{"as_of":"2026-08-09T01:18:00Z","caps":{"database_statements":6,"inbound":100,"outbound":100},"context_digest":"sha256:34845025a5419d95817b6ac9fe9f504ad88c886e51e2d1ca808f5d4e84395ddd","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":"2026-08-08T06:32:00.761636+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":"2026-08-07T12:05:25.860929Z","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":"2026-08-07T12:05:26.388725Z","state":"measured"}],"external_citation_measurements":[],"inbound":[{"citation":{"cited_paper":{"arxiv_id":"2406.00079","last_updated":"2024-05-31T10:41:03Z","snapshot_observed_at":"2026-07-06T18:23:31.520359Z","submitted_at":"2024-05-31T10:41:03Z","title":"Decision Mamba: Reinforcement Learning via Hybrid Selective Sequence Modeling","version":1},"cited_work":{"arxiv_id":"2406.00079","doi":null,"metadata_source":"pith","pith_arxiv_id":"2406.00079","snapshot_observed_at":"2026-08-07T12:05:26.388725Z","title":"Decision Mamba: Reinforcement Learning via Hybrid Selective Sequence Modeling","venue":"cs.LG","work_id":"c3e60013-ef6d-44e2-8ff7-6539974042f9","year":2024},"citing_paper":{"arxiv_id":"2506.00795","last_updated":"2025-09-11T03:42:40Z","snapshot_observed_at":"2026-08-07T11:55:27.735310Z","submitted_at":"2025-06-01T02:49:26Z","title":"Closing the Gap between TD Learning and Supervised Learning with $Q$-Conditioned Maximization","version":3},"reference_index":24,"source":"arxiv_source","source_observed_at":"2026-08-07T12:05:25.860929Z"},"links":{"cited_paper":"/paper/2406.00079","citing_paper":"/paper/2506.00795"},"observation_digest":"sha256:bbbaf660c5a6176d240ca3477c0e44ba4801b3e05cb3915c9ca9feb5a3193d99","observation_id":"77b97c48-a143-4bf1-abcd-26486fc6b117","resolution":{"observed_at":"2026-08-07T12:05:26.394932Z","resolver_source":"local_arxiv","status":"verified_exact"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-08T06:32:00.761636+00:00","source":"crossref"},{"observed_at":"2026-08-08T06:31:55.24221+00:00","source":"retraction_watch"}],"state":"measured"}}],"links":{"evidence":"/evidence","html":"/paper/2406.00079/citation-record","integrity":"/paper/2406.00079/integrity","json":"/paper/2406.00079/citation-record.json","paper":"/paper/2406.00079"},"outbound":[],"paper":{"arxiv_id":"2406.00079","last_updated":"2024-05-31T10:41:03Z","latest_version":1,"primary_category":"cs.LG","snapshot_observed_at":"2026-07-06T18:23:31.520359Z","submitted_at":"2024-05-31T10:41:03Z","title":"Decision Mamba: Reinforcement Learning via Hybrid Selective Sequence Modeling"},"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":"2026-08-08T06:32:00.761636+00:00","source":"crossref"},{"observed_at":"2026-08-08T06:31:55.24221+00:00","source":"retraction_watch"}],"thesis":"As of 9 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 1 inbound Pith citation observation for arXiv:2406.00079."}