{"as_of":"2026-08-16T04:43:00Z","caps":{"database_statements":6,"inbound":100,"outbound":100},"context_digest":"sha256:ae8505f4293ccaa1acc1ce3f74bfad40846fee1e3e49d1ecd8fa3ab9a1669ffa","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":8,"lane":"standing_notices","note":"One-hop event checks from named stored sources.","records_observed":8,"source":"scholarly_work_events, retraction_status_cache","source_observed_at":"2026-08-15T06:32:42.880941+00:00","state":"measured"},{"denominator":8,"lane":"inbound_itemization","note":"Pith citing papers itemized under the disclosed page cap.","records_observed":8,"source":"paper_references, paper_reference_links","source_observed_at":"2026-08-15T19:41:05.269216Z","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":"2026-07-04T17:20:00.898403Z","state":"measured"}],"external_citation_measurements":[],"inbound":[{"citation":{"cited_paper":{"arxiv_id":"2106.02713","last_updated":"2022-03-15T01:53:28Z","snapshot_observed_at":"2026-08-13T19:09:41.078219Z","submitted_at":"2021-06-04T20:48:20Z","title":"Learning Curves for SGD on Structured Features","version":5},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2106.02713","snapshot_observed_at":"2026-08-07T22:45:01.729201Z","title":null,"venue":null,"work_id":null,"year":2021},"citing_paper":{"arxiv_id":"2502.09106","last_updated":"2025-02-13T09:29:04Z","snapshot_observed_at":"2026-08-15T00:33:27.243490Z","submitted_at":"2025-02-13T09:29:04Z","title":"Scaling Law for Stochastic Gradient Descent in Quadratically Parameterized Linear Regression","version":1},"reference_index":11,"source":"pdf_text","source_observed_at":"2026-08-07T22:45:01.729201Z"},"links":{"cited_paper":"/paper/2106.02713","citing_paper":"/paper/2502.09106"},"observation_digest":"sha256:aab7785558fa893dda5b8921ddc5069cfccf69d77e46d826df18c3f1371197f8","observation_id":"59f46074-dd84-4d79-b353-30f07fd49667","resolution":{"observed_at":"2026-08-07T22:45:01.729201Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2106.02713","last_updated":"2022-03-15T01:53:28Z","snapshot_observed_at":"2026-08-13T19:09:41.078219Z","submitted_at":"2021-06-04T20:48:20Z","title":"Learning Curves for SGD on Structured Features","version":5},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2106.02713","snapshot_observed_at":"2026-08-15T19:41:05.269216Z","title":"Learning curves for sgd on structured features","venue":null,"work_id":null,"year":2021},"citing_paper":{"arxiv_id":"2506.15535","last_updated":"2025-06-18T15:10:38Z","snapshot_observed_at":"2026-08-15T19:30:46.441354Z","submitted_at":"2025-06-18T15:10:38Z","title":"A Simplified Analysis of SGD for Linear Regression with Weight Averaging","version":1},"reference_index":2,"source":"arxiv_source","source_observed_at":"2026-08-15T19:41:05.269216Z"},"links":{"cited_paper":"/paper/2106.02713","citing_paper":"/paper/2506.15535"},"observation_digest":"sha256:53c608b894fa357144d3d82bf6818e51a565483b87f5b65543d31cbd600a0c3d","observation_id":"2498633a-4663-42ca-a32f-4e50f8f85f2b","resolution":{"observed_at":"2026-08-15T19:41:05.269216Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2106.02713","last_updated":"2022-03-15T01:53:28Z","snapshot_observed_at":"2026-08-13T19:09:41.078219Z","submitted_at":"2021-06-04T20:48:20Z","title":"Learning Curves for SGD on Structured Features","version":5},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2106.02713","snapshot_observed_at":"2026-08-04T09:38:49.434717Z","title":"Learning curves for sgd on structured features","venue":null,"work_id":null,"year":2021},"citing_paper":{"arxiv_id":"2510.14717","last_updated":"2026-07-27T17:12:10Z","snapshot_observed_at":"2026-08-15T03:52:36.821423Z","submitted_at":"2025-10-16T14:17:38Z","title":"Seesaw: Accelerating Training by Balancing