{"as_of":"2026-08-17T12:32:00Z","caps":{"database_statements":6,"inbound":100,"outbound":100},"context_digest":"sha256:0b889ee4ef46fe74cb930afa3808d64b9bad4b97d718a99d655b78a141bac863","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":"2026-08-05T13:55:20.429792Z","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":"2026-05-16T09:07:39.268358Z","state":"measured"}],"external_citation_measurements":[],"inbound":[{"citation":{"cited_paper":{"arxiv_id":"2209.08466","last_updated":"2023-06-24T19:05:46Z","snapshot_observed_at":"2026-08-16T16:31:45.884149Z","submitted_at":"2022-09-18T03:51:58Z","title":"Simplifying Model-based RL: Learning Representations, Latent-space Models, and Policies with One Objective","version":3},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2209.08466","snapshot_observed_at":"2026-08-05T13:55:20.429792Z","title":"Ghugare, H","venue":null,"work_id":null,"year":2022},"citing_paper":{"arxiv_id":"2509.00215","last_updated":"2025-09-04T12:46:04Z","snapshot_observed_at":"2026-08-15T00:23:15.253590Z","submitted_at":"2025-08-29T19:55:25Z","title":"First Order Model-Based RL through Decoupled Backpropagation","version":2},"reference_index":34,"source":"pdf_text","source_observed_at":"2026-08-05T13:55:20.429792Z"},"links":{"cited_paper":"/paper/2209.08466","citing_paper":"/paper/2509.00215"},"observation_digest":"sha256:3274f08c6d48ce950f63655d21c878afa3bedef93b3f7225d06523681f2dc5fb","observation_id":"4bda6bbb-e76f-4d54-b507-8cfecbb5d497","resolution":{"observed_at":"2026-08-05T13:55:20.429792Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2209.08466","last_updated":"2023-06-24T19:05:46Z","snapshot_observed_at":"2026-08-16T16:31:45.884149Z","submitted_at":"2022-09-18T03:51:58Z","title":"Simplifying Model-based RL: Learning Representations, Latent-space Models, and Policies with One Objective","version":3},"cited_work":{"arxiv_id":"2209.08466","doi":null,"metadata_source":"arxiv_reference","pith_arxiv_id":"2209.08466","snapshot_observed_at":"2026-06-05T21:23:00.469572Z","title":"Simplifying model-based rl: learn- ing representations, latent-space models, and policies with one objective.arXiv preprint arXiv:2209.08466","venue":null,"work_id":"3b9c6715-c56b-4913-926c-6801fb771ba0","year":null},"citing_paper":{"arxiv_id":"2602.00297","last_updated":"2026-05-12T15:25:15Z","snapshot_observed_at":"2026-08-10T21:07:17.973191Z","submitted_at":"2026-01-30T20:39:44Z","title":"From Observations to States: Latent Time Series Forecasting","version":2},"reference_index":3,"source":"pdf_text","source_observed_at":"2026-05-16T09:03:49.988075Z"},"links":{"cited_paper":"/paper/2209.08466","citing_paper":"/paper/2602.00297"},"observation_digest":"sha256:47a3326a13990a7f5c1453c71901914344fe15c44270a09a02bb03fed4894008","observation_id":"748ccd38-b0a8-475b-8bac-d77a7246d42c","resolution":{"observed_at":"2026-05-16T09:07:39.270892Z","resolver_source":"arxiv_id","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"}}],"links":{"evidence":"/evidence","html":"/paper/2209.08466/citation-record","integrity":"/paper/2209.08466/integrity","json":"/paper/2209.08466/citation-record.json","paper":"/paper/2209.08466"},"outbound":[],"paper":{"arxiv_id":"2209.08466","last_updated":"2023-06-24T19:05:46Z","latest_version":3,"primary_category":"cs.LG","snapshot_observed_at":"2026-08-16T16:31:45.884149Z","submitted_at":"2022-09-18T03:51:58Z","title":"Simplifying Model-based RL: Learning Representations, Latent-space Models, and Policies with One Objective"},"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:2209.08466."}