{"as_of":"2026-08-07T14:03:00Z","caps":{"database_statements":6,"inbound":100,"outbound":100},"context_digest":"sha256:dfe2f6c1e9eba778bdf7da541edbd1519a84cd9a3de185e80c573f94f56df1c2","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":3,"lane":"standing_notices","note":"One-hop event checks from named stored sources.","records_observed":3,"source":"scholarly_work_events, retraction_status_cache","source_observed_at":"2026-08-07T06:34:17.273281+00:00","state":"measured"},{"denominator":3,"lane":"inbound_itemization","note":"Pith citing papers itemized under the disclosed page cap.","records_observed":3,"source":"paper_references, paper_reference_links","source_observed_at":"2026-08-02T20:37:01.591623Z","state":"measured"},{"denominator":1,"lane":"external_citation_measurements","note":"A source-named dated measurement, never combined with another source.","records_observed":1,"source":"arxiv_reference","source_observed_at":"2026-08-05T02:28:24.338817Z","state":"measured"}],"external_citation_measurements":[{"count":0,"observed_at":"2026-08-05T02:28:24.338817Z","source":"arxiv_reference"}],"inbound":[{"citation":{"cited_paper":{"arxiv_id":"2502.03210","last_updated":"2025-05-28T12:21:28Z","snapshot_observed_at":"2026-08-07T10:59:32.880212Z","submitted_at":"2025-02-05T14:26:50Z","title":"From Kernels to Features: A Multi-Scale Adaptive Theory of Feature Learning","version":2},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2502.03210","snapshot_observed_at":"2026-08-02T20:37:01.591623Z","title":"From kernels to features: A multi-scale adaptive theory of feature learning","venue":null,"work_id":null,"year":2025},"citing_paper":{"arxiv_id":"2602.23039","last_updated":"2026-06-01T09:29:09Z","snapshot_observed_at":"2026-08-04T13:27:32.737495Z","submitted_at":"2026-02-26T14:24:11Z","title":"Dynamics of neural scaling laws in random feature regression with powerlaw-distributed kernel eigenvalues","version":2},"reference_index":31,"source":"arxiv_source","source_observed_at":"2026-08-02T20:37:01.591623Z"},"links":{"cited_paper":"/paper/2502.03210","citing_paper":"/paper/2602.23039"},"observation_digest":"sha256:3a62b9479ef9d06a9a549cc3db0b5424f3b9e9471610e2fd9df5ffe17326ba41","observation_id":"c4c94aa7-1cb5-4295-8165-3e9555019c3b","resolution":{"observed_at":"2026-08-02T20:37:01.591623Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2502.03210","last_updated":"2025-05-28T12:21:28Z","snapshot_observed_at":"2026-08-07T10:59:32.880212Z","submitted_at":"2025-02-05T14:26:50Z","title":"From Kernels to Features: A Multi-Scale Adaptive Theory of Feature Learning","version":2},"cited_work":{"arxiv_id":"2502.03210","doi":"10.48550/arxiv.2502.03210","metadata_source":"arxiv_reference","pith_arxiv_id":"2502.03210","snapshot_observed_at":"2026-08-05T02:28:24.338817Z","title":null,"venue":"JuSER (Forschungszentrum Jülich)","work_id":"e2f80662-3959-4df9-8230-ab4b288b80e6","year":null},"citing_paper":{"arxiv_id":"2606.20299","last_updated":"2026-07-01T14:03:37Z","snapshot_observed_at":"2026-07-06T23:55:29.991442Z","submitted_at":"2026-06-18T14:35:53Z","title":"Statistical Properties of Training & Generalization","version":1},"reference_index":18,"source":"arxiv_source","source_observed_at":"2026-06-26T15:35:51.654392Z"},"links":{"cited_paper":"/paper/2502.03210","citing_paper":"/paper/2606.20299"},"observation_digest":"sha256:94f5bed22b82f413cbb3818c44b6e64b6ded58cebe896c3910a336a9875a3208","observation_id":"ab1c7560-6ecc-419e-b771-62dfd2a8b05e","resolution":{"observed_at":"2026-06-26T15:39:33.199820Z","resolver_source":"arxiv_id","status":"verified_exact"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.","reason":null,"source_receipts":[{"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"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"2502.03210","last_updated":"2025-05-28T12:21:28Z","snapshot_observed_at":"2026-08-07T10:59:32.880212Z","submitted_at":"2025-02-05T14:26:50Z","title":"From Kernels to Features: A Multi-Scale Adaptive Theory of Feature Learning","version":2},"cited_work":{"arxiv_id":"2502.03210","doi":"10.48550/arxiv.2502.03210","metadata_source":"arxiv_reference","pith_arxiv_id":"2502.03210","snapshot_observed_at":"2026-08-05T02:28:24.338817Z","title":null,"venue":"JuSER (Forschungszentrum Jülich)","work_id":"e2f80662-3959-4df9-8230-ab4b288b80e6","year":null},"citing_paper":{"arxiv_id":"2606.20299","last_updated":"2026-07-01T14:03:37Z","snapshot_observed_at":"2026-07-06T23:55:29.991442Z","submitted_at":"2026-06-18T14:35:53Z","title":"Statistical Properties of Training & Generalization","version":2},"reference_index":18,"source":"arxiv_source","source_observed_at":"2026-07-02T21:51:13.457071Z"},"links":{"cited_paper":"/paper/2502.03210","citing_paper":"/paper/2606.20299"},"observation_digest":"sha256:8ced4cfca9093c9d11aa7d289b75a3eead5dbe795ffc505a301a415d456b750a","observation_id":"b1129547-647b-4070-bd20-9eac7197c832","resolution":{"observed_at":"2026-07-02T21:57:25.338292Z","resolver_source":"arxiv_id","status":"verified_exact"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.","reason":null,"source_receipts":[{"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"}],"state":"measured"}}],"links":{"evidence":"/evidence","html":"/paper/2502.03210/citation-record","integrity":"/paper/2502.03210/integrity","json":"/paper/2502.03210/citation-record.json","paper":"/paper/2502.03210"},"outbound":[],"paper":{"arxiv_id":"2502.03210","last_updated":"2025-05-28T12:21:28Z","latest_version":2,"primary_category":"cond-mat.dis-nn","snapshot_observed_at":"2026-08-07T10:59:32.880212Z","submitted_at":"2025-02-05T14:26:50Z","title":"From Kernels to Features: A Multi-Scale Adaptive Theory of Feature 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":"2026-08-07T06:34:17.273281+00:00","source":"crossref"},{"observed_at":"2026-08-07T06:34:11.927384+00:00","source":"retraction_watch"}],"thesis":"As of 7 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 3 inbound Pith citation observations for arXiv:2502.03210."}