{"as_of":"2026-08-21T16:48:00Z","caps":{"database_statements":6,"inbound":100,"outbound":100},"context_digest":"sha256:9d7c4dcc47ab2ae7ed5c5a2222472124793620829230dccc10e8572aa3ba7c00","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":"2026-08-21T06:32:19.484+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":"2026-08-08T19:59:24.232239Z","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":"2026-05-11T10:16:08.057068Z","state":"measured"}],"external_citation_measurements":[],"inbound":[{"citation":{"cited_paper":{"arxiv_id":"2405.16644","last_updated":"2025-02-02T12:01:52Z","snapshot_observed_at":"2026-08-17T23:55:02.296997Z","submitted_at":"2024-05-26T17:43:30Z","title":"Gaussian Approximation and Multiplier Bootstrap for Polyak-Ruppert Averaged Linear Stochastic Approximation with Applications to TD Learning","version":2},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2405.16644","snapshot_observed_at":"2026-08-08T19:59:24.232239Z","title":"Gaussian approximation and multiplier bootstrap for polyak-ruppert averaged linear stochastic approximation with applications to td learning","venue":null,"work_id":null,"year":2024},"citing_paper":{"arxiv_id":"2502.05305","last_updated":"2025-08-12T02:41:58Z","snapshot_observed_at":"2026-08-18T12:38:26.569392Z","submitted_at":"2025-02-07T20:16:51Z","title":"Online Covariance Estimation in Nonsmooth Stochastic Approximation","version":2},"reference_index":7,"source":"pdf_text","source_observed_at":"2026-08-08T19:59:24.232239Z"},"links":{"cited_paper":"/paper/2405.16644","citing_paper":"/paper/2502.05305"},"observation_digest":"sha256:90e6c28368a1fb368c1ef817ac198143c872b49d89cedd6a2a5d128f613d781d","observation_id":"08e608fa-d7a4-42e2-9505-54fcc5a531bc","resolution":{"observed_at":"2026-08-08T19:59:24.232239Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2405.16644","last_updated":"2025-02-02T12:01:52Z","snapshot_observed_at":"2026-08-17T23:55:02.296997Z","submitted_at":"2024-05-26T17:43:30Z","title":"Gaussian Approximation and Multiplier Bootstrap for Polyak-Ruppert Averaged Linear Stochastic Approximation with Applications to TD Learning","version":2},"cited_work":{"arxiv_id":"2405.16644","doi":null,"metadata_source":"arxiv_reference","pith_arxiv_id":"2405.16644","snapshot_observed_at":"2026-06-05T21:23:00.469572Z","title":"and NAUMOV, A","venue":null,"work_id":"79599d20-3632-43df-ade6-dfdc4d4cb80a","year":2024},"citing_paper":{"arxiv_id":"2604.10814","last_updated":"2026-04-12T20:49:33Z","snapshot_observed_at":"2026-08-21T13:36:17.917043Z","submitted_at":"2026-04-12T20:49:33Z","title":"Online Covariance Estimation in Averaged SGD: Improved Batch-Mean Rates and Minimax Optimality via Trajectory Regression","version":1},"reference_index":13,"source":"pdf_text","source_observed_at":"2026-05-10T15:33:52.700578Z"},"links":{"cited_paper":"/paper/2405.16644","citing_paper":"/paper/2604.10814"},"observation_digest":"sha256:4751069f2a6fb60bd13de2ceb7568bdf23756f46794ac922038d26a42681e774","observation_id":"a60c6772-1158-4b4f-8464-d0ee5fc23ab9","resolution":{"observed_at":"2026-05-11T10:16:08.062974Z","resolver_source":"arxiv_id","status":"verified_exact"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-21T06:32:19.484+00:00","source":"crossref"},{"observed_at":"2026-08-21T06:32:16.066871+00:00","source":"retraction_watch"}],"state":"measured"}}],"links":{"evidence":"/evidence","html":"/paper/2405.16644/citation-record","integrity":"/paper/2405.16644/integrity","json":"/paper/2405.16644/citation-record.json","paper":"/paper/2405.16644"},"outbound":[],"paper":{"arxiv_id":"2405.16644","last_updated":"2025-02-02T12:01:52Z","latest_version":2,"primary_category":"stat.ML","snapshot_observed_at":"2026-08-17T23:55:02.296997Z","submitted_at":"2024-05-26T17:43:30Z","title":"Gaussian Approximation and Multiplier Bootstrap for Polyak-Ruppert Averaged Linear Stochastic Approximation with Applications to TD 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":"2026-08-21T06:32:19.484+00:00","source":"crossref"},{"observed_at":"2026-08-21T06:32:16.066871+00:00","source":"retraction_watch"}],"thesis":"As of 21 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 2 inbound Pith citation observations for arXiv:2405.16644."}