{"as_of":"2026-08-19T15:47:00Z","caps":{"database_statements":6,"inbound":100,"outbound":100},"context_digest":"sha256:4c34ac29fc8383acde7ff2689c328f91a9d3ee29ade54bc31c7f45aff1f62e53","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":"2026-08-19T06:32:44.657259+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":"2026-08-14T12:19:05.619691Z","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":"2026-08-14T10:28:44.902746Z","state":"measured"}],"external_citation_measurements":[],"inbound":[{"citation":{"cited_paper":{"arxiv_id":"1812.03413","last_updated":"2019-11-25T15:34:55Z","snapshot_observed_at":"2026-08-14T17:46:31.184530Z","submitted_at":"2018-12-09T02:11:03Z","title":"Learning Transferable Adversarial Examples via Ghost Networks","version":3},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"1812.03413","snapshot_observed_at":"2026-08-14T12:19:05.619691Z","title":"arXiv preprint arXiv:1812.03413 (2018)","venue":null,"work_id":null,"year":2018},"citing_paper":{"arxiv_id":"1908.07558","last_updated":"2020-02-26T17:00:28Z","snapshot_observed_at":"2026-08-18T19:14:32.057186Z","submitted_at":"2019-08-20T18:24:32Z","title":"Transferring Robustness for Graph Neural Network Against Poisoning Attacks","version":3},"reference_index":2018,"source":"pdf_text","source_observed_at":"2026-08-14T12:19:05.619691Z"},"links":{"cited_paper":"/paper/1812.03413","citing_paper":"/paper/1908.07558"},"observation_digest":"sha256:98571accb422a26479bca307afdcbeb3dc9f9eb381d1dd0d892fd4e0a548ef4f","observation_id":"c98e70ef-c376-4ec8-b6e3-9f825d25a614","resolution":{"observed_at":"2026-08-14T12:19:05.619691Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"1812.03413","last_updated":"2019-11-25T15:34:55Z","snapshot_observed_at":"2026-08-14T17:46:31.184530Z","submitted_at":"2018-12-09T02:11:03Z","title":"Learning Transferable Adversarial Examples via Ghost Networks","version":3},"cited_work":{"arxiv_id":"1812.03413","doi":null,"metadata_source":"pith","pith_arxiv_id":"1812.03413","snapshot_observed_at":"2026-08-14T10:28:44.902746Z","title":"Learning Transferable Adversarial Examples via Ghost Networks","venue":"cs.CV","work_id":"b0e772e6-d80c-4ec4-a1ac-2d6f52089d80","year":2018},"citing_paper":{"arxiv_id":"1908.11091","last_updated":"2019-08-29T08:22:05Z","snapshot_observed_at":"2026-08-19T00:40:42.516928Z","submitted_at":"2019-08-29T08:22:05Z","title":"Deep Neural Network Ensembles against Deception: Ensemble Diversity, Accuracy and Robustness","version":1},"reference_index":12,"source":"pdf_text","source_observed_at":"2026-08-14T10:28:44.191932Z"},"links":{"cited_paper":"/paper/1812.03413","citing_paper":"/paper/1908.11091"},"observation_digest":"sha256:268fcd578db43db053564aa842468fc57a32c3e43ca32907da776fa4e901e232","observation_id":"97e63b91-31cd-4f8b-ba9d-2eb2e9008d2d","resolution":{"observed_at":"2026-08-14T10:28:44.933758Z","resolver_source":"local_arxiv","status":"verified_exact"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-19T06:32:44.657259+00:00","source":"crossref"},{"observed_at":"2026-08-19T06:32:39.956319+00:00","source":"retraction_watch"}],"state":"measured"}}],"links":{"evidence":"/evidence","html":"/paper/1812.03413/citation-record","integrity":"/paper/1812.03413/integrity","json":"/paper/1812.03413/citation-record.json","paper":"/paper/1812.03413"},"outbound":[],"paper":{"arxiv_id":"1812.03413","last_updated":"2019-11-25T15:34:55Z","latest_version":3,"primary_category":"cs.CV","snapshot_observed_at":"2026-08-14T17:46:31.184530Z","submitted_at":"2018-12-09T02:11:03Z","title":"Learning Transferable Adversarial Examples via Ghost Networks"},"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":"2026-08-19T06:32:44.657259+00:00","source":"crossref"},{"observed_at":"2026-08-19T06:32:39.956319+00:00","source":"retraction_watch"}],"thesis":"As of 19 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 2 inbound Pith citation observations for arXiv:1812.03413."}