{"as_of":"2026-08-04T09:06:00Z","caps":{"database_statements":6,"inbound":100,"outbound":100},"context_digest":"sha256:26d864619b5fdedcdc6ec37bf2d317735f7b81dc0955bf36c3a0b2580b9094ba","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":"2026-06-29T17:27:29.241219Z","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":"2026-06-29T17:33:45.392813Z","state":"measured"}],"external_citation_measurements":[],"inbound":[{"citation":{"cited_paper":{"arxiv_id":"2411.09776","last_updated":"2025-08-14T17:44:57Z","snapshot_observed_at":"2026-07-06T19:50:37.783055Z","submitted_at":"2024-11-14T19:41:51Z","title":"Combining Machine Learning Defenses without Conflicts","version":2},"cited_work":{"arxiv_id":"2411.09776","doi":null,"metadata_source":"arxiv_reference","pith_arxiv_id":"2411.09776","snapshot_observed_at":"2026-06-29T17:33:45.392813Z","title":null,"venue":null,"work_id":"6c7949a9-bf26-4720-b078-a0f6068a2bef","year":2024},"citing_paper":{"arxiv_id":"2605.27148","last_updated":"2026-06-01T21:00:09Z","snapshot_observed_at":"2026-07-06T23:36:53.330986Z","submitted_at":"2026-05-26T15:10:35Z","title":"Landseer: Exploring the Machine Learning Defense Landscape","version":2},"reference_index":31,"source":"pdf_text","source_observed_at":"2026-06-29T17:27:29.241219Z"},"links":{"cited_paper":"/paper/2411.09776","citing_paper":"/paper/2605.27148"},"observation_digest":"sha256:ec911a311a678417462f30f31351e0ebb58feaf22bc44b7226e189fe76d9c9df","observation_id":"e8802b72-f763-4eea-9f4e-5002eed0ca23","resolution":{"observed_at":"2026-06-29T17:33:45.394463Z","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/2411.09776/citation-record","integrity":"/paper/2411.09776/integrity","json":"/paper/2411.09776/citation-record.json","paper":"/paper/2411.09776"},"outbound":[],"paper":{"arxiv_id":"2411.09776","last_updated":"2025-08-14T17:44:57Z","latest_version":2,"primary_category":"cs.CR","snapshot_observed_at":"2026-07-06T19:50:37.783055Z","submitted_at":"2024-11-14T19:41:51Z","title":"Combining Machine Learning Defenses without Conflicts"},"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:2411.09776."}