{"as_of":"2026-08-11T07:28:00Z","caps":{"database_statements":6,"inbound":100,"outbound":100},"context_digest":"sha256:4a3f5b025b1543925ad5580d98a2bc53fb2335dc4bf4771f1433892f70912b9a","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":5,"lane":"standing_notices","note":"One-hop event checks from named stored sources.","records_observed":5,"source":"scholarly_work_events, retraction_status_cache","source_observed_at":"2026-08-11T06:34:44.6726+00:00","state":"measured"},{"denominator":5,"lane":"inbound_itemization","note":"Pith citing papers itemized under the disclosed page cap.","records_observed":5,"source":"paper_references, paper_reference_links","source_observed_at":"2026-08-06T00:43:15.173383Z","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":"2026-05-23T04:17:30.984851Z","state":"measured"}],"external_citation_measurements":[],"inbound":[{"citation":{"cited_paper":{"arxiv_id":"2406.08466","last_updated":"2025-06-10T04:25:56Z","snapshot_observed_at":"2026-08-08T00:11:02.392215Z","submitted_at":"2024-06-12T17:53:29Z","title":"Scaling Laws in Linear Regression: Compute, Parameters, and Data","version":3},"cited_work":{"arxiv_id":"2406.08466","doi":null,"metadata_source":"arxiv_reference","pith_arxiv_id":"2406.08466","snapshot_observed_at":"2026-06-05T21:23:00.469572Z","title":"Scaling laws in linear regression: Compute, parameters, and data","venue":null,"work_id":"c7931e4f-b28f-4875-b834-a6823cbd1321","year":2024},"citing_paper":{"arxiv_id":"2502.05074","last_updated":"2025-11-10T21:45:46Z","snapshot_observed_at":"2026-07-06T02:11:23.670680Z","submitted_at":"2025-02-07T16:45:40Z","title":"Two-Point Deterministic Equivalence for Stochastic Gradient Dynamics in Linear Models","version":3},"reference_index":27,"source":"pdf_text","source_observed_at":"2026-05-23T04:16:04.110552Z"},"links":{"cited_paper":"/paper/2406.08466","citing_paper":"/paper/2502.05074"},"observation_digest":"sha256:59bd15130a777be132731271727b9b384b0b47bb6b7dc04cef971b07d8d2a198","observation_id":"7db509b1-d7ca-4cfb-b347-b9c6893975e4","resolution":{"observed_at":"2026-05-23T04:17:30.988370Z","resolver_source":"arxiv_id","status":"verified_exact"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-11T06:34:44.6726+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-11T06:34:44.6726+00:00","source":"crossref"},{"observed_at":"2026-08-11T06:34:36.301508+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"2406.08466","last_updated":"2025-06-10T04:25:56Z","snapshot_observed_at":"2026-08-08T00:11:02.392215Z","submitted_at":"2024-06-12T17:53:29Z","title":"Scaling Laws in Linear Regression: Compute, Parameters, and Data","version":3},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2406.08466","snapshot_observed_at":"2026-08-03T14:02:56.706117Z","title":"[L WK+24] Licong Lin, Jingfeng Wu, Sham M Kakade, Peter L Bartlett, and Jason D Lee","venue":null,"work_id":null,"year":null},"citing_paper":{"arxiv_id":"2512.22088","last_updated":"2026-06-10T15:31:41Z","snapshot_observed_at":"2026-08-09T06:43:58.919201Z","submitted_at":"2025-12-26T17:20:09Z","title":"Unifying Learning Dynamics and Generalization in Transformers Scaling Law","version":3},"reference_index":43,"source":"pdf_text","source_observed_at":"2026-08-03T14:02:56.706117Z"},"links":{"cited_paper":"/paper/2406.08466","citing_paper":"/paper/2512.22088"},"observation_digest":"sha256:c14862c4191d9bddb58ce1e8d973c0124c792d43c31b3ade131ff45afae710c4","observation_id":"7253aca4-cba3-480a-a09e-25da7bf8864a","resolution":{"observed_at":"2026-08-03T14:02:56.706117Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2406.08466","last_updated":"2025-06-10T04:25:56Z","snapshot_observed_at":"2026-08-08T00:11:02.392215Z","submitted_at":"2024-06-12T17:53:29Z","title":"Scaling Laws in Linear Regression: Compute, Parameters, and Data","version":3},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2406.08466","snapshot_observed_at":"2026-08-03T04:14:15.825611Z","title":null,"venue":null,"work_id":null,"year":2024},"citing_paper":{"arxiv_id":"2602.05725","last_updated":"2026-06-03T16:40:26Z","snapshot_observed_at":"2026-08-03T04:14:09.367178Z","submitted_at":"2026-02-05T14:49:40Z","title":"Muon