{"as_of":"2026-08-10T07:29:00Z","caps":{"database_statements":6,"inbound":100,"outbound":100},"context_digest":"sha256:cdf3897ab595d35e8b72379f15f66cbf4172bbd5bc15bd0ffbf6c710eae29bd1","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":1,"lane":"standing_notices","note":"One-hop event checks from named stored sources.","records_observed":1,"source":"scholarly_work_events, retraction_status_cache","source_observed_at":"2026-08-10T06:31:04.303077+00:00","state":"measured"},{"denominator":1,"lane":"inbound_itemization","note":"Pith citing papers itemized under the disclosed page cap.","records_observed":1,"source":"paper_references, paper_reference_links","source_observed_at":"2026-08-03T07:16:22.109036Z","state":"measured"},{"denominator":1,"lane":"external_citation_measurements","note":"A source-named dated measurement, never combined with another source.","records_observed":0,"source":"cited_works","source_observed_at":null,"state":"measured"}],"external_citation_measurements":[],"inbound":[{"citation":{"cited_paper":{"arxiv_id":"2110.06742","last_updated":"2024-05-21T11:30:00Z","snapshot_observed_at":"2026-07-06T11:57:28.465843Z","submitted_at":"2021-10-13T14:21:21Z","title":"A Review of the Deep Sea Treasure problem as a Multi-Objective Reinforcement Learning Benchmark","version":4},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2110.06742","snapshot_observed_at":"2026-08-03T07:16:22.109036Z","title":"A review of the deep sea treasure problem as a multi-objective reinforcement learning benchmark.CoRR, abs/2110.06742,","venue":null,"work_id":null,"year":2021},"citing_paper":{"arxiv_id":"2601.20753","last_updated":"2026-07-07T10:01:44Z","snapshot_observed_at":"2026-08-09T00:13:02.404401Z","submitted_at":"2026-01-28T16:36:37Z","title":"GraphAllocBench: A Flexible Benchmark for Preference-Conditioned Multi-Objective Policy Learning","version":4},"reference_index":2020,"source":"pdf_text","source_observed_at":"2026-08-03T07:16:22.109036Z"},"links":{"cited_paper":"/paper/2110.06742","citing_paper":"/paper/2601.20753"},"observation_digest":"sha256:a076d0a3066cf918818ea1f7e1739ca63ab13a911f7bf0868b6f65ef298238d8","observation_id":"720b7142-af1f-4a50-adcd-bb78ae5c0d07","resolution":{"observed_at":"2026-08-03T07:16:22.109036Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}}],"links":{"evidence":"/evidence","html":"/paper/2110.06742/citation-record","integrity":"/paper/2110.06742/integrity","json":"/paper/2110.06742/citation-record.json","paper":"/paper/2110.06742"},"outbound":[],"paper":{"arxiv_id":"2110.06742","last_updated":"2024-05-21T11:30:00Z","latest_version":4,"primary_category":"cs.LG","snapshot_observed_at":"2026-07-06T11:57:28.465843Z","submitted_at":"2021-10-13T14:21:21Z","title":"A Review of the Deep Sea Treasure problem as a Multi-Objective Reinforcement Learning Benchmark"},"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":"2026-08-10T06:31:04.303077+00:00","source":"crossref"},{"observed_at":"2026-08-10T06:30:57.382061+00:00","source":"retraction_watch"}],"thesis":"As of 10 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 1 inbound Pith citation observation for arXiv:2110.06742."}