{"as_of":"2026-08-13T19:26:00Z","caps":{"database_statements":6,"inbound":100,"outbound":100},"context_digest":"sha256:47b74e5746da0129c2ab92349c49f73609405819861968033fc39a6cbb0817b2","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":4,"lane":"standing_notices","note":"One-hop event checks from named stored sources.","records_observed":4,"source":"scholarly_work_events, retraction_status_cache","source_observed_at":"2026-08-13T06:32:02.005865+00:00","state":"measured"},{"denominator":4,"lane":"inbound_itemization","note":"Pith citing papers itemized under the disclosed page cap.","records_observed":4,"source":"paper_references, paper_reference_links","source_observed_at":"2026-08-06T14:07:57.471246Z","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":"2026-07-03T20:58:58.451676Z","state":"measured"}],"external_citation_measurements":[],"inbound":[{"citation":{"cited_paper":{"arxiv_id":"2301.07784","last_updated":"2023-03-23T16:29:23Z","snapshot_observed_at":"2026-08-13T13:02:15.453372Z","submitted_at":"2023-01-18T20:54:40Z","title":"Sample-Efficient Multi-Objective Learning via Generalized Policy Improvement Prioritization","version":2},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2301.07784","snapshot_observed_at":"2026-08-06T14:07:57.471246Z","title":", author Bazzan, A.L.C","venue":null,"work_id":null,"year":2023},"citing_paper":{"arxiv_id":"2507.19788","last_updated":"2025-07-26T04:30:11Z","snapshot_observed_at":"2026-08-12T18:18:05.932003Z","submitted_at":"2025-07-26T04:30:11Z","title":"Reinforcement Learning for Multi-Objective Multi-Echelon Supply Chain Optimisation","version":1},"reference_index":4,"source":"arxiv_source","source_observed_at":"2026-08-06T14:07:57.471246Z"},"links":{"cited_paper":"/paper/2301.07784","citing_paper":"/paper/2507.19788"},"observation_digest":"sha256:cec87f29a42f1399d3788ff135c48f396acfb4cce4d284bf15cb3674a300bec3","observation_id":"587b2e84-25d8-4787-bf2e-2c391fe2eb36","resolution":{"observed_at":"2026-08-06T14:07:57.471246Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2301.07784","last_updated":"2023-03-23T16:29:23Z","snapshot_observed_at":"2026-08-13T13:02:15.453372Z","submitted_at":"2023-01-18T20:54:40Z","title":"Sample-Efficient Multi-Objective Learning via Generalized Policy Improvement Prioritization","version":2},"cited_work":{"arxiv_id":"2301.07784","doi":null,"metadata_source":"arxiv_reference","pith_arxiv_id":"2301.07784","snapshot_observed_at":"2026-07-03T20:58:58.451676Z","title":"Sample- efficient multi-objective learning via generalized policy improvement prioritization.arXiv preprint arXiv:2301.07784,","venue":null,"work_id":"59c5ad80-df90-4e15-9247-6c2b28cf1271","year":2023},"citing_paper":{"arxiv_id":"2605.25025","last_updated":"2026-05-24T12:04:29Z","snapshot_observed_at":"2026-08-05T00:25:58.011074Z","submitted_at":"2026-05-24T12:04:29Z","title":"Micro-Swarm Locomotion Optimization in Dynamic Flow using Multi-Objective Multi-Agent Reinforcement Learning","version":1},"reference_index":54,"source":"pdf_text","source_observed_at":"2026-06-30T00:30:56.136600Z"},"links":{"cited_paper":"/paper/2301.07784","citing_paper":"/paper/2605.25025"},"observation_digest":"sha256:864e458a772681b330001dee5418be4fe31a46bf542204ac78d7fec0f7063786","observation_id":"972e325b-4dd9-45f5-bbeb-e80c22762383","resolution":{"observed_at":"2026-07-01T16:35:50.553809Z","resolver_source":"arxiv_id","status":"verified_exact"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-13T06:32:02.005865+00:00","source":"crossref"},{"observed_at":"2026-08-13T06:31:53.387327+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"2301.07784","last_updated":"2023-03-23T16:29:23Z","snapshot_observed_at":"2026-08-13T13:02:15.453372Z","submitted_at":"2023-01-18T20:54:40Z","title":"Sample-Efficient