{"as_of":"2026-08-10T00:50:00Z","caps":{"database_statements":6,"inbound":100,"outbound":100},"context_digest":"sha256:9a80138278b51135abb58dc5a803f66d7da42ccf13041f5b8835191913bb688c","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":"2026-08-09T06:31:02.800959+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":"2026-08-08T21:05:12.276726Z","state":"measured"},{"denominator":1,"lane":"external_citation_measurements","note":"A source-named dated measurement, never combined with another source.","records_observed":0,"source":"pith","source_observed_at":"2026-08-06T18:41:03.231657Z","state":"measured"}],"external_citation_measurements":[],"inbound":[{"citation":{"cited_paper":{"arxiv_id":"2212.07932","last_updated":"2022-12-15T16:08:31Z","snapshot_observed_at":"2026-08-07T23:03:00.611126Z","submitted_at":"2022-12-15T16:08:31Z","title":"Quantum Reinforcement Learning for Solving a Stochastic Frozen Lake Environment and the Impact of Quantum Architecture Choices","version":1},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2212.07932","snapshot_observed_at":"2026-08-08T21:05:12.276726Z","title":"B., and Lorenz, J","venue":null,"work_id":null,"year":2022},"citing_paper":{"arxiv_id":"2502.04909","last_updated":"2025-03-20T08:08:19Z","snapshot_observed_at":"2026-08-08T20:58:19.971100Z","submitted_at":"2025-02-07T13:28:20Z","title":"Benchmarking Quantum Reinforcement Learning","version":2},"reference_index":14,"source":"arxiv_source","source_observed_at":"2026-08-08T21:05:12.276726Z"},"links":{"cited_paper":"/paper/2212.07932","citing_paper":"/paper/2502.04909"},"observation_digest":"sha256:3009cc1cbb31a50abc0c254e9367990ed25faf930803832f8cad25f0135f1c68","observation_id":"f512103a-72ee-4892-a9c1-918f79bda482","resolution":{"observed_at":"2026-08-08T21:05:12.276726Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2212.07932","last_updated":"2022-12-15T16:08:31Z","snapshot_observed_at":"2026-08-07T23:03:00.611126Z","submitted_at":"2022-12-15T16:08:31Z","title":"Quantum Reinforcement Learning for Solving a Stochastic Frozen Lake Environment and the Impact of Quantum Architecture Choices","version":1},"cited_work":{"arxiv_id":"2212.07932","doi":null,"metadata_source":"pith","pith_arxiv_id":"2212.07932","snapshot_observed_at":"2026-08-06T18:41:03.231657Z","title":"Quantum Reinforcement Learning for Solving a Stochastic Frozen Lake Environment and the Impact of Quantum Architecture Choices","venue":"quant-ph","work_id":"76f1a691-1a34-44e6-b45d-039d36db1c5c","year":2022},"citing_paper":{"arxiv_id":"2507.07593","last_updated":"2025-07-10T09:53:39Z","snapshot_observed_at":"2026-08-08T12:52:06.151806Z","submitted_at":"2025-07-10T09:53:39Z","title":"CleanQRL: Lightweight Single-file Implementations of Quantum Reinforcement Learning Algorithms","version":1},"reference_index":6,"source":"pdf_text","source_observed_at":"2026-08-06T18:41:02.182611Z"},"links":{"cited_paper":"/paper/2212.07932","citing_paper":"/paper/2507.07593"},"observation_digest":"sha256:3bc65fafd86a47403f13f5bd1c91e397a34a5de2eb94b4c582ba8f29ccf94381","observation_id":"8bbf1df3-4d75-44f9-a484-2f2650150d24","resolution":{"observed_at":"2026-08-06T18:41:03.303645Z","resolver_source":"local_arxiv","status":"verified_exact"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-09T06:31:02.800959+00:00","source":"crossref"},{"observed_at":"2026-08-09T06:30:57.326959+00:00","source":"retraction_watch"}],"state":"measured"}}],"links":{"evidence":"/evidence","html":"/paper/2212.07932/citation-record","integrity":"/paper/2212.07932/integrity","json":"/paper/2212.07932/citation-record.json","paper":"/paper/2212.07932"},"outbound":[],"paper":{"arxiv_id":"2212.07932","last_updated":"2022-12-15T16:08:31Z","latest_version":1,"primary_category":"quant-ph","snapshot_observed_at":"2026-08-07T23:03:00.611126Z","submitted_at":"2022-12-15T16:08:31Z","title":"Quantum Reinforcement Learning for Solving a Stochastic Frozen Lake Environment and the Impact of Quantum Architecture Choices"},"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":"2026-08-09T06:31:02.800959+00:00","source":"crossref"},{"observed_at":"2026-08-09T06:30:57.326959+00:00","source":"retraction_watch"}],"thesis":"As of 10 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 2 inbound Pith citation observations for arXiv:2212.07932."}