{"as_of":"2026-08-08T15:18:00Z","caps":{"database_statements":6,"inbound":100,"outbound":100},"context_digest":"sha256:67124556782137b2c843e4a0c63e0b18b49d83ad0b93aba1356c3d8bbbfe852d","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":"2026-08-08T06:32:00.761636+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":"2026-08-07T13:15:36.525386Z","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":"2010.02174","last_updated":"2020-11-30T18:39:39Z","snapshot_observed_at":"2026-08-05T10:29:08.573439Z","submitted_at":"2020-10-05T17:22:22Z","title":"A rigorous and robust quantum speed-up in supervised machine learning","version":2},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2010.02174","snapshot_observed_at":"2026-08-07T13:15:36.525386Z","title":"A rigorous and robust quantum speed-up in supervised machine learning","venue":null,"work_id":null,"year":2021},"citing_paper":{"arxiv_id":"2505.22502","last_updated":"2025-07-03T11:27:35Z","snapshot_observed_at":"2026-08-07T13:03:16.820031Z","submitted_at":"2025-05-28T15:50:56Z","title":"Assessing Quantum Advantage for Gaussian Process Regression","version":2},"reference_index":38,"source":"pdf_text","source_observed_at":"2026-08-07T13:15:36.525386Z"},"links":{"cited_paper":"/paper/2010.02174","citing_paper":"/paper/2505.22502"},"observation_digest":"sha256:d28e35c73a53ae417b595f4536a20a81f893d341f44f59985af4c1168adc30ac","observation_id":"3fcddc55-da66-4c9c-a005-ad1ed1e35e23","resolution":{"observed_at":"2026-08-07T13:15:36.525386Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2010.02174","last_updated":"2020-11-30T18:39:39Z","snapshot_observed_at":"2026-08-05T10:29:08.573439Z","submitted_at":"2020-10-05T17:22:22Z","title":"A rigorous and robust quantum speed-up in supervised machine learning","version":2},"cited_work":{"arxiv_id":"2010.02174","doi":"10.48550/arxiv.2010.02174","metadata_source":"arxiv_reference","pith_arxiv_id":"2010.02174","snapshot_observed_at":"2026-08-05T02:28:24.338817Z","title":"doi:10.48550/arXiv.2010.02174 , url =","venue":"arXiv (Cornell University)","work_id":"7c44a5af-8ea2-4e02-94b9-ecf8d77ab313","year":2010},"citing_paper":{"arxiv_id":"2605.21276","last_updated":"2026-05-20T15:08:08Z","snapshot_observed_at":"2026-08-01T15:30:40.728585Z","submitted_at":"2026-05-20T15:08:08Z","title":"Benchmarking a machine-learning differential equations solver on a neutral-atom logical processor","version":1},"reference_index":48,"source":"pdf_text","source_observed_at":"2026-05-21T04:39:16.463390Z"},"links":{"cited_paper":"/paper/2010.02174","citing_paper":"/paper/2605.21276"},"observation_digest":"sha256:ca08cdd594db8299e53ba4ce7c6479278aa81225ccf7287f6f9f9247fb139da0","observation_id":"a0950ccf-9a09-46fb-865e-307697ada402","resolution":{"observed_at":"2026-05-21T04:39:35.037256Z","resolver_source":"arxiv_id","status":"verified_exact"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-08T06:32:00.761636+00:00","source":"crossref"},{"observed_at":"2026-08-08T06:31:55.24221+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"2010.02174","last_updated":"2020-11-30T18:39:39Z","snapshot_observed_at":"2026-08-05T10:29:08.573439Z","submitted_at":"2020-10-05T17:22:22Z","title":"A rigorous and robust quantum speed-up in supervised machine learning","version":2},"cited_work":{"arxiv_id":"2010.02174","doi":"10.48550/arxiv.2010.02174","metadata_source":"arxiv_reference","pith_arxiv_id":"2010.02174","snapshot_observed_at":"2026-08-05T02:28:24.338817Z","title":"doi:10.48550/arXiv.2010.02174 , url =","venue":"arXiv (Cornell University)","work_id":"7c44a5af-8ea2-4e02-94b9-ecf8d77ab313","year":2010},"citing_paper":{"arxiv_id":"2606.28169","last_updated":"2026-06-26T15:02:02Z","snapshot_observed_at":"2026-08-03T01:41:22.268005Z","submitted_at":"2026-06-26T15:02:02Z","title":"Time Evolution on Hybrid Tensor Networks -- A Novel and Parallelizable Algorithm","version":1},"reference_index":84,"source":"arxiv_source","source_observed_at":"2026-06-29T03:52:17.171544Z"},"links":{"cited_paper":"/paper/2010.02174","citing_paper":"/paper/2606.28169"},"observation_digest":"sha256:f7e7eeab4552475388005e62ea18e1f92f1a6df5b4e037b2b8f8d6a8cb07a60d","observation_id":"127c57ae-cfa2-4cdc-bca8-9db60fe85f44","resolution":{"observed_at":"2026-06-29T03:53:04.478723Z","resolver_source":"arxiv_id","status":"verified_exact"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-08T06:32:00.761636+00:00","source":"crossref"},{"observed_at":"2026-08-08T06:31:55.24221+00:00","source":"retraction_watch"}],"state":"measured"}}],"links":{"evidence":"/evidence","html":"/paper/2010.02174/citation-record","integrity":"/paper/2010.02174/integrity","json":"/paper/2010.02174/citation-record.json","paper":"/paper/2010.02174"},"outbound":[],"paper":{"arxiv_id":"2010.02174","last_updated":"2020-11-30T18:39:39Z","latest_version":2,"primary_category":"quant-ph","snapshot_observed_at":"2026-08-05T10:29:08.573439Z","submitted_at":"2020-10-05T17:22:22Z","title":"A rigorous and robust quantum speed-up in supervised machine 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":"2026-08-08T06:32:00.761636+00:00","source":"crossref"},{"observed_at":"2026-08-08T06:31:55.24221+00:00","source":"retraction_watch"}],"thesis":"As of 8 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 3 inbound Pith citation observations for arXiv:2010.02174."}