2025-07-25T06:50:09Z","title":"Adapting to Fragmented and Evolving Data: A Fisher Information Perspective","version":1},"reference_index":20,"source":"pdf_text","source_observed_at":"2026-08-15T18:08:24.359132Z"},"links":{"cited_paper":"/paper/2012.14246","citing_paper":"/paper/2507.18996"},"observation_digest":"sha256:233b9159c42fd176f9f0ad9bca30303d50ed096f9762e78e71e97771bbf7f709","observation_id":"faebc8d7-7151-4e47-aeb0-ba8b6827c910","resolution":{"observed_at":"2026-08-15T18:08:25.307762Z","resolver_source":"local_arxiv","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"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-15T18:08:26.540900Z","title":"Testing randomness online.Statistical Science, 36(4):595–611, 2021","venue":null,"work_id":"25b9cf26-c2d4-4989-9cfe-ebea117f6a10","year":2021},"citing_paper":{"arxiv_id":"2507.18996","last_updated":"2025-07-25T06:50:09Z","snapshot_observed_at":"2026-08-16T19:50:54.291617Z","submitted_at":"2025-07-25T06:50:09Z","title":"Adapting to Fragmented and Evolving Data: A Fisher Information Perspective","version":1},"reference_index":21,"source":"pdf_text","source_observed_at":"2026-08-15T18:08:24.367531Z"},"links":{"citing_paper":"/paper/2507.18996"},"observation_digest":"sha256:792fb1ba753101134ff2b1d3b44c0f4df4cd0cb08cac4f478ac7f259f9947edc","observation_id":"0b9c8771-237a-4e93-9db6-d5aef8b51012","resolution":{"observed_at":"2026-08-15T18:08:26.546292Z","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":"2026-08-15T18:08:26.516984Z","title":"Cam- bridge University Press, 2012","venue":null,"work_id":"74a3ee46-ef3f-4d5a-a4ab-7b84cb362ba6","year":2012},"citing_paper":{"arxiv_id":"2507.18996","last_updated":"2025-07-25T06:50:09Z","snapshot_observed_at":"2026-08-16T19:50:54.291617Z","submitted_at":"2025-07-25T06:50:09Z","title":"Adapting to Fragmented and Evolving Data: A Fisher Information Perspective","version":1},"reference_index":22,"source":"pdf_text","source_observed_at":"2026-08-15T18:08:24.374671Z"},"links":{"citing_paper":"/paper/2507.18996"},"observation_digest":"sha256:85b6129c33cdba2bb422d210736b5042ecf3c1af8ef87203dfe1340d77e3fa6c","observation_id":"48e94d1f-15a1-4ca5-9067-8bb64b2a7afe","resolution":{"observed_at":"2026-08-15T18:08:26.528278Z","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":"2026-08-15T18:08:26.397461Z","title":"Scaffold: Stochastic controlled averaging for federated learning","venue":null,"work_id":"b436df3d-c24b-4199-a29f-eb5dd34fbce2","year":2020},"citing_paper":{"arxiv_id":"2507.18996","last_updated":"2025-07-25T06:50:09Z","snapshot_observed_at":"2026-08-16T19:50:54.291617Z","submitted_at":"2025-07-25T06:50:09Z","title":"Adapting to Fragmented and Evolving Data: A Fisher Information Perspective","version":1},"reference_index":23,"source":"pdf_text","source_observed_at":"2026-08-15T18:08:24.440990Z"},"links":{"citing_paper":"/paper/2507.18996"},"observation_digest":"sha256:9eaaa5c7fcb1d8095265c2466c48e31f160f79d6fb41bd250098590e99ce1f78","observation_id":"c0d74161-4ce0-4020-be7b-1beebff25aca","resolution":{"observed_at":"2026-08-15T18:08:26.471534Z","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":"2026-08-15T18:08:24.545335Z","title":"Federated optimization in heterogeneous networks.Proceedings of Machine learning and systems, 2:429–450, 2020","venue":null,"work_id":null,"year":2020},"citing_paper":{"arxiv_id":"2507.18996","last_updated":"2025-07-25T06:50:09Z","snapshot_observed_at":"2026-08-16T19:50:54.291617Z","submitted_at":"2025-07-25T06:50:09Z","title":"Adapting to Fragmented and