{"as_of":"2026-08-10T05:50:00Z","caps":{"database_statements":6,"inbound":100,"outbound":100},"context_digest":"sha256:58f8747b07d56b8c1ebf9c8393263544c394c09483192d4ba422495bd463ff96","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":4,"lane":"standing_notices","note":"One-hop event checks from named stored sources.","records_observed":4,"source":"scholarly_work_events, retraction_status_cache","source_observed_at":"2026-08-09T06:31:02.800959+00:00","state":"measured"},{"denominator":4,"lane":"inbound_itemization","note":"Pith citing papers itemized under the disclosed page cap.","records_observed":4,"source":"paper_references, paper_reference_links","source_observed_at":"2026-08-09T13:39:53.259427Z","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":"2026-07-04T20:20:07.892662Z","state":"measured"}],"external_citation_measurements":[],"inbound":[{"citation":{"cited_paper":{"arxiv_id":"2201.00763","last_updated":"2022-01-03T17:10:07Z","snapshot_observed_at":"2026-08-10T03:41:27.741384Z","submitted_at":"2022-01-03T17:10:07Z","title":"DeepSight: Mitigating Backdoor Attacks in Federated Learning Through Deep Model Inspection","version":1},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2201.00763","snapshot_observed_at":"2026-08-09T13:39:53.259427Z","title":"Deepsight: Mitigating backdoor attacks in federated learning through deep model inspection,","venue":null,"work_id":null,"year":2022},"citing_paper":{"arxiv_id":"2502.02038","last_updated":"2025-02-21T02:55:12Z","snapshot_observed_at":"2026-08-09T13:32:10.040834Z","submitted_at":"2025-02-04T06:12:43Z","title":"SMTFL: Secure Model Training to Untrusted Participants in Federated Learning","version":2},"reference_index":37,"source":"pdf_text","source_observed_at":"2026-08-09T13:39:53.259427Z"},"links":{"cited_paper":"/paper/2201.00763","citing_paper":"/paper/2502.02038"},"observation_digest":"sha256:28674638cfd2a9d4974877027d6c9de025986c42e2bd4c35e4068e4b8cba9330","observation_id":"74380fa4-5c66-4ca6-81b0-91c8acf4561e","resolution":{"observed_at":"2026-08-09T13:39:53.259427Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2201.00763","last_updated":"2022-01-03T17:10:07Z","snapshot_observed_at":"2026-08-10T03:41:27.741384Z","submitted_at":"2022-01-03T17:10:07Z","title":"DeepSight: Mitigating Backdoor Attacks in Federated Learning Through Deep Model Inspection","version":1},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2201.00763","snapshot_observed_at":"2026-08-09T00:45:23.329331Z","title":"Deepsight: Mitigat- ing backdoor attacks in federated learning through deep model inspection","venue":null,"work_id":null,"year":null},"citing_paper":{"arxiv_id":"2502.03801","last_updated":"2025-02-06T06:05:00Z","snapshot_observed_at":"2026-08-09T03:53:53.748148Z","submitted_at":"2025-02-06T06:05:00Z","title":"SoK: Benchmarking Poisoning Attacks and Defenses in Federated Learning","version":1},"reference_index":39,"source":"pdf_text","source_observed_at":"2026-08-09T00:45:23.329331Z"},"links":{"cited_paper":"/paper/2201.00763","citing_paper":"/paper/2502.03801"},"observation_digest":"sha256:1458b658853c01737490efcdfe9accd5959da171277fc0340161b2823cc69650","observation_id":"1c69fcd3-9674-4f44-85d3-e4cc5d7a6c72","resolution":{"observed_at":"2026-08-09T00:45:23.329331Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2201.00763","last_updated":"2022-01-03T17:10:07Z","snapshot_observed_at":"2026-08-10T03:41:27.741384Z","submitted_at":"2022-01-03T17:10:07Z","title":"DeepSight: