{"as_of":"2026-08-17T13:23:00Z","caps":{"database_statements":6,"inbound":100,"outbound":100},"context_digest":"sha256:35f65f729d492df7c7fa2709129b08266f473e58434ce39e783c3598a59942c4","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":"2026-08-17T06:30:58.91139+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":"2026-08-06T15:26:24.524474Z","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":"2026-08-06T15:26:25.283465Z","state":"measured"}],"external_citation_measurements":[],"inbound":[{"citation":{"cited_paper":{"arxiv_id":"1905.07866","last_updated":"2019-07-15T06:44:33Z","snapshot_observed_at":"2026-08-14T16:29:56.441898Z","submitted_at":"2019-05-20T04:17:03Z","title":"Reinforcement Learning without Ground-Truth State","version":2},"cited_work":{"arxiv_id":"1905.07866","doi":null,"metadata_source":"pith","pith_arxiv_id":"1905.07866","snapshot_observed_at":"2026-08-06T15:26:25.283465Z","title":"Reinforcement Learning without Ground-Truth State","venue":"cs.RO","work_id":"a2f050ea-ab07-465b-ad42-83226dca4c4c","year":2019},"citing_paper":{"arxiv_id":"2507.16139","last_updated":"2025-07-22T01:13:45Z","snapshot_observed_at":"2026-08-15T09:57:16.575071Z","submitted_at":"2025-07-22T01:13:45Z","title":"Equivariant Goal Conditioned Contrastive Reinforcement Learning","version":1},"reference_index":14,"source":"pdf_text","source_observed_at":"2026-08-06T15:26:24.524474Z"},"links":{"cited_paper":"/paper/1905.07866","citing_paper":"/paper/2507.16139"},"observation_digest":"sha256:0acbaaab6ac9c834555dac72550b046bfa1d8b5c7fa51e30a3c0ed71dc43dd2f","observation_id":"29378dc2-31fa-4e31-8a90-f21462731cde","resolution":{"observed_at":"2026-08-06T15:26:25.288562Z","resolver_source":"local_arxiv","status":"verified_exact"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-17T06:30:58.91139+00:00","source":"crossref"},{"observed_at":"2026-08-17T06:30:54.323127+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"1905.07866","last_updated":"2019-07-15T06:44:33Z","snapshot_observed_at":"2026-08-14T16:29:56.441898Z","submitted_at":"2019-05-20T04:17:03Z","title":"Reinforcement Learning without Ground-Truth State","version":2},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"1905.07866","snapshot_observed_at":"2026-08-04T17:49:13.782858Z","title":"S., and Held, D","venue":null,"work_id":null,"year":2019},"citing_paper":{"arxiv_id":"2509.10656","last_updated":"2026-07-05T23:05:41Z","snapshot_observed_at":"2026-08-15T03:06:59.599056Z","submitted_at":"2025-09-12T19:35:20Z","title":"Self-Supervised Goal-Reaching Results in Multi-Agent Cooperation and Exploration","version":2},"reference_index":27,"source":"pdf_text","source_observed_at":"2026-08-04T17:49:13.782858Z"},"links":{"cited_paper":"/paper/1905.07866","citing_paper":"/paper/2509.10656"},"observation_digest":"sha256:d7190c8571dc5f34776c86e8f22821c9e45e00b463001ed0179e516f563c6b9f","observation_id":"9fd2106b-1fba-4424-937f-0b5bb0fa41b7","resolution":{"observed_at":"2026-08-04T17:49:13.782858Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}}],"links":{"evidence":"/evidence","html":"/paper/1905.07866/citation-record","integrity":"/paper/1905.07866/integrity","json":"/paper/1905.07866/citation-record.json","paper":"/paper/1905.07866"},"outbound":[],"paper":{"arxiv_id":"1905.07866","last_updated":"2019-07-15T06:44:33Z","latest_version":2,"primary_category":"cs.RO","snapshot_observed_at":"2026-08-14T16:29:56.441898Z","submitted_at":"2019-05-20T04:17:03Z","title":"Reinforcement Learning without Ground-Truth State"},"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":"2026-08-17T06:30:58.91139+00:00","source":"crossref"},{"observed_at":"2026-08-17T06:30:54.323127+00:00","source":"retraction_watch"}],"thesis":"As of 17 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 2 inbound Pith citation observations for arXiv:1905.07866."}