{"as_of":"2026-08-19T06:43:00Z","caps":{"database_statements":6,"inbound":100,"outbound":100},"context_digest":"sha256:1797030d96783b4780106977e24470c2496d2e16b637911480f6fc61e24395cb","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":2,"lane":"standing_notices","note":"One-hop event checks from named stored sources.","records_observed":2,"source":"scholarly_work_events, retraction_status_cache","source_observed_at":"2026-08-19T06:32:44.657259+00:00","state":"measured"},{"denominator":2,"lane":"inbound_itemization","note":"Pith citing papers itemized under the disclosed page cap.","records_observed":2,"source":"paper_references, paper_reference_links","source_observed_at":"2026-08-06T14:17:37.255620Z","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":"2026-05-25T19:11:09.711340Z","state":"measured"}],"external_citation_measurements":[],"inbound":[{"citation":{"cited_paper":{"arxiv_id":"1904.00687","last_updated":"2022-02-27T11:55:01Z","snapshot_observed_at":"2026-08-16T21:32:46.680916Z","submitted_at":"2019-04-01T10:21:24Z","title":"On the Power and Limitations of Random Features for Understanding Neural Networks","version":4},"cited_work":{"arxiv_id":"1904.00687","doi":null,"metadata_source":"arxiv_reference","pith_arxiv_id":"1904.00687","snapshot_observed_at":"2026-06-05T21:23:00.469572Z","title":null,"venue":null,"work_id":"fecea8b5-3438-4ed0-9fcb-119268c0f5f8","year":1904},"citing_paper":{"arxiv_id":"1906.08899","last_updated":"2019-06-21T00:29:54Z","snapshot_observed_at":"2026-08-13T07:24:15.845572Z","submitted_at":"2019-06-21T00:29:54Z","title":"Limitations of Lazy Training of Two-layers Neural Networks","version":1},"reference_index":35,"source":"arxiv_source","source_observed_at":"2026-05-25T19:11:02.369698Z"},"links":{"cited_paper":"/paper/1904.00687","citing_paper":"/paper/1906.08899"},"observation_digest":"sha256:f3b722808c9fbebd34bf9ffb00eb53be47f53762e18df75e6afbe60079b45c06","observation_id":"a6100a71-0acb-4cce-9b2a-8d1fe5fbf906","resolution":{"observed_at":"2026-05-25T19:11:09.714949Z","resolver_source":"arxiv_id","status":"verified_exact"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-19T06:32:44.657259+00:00","source":"crossref"},{"observed_at":"2026-08-19T06:32:39.956319+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"1904.00687","last_updated":"2022-02-27T11:55:01Z","snapshot_observed_at":"2026-08-16T21:32:46.680916Z","submitted_at":"2019-04-01T10:21:24Z","title":"On the Power and Limitations of Random Features for Understanding Neural Networks","version":4},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"1904.00687","snapshot_observed_at":"2026-08-06T14:17:37.255620Z","title":"On the power and limitations of random features for understanding neural networks","venue":null,"work_id":null,"year":1904},"citing_paper":{"arxiv_id":"2507.19680","last_updated":"2025-07-25T21:19:37Z","snapshot_observed_at":"2026-08-16T06:57:12.804004Z","submitted_at":"2025-07-25T21:19:37Z","title":"Feature learning is decoupled from generalization in high capacity neural networks","version":1},"reference_index":71,"source":"arxiv_source","source_observed_at":"2026-08-06T14:17:37.255620Z"},"links":{"cited_paper":"/paper/1904.00687","citing_paper":"/paper/2507.19680"},"observation_digest":"sha256:da7c33a4eabae0236fdb358e551ade789ddc311d03d6b22a027759e757f17906","observation_id":"cee354a0-a4a9-4536-9824-796fe7941253","resolution":{"observed_at":"2026-08-06T14:17:37.255620Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}}],"links":{"evidence":"/evidence","html":"/paper/1904.00687/citation-record","integrity":"/paper/1904.00687/integrity","json":"/paper/1904.00687/citation-record.json","paper":"/paper/1904.00687"},"outbound":[],"paper":{"arxiv_id":"1904.00687","last_updated":"2022-02-27T11:55:01Z","latest_version":4,"primary_category":"cs.LG","snapshot_observed_at":"2026-08-16T21:32:46.680916Z","submitted_at":"2019-04-01T10:21:24Z","title":"On the Power and Limitations of Random Features for Understanding Neural 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":"2026-08-19T06:32:44.657259+00:00","source":"crossref"},{"observed_at":"2026-08-19T06:32:39.956319+00:00","source":"retraction_watch"}],"thesis":"As of 19 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 2 inbound Pith citation observations for arXiv:1904.00687."}