Learning Rate and Batch Size Scheduling","version":2},"reference_index":27,"source":"arxiv_source","source_observed_at":"2026-08-04T09:38:49.434717Z"},"links":{"cited_paper":"/paper/2106.02713","citing_paper":"/paper/2510.14717"},"observation_digest":"sha256:dc09489625cef283df23f9909a67ff82640660a4a7fd585c10f37d4a945b1b44","observation_id":"1b7d1605-e725-40b2-b661-06cc2c980cc8","resolution":{"observed_at":"2026-08-04T09:38:49.434717Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2106.02713","last_updated":"2022-03-15T01:53:28Z","snapshot_observed_at":"2026-08-13T19:09:41.078219Z","submitted_at":"2021-06-04T20:48:20Z","title":"Learning Curves for SGD on Structured Features","version":5},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2106.02713","snapshot_observed_at":"2026-08-03T14:02:56.646373Z","title":"Learning curves for sgd on structured features","venue":null,"work_id":null,"year":null},"citing_paper":{"arxiv_id":"2512.22088","last_updated":"2026-06-10T15:31:41Z","snapshot_observed_at":"2026-08-15T18:34:42.958067Z","submitted_at":"2025-12-26T17:20:09Z","title":"Unifying Learning Dynamics and Generalization in Transformers Scaling Law","version":3},"reference_index":16,"source":"pdf_text","source_observed_at":"2026-08-03T14:02:56.646373Z"},"links":{"cited_paper":"/paper/2106.02713","citing_paper":"/paper/2512.22088"},"observation_digest":"sha256:80f3aa0b5facc0a246b67128daadc7fab6811f65be6dbf63cab6155188c430c8","observation_id":"3b9dbe4f-b7ce-4801-8a1d-f7da7a486998","resolution":{"observed_at":"2026-08-03T14:02:56.646373Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2106.02713","last_updated":"2022-03-15T01:53:28Z","snapshot_observed_at":"2026-08-13T19:09:41.078219Z","submitted_at":"2021-06-04T20:48:20Z","title":"Learning Curves for SGD on Structured Features","version":5},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2106.02713","snapshot_observed_at":"2026-08-03T05:01:10.761729Z","title":"and Pehlevan, C","venue":null,"work_id":null,"year":null},"citing_paper":{"arxiv_id":"2602.03685","last_updated":"2026-08-08T20:17:29Z","snapshot_observed_at":"2026-08-13T23:26:44.430278Z","submitted_at":"2026-02-03T16:06:18Z","title":"Universal One-third Time Scaling in Learning Peaked Distributions","version":2},"reference_index":5,"source":"pdf_text","source_observed_at":"2026-08-03T05:01:10.761729Z"},"links":{"cited_paper":"/paper/2106.02713","citing_paper":"/paper/2602.03685"},"observation_digest":"sha256:9ceeb96382be7d1df4d86670381bdf64695f27e7c8e2fd1f14ef70e962c45b9a","observation_id":"d21ae77e-42af-46f9-bea5-6a0da67e67fc","resolution":{"observed_at":"2026-08-03T05:01:10.761729Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2106.02713","last_updated":"2022-03-15T01:53:28Z","snapshot_observed_at":"2026-08-13T19:09:41.078219Z","submitted_at":"2021-06-04T20:48:20Z","title":"Learning Curves for SGD on Structured Features","version":5},"cited_work":{"arxiv_id":"2106.02713","doi":null,"metadata_source":"arxiv_reference","pith_arxiv_id":"2106.02713","snapshot_observed_at":"2026-07-04T17:20:00.898403Z","title":"Learning curves for sgd on structured features.arXiv preprint arXiv:2106.02713, 2021","venue":null,"work_id":"97226809-fade-4fe2-82f8-579a1ca5259f","year":2021},"citing_paper":{"arxiv_id":"2606.25008","last_updated":"2026-06-23T17:46:30Z","snapshot_observed_at":"2026-08-15T16:35:39.147269Z","submitted_at":"2026-06-23T17:46:30Z","title":"Neural Scaling Universality: If Exponents Are Fixed, Time to Understand