{"as_of":"2026-08-07T11:39:00Z","caps":{"database_statements":6,"inbound":100,"outbound":100},"context_digest":"sha256:8e71d68bc98a56b07c34d1027c7385f23e5721f6a7614eb001ff06140a610f7b","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":3,"lane":"standing_notices","note":"One-hop event checks from named stored sources.","records_observed":3,"source":"scholarly_work_events, retraction_status_cache","source_observed_at":"2026-08-07T06:34:17.273281+00:00","state":"measured"},{"denominator":3,"lane":"inbound_itemization","note":"Pith citing papers itemized under the disclosed page cap.","records_observed":3,"source":"paper_references, paper_reference_links","source_observed_at":"2026-07-31T23:40:00.743668Z","state":"measured"},{"denominator":1,"lane":"external_citation_measurements","note":"A source-named dated measurement, never combined with another source.","records_observed":1,"source":"arxiv_reference","source_observed_at":"2026-08-05T02:28:24.338817Z","state":"measured"}],"external_citation_measurements":[{"count":0,"observed_at":"2026-08-05T02:28:24.338817Z","source":"arxiv_reference"}],"inbound":[{"citation":{"cited_paper":{"arxiv_id":"2206.12227","last_updated":"2022-10-11T09:41:37Z","snapshot_observed_at":"2026-07-06T13:24:20.984230Z","submitted_at":"2022-06-24T11:53:12Z","title":"Adversarial Robustness of Deep Neural Networks: A Survey from a Formal Verification Perspective","version":2},"cited_work":{"arxiv_id":"2206.12227","doi":"10.48550/arxiv.2206.12227","metadata_source":"arxiv_reference","pith_arxiv_id":"2206.12227","snapshot_observed_at":"2026-08-05T02:28:24.338817Z","title":"CoRRabs/2206.12227(2022)","venue":"arXiv (Cornell University)","work_id":"c915a5f3-7593-4d67-9501-10eb043b3f47","year":2022},"citing_paper":{"arxiv_id":"2604.21556","last_updated":"2026-04-23T11:31:06Z","snapshot_observed_at":"2026-07-06T23:08:05.568089Z","submitted_at":"2026-04-23T11:31:06Z","title":"Probabilistic Verification of Neural Networks via Efficient Probabilistic Hull Generation","version":1},"reference_index":10,"source":"pdf_text","source_observed_at":"2026-05-09T21:10:18.557475Z"},"links":{"cited_paper":"/paper/2206.12227","citing_paper":"/paper/2604.21556"},"observation_digest":"sha256:4f30856fb6c0b4857c546864eabf9713d7d287fed9e802b3d66db71175769e96","observation_id":"aa94c9bb-4101-4b3d-ae16-8b4153784f5e","resolution":{"observed_at":"2026-05-11T14:41:38.105619Z","resolver_source":"arxiv_id","status":"verified_exact"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-07T06:34:17.273281+00:00","source":"crossref"},{"observed_at":"2026-08-07T06:34:11.927384+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"2206.12227","last_updated":"2022-10-11T09:41:37Z","snapshot_observed_at":"2026-07-06T13:24:20.984230Z","submitted_at":"2022-06-24T11:53:12Z","title":"Adversarial Robustness of Deep Neural Networks: A Survey from a Formal Verification Perspective","version":2},"cited_work":{"arxiv_id":"2206.12227","doi":"10.48550/arxiv.2206.12227","metadata_source":"arxiv_reference","pith_arxiv_id":"2206.12227","snapshot_observed_at":"2026-08-05T02:28:24.338817Z","title":"CoRRabs/2206.12227(2022)","venue":"arXiv (Cornell University)","work_id":"c915a5f3-7593-4d67-9501-10eb043b3f47","year":2022},"citing_paper":{"arxiv_id":"2605.12792","last_updated":"2026-05-12T22:10:01Z","snapshot_observed_at":"2026-07-06T23:24:27.821980Z","submitted_at":"2026-05-12T22:10:01Z","title":"SoK: A Comprehensive Analysis of the Current Status of Neural Tangent Generalization Attacks with Research Directions","version":1},"reference_index":64,"source":"pdf_text","source_observed_at":"2026-05-14T20:41:10.931383Z"},"links":{"cited_paper":"/paper/2206.12227","citing_paper":"/paper/2605.12792"},"observation_digest":"sha256:da1493ddf9a8ca1c7b56fa6ac1557d78a5ea3947341e1f0eff289f8dcadfd6be","observation_id":"e91bb73d-ee4e-49e7-831a-d1bea1cf1371","resolution":{"observed_at":"2026-05-14T20:42:56.146257Z","resolver_source":"arxiv_id","status":"verified_exact"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-07T06:34:17.273281+00:00","source":"crossref"},{"observed_at":"2026-08-07T06:34:11.927384+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"2206.12227","last_updated":"2022-10-11T09:41:37Z","snapshot_observed_at":"2026-07-06T13:24:20.984230Z","submitted_at":"2022-06-24T11:53:12Z","title":"Adversarial Robustness of Deep Neural Networks: A Survey from a Formal Verification Perspective","version":2},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2206.12227","snapshot_observed_at":"2026-07-31T23:40:00.743668Z","title":null,"venue":null,"work_id":null,"year":2022},"citing_paper":{"arxiv_id":"2607.23365","last_updated":"2026-07-25T21:15:41Z","snapshot_observed_at":"2026-08-02T08:44:18.131884Z","submitted_at":"2026-07-25T21:15:41Z","title":"On AI Safety and Security Technical Debt in Engineering AI-Enabled Systems","version":1},"reference_index":137,"source":"pdf_text","source_observed_at":"2026-07-31T23:40:00.743668Z"},"links":{"cited_paper":"/paper/2206.12227","citing_paper":"/paper/2607.23365"},"observation_digest":"sha256:f78d75a0eb49888a8098a7a370ae45dab92fbbb3fc324eafb6dfb74ce53405fa","observation_id":"a3164fe8-059b-4497-9792-85b4a68e6365","resolution":{"observed_at":"2026-07-31T23:40:00.743668Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}}],"links":{"evidence":"/evidence","html":"/paper/2206.12227/citation-record","integrity":"/paper/2206.12227/integrity","json":"/paper/2206.12227/citation-record.json","paper":"/paper/2206.12227"},"outbound":[],"paper":{"arxiv_id":"2206.12227","last_updated":"2022-10-11T09:41:37Z","latest_version":2,"primary_category":"cs.CR","snapshot_observed_at":"2026-07-06T13:24:20.984230Z","submitted_at":"2022-06-24T11:53:12Z","title":"Adversarial Robustness of Deep Neural Networks: A Survey from a Formal Verification Perspective"},"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":"2026-08-07T06:34:17.273281+00:00","source":"crossref"},{"observed_at":"2026-08-07T06:34:11.927384+00:00","source":"retraction_watch"}],"thesis":"As of 7 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 3 inbound Pith citation observations for arXiv:2206.12227."}