{"as_of":"2026-08-07T15:27:00Z","caps":{"database_statements":6,"inbound":100,"outbound":100},"context_digest":"sha256:f20215afb8de42ab9489b553d710af13d669e611b83ee019b9b087281e40df3a","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":5,"lane":"standing_notices","note":"One-hop event checks from named stored sources.","records_observed":5,"source":"scholarly_work_events, retraction_status_cache","source_observed_at":"2026-08-07T06:34:17.273281+00:00","state":"measured"},{"denominator":5,"lane":"inbound_itemization","note":"Pith citing papers itemized under the disclosed page cap.","records_observed":5,"source":"paper_references, paper_reference_links","source_observed_at":"2026-08-07T14:14:46.138209Z","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":"2026-07-02T23:47:28.412322Z","state":"measured"}],"external_citation_measurements":[],"inbound":[{"citation":{"cited_paper":{"arxiv_id":"2211.11092","last_updated":"2023-01-30T11:30:19Z","snapshot_observed_at":"2026-07-06T14:20:54.903780Z","submitted_at":"2022-11-20T21:48:25Z","title":"Q-Ensemble for Offline RL: Don't Scale the Ensemble, Scale the Batch Size","version":2},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2211.11092","snapshot_observed_at":"2026-08-07T14:14:46.138209Z","title":"Q-ensemble for offline rl: Don’t scale the ensemble, scale the batch size.arXiv preprint arXiv:2211.11092,","venue":null,"work_id":null,"year":null},"citing_paper":{"arxiv_id":"2505.19923","last_updated":"2025-05-26T12:45:54Z","snapshot_observed_at":"2026-08-07T14:01:31.748245Z","submitted_at":"2025-05-26T12:45:54Z","title":"Learning to Trust Bellman Updates: Selective State-Adaptive Regularization for Offline RL","version":1},"reference_index":14,"source":"pdf_text","source_observed_at":"2026-08-07T14:14:46.138209Z"},"links":{"cited_paper":"/paper/2211.11092","citing_paper":"/paper/2505.19923"},"observation_digest":"sha256:ed541e48ff7919584b2926ea8fbfb2f4706ea54d19915b9682d841251fcdf72e","observation_id":"4abe55e6-075f-41d3-b5de-45378bc73e6d","resolution":{"observed_at":"2026-08-07T14:14:46.138209Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2211.11092","last_updated":"2023-01-30T11:30:19Z","snapshot_observed_at":"2026-07-06T14:20:54.903780Z","submitted_at":"2022-11-20T21:48:25Z","title":"Q-Ensemble for Offline RL: Don't Scale the Ensemble, Scale the Batch Size","version":2},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2211.11092","snapshot_observed_at":"2026-08-06T04:39:05.661675Z","title":"Q-ensemble for offline rl: Don’t scale the ensemble, scale the batch size","venue":null,"work_id":null,"year":null},"citing_paper":{"arxiv_id":"2508.03194","last_updated":"2025-08-05T08:03:12Z","snapshot_observed_at":"2026-08-06T11:32:36.516059Z","submitted_at":"2025-08-05T08:03:12Z","title":"Scaling DRL for Decision Making: A Survey on Data, Network, and Training Budget Strategies","version":1},"reference_index":35,"source":"pdf_text","source_observed_at":"2026-08-06T04:39:05.661675Z"},"links":{"cited_paper":"/paper/2211.11092","citing_paper":"/paper/2508.03194"},"observation_digest":"sha256:4f4abaa9090fd3e9c05f24bf537764f8b3d9fb0bc9399b2da8c449bd2a92ddd1","observation_id":"d69bd5f6-b29c-4465-8e1a-1022b874b711","resolution":{"observed_at":"2026-08-06T04:39:05.661675Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2211.11092","last_updated":"2023-01-30T11:30:19Z","snapshot_observed_at":"2026-07-06T14:20:54.903780Z","submitted_at":"2022-11-20T21:48:25Z","title":"Q-Ensemble for Offline RL: Don't Scale the Ensemble, Scale the Batch Size","version":2},"cited_work":{"arxiv_id":"2211.11092","doi":null,"metadata_source":"arxiv_reference","pith_arxiv_id":"2211.11092","snapshot_observed_at":"2026-07-02T23:47:28.412322Z","title":"arXiv preprint arXiv:2211.11092 , year=","venue":null,"work_id":"8b14e4e6-da53-4436-b212-e41e81a76065","year":2023},"citing_paper":{"arxiv_id":"2605.01968","last_updated":"2026-05-03T16:53:29Z","snapshot_observed_at":"2026-08-05T17:06:11.864759Z","submitted_at":"2026-05-03T16:53:29Z","title":"AdamO: A Collapse-Suppressed Optimizer for Offline RL","version":1},"reference_index":40,"source":"arxiv_source","source_observed_at":"2026-05-10T14:48:05.166453Z"},"links":{"cited_paper":"/paper/2211.11092","citing_paper":"/paper/2605.01968"},"observation_digest":"sha256:cfd18fe15affeb3797dbc80c08929aa461aaf49557bda18fff35b07e30bff39f","observation_id":"b97def42-d314-4429-8b64-52379f673bea","resolution":{"observed_at":"2026-05-11T11:31:03.454202Z","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":"2211.11092","last_updated":"2023-01-30T11:30:19Z","snapshot_observed_at":"2026-07-06T14:20:54.903780Z","submitted_at":"2022-11-20T21:48:25Z","title":"Q-Ensemble for Offline RL: Don't Scale the Ensemble, Scale the Batch Size","version":2},"cited_work":{"arxiv_id":"2211.11092","doi":null,"metadata_source":"arxiv_reference","pith_arxiv_id":"2211.11092","snapshot_observed_at":"2026-07-02T23:47:28.412322Z","title":"arXiv preprint arXiv:2211.11092 , year=","venue":null,"work_id":"8b14e4e6-da53-4436-b212-e41e81a76065","year":2023},"citing_paper":{"arxiv_id":"2606.08803","last_updated":"2026-06-07T19:46:48Z","snapshot_observed_at":"2026-08-07T09:32:30.121113Z","submitted_at":"2026-06-07T19:46:48Z","title":"Some Essential Constructive Foundations for Systems and Control","version":1},"reference_index":8,"source":"arxiv_source","source_observed_at":"2026-06-27T17:48:35.402903Z"},"links":{"cited_paper":"/paper/2211.11092","citing_paper":"/paper/2606.08803"},"observation_digest":"sha256:d4b883cb33e8547c0a0db745d1331a7f4dd03652f6fc54116591c6268ab47287","observation_id":"d82a7420-8dff-465c-a973-e7194f19b4e7","resolution":{"observed_at":"2026-07-02T23:47:28.413744Z","resolver_source":"arxiv_id","status":"metadata_mismatch"},"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":"2211.11092","last_updated":"2023-01-30T11:30:19Z","snapshot_observed_at":"2026-07-06T14:20:54.903780Z","submitted_at":"2022-11-20T21:48:25Z","title":"Q-Ensemble for Offline RL: Don't Scale the Ensemble, Scale the Batch Size","version":2},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2211.11092","snapshot_observed_at":"2026-08-01T13:15:13.289352Z","title":"Nikulin, V","venue":null,"work_id":null,"year":2022},"citing_paper":{"arxiv_id":"2607.19199","last_updated":"2026-07-21T15:34:06Z","snapshot_observed_at":"2026-08-07T10:56:19.255296Z","submitted_at":"2026-07-21T15:34:06Z","title":"Conservative Query and Adaptive Regularization for Offline RL Under Uncertainty Estimation","version":1},"reference_index":28,"source":"pdf_text","source_observed_at":"2026-08-01T13:15:13.289352Z"},"links":{"cited_paper":"/paper/2211.11092","citing_paper":"/paper/2607.19199"},"observation_digest":"sha256:743fef87223a215d61a365370975bd343a1540b0488a38efe75ffa3c468f02d2","observation_id":"612f72d6-63cb-4e19-b33e-2441c80f0a9a","resolution":{"observed_at":"2026-08-01T13:15:13.289352Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}}],"links":{"evidence":"/evidence","html":"/paper/2211.11092/citation-record","integrity":"/paper/2211.11092/integrity","json":"/paper/2211.11092/citation-record.json","paper":"/paper/2211.11092"},"outbound":[],"paper":{"arxiv_id":"2211.11092","last_updated":"2023-01-30T11:30:19Z","latest_version":2,"primary_category":"cs.LG","snapshot_observed_at":"2026-07-06T14:20:54.903780Z","submitted_at":"2022-11-20T21:48:25Z","title":"Q-Ensemble for Offline RL: Don't Scale the Ensemble, Scale the Batch Size"},"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 5 inbound Pith citation observations for arXiv:2211.11092."}