Coefficients","version":1},"reference_index":33,"source":"pdf_text","source_observed_at":"2026-06-25T23:45:54.283436Z"},"links":{"cited_paper":"/paper/2106.02713","citing_paper":"/paper/2606.25008"},"observation_digest":"sha256:e18b9c243d16ad42755afdfc547973567c7dc5430990edab4b2fc7b74afe9883","observation_id":"8d100ea2-4755-4cbe-870f-fb928b46f84e","resolution":{"observed_at":"2026-07-04T17:20:00.900196Z","resolver_source":"arxiv_id","status":"verified_exact"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-15T06:32:42.880941+00:00","source":"crossref"},{"observed_at":"2026-08-15T06:32:39.529945+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"2106.02713","last_updated":"2022-03-15T01:53:28Z","snapshot_observed_at":"2026-08-13T19:09:41.078219Z","submitted_at":"2021-06-04T20:48:20Z","title":"Learning Curves for SGD on Structured Features","version":5},"cited_work":{"arxiv_id":"2106.02713","doi":null,"metadata_source":"arxiv_reference","pith_arxiv_id":"2106.02713","snapshot_observed_at":"2026-07-04T17:20:00.898403Z","title":"Learning curves for sgd on structured features.arXiv preprint arXiv:2106.02713, 2021","venue":null,"work_id":"97226809-fade-4fe2-82f8-579a1ca5259f","year":2021},"citing_paper":{"arxiv_id":"2607.00207","last_updated":"2026-06-30T21:38:10Z","snapshot_observed_at":"2026-08-07T07:17:58.817162Z","submitted_at":"2026-06-30T21:38:10Z","title":"Homogenization of $\\ell_2$-Adversarial Training in High-Dimensions: Exact Dynamics under Stochastic Gradient Descent","version":1},"reference_index":12,"source":"pdf_text","source_observed_at":"2026-07-02T17:31:02.850791Z"},"links":{"cited_paper":"/paper/2106.02713","citing_paper":"/paper/2607.00207"},"observation_digest":"sha256:d6a79f757e671bc014b857d4533bbea33d2f70add917202fa606c01090862cff","observation_id":"f41e988c-b174-4943-9c22-ed9ac2c4e491","resolution":{"observed_at":"2026-07-02T17:37:13.853798Z","resolver_source":"arxiv_id","status":"verified_exact"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-15T06:32:42.880941+00:00","source":"crossref"},{"observed_at":"2026-08-15T06:32:39.529945+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"2106.02713","last_updated":"2022-03-15T01:53:28Z","snapshot_observed_at":"2026-08-13T19:09:41.078219Z","submitted_at":"2021-06-04T20:48:20Z","title":"Learning Curves for SGD on Structured Features","version":5},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2106.02713","snapshot_observed_at":"2026-08-01T06:58:09.845006Z","title":"Learning curves for sgd on structured features.arXiv preprint arXiv:2106.02713,","venue":null,"work_id":null,"year":null},"citing_paper":{"arxiv_id":"2607.21716","last_updated":"2026-07-23T18:02:03Z","snapshot_observed_at":"2026-08-09T14:14:32.562223Z","submitted_at":"2026-07-23T18:02:03Z","title":"A Defense of the Quadratic Model","version":1},"reference_index":2021,"source":"pdf_text","source_observed_at":"2026-08-01T06:58:09.845006Z"},"links":{"cited_paper":"/paper/2106.02713","citing_paper":"/paper/2607.21716"},"observation_digest":"sha256:4da7363c4bbb617ca716511579c87cac2d4b87a299e4cc0a08c335f601bd8c1f","observation_id":"6656265a-06a3-4261-89db-376489d3b9f2","resolution":{"observed_at":"2026-08-01T06:58:09.845006Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}}],"links":{"evidence":"/evidence","html":"/paper/2106.02713/citation-record","integrity":"/paper/2106.02713/integrity","json":"/paper/2106.02713/citation-record.json","paper":"/paper/2106.02713"},"outbound":[],"paper":{"arxiv_id":"2106.02713","last_updated":"2022-03-15T01:53:28Z","latest_version":5,"primary_category":"stat.ML","snapshot_observed_at":"2026-08-13T19:09:41.078219Z","submitted_at":"2021-06-04T20:48:20Z","title":"Learning Curves for SGD on Structured Features"},"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":"2026-08-15T06:32:42.880941+00:00","source":"crossref"},{"observed_at":"2026-08-15T06:32:39.529945+00:00","source":"retraction_watch"}],"thesis":"As of 16 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 8 inbound Pith citation observations for arXiv:2106.02713."}