{"as_of":"2026-08-10T14:07:00Z","caps":{"database_statements":6,"inbound":100,"outbound":100},"context_digest":"sha256:4c33f152a4927b71cf101517da0ef867ba281ffcf18ac95de2aa928cfcf8c064","coverage":[{"denominator":0,"lane":"reference_resolution","note":"Typed states for the displayed outbound observations.","records_observed":0,"source":"paper_references, paper_reference_links","source_observed_at":null,"state":"measured"},{"denominator":2,"lane":"standing_notices","note":"One-hop event checks from named stored sources.","records_observed":2,"source":"scholarly_work_events, retraction_status_cache","source_observed_at":"2026-08-10T06:31:04.303077+00:00","state":"measured"},{"denominator":2,"lane":"inbound_itemization","note":"Pith citing papers itemized under the disclosed page cap.","records_observed":2,"source":"paper_references, paper_reference_links","source_observed_at":"2026-08-09T14:12:23.236174Z","state":"measured"},{"denominator":1,"lane":"external_citation_measurements","note":"A source-named dated measurement, never combined with another source.","records_observed":0,"source":"pith","source_observed_at":"2026-08-08T13:56:55.083391Z","state":"measured"}],"external_citation_measurements":[],"inbound":[{"citation":{"cited_paper":{"arxiv_id":"1910.09933","last_updated":"2019-12-06T06:13:55Z","snapshot_observed_at":"2026-07-06T08:31:20.606383Z","submitted_at":"2019-10-22T12:48:07Z","title":"Abnormal Client Behavior Detection in Federated Learning","version":2},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"1910.09933","snapshot_observed_at":"2026-08-09T14:12:23.236174Z","title":null,"venue":null,"work_id":null,"year":2019},"citing_paper":{"arxiv_id":"2502.05211","last_updated":"2025-02-03T23:14:02Z","snapshot_observed_at":"2026-08-09T18:43:04.625886Z","submitted_at":"2025-02-03T23:14:02Z","title":"Decoding FL Defenses: Systemization, Pitfalls, and Remedies","version":1},"reference_index":50,"source":"pdf_text","source_observed_at":"2026-08-09T14:12:23.236174Z"},"links":{"cited_paper":"/paper/1910.09933","citing_paper":"/paper/2502.05211"},"observation_digest":"sha256:a03b6a518c379b1288e083204c6f95ea7257fdc3abf98d62ebb10a263e0558d1","observation_id":"47b14abd-56d6-478e-bb3c-03329bc5911a","resolution":{"observed_at":"2026-08-09T14:12:23.236174Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"1910.09933","last_updated":"2019-12-06T06:13:55Z","snapshot_observed_at":"2026-07-06T08:31:20.606383Z","submitted_at":"2019-10-22T12:48:07Z","title":"Abnormal Client Behavior Detection in Federated Learning","version":2},"cited_work":{"arxiv_id":"1910.09933","doi":null,"metadata_source":"pith","pith_arxiv_id":"1910.09933","snapshot_observed_at":"2026-08-08T13:56:55.083391Z","title":"Abnormal Client Behavior Detection in Federated Learning","venue":"cs.LG","work_id":"1ccb5557-1cb4-457a-b69c-e68479da19bc","year":2019},"citing_paper":{"arxiv_id":"2502.07059","last_updated":"2025-07-04T00:22:16Z","snapshot_observed_at":"2026-08-09T12:40:10.530801Z","submitted_at":"2025-02-10T21:51:02Z","title":"Federated Continual Learning: Concepts, Challenges, and Solutions","version":2},"reference_index":142,"source":"pdf_text","source_observed_at":"2026-08-08T13:56:53.866942Z"},"links":{"cited_paper":"/paper/1910.09933","citing_paper":"/paper/2502.07059"},"observation_digest":"sha256:a62afdc644977cd6b2c1220503b199204792128a15466ea5e92cf2f00ed0a0d4","observation_id":"80f02577-300d-4ff7-9752-904c5032014c","resolution":{"observed_at":"2026-08-08T13:56:55.088278Z","resolver_source":"local_arxiv","status":"verified_exact"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-10T06:31:04.303077+00:00","source":"crossref"},{"observed_at":"2026-08-10T06:30:57.382061+00:00","source":"retraction_watch"}],"state":"measured"}}],"links":{"evidence":"/evidence","html":"/paper/1910.09933/citation-record","integrity":"/paper/1910.09933/integrity","json":"/paper/1910.09933/citation-record.json","paper":"/paper/1910.09933"},"outbound":[],"paper":{"arxiv_id":"1910.09933","last_updated":"2019-12-06T06:13:55Z","latest_version":2,"primary_category":"cs.LG","snapshot_observed_at":"2026-07-06T08:31:20.606383Z","submitted_at":"2019-10-22T12:48:07Z","title":"Abnormal Client Behavior Detection in Federated Learning"},"reference_resolution":{"displayed":0,"state_counts":{"malformed_identifier":0,"metadata_mismatch":0,"parse_uncertain":0,"unresolved":0,"verified_exact":0,"verified_fuzzy":0},"total_outbound_references":0},"refusal":"A citation records a reference. It does not transfer a finding from one paper to another.","schema":"pith.paper-citation-record.v1","standing_sources":[{"observed_at":"2026-08-10T06:31:04.303077+00:00","source":"crossref"},{"observed_at":"2026-08-10T06:30:57.382061+00:00","source":"retraction_watch"}],"thesis":"As of 10 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 2 inbound Pith citation observations for arXiv:1910.09933."}