{"as_of":"2026-08-11T01:11:00Z","caps":{"database_statements":6,"inbound":100,"outbound":100},"context_digest":"sha256:440f264425016f8cd65fb3d871b6dedb47144b79aeff1a41ef51f24f52fa7010","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":"2026-08-10T06:31:04.303077+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":"2026-08-03T17:18:55.829407Z","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":"2026-05-12T00:56:14.254077Z","state":"measured"}],"external_citation_measurements":[],"inbound":[{"citation":{"cited_paper":{"arxiv_id":"2502.12584","last_updated":"2025-05-28T22:49:18Z","snapshot_observed_at":"2026-08-10T22:38:16.651747Z","submitted_at":"2025-02-18T06:41:53Z","title":"Enhancing Semi-supervised Learning with Zero-shot Pseudolabels","version":2},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2502.12584","snapshot_observed_at":"2026-08-03T17:18:55.829407Z","title":"Enhancing semi-supervised learning with zero-shot pseudolabels.arXiv preprint arXiv:2502.12584, 2025","venue":null,"work_id":null,"year":2025},"citing_paper":{"arxiv_id":"2512.10244","last_updated":"2026-06-25T05:14:55Z","snapshot_observed_at":"2026-08-03T17:18:52.692516Z","submitted_at":"2025-12-11T03:06:16Z","title":"Solving Semi-Supervised Few-Shot Learning from an Auto-Annotation Perspective","version":3},"reference_index":13,"source":"pdf_text","source_observed_at":"2026-08-03T17:18:55.829407Z"},"links":{"cited_paper":"/paper/2502.12584","citing_paper":"/paper/2512.10244"},"observation_digest":"sha256:afdeb49fb581487914930f43e57cc819ddca8afd594ad24382574721d7adc7e0","observation_id":"cf81058d-3bfc-4e38-a840-df30bbd1697c","resolution":{"observed_at":"2026-08-03T17:18:55.829407Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2502.12584","last_updated":"2025-05-28T22:49:18Z","snapshot_observed_at":"2026-08-10T22:38:16.651747Z","submitted_at":"2025-02-18T06:41:53Z","title":"Enhancing Semi-supervised Learning with Zero-shot Pseudolabels","version":2},"cited_work":{"arxiv_id":"2502.12584","doi":null,"metadata_source":"arxiv_reference","pith_arxiv_id":"2502.12584","snapshot_observed_at":"2026-06-05T21:23:00.469572Z","title":"arXiv preprint arXiv:2502.12584 , year=","venue":null,"work_id":"0b5bcc7e-b6bc-4005-80d0-112fcb9794e9","year":null},"citing_paper":{"arxiv_id":"2605.08448","last_updated":"2026-05-08T20:15:40Z","snapshot_observed_at":"2026-08-02T07:11:56.869921Z","submitted_at":"2026-05-08T20:15:40Z","title":"LLM-guided Semi-Supervised Approaches for Social Media Crisis Data Classification","version":1},"reference_index":40,"source":"arxiv_source","source_observed_at":"2026-05-12T00:54:53.402959Z"},"links":{"cited_paper":"/paper/2502.12584","citing_paper":"/paper/2605.08448"},"observation_digest":"sha256:76d0de44415cb14642fde0f75f0a4e799c79c12f6a1191d57809f0272091ddbd","observation_id":"1784434c-7325-43ea-8785-ef7e5bc8cb25","resolution":{"observed_at":"2026-05-12T00:56:14.255928Z","resolver_source":"arxiv_id","status":"verified_exact"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-10T06:31:04.303077+00:00","source":"crossref"},{"observed_at":"2026-08-10T06:30:57.382061+00:00","source":"retraction_watch"}],"state":"measured"}}],"links":{"evidence":"/evidence","html":"/paper/2502.12584/citation-record","integrity":"/paper/2502.12584/integrity","json":"/paper/2502.12584/citation-record.json","paper":"/paper/2502.12584"},"outbound":[],"paper":{"arxiv_id":"2502.12584","last_updated":"2025-05-28T22:49:18Z","latest_version":2,"primary_category":"cs.LG","snapshot_observed_at":"2026-08-10T22:38:16.651747Z","submitted_at":"2025-02-18T06:41:53Z","title":"Enhancing Semi-supervised Learning with Zero-shot Pseudolabels"},"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":"2026-08-10T06:31:04.303077+00:00","source":"crossref"},{"observed_at":"2026-08-10T06:30:57.382061+00:00","source":"retraction_watch"}],"thesis":"As of 11 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 2 inbound Pith citation observations for arXiv:2502.12584."}