{"as_of":"2026-08-04T14:59:00Z","caps":{"database_statements":6,"inbound":100,"outbound":100},"context_digest":"sha256:c791015cf81cb8ee3a6da879b5df463a4d6fd964063628944cb6d57c3dded367","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":"2026-08-04T06:34:03.388597+00:00","state":"measured"},{"denominator":1,"lane":"inbound_itemization","note":"Pith citing papers itemized under the disclosed page cap.","records_observed":1,"source":"paper_references, paper_reference_links","source_observed_at":"2026-05-13T17:26:20.023039Z","state":"measured"},{"denominator":1,"lane":"external_citation_measurements","note":"A source-named dated measurement, never combined with another source.","records_observed":0,"source":"arxiv_reference","source_observed_at":"2026-05-13T17:28:02.242870Z","state":"measured"}],"external_citation_measurements":[],"inbound":[{"citation":{"cited_paper":{"arxiv_id":"2312.04432","last_updated":"2024-01-16T08:40:12Z","snapshot_observed_at":"2026-08-04T14:06:31.856481Z","submitted_at":"2023-12-07T16:56:24Z","title":"FreqFed: A Frequency Analysis-Based Approach for Mitigating Poisoning Attacks in Federated Learning","version":2},"cited_work":{"arxiv_id":"2312.04432","doi":null,"metadata_source":"arxiv_reference","pith_arxiv_id":"2312.04432","snapshot_observed_at":"2026-06-05T21:23:00.469572Z","title":"arXiv preprint arXiv:2312.04432 (2023)","venue":null,"work_id":"a1733544-e9e2-4deb-9b13-0c814b1acedc","year":2023},"citing_paper":{"arxiv_id":"2604.04030","last_updated":"2026-04-05T09:13:12Z","snapshot_observed_at":"2026-08-04T10:59:42.357466Z","submitted_at":"2026-04-05T09:13:12Z","title":"Jellyfish: Zero-Shot Federated Unlearning Scheme with Knowledge Disentanglement","version":1},"reference_index":69,"source":"pdf_text","source_observed_at":"2026-05-13T17:26:20.023039Z"},"links":{"cited_paper":"/paper/2312.04432","citing_paper":"/paper/2604.04030"},"observation_digest":"sha256:2bcea1b80c3a1aa471917f40461cdbd8974fe99d8d08392f5356c886e625f562","observation_id":"61b81b02-73ad-4771-8e29-fd4e170a5f3e","resolution":{"observed_at":"2026-05-13T17:28:02.244099Z","resolver_source":"arxiv_id","status":"verified_exact"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-04T06:34:03.388597+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-04T06:34:03.388597+00:00","source":"crossref"},{"observed_at":"2026-08-04T06:33:57.428241+00:00","source":"retraction_watch"}],"state":"measured"}}],"links":{"evidence":"/evidence","html":"/paper/2312.04432/citation-record","integrity":"/paper/2312.04432/integrity","json":"/paper/2312.04432/citation-record.json","paper":"/paper/2312.04432"},"outbound":[],"paper":{"arxiv_id":"2312.04432","last_updated":"2024-01-16T08:40:12Z","latest_version":2,"primary_category":"cs.CR","snapshot_observed_at":"2026-08-04T14:06:31.856481Z","submitted_at":"2023-12-07T16:56:24Z","title":"FreqFed: A Frequency Analysis-Based Approach for Mitigating Poisoning Attacks 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":"2026-08-04T06:34:03.388597+00:00","source":"crossref"},{"observed_at":"2026-08-04T06:33:57.428241+00:00","source":"retraction_watch"}],"thesis":"As of 4 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 1 inbound Pith citation observation for arXiv:2312.04432."}