{"as_of":"2026-08-06T21:31:00Z","caps":{"database_statements":6,"inbound":100,"outbound":100},"context_digest":"sha256:214bcdffbef9c134f9cc9a086b43a18b3a96c88fe06c1e3cfec38edf5bbbce0a","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":"2026-08-06T06:34:29.942622+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":"2026-05-12T05:27:11.761971Z","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":"2026-05-12T05:31:24.112962Z","state":"measured"}],"external_citation_measurements":[],"inbound":[{"citation":{"cited_paper":{"arxiv_id":"2010.01369","last_updated":"2020-10-03T14:24:59Z","snapshot_observed_at":"2026-08-05T16:02:01.028702Z","submitted_at":"2020-10-03T14:24:59Z","title":"Computational Separation Between Convolutional and Fully-Connected Networks","version":1},"cited_work":{"arxiv_id":"2010.01369","doi":null,"metadata_source":"arxiv_reference","pith_arxiv_id":"2010.01369","snapshot_observed_at":"2026-06-05T21:23:00.469572Z","title":"arXiv preprint arXiv:2010.01369 , year=","venue":null,"work_id":"8479805c-abae-47fb-b313-97bb5571e751","year":2010},"citing_paper":{"arxiv_id":"2605.10237","last_updated":"2026-05-11T09:11:20Z","snapshot_observed_at":"2026-07-06T23:22:13.774652Z","submitted_at":"2026-05-11T09:11:20Z","title":"The Benefits of Temporal Correlations: SGD Learns k-Juntas from Random Walks Efficiently","version":1},"reference_index":7,"source":"arxiv_source","source_observed_at":"2026-05-12T05:27:11.761971Z"},"links":{"cited_paper":"/paper/2010.01369","citing_paper":"/paper/2605.10237"},"observation_digest":"sha256:01fe7e3c3b84a03afe822dc6a0d86c77360ad82eda8d9009d314665eb87f51dc","observation_id":"92a997ac-a3af-448b-ad71-616a2738d6a9","resolution":{"observed_at":"2026-05-12T05:31:24.116537Z","resolver_source":"arxiv_id","status":"verified_exact"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-06T06:34:29.942622+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-06T06:34:29.942622+00:00","source":"crossref"},{"observed_at":"2026-08-06T06:34:23.284952+00:00","source":"retraction_watch"}],"state":"measured"}}],"links":{"evidence":"/evidence","html":"/paper/2010.01369/citation-record","integrity":"/paper/2010.01369/integrity","json":"/paper/2010.01369/citation-record.json","paper":"/paper/2010.01369"},"outbound":[],"paper":{"arxiv_id":"2010.01369","last_updated":"2020-10-03T14:24:59Z","latest_version":1,"primary_category":"cs.LG","snapshot_observed_at":"2026-08-05T16:02:01.028702Z","submitted_at":"2020-10-03T14:24:59Z","title":"Computational Separation Between Convolutional and Fully-Connected 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":"2026-08-06T06:34:29.942622+00:00","source":"crossref"},{"observed_at":"2026-08-06T06:34:23.284952+00:00","source":"retraction_watch"}],"thesis":"As of 6 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 1 inbound Pith citation observation for arXiv:2010.01369."}