Evolving Data: A Fisher Information Perspective","version":1},"reference_index":24,"source":"pdf_text","source_observed_at":"2026-08-15T18:08:24.545335Z"},"links":{"citing_paper":"/paper/2507.18996"},"observation_digest":"sha256:d94595f4fe5509019ac9e374b583012fb12a8c175edae3dacf3154c7ea59667b","observation_id":"2e3ed5d3-a7ac-461f-904b-355d88603800","resolution":{"observed_at":"2026-08-15T18:08:24.545335Z","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":"2026-08-15T18:08:26.318651Z","title":"Big data: Principles and best practices of scalable realtime data systems","venue":null,"work_id":"b794dc2e-72b4-4c55-b4b6-861bd65828d4","year":2015},"citing_paper":{"arxiv_id":"2507.18996","last_updated":"2025-07-25T06:50:09Z","snapshot_observed_at":"2026-08-16T19:50:54.291617Z","submitted_at":"2025-07-25T06:50:09Z","title":"Adapting to Fragmented and Evolving Data: A Fisher Information Perspective","version":1},"reference_index":25,"source":"pdf_text","source_observed_at":"2026-08-15T18:08:24.672609Z"},"links":{"citing_paper":"/paper/2507.18996"},"observation_digest":"sha256:1835da5b5815fd5a30d8f0bbcec6f8c49303c50c12b140acc04076706a57fda2","observation_id":"242f3955-cff0-4436-a642-84c6560a489c","resolution":{"observed_at":"2026-08-15T18:08:26.357725Z","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":"2026-08-15T18:08:26.151433Z","title":"Spark: Cluster computing with working sets.HotCloud, 10(10-10):95, 2010","venue":null,"work_id":"5d5abd93-58a8-4d62-b4db-bd5e22556c08","year":2010},"citing_paper":{"arxiv_id":"2507.18996","last_updated":"2025-07-25T06:50:09Z","snapshot_observed_at":"2026-08-16T19:50:54.291617Z","submitted_at":"2025-07-25T06:50:09Z","title":"Adapting to Fragmented and Evolving Data: A Fisher Information Perspective","version":1},"reference_index":26,"source":"pdf_text","source_observed_at":"2026-08-15T18:08:24.723269Z"},"links":{"citing_paper":"/paper/2507.18996"},"observation_digest":"sha256:ee84191928760965668203bc2871cb55808c700cebaeedfea5773c2a7ca1eee6","observation_id":"a7a664e0-77ba-4275-8416-9e0fd7ada424","resolution":{"observed_at":"2026-08-15T18:08:26.197403Z","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":"2026-08-15T18:08:26.130884Z","title":"Mahout in action: Manning shelter island","venue":null,"work_id":"dcace899-5142-44fd-b78e-430d84753c45","year":2011},"citing_paper":{"arxiv_id":"2507.18996","last_updated":"2025-07-25T06:50:09Z","snapshot_observed_at":"2026-08-16T19:50:54.291617Z","submitted_at":"2025-07-25T06:50:09Z","title":"Adapting to Fragmented and Evolving Data: A Fisher Information Perspective","version":1},"reference_index":27,"source":"pdf_text","source_observed_at":"2026-08-15T18:08:24.729194Z"},"links":{"citing_paper":"/paper/2507.18996"},"observation_digest":"sha256:29e3d19e2a911b335d83665f966e6227fe0e2fa4f0d6003449a2e28d518dc11b","observation_id":"ce38820d-6f71-4ecc-a518-4577caac58f0","resolution":{"observed_at":"2026-08-15T18:08:26.136422Z","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":"2026-08-15T18:08:25.974625Z","title":"Domain-adversarial training of neural networks.Journal of machine learning research, 17(59):1–35, 2016","venue":null,"work_id":"87ca65ab-83a6-448a-9599-020032fdbfbf","year":2016},"citing_paper":{"arxiv_id":"2507.18996","last_updated":"2025-07-25T06:50:09Z","snapshot_observed_at":"2026-08-16T19:50:54.291617Z","submitted_at":"2025-07-25T06:50:09Z","title":"Adapting to Fragmented and Evolving Data: A Fisher Information