{"as_of":"2026-08-08T23:06:00Z","caps":{"database_statements":6,"inbound":100,"outbound":100},"context_digest":"sha256:a4bf2a5acb3b0bd5a8b637afb2cadd9bbe0ad2bf88dc8402507851a5f396088c","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":"2026-08-08T06:32:00.761636+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":"2026-08-05T11:52:15.261022Z","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":"2026-08-05T11:52:16.647743Z","state":"measured"}],"external_citation_measurements":[],"inbound":[{"citation":{"cited_paper":{"arxiv_id":"2110.10802","last_updated":"2022-08-29T23:16:19Z","snapshot_observed_at":"2026-07-06T12:00:03.070535Z","submitted_at":"2021-10-20T22:07:40Z","title":"A Data-Centric Optimization Framework for Machine Learning","version":3},"cited_work":{"arxiv_id":"2110.10802","doi":null,"metadata_source":"pith","pith_arxiv_id":"2110.10802","snapshot_observed_at":"2026-08-05T11:52:16.647743Z","title":"A Data-Centric Optimization Framework for Machine Learning","venue":"cs.LG","work_id":"c2e1b99d-ec3c-4eb8-8965-eaf899492edf","year":2021},"citing_paper":{"arxiv_id":"2509.02197","last_updated":"2025-09-02T11:09:45Z","snapshot_observed_at":"2026-08-07T08:01:45.628491Z","submitted_at":"2025-09-02T11:09:45Z","title":"DaCe AD: Unifying High-Performance Automatic Differentiation for Machine Learning and Scientific Computing","version":1},"reference_index":26,"source":"pdf_text","source_observed_at":"2026-08-05T11:52:15.261022Z"},"links":{"cited_paper":"/paper/2110.10802","citing_paper":"/paper/2509.02197"},"observation_digest":"sha256:6bbb056271fe82db65b04ad2d3bac7b5f3b6479288ff01270f3381f61fd8896d","observation_id":"de90c4e7-d19b-418e-ad3f-ba9d1114c4c1","resolution":{"observed_at":"2026-08-05T11:52:16.657864Z","resolver_source":"local_arxiv","status":"verified_exact"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-08T06:32:00.761636+00:00","source":"crossref"},{"observed_at":"2026-08-08T06:31:55.24221+00:00","source":"retraction_watch"}],"state":"measured"}}],"links":{"evidence":"/evidence","html":"/paper/2110.10802/citation-record","integrity":"/paper/2110.10802/integrity","json":"/paper/2110.10802/citation-record.json","paper":"/paper/2110.10802"},"outbound":[],"paper":{"arxiv_id":"2110.10802","last_updated":"2022-08-29T23:16:19Z","latest_version":3,"primary_category":"cs.LG","snapshot_observed_at":"2026-07-06T12:00:03.070535Z","submitted_at":"2021-10-20T22:07:40Z","title":"A Data-Centric Optimization Framework for Machine 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":"2026-08-08T06:32:00.761636+00:00","source":"crossref"},{"observed_at":"2026-08-08T06:31:55.24221+00:00","source":"retraction_watch"}],"thesis":"As of 8 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 1 inbound Pith citation observation for arXiv:2110.10802."}