{"as_of":"2026-08-09T20:36:00Z","caps":{"database_statements":6,"inbound":100,"outbound":100},"context_digest":"sha256:004b314cf4706ef443e89c9fb30ee976e832a5bacc9b19b2951f7c49f2c787b7","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":"2026-08-08T22:30:49.068316Z","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":"2026-08-08T11:45:36.091036Z","state":"measured"}],"external_citation_measurements":[],"inbound":[{"citation":{"cited_paper":{"arxiv_id":"2405.14183","last_updated":"2024-10-30T22:58:51Z","snapshot_observed_at":"2026-08-03T20:15:43.364817Z","submitted_at":"2024-05-23T05:27:51Z","title":"Deterministic Policies for Constrained Reinforcement Learning in Polynomial Time","version":2},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2405.14183","snapshot_observed_at":"2026-08-08T22:30:49.068316Z","title":"Lin, J., Zhang, A., L ´ecuyer, M., Li, J., Panda, A., and Sen, S","venue":null,"work_id":null,"year":2022},"citing_paper":{"arxiv_id":"2502.04554","last_updated":"2026-05-29T12:53:02Z","snapshot_observed_at":"2026-08-08T22:18:13.061562Z","submitted_at":"2025-02-06T23:03:10Z","title":"Unifying and Optimizing Data Values for Selection via Sequential Decision-Making","version":2},"reference_index":2024,"source":"pdf_text","source_observed_at":"2026-08-08T22:30:49.068316Z"},"links":{"cited_paper":"/paper/2405.14183","citing_paper":"/paper/2502.04554"},"observation_digest":"sha256:740ac4fabdb1be42c0bcd0fd2c46b8ecee56060e5c7ae8e7f5a2ded6f09bc71a","observation_id":"951f6199-1e60-4cd0-9044-36f5e678e5d4","resolution":{"observed_at":"2026-08-08T22:30:49.068316Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2405.14183","last_updated":"2024-10-30T22:58:51Z","snapshot_observed_at":"2026-08-03T20:15:43.364817Z","submitted_at":"2024-05-23T05:27:51Z","title":"Deterministic Policies for Constrained Reinforcement Learning in Polynomial Time","version":2},"cited_work":{"arxiv_id":"2405.14183","doi":null,"metadata_source":"pith","pith_arxiv_id":"2405.14183","snapshot_observed_at":"2026-08-08T11:45:36.091036Z","title":"Deterministic Policies for Constrained Reinforcement Learning in Polynomial Time","venue":"cs.LG","work_id":"a4dec072-3f3a-496f-bfae-5ad524b11f1b","year":2024},"citing_paper":{"arxiv_id":"2502.07764","last_updated":"2025-02-11T18:47:53Z","snapshot_observed_at":"2026-08-09T19:47:21.080712Z","submitted_at":"2025-02-11T18:47:53Z","title":"Polynomial-Time Approximability of Constrained Reinforcement Learning","version":1},"reference_index":26,"source":"pdf_text","source_observed_at":"2026-08-08T11:45:35.671359Z"},"links":{"cited_paper":"/paper/2405.14183","citing_paper":"/paper/2502.07764"},"observation_digest":"sha256:c84ca2482e71375af4c2d8be9fe68fe9dbd77829c1524c1c41f92815d1a4b9f6","observation_id":"e08598d7-e897-4fdc-9236-6ab7b1143200","resolution":{"observed_at":"2026-08-08T11:45:36.094985Z","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/2405.14183/citation-record","integrity":"/paper/2405.14183/integrity","json":"/paper/2405.14183/citation-record.json","paper":"/paper/2405.14183"},"outbound":[],"paper":{"arxiv_id":"2405.14183","last_updated":"2024-10-30T22:58:51Z","latest_version":2,"primary_category":"cs.LG","snapshot_observed_at":"2026-08-03T20:15:43.364817Z","submitted_at":"2024-05-23T05:27:51Z","title":"Deterministic Policies for Constrained Reinforcement Learning in Polynomial Time"},"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 9 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 2 inbound Pith citation observations for arXiv:2405.14183."}