{"as_of":"2026-07-23T17:38:00Z","caps":{"database_statements":6,"inbound":100,"outbound":100},"context_digest":"sha256:f4437e9ce56fb3aa488b5dae9877f1fdc41797811c8446d907e4c5db8b20b3ec","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":"2026-07-23T06:31:01.910684+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":"2026-05-17T20:08:21.578954Z","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":"2026-05-17T20:10:10.939950Z","state":"measured"}],"external_citation_measurements":[],"inbound":[{"citation":{"cited_paper":{"arxiv_id":"1902.06156","last_updated":"2019-02-16T21:05:29Z","snapshot_observed_at":"2026-07-06T07:33:30.901233Z","submitted_at":"2019-02-16T21:05:29Z","title":"A Little Is Enough: Circumventing Defenses For Distributed Learning","version":1},"cited_work":{"arxiv_id":"1902.06156","doi":null,"metadata_source":"arxiv_reference","pith_arxiv_id":"1902.06156","snapshot_observed_at":"2026-06-05T21:23:00.469572Z","title":"A little is enough: Circumventing defenses for distributed learning","venue":null,"work_id":"c8f18a6f-639d-47fb-9623-6ac294766215","year":2019},"citing_paper":{"arxiv_id":"2511.14715","last_updated":"2026-05-12T06:00:59Z","snapshot_observed_at":"2026-07-06T22:36:13.287872Z","submitted_at":"2025-11-18T17:57:40Z","title":"FLARE: Adaptive Multi-Dimensional Reputation for Robust Client Reliability in Federated Learning","version":3},"reference_index":42,"source":"pdf_text","source_observed_at":"2026-05-17T20:08:21.578954Z"},"links":{"cited_paper":"/paper/1902.06156","citing_paper":"/paper/2511.14715"},"observation_digest":"sha256:898b324fcf1fddc2c6ee5a4a9b413d477cf3aa4d9d66e355d2ec336907c85a1b","observation_id":"9956ec7d-c338-4e37-956b-1e614697f1b0","resolution":{"observed_at":"2026-05-17T20:10:10.942103Z","resolver_source":"arxiv_id","status":"verified_exact"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-07-23T06:31:01.910684+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-07-23T06:31:01.910684+00:00","source":"crossref"},{"observed_at":"2026-07-23T06:30:56.940895+00:00","source":"retraction_watch"}],"state":"measured"}}],"links":{"evidence":"/evidence","html":"/paper/1902.06156/citation-record","integrity":"/paper/1902.06156/integrity","json":"/paper/1902.06156/citation-record.json","paper":"/paper/1902.06156"},"outbound":[],"paper":{"arxiv_id":"1902.06156","last_updated":"2019-02-16T21:05:29Z","latest_version":1,"primary_category":"cs.LG","snapshot_observed_at":"2026-07-06T07:33:30.901233Z","submitted_at":"2019-02-16T21:05:29Z","title":"A Little Is Enough: Circumventing Defenses For Distributed 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":"2026-07-23T06:31:01.910684+00:00","source":"crossref"},{"observed_at":"2026-07-23T06:30:56.940895+00:00","source":"retraction_watch"}],"thesis":"As of 23 July 2026, this Paper Citation Record lists 0 of 0 outbound references and 1 inbound Pith citation observation for arXiv:1902.06156."}