Perspective","version":1},"reference_index":28,"source":"pdf_text","source_observed_at":"2026-08-15T18:08:24.734145Z"},"links":{"citing_paper":"/paper/2507.18996"},"observation_digest":"sha256:981d350af9efb234257fcc2ed792a07bbb3ce1619ca62f29ca615928e3f19ffb","observation_id":"9b7d6d5a-ed67-45c2-a33a-47466493c6c8","resolution":{"observed_at":"2026-08-15T18:08:26.075646Z","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":"2026-08-15T18:08:24.739523Z","title":"Communication- efficient learning of deep networks from decentralized data","venue":null,"work_id":null,"year":2017},"citing_paper":{"arxiv_id":"2507.18996","last_updated":"2025-07-25T06:50:09Z","snapshot_observed_at":"2026-08-16T19:50:54.291617Z","submitted_at":"2025-07-25T06:50:09Z","title":"Adapting to Fragmented and Evolving Data: A Fisher Information Perspective","version":1},"reference_index":29,"source":"pdf_text","source_observed_at":"2026-08-15T18:08:24.739523Z"},"links":{"citing_paper":"/paper/2507.18996"},"observation_digest":"sha256:00e9aefc683f619386c275976aaed6207546d86e828d5e1bb74e60c3e17d7b9c","observation_id":"cf05a7cd-bf48-4a3e-975d-8fecdd2f8074","resolution":{"observed_at":"2026-08-15T18:08:24.739523Z","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":"2026-08-15T18:08:25.910310Z","title":"These studies, however, do not belong to history yet","venue":null,"work_id":"b74cd5fb-435f-4cf1-9c2f-67d6dc8ba347","year":1998},"citing_paper":{"arxiv_id":"2507.18996","last_updated":"2025-07-25T06:50:09Z","snapshot_observed_at":"2026-08-16T19:50:54.291617Z","submitted_at":"2025-07-25T06:50:09Z","title":"Adapting to Fragmented and Evolving Data: A Fisher Information Perspective","version":1},"reference_index":30,"source":"pdf_text","source_observed_at":"2026-08-15T18:08:24.747723Z"},"links":{"citing_paper":"/paper/2507.18996"},"observation_digest":"sha256:0a18fc397d5e27a964967084c05242b6344aab0a36ea86e38ce76dff4a42cf1e","observation_id":"2bf55fca-50e8-4f8c-8790-c3610b8a664a","resolution":{"observed_at":"2026-08-15T18:08:25.917245Z","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":"2026-08-15T18:08:25.795587Z","title":"Relative density- ratio estimation for robust distribution comparison.Neural computation, 25(5):1324–1370, 2013","venue":null,"work_id":"d3179f6d-fd8c-499e-b243-380c60fb89ad","year":2013},"citing_paper":{"arxiv_id":"2507.18996","last_updated":"2025-07-25T06:50:09Z","snapshot_observed_at":"2026-08-16T19:50:54.291617Z","submitted_at":"2025-07-25T06:50:09Z","title":"Adapting to Fragmented and Evolving Data: A Fisher Information Perspective","version":1},"reference_index":31,"source":"pdf_text","source_observed_at":"2026-08-15T18:08:24.798432Z"},"links":{"citing_paper":"/paper/2507.18996"},"observation_digest":"sha256:dec2b013c93f616719048d9d1fa024f15bfb5fbcdce2fbfa8d83a116102392c3","observation_id":"4ed51f47-b29c-419e-b62b-35dd374db4f4","resolution":{"observed_at":"2026-08-15T18:08:25.863914Z","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":"2026-08-15T18:08:25.683605Z","title":"Rethinking importance weighting for deep learning under distribution shift.Advances in neural information processing systems, 33:11996–12007, 2020","venue":null,"work_id":"ea9d2983-5d71-4c84-86cb-6e87905c86a4","year":2020},"citing_paper":{"arxiv_id":"2507.18996","last_updated":"2025-07-25T06:50:09Z","snapshot_observed_at":"2026-08-16T19:50:54.291617Z","submitted_at":"2025-07-25T06:50:09Z","title":"Adapting to Fragmented and Evolving Data: A Fisher Information