in Associative Memory Learning: Training Dynamics and Scaling Laws","version":3},"reference_index":40,"source":"arxiv_source","source_observed_at":"2026-08-03T04:14:15.825611Z"},"links":{"cited_paper":"/paper/2406.08466","citing_paper":"/paper/2602.05725"},"observation_digest":"sha256:ab84bc9bf9cc789e15efef23bf4d48812dcbf98fa60c665511730c4e1346e025","observation_id":"bbecf1f3-904c-4497-90b8-7f7debb79587","resolution":{"observed_at":"2026-08-03T04:14:15.825611Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2406.08466","last_updated":"2025-06-10T04:25:56Z","snapshot_observed_at":"2026-08-08T00:11:02.392215Z","submitted_at":"2024-06-12T17:53:29Z","title":"Scaling Laws in Linear Regression: Compute, Parameters, and Data","version":3},"cited_work":{"arxiv_id":"2406.08466","doi":null,"metadata_source":"arxiv_reference","pith_arxiv_id":"2406.08466","snapshot_observed_at":"2026-06-05T21:23:00.469572Z","title":"Scaling laws in linear regression: Compute, parameters, and data","venue":null,"work_id":"c7931e4f-b28f-4875-b834-a6823cbd1321","year":2024},"citing_paper":{"arxiv_id":"2603.26554","last_updated":"2026-04-28T07:36:37Z","snapshot_observed_at":"2026-07-06T22:50:46.243903Z","submitted_at":"2026-03-27T16:13:18Z","title":"Sharp Capacity Scaling of Spectral Optimizers in Learning Associative Memory","version":2},"reference_index":32,"source":"pdf_text","source_observed_at":"2026-05-14T23:37:33.106390Z"},"links":{"cited_paper":"/paper/2406.08466","citing_paper":"/paper/2603.26554"},"observation_digest":"sha256:8cb25d9414be96f969325aa36cc64b4fb9d3d92cc3ed55c0ea34a4022cbb7db9","observation_id":"ee6d3d6b-cf1f-46ad-bbec-db4b20c783f9","resolution":{"observed_at":"2026-05-14T23:38:16.542266Z","resolver_source":"arxiv_id","status":"verified_exact"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-11T06:34:44.6726+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-11T06:34:44.6726+00:00","source":"crossref"},{"observed_at":"2026-08-11T06:34:36.301508+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"2406.08466","last_updated":"2025-06-10T04:25:56Z","snapshot_observed_at":"2026-08-08T00:11:02.392215Z","submitted_at":"2024-06-12T17:53:29Z","title":"Scaling Laws in Linear Regression: Compute, Parameters, and Data","version":3},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2406.08466","snapshot_observed_at":"2026-08-06T00:43:15.173383Z","title":"Kakade, Peter L","venue":null,"work_id":null,"year":2024},"citing_paper":{"arxiv_id":"2608.01032","last_updated":"2026-08-02T06:27:55Z","snapshot_observed_at":"2026-08-09T06:27:10.466682Z","submitted_at":"2026-08-02T06:27:55Z","title":"The Fourth Quadrant: A Stylized View of Benign Misfitting","version":1},"reference_index":121,"source":"pdf_text","source_observed_at":"2026-08-06T00:43:15.173383Z"},"links":{"cited_paper":"/paper/2406.08466","citing_paper":"/paper/2608.01032"},"observation_digest":"sha256:b9adfefcc3e589fb59c687f5bee77aa197a78bf55583588f65772cabe2e1ccf4","observation_id":"95b78925-6456-4d53-b9bf-c07134a3f37c","resolution":{"observed_at":"2026-08-06T00:43:15.173383Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}}],"links":{"evidence":"/evidence","html":"/paper/2406.08466/citation-record","integrity":"/paper/2406.08466/integrity","json":"/paper/2406.08466/citation-record.json","paper":"/paper/2406.08466"},"outbound":[],"paper":{"arxiv_id":"2406.08466","last_updated":"2025-06-10T04:25:56Z","latest_version":3,"primary_category":"cs.LG","snapshot_observed_at":"2026-08-08T00:11:02.392215Z","submitted_at":"2024-06-12T17:53:29Z","title":"Scaling Laws in Linear Regression: Compute, Parameters, and Data"},"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":"2026-08-11T06:34:44.6726+00:00","source":"crossref"},{"observed_at":"2026-08-11T06:34:36.301508+00:00","source":"retraction_watch"}],"thesis":"As of 11 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 5 inbound Pith citation observations for arXiv:2406.08466."}