{"as_of":"2026-08-14T12:14:00Z","caps":{"database_statements":6,"inbound":100,"outbound":100},"context_digest":"sha256:c21f6ff7ea4e52fefe023fdabcb45376e81950bdd98bc2fcecb5840b65d0d549","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":"2026-08-08T12:54:36.457407Z","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":"2026-08-08T12:54:36.542630Z","state":"measured"}],"external_citation_measurements":[],"inbound":[{"citation":{"cited_paper":{"arxiv_id":"2311.12253","last_updated":"2023-11-21T00:21:15Z","snapshot_observed_at":"2026-08-13T05:20:48.880141Z","submitted_at":"2023-11-21T00:21:15Z","title":"The limitation of neural nets for approximation and optimization","version":1},"cited_work":{"arxiv_id":"2311.12253","doi":null,"metadata_source":"pith","pith_arxiv_id":"2311.12253","snapshot_observed_at":"2026-08-08T12:54:36.542630Z","title":"The limitation of neural nets for approximation and optimization","venue":"cs.LG","work_id":"eba65472-e5eb-4e26-852a-a83bca477fde","year":2023},"citing_paper":{"arxiv_id":"2502.07435","last_updated":"2025-02-11T10:24:35Z","snapshot_observed_at":"2026-08-13T18:20:46.645809Z","submitted_at":"2025-02-11T10:24:35Z","title":"Enhancing finite-difference based derivative-free optimization methods with machine learning","version":1},"reference_index":9,"source":"pdf_text","source_observed_at":"2026-08-08T12:54:36.457407Z"},"links":{"cited_paper":"/paper/2311.12253","citing_paper":"/paper/2502.07435"},"observation_digest":"sha256:348f6478fcecb32d0cd4c10222f219dd8a9b55336c25dbc33c848d0549b7a9b4","observation_id":"3dbd8a0b-1a33-4118-93d2-926c838da55e","resolution":{"observed_at":"2026-08-08T12:54:36.546021Z","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/2311.12253/citation-record","integrity":"/paper/2311.12253/integrity","json":"/paper/2311.12253/citation-record.json","paper":"/paper/2311.12253"},"outbound":[],"paper":{"arxiv_id":"2311.12253","last_updated":"2023-11-21T00:21:15Z","latest_version":1,"primary_category":"cs.LG","snapshot_observed_at":"2026-08-13T05:20:48.880141Z","submitted_at":"2023-11-21T00:21:15Z","title":"The limitation of neural nets for approximation and optimization"},"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:2311.12253."}