Perspective","version":1},"reference_index":32,"source":"pdf_text","source_observed_at":"2026-08-15T18:08:24.861077Z"},"links":{"citing_paper":"/paper/2507.18996"},"observation_digest":"sha256:26ac9c1f69fb045cf11386103f4f3350468b88757cd780318521b0ca594be00c","observation_id":"c2fcddf7-c2f6-48f1-abc5-329b0c6dd693","resolution":{"observed_at":"2026-08-15T18:08:25.734954Z","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":"2026-08-15T18:08:24.879480Z","title":"Overcoming catastrophic forgetting in neural networks.Proceedings of the national academy of sciences, 114(13):3521–3526, 2017","venue":null,"work_id":null,"year":2017},"citing_paper":{"arxiv_id":"2507.18996","last_updated":"2025-07-25T06:50:09Z","snapshot_observed_at":"2026-08-16T19:50:54.291617Z","submitted_at":"2025-07-25T06:50:09Z","title":"Adapting to Fragmented and Evolving Data: A Fisher Information Perspective","version":1},"reference_index":33,"source":"pdf_text","source_observed_at":"2026-08-15T18:08:24.879480Z"},"links":{"citing_paper":"/paper/2507.18996"},"observation_digest":"sha256:e0d78e64e1a31df46f9a1c5f76233b536a2ec2560daceffc63cedb8ec6ee16a8","observation_id":"306c0931-de41-44e1-9d53-d1e8b05e89d7","resolution":{"observed_at":"2026-08-15T18:08:24.879480Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2006.10726","last_updated":"2021-03-18T17:58:01Z","snapshot_observed_at":"2026-08-16T06:30:33.794820Z","submitted_at":"2020-06-18T17:55:28Z","title":"Tent: Fully Test-time Adaptation by Entropy Minimization","version":3},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2006.10726","snapshot_observed_at":"2026-08-15T18:08:24.910596Z","title":"Tent: Fully test-time adaptation by entropy minimization.arXiv preprint arXiv:2006.10726, 2020","venue":null,"work_id":null,"year":2006},"citing_paper":{"arxiv_id":"2507.18996","last_updated":"2025-07-25T06:50:09Z","snapshot_observed_at":"2026-08-16T19:50:54.291617Z","submitted_at":"2025-07-25T06:50:09Z","title":"Adapting to Fragmented and Evolving Data: A Fisher Information Perspective","version":1},"reference_index":34,"source":"pdf_text","source_observed_at":"2026-08-15T18:08:24.910596Z"},"links":{"cited_paper":"/paper/2006.10726","citing_paper":"/paper/2507.18996"},"observation_digest":"sha256:942d78899d20c3844dd63a46da50f1baec55bc4ee26cb4429e9605834a787bfa","observation_id":"3e4fbfac-a657-44e6-89bc-69b04803f751","resolution":{"observed_at":"2026-08-15T18:08:24.910596Z","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":"2026-08-15T18:08:25.594766Z","title":"Online convex programming and generalized infinitesimal gradient ascent","venue":null,"work_id":"3533e15d-85ba-44f5-afd2-ceb7c836e91f","year":2003},"citing_paper":{"arxiv_id":"2507.18996","last_updated":"2025-07-25T06:50:09Z","snapshot_observed_at":"2026-08-16T19:50:54.291617Z","submitted_at":"2025-07-25T06:50:09Z","title":"Adapting to Fragmented and Evolving Data: A Fisher Information Perspective","version":1},"reference_index":35,"source":"pdf_text","source_observed_at":"2026-08-15T18:08:24.918199Z"},"links":{"citing_paper":"/paper/2507.18996"},"observation_digest":"sha256:c170b1c8a94d617555b31569131bf5f89a15db48d8c0f6a377839715642e17d2","observation_id":"8dfd4b26-c856-4084-9175-7713797a2df2","resolution":{"observed_at":"2026-08-15T18:08:25.642329Z","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":"2026-08-15T18:08:24.923985Z","title":"The mnist database of handwritten digits.http://yann","venue":null,"work_id":null,"year":1998},"citing_paper":{"arxiv_id":"2507.18996","last_updated":"2025-07-25T06:50:09Z","snapshot_observed_at":"2026-08-16T19:50:54.291617Z","submitted_at":"2025-07-25T06:50:09Z","title":"Adapting to Fragmented and Evolving