{"as_of":"2026-08-14T11:40:00Z","caps":{"database_statements":6,"inbound":100,"outbound":100},"context_digest":"sha256:52c222fe36c5c83a30317d9d68855c058093e5f141335ac431c8a877723f0738","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":"2026-08-14T06:32:32.682623+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":"2026-06-28T16:43:54.405426Z","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":"2026-07-04T03:09:30.498865Z","state":"measured"}],"external_citation_measurements":[],"inbound":[{"citation":{"cited_paper":{"arxiv_id":"2311.08376","last_updated":"2025-01-15T15:41:09Z","snapshot_observed_at":"2026-08-14T07:24:42.809336Z","submitted_at":"2023-11-14T18:41:28Z","title":"Ensemble sampling for linear bandits: small ensembles suffice","version":4},"cited_work":{"arxiv_id":"2311.08376","doi":null,"metadata_source":"arxiv_reference","pith_arxiv_id":"2311.08376","snapshot_observed_at":"2026-07-04T03:09:30.498865Z","title":"arXiv preprint arXiv:2311.08376 , year=","venue":null,"work_id":"d62d89b1-b454-45aa-970b-12d21e7d361c","year":null},"citing_paper":{"arxiv_id":"2606.00984","last_updated":"2026-05-31T03:46:16Z","snapshot_observed_at":"2026-08-10T01:50:23.201446Z","submitted_at":"2026-05-31T03:46:16Z","title":"Practical and Optimal Algorithm for Linear Contextual Bandits with Rare Parameter Updates","version":1},"reference_index":4,"source":"arxiv_source","source_observed_at":"2026-06-28T16:43:54.405426Z"},"links":{"cited_paper":"/paper/2311.08376","citing_paper":"/paper/2606.00984"},"observation_digest":"sha256:593fb0f659aa2098564beed02bbe3dcbde4e0b2a36a34fff5a1d4a984580e1d7","observation_id":"99373099-d1a9-4812-a0fb-0edd07e0eb66","resolution":{"observed_at":"2026-07-01T21:36:15.092006Z","resolver_source":"arxiv_id","status":"verified_exact"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-14T06:32:32.682623+00:00","source":"crossref"},{"observed_at":"2026-08-14T06:32:18.44784+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"2311.08376","last_updated":"2025-01-15T15:41:09Z","snapshot_observed_at":"2026-08-14T07:24:42.809336Z","submitted_at":"2023-11-14T18:41:28Z","title":"Ensemble sampling for linear bandits: small ensembles suffice","version":4},"cited_work":{"arxiv_id":"2311.08376","doi":null,"metadata_source":"arxiv_reference","pith_arxiv_id":"2311.08376","snapshot_observed_at":"2026-07-04T03:09:30.498865Z","title":"arXiv preprint arXiv:2311.08376 , year=","venue":null,"work_id":"d62d89b1-b454-45aa-970b-12d21e7d361c","year":null},"citing_paper":{"arxiv_id":"2606.20107","last_updated":"2026-06-18T11:30:59Z","snapshot_observed_at":"2026-08-07T07:50:16.581167Z","submitted_at":"2026-06-18T11:30:59Z","title":"Quantile of Means: A Bonus-Free Ensemble Method for Minimax Optimal Reinforcement Learning","version":1},"reference_index":47,"source":"arxiv_source","source_observed_at":"2026-06-26T18:19:02.314185Z"},"links":{"cited_paper":"/paper/2311.08376","citing_paper":"/paper/2606.20107"},"observation_digest":"sha256:0f15f39a4ffae40a3dea18c55e6663f0ec9059d53e42a77cd36a5971a5d9140c","observation_id":"5374735b-6114-4681-9df8-05501013a69e","resolution":{"observed_at":"2026-07-04T03:09:30.500673Z","resolver_source":"arxiv_id","status":"verified_exact"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-14T06:32:32.682623+00:00","source":"crossref"},{"observed_at":"2026-08-14T06:32:18.44784+00:00","source":"retraction_watch"}],"state":"measured"}}],"links":{"evidence":"/evidence","html":"/paper/2311.08376/citation-record","integrity":"/paper/2311.08376/integrity","json":"/paper/2311.08376/citation-record.json","paper":"/paper/2311.08376"},"outbound":[],"paper":{"arxiv_id":"2311.08376","last_updated":"2025-01-15T15:41:09Z","latest_version":4,"primary_category":"stat.ML","snapshot_observed_at":"2026-08-14T07:24:42.809336Z","submitted_at":"2023-11-14T18:41:28Z","title":"Ensemble sampling for linear bandits: small ensembles suffice"},"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":"2026-08-14T06:32:32.682623+00:00","source":"crossref"},{"observed_at":"2026-08-14T06:32:18.44784+00:00","source":"retraction_watch"}],"thesis":"As of 14 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 2 inbound Pith citation observations for arXiv:2311.08376."}