{"as_of":"2026-08-13T18:47:00Z","caps":{"database_statements":6,"inbound":100,"outbound":100},"context_digest":"sha256:93336a98e7d61cbafa175e856740c96e9a3e61c461a60e9019b8b96eefdcbf03","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":"2026-08-13T06:32:02.005865+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":"2026-08-12T15:37:16.890216Z","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":"2026-08-12T15:37:16.936777Z","state":"measured"}],"external_citation_measurements":[],"inbound":[{"citation":{"cited_paper":{"arxiv_id":"1704.01415","last_updated":"2017-04-04T12:50:25Z","snapshot_observed_at":"2026-07-06T05:36:39.612294Z","submitted_at":"2017-04-04T12:50:25Z","title":"Multi-Label Learning with Global and Local Label Correlation","version":1},"cited_work":{"arxiv_id":"1704.01415","doi":null,"metadata_source":"pith","pith_arxiv_id":"1704.01415","snapshot_observed_at":"2026-08-12T15:37:16.936777Z","title":"Multi-Label Learning with Global and Local Label Correlation","venue":"cs.LG","work_id":"e505dda4-98fe-41bc-a786-535a2af2893d","year":2017},"citing_paper":{"arxiv_id":"2411.14094","last_updated":"2024-11-21T12:59:39Z","snapshot_observed_at":"2026-08-12T15:30:41.270002Z","submitted_at":"2024-11-21T12:59:39Z","title":"GNN-MultiFix: Addressing the pitfalls for GNNs for multi-label node classification","version":1},"reference_index":38,"source":"pdf_text","source_observed_at":"2026-08-12T15:37:16.890216Z"},"links":{"cited_paper":"/paper/1704.01415","citing_paper":"/paper/2411.14094"},"observation_digest":"sha256:129a747b3b325f1b8ce48c5b86a5c09d14b07b6072624f863f1a224af98f567a","observation_id":"1ec1b940-1ac5-4d03-b629-86a93ccb863e","resolution":{"observed_at":"2026-08-12T15:37:16.940166Z","resolver_source":"local_arxiv","status":"verified_exact"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-13T06:32:02.005865+00:00","source":"crossref"},{"observed_at":"2026-08-13T06:31:53.387327+00:00","source":"retraction_watch"}],"state":"measured"}}],"links":{"evidence":"/evidence","html":"/paper/1704.01415/citation-record","integrity":"/paper/1704.01415/integrity","json":"/paper/1704.01415/citation-record.json","paper":"/paper/1704.01415"},"outbound":[],"paper":{"arxiv_id":"1704.01415","last_updated":"2017-04-04T12:50:25Z","latest_version":1,"primary_category":"cs.LG","snapshot_observed_at":"2026-07-06T05:36:39.612294Z","submitted_at":"2017-04-04T12:50:25Z","title":"Multi-Label Learning with Global and Local Label Correlation"},"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":"2026-08-13T06:32:02.005865+00:00","source":"crossref"},{"observed_at":"2026-08-13T06:31:53.387327+00:00","source":"retraction_watch"}],"thesis":"As of 13 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 1 inbound Pith citation observation for arXiv:1704.01415."}