{"as_of":"2026-08-14T08:32:00Z","caps":{"database_statements":6,"inbound":100,"outbound":100},"context_digest":"sha256:a71aa4aae0882f1bfe890312432eac33488ad5731c4ba87cfb329feca3295238","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":"2026-08-12T12:40:42.620973Z","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":"2026-08-12T12:40:42.766373Z","state":"measured"}],"external_citation_measurements":[],"inbound":[{"citation":{"cited_paper":{"arxiv_id":"2307.13869","last_updated":"2024-12-10T14:00:35Z","snapshot_observed_at":"2026-08-13T16:35:05.194763Z","submitted_at":"2023-07-26T00:01:21Z","title":"Number Theoretic Accelerated Learning of Physics-Informed Neural Networks","version":2},"cited_work":{"arxiv_id":"2307.13869","doi":null,"metadata_source":"pith","pith_arxiv_id":"2307.13869","snapshot_observed_at":"2026-08-12T12:40:42.766373Z","title":"Number Theoretic Accelerated Learning of Physics-Informed Neural Networks","venue":"cs.LG","work_id":"b5121be8-d54e-4317-b3ab-ceb74ee4ee80","year":2023},"citing_paper":{"arxiv_id":"2411.17039","last_updated":"2025-07-02T15:16:41Z","snapshot_observed_at":"2026-08-12T12:33:24.208570Z","submitted_at":"2024-11-26T02:05:37Z","title":"A novel number-theoretic sampling method for neural network solutions of partial differential equations","version":7},"reference_index":31,"source":"pdf_text","source_observed_at":"2026-08-12T12:40:42.620973Z"},"links":{"cited_paper":"/paper/2307.13869","citing_paper":"/paper/2411.17039"},"observation_digest":"sha256:7c88ea157c4da5ff84026df6f8ca31915df148101e22be5290c1575aad59ec0f","observation_id":"7e374668-cdc9-4d7c-a243-6d9a8e786763","resolution":{"observed_at":"2026-08-12T12:40:42.775269Z","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/2307.13869/citation-record","integrity":"/paper/2307.13869/integrity","json":"/paper/2307.13869/citation-record.json","paper":"/paper/2307.13869"},"outbound":[],"paper":{"arxiv_id":"2307.13869","last_updated":"2024-12-10T14:00:35Z","latest_version":2,"primary_category":"cs.LG","snapshot_observed_at":"2026-08-13T16:35:05.194763Z","submitted_at":"2023-07-26T00:01:21Z","title":"Number Theoretic Accelerated Learning of Physics-Informed Neural Networks"},"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:2307.13869."}