{"as_of":"2026-08-08T04:38:00Z","caps":{"database_statements":6,"inbound":100,"outbound":100},"context_digest":"sha256:f815c888e08f28579811d47be9c3721dadf44dcaae95fe5fb5460ba9c86a2eba","coverage":[{"denominator":4,"lane":"reference_resolution","note":"Typed states for the displayed outbound observations.","records_observed":4,"source":"paper_references, paper_reference_links","source_observed_at":"2026-08-03T09:02:59.245225Z","state":"measured"},{"denominator":4,"lane":"standing_notices","note":"One-hop event checks from named stored sources.","records_observed":4,"source":"scholarly_work_events, retraction_status_cache","source_observed_at":"2026-08-07T06:34:17.273281+00:00","state":"measured"},{"denominator":0,"lane":"inbound_itemization","note":"Pith citing papers itemized under the disclosed page cap.","records_observed":0,"source":"paper_references, paper_reference_links","source_observed_at":null,"state":"measured"},{"denominator":1,"lane":"external_citation_measurements","note":"A source-named dated measurement, never combined with another source.","records_observed":0,"source":"cited_works","source_observed_at":null,"state":"measured"}],"external_citation_measurements":[],"inbound":[],"links":{"evidence":"/evidence","html":"/paper/2601.15212/citation-record","integrity":"/paper/2601.15212/integrity","json":"/paper/2601.15212/citation-record.json","paper":"/paper/2601.15212"},"outbound":[{"citation":{"cited_paper":{"arxiv_id":"2407.02772","last_updated":"2025-05-17T23:04:24Z","snapshot_observed_at":"2026-07-06T18:40:39.990816Z","submitted_at":"2024-07-03T03:01:43Z","title":"Gradient descent with generalized Newton's method","version":3},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2407.02772","snapshot_observed_at":"2026-08-03T09:02:59.069502Z","title":"and Xu, S","venue":null,"work_id":null,"year":null},"citing_paper":{"arxiv_id":"2601.15212","last_updated":"2026-07-01T19:37:58Z","snapshot_observed_at":"2026-08-03T09:02:57.644226Z","submitted_at":"2026-01-21T17:36:12Z","title":"ZENITH: Automated Gradient Norm Informed Stochastic Optimization","version":2},"reference_index":2014,"source":"pdf_text","source_observed_at":"2026-08-03T09:02:59.069502Z"},"links":{"cited_paper":"/paper/2407.02772","citing_paper":"/paper/2601.15212"},"observation_digest":"sha256:ac45b546df267a485a84f2c13c9cd3dba26cc01dfeddaa7d945838015873299a","observation_id":"c78d2dea-36ae-4a8d-b954-ca16698ca660","resolution":{"observed_at":"2026-08-03T09:02:59.069502Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2306.06101","last_updated":"2024-03-19T23:01:06Z","snapshot_observed_at":"2026-08-05T09:04:21.780090Z","submitted_at":"2023-06-09T17:59:35Z","title":"Prodigy: An Expeditiously Adaptive Parameter-Free Learner","version":4},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2306.06101","snapshot_observed_at":"2026-08-03T09:02:59.189149Z","title":"and Defazio, A","venue":null,"work_id":null,"year":null},"citing_paper":{"arxiv_id":"2601.15212","last_updated":"2026-07-01T19:37:58Z","snapshot_observed_at":"2026-08-03T09:02:57.644226Z","submitted_at":"2026-01-21T17:36:12Z","title":"ZENITH: Automated Gradient Norm Informed Stochastic Optimization","version":2},"reference_index":2016,"source":"pdf_text","source_observed_at":"2026-08-03T09:02:59.189149Z"},"links":{"cited_paper":"/paper/2306.06101","citing_paper":"/paper/2601.15212"},"observation_digest":"sha256:d41abc31ed7b711c5c56537472b4d61e8dd41b300d9cdb32bb2284c461bd5efd","observation_id":"0016de6f-7528-49a7-96d3-616fb580f6cf","resolution":{"observed_at":"2026-08-03T09:02:59.189149Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"1409.1556","last_updated":"2015-04-10T16:25:04Z","snapshot_observed_at":"2026-07-06T03:53:32.549552Z","submitted_at":"2014-09-04T19:48:04Z","title":"Very Deep Convolutional Networks for Large-Scale Image Recognition","version":6},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"1409.1556","snapshot_observed_at":"2026-08-03T09:02:59.245225Z","title":"and Zisserman, A","venue":null,"work_id":null,"year":null},"citing_paper":{"arxiv_id":"2601.15212","last_updated":"2026-07-01T19:37:58Z","snapshot_observed_at":"2026-08-03T09:02:57.644226Z","submitted_at":"2026-01-21T17:36:12Z","title":"ZENITH: Automated Gradient Norm Informed Stochastic Optimization","version":2},"reference_index":2018,"source":"pdf_text","source_observed_at":"2026-08-03T09:02:59.245225Z"},"links":{"cited_paper":"/paper/1409.1556","citing_paper":"/paper/2601.15212"},"observation_digest":"sha256:cade639e7980fdf1be11c97923052748db706f44d5fadf210a902bb2d2ad6e7e","observation_id":"4d919358-12f1-4e6b-909d-b99480ba1db4","resolution":{"observed_at":"2026-08-03T09:02:59.245225Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"1608.03983","last_updated":"2017-05-03T16:28:09Z","snapshot_observed_at":"2026-07-06T05:06:55.589962Z","submitted_at":"2016-08-13T13:46:05Z","title":"SGDR: Stochastic Gradient Descent with Warm Restarts","version":5},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"1608.03983","snapshot_observed_at":"2026-08-03T09:02:59.133045Z","title":"and Hutter, F","venue":null,"work_id":null,"year":null},"citing_paper":{"arxiv_id":"2601.15212","last_updated":"2026-07-01T19:37:58Z","snapshot_observed_at":"2026-08-03T09:02:57.644226Z","submitted_at":"2026-01-21T17:36:12Z","title":"ZENITH: Automated Gradient Norm Informed Stochastic Optimization","version":2},"reference_index":2021,"source":"pdf_text","source_observed_at":"2026-08-03T09:02:59.133045Z"},"links":{"cited_paper":"/paper/1608.03983","citing_paper":"/paper/2601.15212"},"observation_digest":"sha256:0535fd27406eb41ce6a415f3c6bc29d500aa2802cc0f8cd04efc05a5c8b73396","observation_id":"a2f07ea3-3c8a-49dd-bc34-e79f580cc2d6","resolution":{"observed_at":"2026-08-03T09:02:59.133045Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}}],"paper":{"arxiv_id":"2601.15212","last_updated":"2026-07-01T19:37:58Z","latest_version":2,"primary_category":"cs.LG","snapshot_observed_at":"2026-08-03T09:02:57.644226Z","submitted_at":"2026-01-21T17:36:12Z","title":"ZENITH: Automated Gradient Norm Informed Stochastic Optimization"},"reference_resolution":{"displayed":4,"state_counts":{"malformed_identifier":0,"metadata_mismatch":0,"parse_uncertain":0,"unresolved":4,"verified_exact":0,"verified_fuzzy":0},"total_outbound_references":4},"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":"2026-08-07T06:34:17.273281+00:00","source":"crossref"},{"observed_at":"2026-08-07T06:34:11.927384+00:00","source":"retraction_watch"}],"thesis":"As of 8 August 2026, this Paper Citation Record lists 4 of 4 outbound references and 0 inbound Pith citation observations for arXiv:2601.15212."}