{"as_of":"2026-08-13T11:59:00Z","caps":{"database_statements":6,"inbound":100,"outbound":100},"context_digest":"sha256:0ea54d3c86589e6c2c5052b768377bed67325850584ec3a8a035f75fec797d79","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":"2026-08-13T06:32:02.005865+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":"2026-08-11T12:27:14.698765Z","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":"2026-08-06T15:03:25.681499Z","state":"measured"}],"external_citation_measurements":[],"inbound":[{"citation":{"cited_paper":{"arxiv_id":"2204.10374","last_updated":"2022-04-21T19:07:50Z","snapshot_observed_at":"2026-08-11T07:44:56.766067Z","submitted_at":"2022-04-21T19:07:50Z","title":"Learning how to Interact with a Complex Interface using Hierarchical Reinforcement Learning","version":1},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2204.10374","snapshot_observed_at":"2026-08-11T12:27:14.698765Z","title":"Learning how to interact with a complex interface using hierarchical reinforcement learning","venue":null,"work_id":null,"year":2022},"citing_paper":{"arxiv_id":"2412.14355","last_updated":"2024-12-18T21:43:40Z","snapshot_observed_at":"2026-08-11T19:04:40.952532Z","submitted_at":"2024-12-18T21:43:40Z","title":"Enabling Realtime Reinforcement Learning at Scale with Staggered Asynchronous Inference","version":1},"reference_index":14,"source":"pdf_text","source_observed_at":"2026-08-11T12:27:14.698765Z"},"links":{"cited_paper":"/paper/2204.10374","citing_paper":"/paper/2412.14355"},"observation_digest":"sha256:9d8a1ae0c680696dfe7cceb10f8f4fee980ab5ec08ffb9f4aa047902ceb67a4a","observation_id":"4d3f0895-871a-4fdf-b5bc-65912eb48c3f","resolution":{"observed_at":"2026-08-11T12:27:14.698765Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2204.10374","last_updated":"2022-04-21T19:07:50Z","snapshot_observed_at":"2026-08-11T07:44:56.766067Z","submitted_at":"2022-04-21T19:07:50Z","title":"Learning how to Interact with a Complex Interface using Hierarchical Reinforcement Learning","version":1},"cited_work":{"arxiv_id":"2204.10374","doi":null,"metadata_source":"pith","pith_arxiv_id":"2204.10374","snapshot_observed_at":"2026-08-06T15:03:25.681499Z","title":"Learning how to Interact with a Complex Interface using Hierarchical Reinforcement Learning","venue":"cs.LG","work_id":"1e0d0909-828b-4d1b-9228-d385a9a526bf","year":2022},"citing_paper":{"arxiv_id":"2507.16983","last_updated":"2025-07-22T19:47:04Z","snapshot_observed_at":"2026-08-13T08:55:49.881097Z","submitted_at":"2025-07-22T19:47:04Z","title":"Hierarchical Reinforcement Learning Framework for Adaptive Walking Control Using General Value Functions of Lower-Limb Sensor Signals","version":1},"reference_index":4,"source":"pdf_text","source_observed_at":"2026-08-06T15:03:24.517874Z"},"links":{"cited_paper":"/paper/2204.10374","citing_paper":"/paper/2507.16983"},"observation_digest":"sha256:848747d54b33241b365af016d2e08f3d44aa8937df71698b5e42dc0ade144834","observation_id":"f4cf89bb-5d02-4d81-bc92-3a8a92c6d5f6","resolution":{"observed_at":"2026-08-06T15:03:25.721528Z","resolver_source":"local_arxiv","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/2204.10374/citation-record","integrity":"/paper/2204.10374/integrity","json":"/paper/2204.10374/citation-record.json","paper":"/paper/2204.10374"},"outbound":[],"paper":{"arxiv_id":"2204.10374","last_updated":"2022-04-21T19:07:50Z","latest_version":1,"primary_category":"cs.LG","snapshot_observed_at":"2026-08-11T07:44:56.766067Z","submitted_at":"2022-04-21T19:07:50Z","title":"Learning how to Interact with a Complex Interface using Hierarchical Reinforcement Learning"},"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 2 inbound Pith citation observations for arXiv:2204.10374."}