Multi-Objective Learning via Generalized Policy Improvement Prioritization","version":2},"cited_work":{"arxiv_id":"2301.07784","doi":null,"metadata_source":"arxiv_reference","pith_arxiv_id":"2301.07784","snapshot_observed_at":"2026-07-03T20:58:58.451676Z","title":"Sample- efficient multi-objective learning via generalized policy improvement prioritization.arXiv preprint arXiv:2301.07784,","venue":null,"work_id":"59c5ad80-df90-4e15-9247-6c2b28cf1271","year":2023},"citing_paper":{"arxiv_id":"2606.18111","last_updated":"2026-06-16T16:16:54Z","snapshot_observed_at":"2026-08-05T13:40:52.360184Z","submitted_at":"2026-06-16T16:16:54Z","title":"Learning Fair Pareto-Optimal Policies in Multi-Objective Reinforcement Learning","version":1},"reference_index":1,"source":"pdf_text","source_observed_at":"2026-06-27T00:58:29.900902Z"},"links":{"cited_paper":"/paper/2301.07784","citing_paper":"/paper/2606.18111"},"observation_digest":"sha256:687ce82066e562f61e0802000bd98a9c2d7bcefdf826610599c0fa6dca6396a7","observation_id":"74dbb2a3-7c81-4757-82ff-0deabc319379","resolution":{"observed_at":"2026-07-03T20:58:58.453398Z","resolver_source":"arxiv_id","status":"verified_exact"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-13T06:32:02.005865+00:00","source":"crossref"},{"observed_at":"2026-08-13T06:31:53.387327+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"2301.07784","last_updated":"2023-03-23T16:29:23Z","snapshot_observed_at":"2026-08-13T13:02:15.453372Z","submitted_at":"2023-01-18T20:54:40Z","title":"Sample-Efficient Multi-Objective Learning via Generalized Policy Improvement Prioritization","version":2},"cited_work":{"arxiv_id":"2301.07784","doi":null,"metadata_source":"arxiv_reference","pith_arxiv_id":"2301.07784","snapshot_observed_at":"2026-07-03T20:58:58.451676Z","title":"Sample- efficient multi-objective learning via generalized policy improvement prioritization.arXiv preprint arXiv:2301.07784,","venue":null,"work_id":"59c5ad80-df90-4e15-9247-6c2b28cf1271","year":2023},"citing_paper":{"arxiv_id":"2606.30893","last_updated":"2026-06-29T20:31:03Z","snapshot_observed_at":"2026-08-07T04:31:26.168210Z","submitted_at":"2026-06-29T20:31:03Z","title":"Sampling-Based Coordination-Informed Multi-Objective Multi-Robot Reinforcement Learning","version":1},"reference_index":12,"source":"pdf_text","source_observed_at":"2026-07-01T01:16:42.888352Z"},"links":{"cited_paper":"/paper/2301.07784","citing_paper":"/paper/2606.30893"},"observation_digest":"sha256:984eed32ac91f8e4f2f6b142c0945aaad31080aad90b86fc5b3fad92f4738b6d","observation_id":"18214058-f794-4dd8-bb70-c4ab21e01681","resolution":{"observed_at":"2026-07-01T13:05:44.741097Z","resolver_source":"arxiv_id","status":"verified_exact"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-13T06:32:02.005865+00:00","source":"crossref"},{"observed_at":"2026-08-13T06:31:53.387327+00:00","source":"retraction_watch"}],"state":"measured"}}],"links":{"evidence":"/evidence","html":"/paper/2301.07784/citation-record","integrity":"/paper/2301.07784/integrity","json":"/paper/2301.07784/citation-record.json","paper":"/paper/2301.07784"},"outbound":[],"paper":{"arxiv_id":"2301.07784","last_updated":"2023-03-23T16:29:23Z","latest_version":2,"primary_category":"cs.LG","snapshot_observed_at":"2026-08-13T13:02:15.453372Z","submitted_at":"2023-01-18T20:54:40Z","title":"Sample-Efficient Multi-Objective Learning via Generalized Policy Improvement Prioritization"},"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":"2026-08-13T06:32:02.005865+00:00","source":"crossref"},{"observed_at":"2026-08-13T06:31:53.387327+00:00","source":"retraction_watch"}],"thesis":"As of 13 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 4 inbound Pith citation observations for arXiv:2301.07784."}