Data: A Fisher Information Perspective","version":1},"reference_index":36,"source":"pdf_text","source_observed_at":"2026-08-15T18:08:24.923985Z"},"links":{"citing_paper":"/paper/2507.18996"},"observation_digest":"sha256:6daeb002b1a328a0918929cc4ddf6cd3728423ea14f8e1d382d8b24fafef4daa","observation_id":"f14064c2-b82d-4718-af51-59c9cb522061","resolution":{"observed_at":"2026-08-15T18:08:24.923985Z","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":"2026-08-15T18:08:24.931117Z","title":"Learning multiple layers of features from tiny images","venue":null,"work_id":null,"year":2009},"citing_paper":{"arxiv_id":"2507.18996","last_updated":"2025-07-25T06:50:09Z","snapshot_observed_at":"2026-08-16T19:50:54.291617Z","submitted_at":"2025-07-25T06:50:09Z","title":"Adapting to Fragmented and Evolving Data: A Fisher Information Perspective","version":1},"reference_index":37,"source":"pdf_text","source_observed_at":"2026-08-15T18:08:24.931117Z"},"links":{"citing_paper":"/paper/2507.18996"},"observation_digest":"sha256:6b08050c985505dc6d1deca2407e48c75835848d3daa8c504d85c4fdb59fb52a","observation_id":"ffd359d1-c0ff-4b7c-9cac-f26024e7bb80","resolution":{"observed_at":"2026-08-15T18:08:24.931117Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2403.03952","last_updated":"2026-04-20T06:05:54Z","snapshot_observed_at":"2026-08-03T00:56:47.399756Z","submitted_at":"2024-03-06T18:56:36Z","title":"Bridging Language and Items for Retrieval and Recommendation: Benchmarking LLMs as Semantic Encoders","version":2},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2403.03952","snapshot_observed_at":"2026-08-15T18:08:24.935938Z","title":"Bridging language and items for retrieval and recommendation.arXiv preprint arXiv:2403.03952, 2024","venue":null,"work_id":null,"year":2024},"citing_paper":{"arxiv_id":"2507.18996","last_updated":"2025-07-25T06:50:09Z","snapshot_observed_at":"2026-08-16T19:50:54.291617Z","submitted_at":"2025-07-25T06:50:09Z","title":"Adapting to Fragmented and Evolving Data: A Fisher Information Perspective","version":1},"reference_index":38,"source":"pdf_text","source_observed_at":"2026-08-15T18:08:24.935938Z"},"links":{"cited_paper":"/paper/2403.03952","citing_paper":"/paper/2507.18996"},"observation_digest":"sha256:d7c0b10937e84b639e8ad89cc43cfbda1d5116969aa09edc77d50af93efbf967","observation_id":"80aaaa81-86d1-41b6-a5c8-90a79259af82","resolution":{"observed_at":"2026-08-15T18:08:24.935938Z","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":"2026-08-15T18:08:25.396278Z","title":"Credit-card-fraud detection-imbalanced-dataset.Kaggle","venue":null,"work_id":"38a08e21-7b3d-48f8-b7d6-2fc3d05b23c5","year":2023},"citing_paper":{"arxiv_id":"2507.18996","last_updated":"2025-07-25T06:50:09Z","snapshot_observed_at":"2026-08-16T19:50:54.291617Z","submitted_at":"2025-07-25T06:50:09Z","title":"Adapting to Fragmented and Evolving Data: A Fisher Information Perspective","version":1},"reference_index":39,"source":"pdf_text","source_observed_at":"2026-08-15T18:08:24.942026Z"},"links":{"citing_paper":"/paper/2507.18996"},"observation_digest":"sha256:7142ddf7a16acb10ff2c7778721e6b45ba26dd98b672445796859b6cf379fb7e","observation_id":"d4fd9d1b-ef03-4974-9fec-4cd464f35c29","resolution":{"observed_at":"2026-08-15T18:08:25.438871Z","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":"1708.03731","last_updated":"2021-11-22T13:58:04Z","snapshot_observed_at":"2026-08-15T16:15:34.381928Z","submitted_at":"2017-08-11T23:28:48Z","title":"OpenML Benchmarking