Mitigating Backdoor Attacks in Federated Learning Through Deep Model Inspection","version":1},"cited_work":{"arxiv_id":"2201.00763","doi":null,"metadata_source":"arxiv_reference","pith_arxiv_id":"2201.00763","snapshot_observed_at":"2026-07-04T20:20:07.892662Z","title":"arXiv preprint arXiv:2201.00763 (2022)","venue":null,"work_id":"ab0e109d-363c-4dfb-83fe-7b856113391e","year":2022},"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":66,"source":"pdf_text","source_observed_at":"2026-05-13T17:26:20.023039Z"},"links":{"cited_paper":"/paper/2201.00763","citing_paper":"/paper/2604.04030"},"observation_digest":"sha256:1ff8a0a5734aaddf47c1ab235bf519edb9215b63621b5b194b7095fa5a182e75","observation_id":"68627dbf-0303-4baf-8a6b-670526d61580","resolution":{"observed_at":"2026-05-13T17:28:02.254731Z","resolver_source":"arxiv_id","status":"verified_exact"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-09T06:31:02.800959+00:00","source":"crossref"},{"observed_at":"2026-08-09T06:30:57.326959+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"2201.00763","last_updated":"2022-01-03T17:10:07Z","snapshot_observed_at":"2026-08-10T03:41:27.741384Z","submitted_at":"2022-01-03T17:10:07Z","title":"DeepSight: Mitigating Backdoor Attacks in Federated Learning Through Deep Model Inspection","version":1},"cited_work":{"arxiv_id":"2201.00763","doi":null,"metadata_source":"arxiv_reference","pith_arxiv_id":"2201.00763","snapshot_observed_at":"2026-07-04T20:20:07.892662Z","title":"arXiv preprint arXiv:2201.00763 (2022)","venue":null,"work_id":"ab0e109d-363c-4dfb-83fe-7b856113391e","year":2022},"citing_paper":{"arxiv_id":"2606.25858","last_updated":"2026-06-24T14:07:10Z","snapshot_observed_at":"2026-08-08T05:19:19.072573Z","submitted_at":"2026-06-24T14:07:10Z","title":"Color Matters: Trigger Color Affects Success in Federated Backdoor Attacks","version":1},"reference_index":28,"source":"pdf_text","source_observed_at":"2026-06-25T20:12:50.848080Z"},"links":{"cited_paper":"/paper/2201.00763","citing_paper":"/paper/2606.25858"},"observation_digest":"sha256:82d07a36fca92854d3b3e95969111c1324e6a43f128a1f3a91c50253aa7ab94a","observation_id":"6b16f9f2-dfbd-4ec4-921d-16bb4d5af5c9","resolution":{"observed_at":"2026-07-04T20:20:07.894466Z","resolver_source":"arxiv_id","status":"metadata_mismatch"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-09T06:31:02.800959+00:00","source":"crossref"},{"observed_at":"2026-08-09T06:30:57.326959+00:00","source":"retraction_watch"}],"state":"measured"}}],"links":{"evidence":"/evidence","html":"/paper/2201.00763/citation-record","integrity":"/paper/2201.00763/integrity","json":"/paper/2201.00763/citation-record.json","paper":"/paper/2201.00763"},"outbound":[],"paper":{"arxiv_id":"2201.00763","last_updated":"2022-01-03T17:10:07Z","latest_version":1,"primary_category":"cs.CR","snapshot_observed_at":"2026-08-10T03:41:27.741384Z","submitted_at":"2022-01-03T17:10:07Z","title":"DeepSight: Mitigating Backdoor Attacks in Federated Learning Through Deep Model Inspection"},"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":"2026-08-09T06:31:02.800959+00:00","source":"crossref"},{"observed_at":"2026-08-09T06:30:57.326959+00:00","source":"retraction_watch"}],"thesis":"As of 10 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 4 inbound Pith citation observations for arXiv:2201.00763."}