{"as_of":"2026-08-15T01:14:00Z","caps":{"database_statements":6,"inbound":100,"outbound":100},"context_digest":"sha256:8d09000c7c9f56911404427df21bca5feeed0841e33f3671c5a5422d642657e4","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":1,"lane":"standing_notices","note":"One-hop event checks from named stored sources.","records_observed":1,"source":"scholarly_work_events, retraction_status_cache","source_observed_at":"2026-08-14T06:32:32.682623+00:00","state":"measured"},{"denominator":1,"lane":"inbound_itemization","note":"Pith citing papers itemized under the disclosed page cap.","records_observed":1,"source":"paper_references, paper_reference_links","source_observed_at":"2026-08-12T11:26:16.924020Z","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":"2026-08-12T11:26:17.425038Z","state":"measured"}],"external_citation_measurements":[],"inbound":[{"citation":{"cited_paper":{"arxiv_id":"2208.05174","last_updated":"2025-04-22T10:26:17Z","snapshot_observed_at":"2026-08-13T14:47:54.654767Z","submitted_at":"2022-08-10T06:36:49Z","title":"FedOBD: Opportunistic Block Dropout for Efficiently Training Large-scale Neural Networks through Federated Learning","version":6},"cited_work":{"arxiv_id":"2208.05174","doi":null,"metadata_source":"pith","pith_arxiv_id":"2208.05174","snapshot_observed_at":"2026-08-12T11:26:17.425038Z","title":"FedOBD: Opportunistic Block Dropout for Efficiently Training Large-scale Neural Networks through Federated Learning","venue":"cs.LG","work_id":"9f3eee81-47bb-49fe-931d-ab35089a3e22","year":2022},"citing_paper":{"arxiv_id":"2411.18269","last_updated":"2024-11-27T12:04:37Z","snapshot_observed_at":"2026-08-12T11:19:42.557913Z","submitted_at":"2024-11-27T12:04:37Z","title":"Hidden Data Privacy Breaches in Federated Learning","version":1},"reference_index":12,"source":"pdf_text","source_observed_at":"2026-08-12T11:26:16.924020Z"},"links":{"cited_paper":"/paper/2208.05174","citing_paper":"/paper/2411.18269"},"observation_digest":"sha256:bfa9568c04bc1e51fd3f78503eac8371a3287d6c6b9e0cc8d5e303280101a0f7","observation_id":"0030a216-5ef9-4b35-99c6-e6e2120e5546","resolution":{"observed_at":"2026-08-12T11:26:17.432172Z","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"}}],"links":{"evidence":"/evidence","html":"/paper/2208.05174/citation-record","integrity":"/paper/2208.05174/integrity","json":"/paper/2208.05174/citation-record.json","paper":"/paper/2208.05174"},"outbound":[],"paper":{"arxiv_id":"2208.05174","last_updated":"2025-04-22T10:26:17Z","latest_version":6,"primary_category":"cs.LG","snapshot_observed_at":"2026-08-13T14:47:54.654767Z","submitted_at":"2022-08-10T06:36:49Z","title":"FedOBD: Opportunistic Block Dropout for Efficiently Training Large-scale Neural Networks through 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":"2026-08-14T06:32:32.682623+00:00","source":"crossref"},{"observed_at":"2026-08-14T06:32:18.44784+00:00","source":"retraction_watch"}],"thesis":"As of 15 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 1 inbound Pith citation observation for arXiv:2208.05174."}