Suites","version":3},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"1708.03731","snapshot_observed_at":"2026-08-15T18:08:24.979972Z","title":"Openml benchmarking suites.arXiv preprint arXiv:1708.03731, 2017","venue":null,"work_id":null,"year":2017},"citing_paper":{"arxiv_id":"2507.18996","last_updated":"2025-07-25T06:50:09Z","snapshot_observed_at":"2026-08-16T19:50:54.291617Z","submitted_at":"2025-07-25T06:50:09Z","title":"Adapting to Fragmented and Evolving Data: A Fisher Information Perspective","version":1},"reference_index":40,"source":"pdf_text","source_observed_at":"2026-08-15T18:08:24.979972Z"},"links":{"cited_paper":"/paper/1708.03731","citing_paper":"/paper/2507.18996"},"observation_digest":"sha256:64ccf2dabaa8410760984ed1c76f6d7098f3b245b962676bad318420723d5ced","observation_id":"e6319a81-532e-460a-9dfe-bbce84daf3f9","resolution":{"observed_at":"2026-08-15T18:08:24.979972Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"1812.01097","last_updated":"2019-12-09T20:02:37Z","snapshot_observed_at":"2026-08-16T19:49:29.879809Z","submitted_at":"2018-12-03T21:59:41Z","title":"LEAF: A Benchmark for Federated Settings","version":3},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"1812.01097","snapshot_observed_at":"2026-08-15T18:08:25.069684Z","title":"Leaf: A benchmark for federated settings.arXiv preprint arXiv:1812.01097, 2018","venue":null,"work_id":null,"year":2018},"citing_paper":{"arxiv_id":"2507.18996","last_updated":"2025-07-25T06:50:09Z","snapshot_observed_at":"2026-08-16T19:50:54.291617Z","submitted_at":"2025-07-25T06:50:09Z","title":"Adapting to Fragmented and Evolving Data: A Fisher Information Perspective","version":1},"reference_index":41,"source":"pdf_text","source_observed_at":"2026-08-15T18:08:25.069684Z"},"links":{"cited_paper":"/paper/1812.01097","citing_paper":"/paper/2507.18996"},"observation_digest":"sha256:a94c6515f2485319dd4f61af8607707b4126a44d8ba458d413c4cd6be4da0365","observation_id":"e0d1df3c-bd71-466a-a2d2-e089880baac2","resolution":{"observed_at":"2026-08-15T18:08:25.069684Z","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":"2026-08-15T18:08:25.369507Z","title":"Reading digits in natural images with unsupervised feature learning","venue":null,"work_id":"0d65a1a4-d9ce-4388-881a-5dac47fc4040","year":2011},"citing_paper":{"arxiv_id":"2507.18996","last_updated":"2025-07-25T06:50:09Z","snapshot_observed_at":"2026-08-16T19:50:54.291617Z","submitted_at":"2025-07-25T06:50:09Z","title":"Adapting to Fragmented and Evolving Data: A Fisher Information Perspective","version":1},"reference_index":42,"source":"pdf_text","source_observed_at":"2026-08-15T18:08:25.114202Z"},"links":{"citing_paper":"/paper/2507.18996"},"observation_digest":"sha256:03e2c2c2c189a4d3560668446325c5c1f0e7abc1e5bb2293c440d99d5bc1083a","observation_id":"bdd573f5-2caf-4cc1-9377-50d9464992d5","resolution":{"observed_at":"2026-08-15T18:08:25.383984Z","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":"2507.18996","last_updated":"2025-07-25T06:50:09Z","latest_version":1,"primary_category":"cs.LG","snapshot_observed_at":"2026-08-16T19:50:54.291617Z","submitted_at":"2025-07-25T06:50:09Z","title":"Adapting to Fragmented and Evolving Data: A Fisher Information Perspective"},"reference_resolution":{"displayed":42,"state_counts":{"malformed_identifier":0,"metadata_mismatch":0,"parse_uncertain":0,"unresolved":12,"verified_exact":1,"verified_fuzzy":29},"total_outbound_references":42},"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 42 of 42 outbound references and 0 inbound Pith citation observations for arXiv:2507.18996."}