{"as_of":"2026-08-14T07:15:00Z","caps":{"database_statements":6,"inbound":100,"outbound":100},"context_digest":"sha256:f26b47af7908d56df89f7dc5fc59c6cc4589b7e39f623c4e8c42839a8ef2edbb","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":"2026-08-14T06:32:32.682623+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":"2026-08-11T11:25:42.084309Z","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":"2026-08-11T11:25:42.294159Z","state":"measured"}],"external_citation_measurements":[],"inbound":[{"citation":{"cited_paper":{"arxiv_id":"2103.01495","last_updated":"2021-10-28T06:02:32Z","snapshot_observed_at":"2026-08-13T18:55:33.703769Z","submitted_at":"2021-03-02T06:30:51Z","title":"Task-Adaptive Neural Network Search with Meta-Contrastive Learning","version":2},"cited_work":{"arxiv_id":"2103.01495","doi":null,"metadata_source":"pith","pith_arxiv_id":"2103.01495","snapshot_observed_at":"2026-08-11T11:25:42.294159Z","title":"Task-Adaptive Neural Network Search with Meta-Contrastive Learning","venue":"cs.LG","work_id":"adee5d5d-1a99-4b57-8cac-1c8b5d78542f","year":2021},"citing_paper":{"arxiv_id":"2412.16251","last_updated":"2024-12-20T02:56:46Z","snapshot_observed_at":"2026-08-11T11:19:51.665509Z","submitted_at":"2024-12-20T02:56:46Z","title":"Know2Vec: A Black-Box Proxy for Neural Network Retrieval","version":1},"reference_index":21,"source":"arxiv_source","source_observed_at":"2026-08-11T11:25:42.084309Z"},"links":{"cited_paper":"/paper/2103.01495","citing_paper":"/paper/2412.16251"},"observation_digest":"sha256:dfd49ea00133359b5a383a9b65c201359d09e5e85f3d2fd893cf1f956043e18d","observation_id":"1587d0d6-4ac7-4b3f-8349-de4aae8edb42","resolution":{"observed_at":"2026-08-11T11:25:42.301146Z","resolver_source":"local_arxiv","status":"verified_exact"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-14T06:32:32.682623+00:00","source":"crossref"},{"observed_at":"2026-08-14T06:32:18.44784+00:00","source":"retraction_watch"}],"state":"measured"}}],"links":{"evidence":"/evidence","html":"/paper/2103.01495/citation-record","integrity":"/paper/2103.01495/integrity","json":"/paper/2103.01495/citation-record.json","paper":"/paper/2103.01495"},"outbound":[],"paper":{"arxiv_id":"2103.01495","last_updated":"2021-10-28T06:02:32Z","latest_version":2,"primary_category":"cs.LG","snapshot_observed_at":"2026-08-13T18:55:33.703769Z","submitted_at":"2021-03-02T06:30:51Z","title":"Task-Adaptive Neural Network Search with Meta-Contrastive Learning"},"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":"2026-08-14T06:32:32.682623+00:00","source":"crossref"},{"observed_at":"2026-08-14T06:32:18.44784+00:00","source":"retraction_watch"}],"thesis":"As of 14 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 1 inbound Pith citation observation for arXiv:2103.01495."}