{"as_of":"2026-08-09T16:28:00Z","caps":{"database_statements":6,"inbound":100,"outbound":100},"context_digest":"sha256:0c7be97eb0bef4bf2ccfa894f16f818142f988cc1fd227afa515d21139ad03d4","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":"2026-08-09T06:31:02.800959+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":"2026-08-07T19:25:37.918588Z","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":"2026-08-08T00:16:16.039225Z","state":"measured"}],"external_citation_measurements":[],"inbound":[{"citation":{"cited_paper":{"arxiv_id":"2505.10861","last_updated":"2025-05-16T05:03:39Z","snapshot_observed_at":"2026-08-07T15:44:50.684850Z","submitted_at":"2025-05-16T05:03:39Z","title":"Improving the Data-efficiency of Reinforcement Learning by Warm-starting with LLM","version":1},"cited_work":{"arxiv_id":"2505.10861","doi":"10.48550/arxiv.2505.10861","metadata_source":"pith","pith_arxiv_id":"2505.10861","snapshot_observed_at":"2026-08-08T00:16:16.039225Z","title":"Improving the Data-efficiency of Reinforcement Learning by Warm-starting with LLM","venue":"cs.LG","work_id":"64f5173f-6c73-4318-84d7-ef9ceafa6f88","year":2025},"citing_paper":{"arxiv_id":"2608.06015","last_updated":"2026-08-06T13:19:29Z","snapshot_observed_at":"2026-08-09T16:12:25.170590Z","submitted_at":"2026-08-06T13:19:29Z","title":"ProDVI: Programmatic Dynamics Priors for Value Network Initialization","version":1},"reference_index":62,"source":"arxiv_source","source_observed_at":"2026-08-07T19:25:37.918588Z"},"links":{"cited_paper":"/paper/2505.10861","citing_paper":"/paper/2608.06015"},"observation_digest":"sha256:04e6473434f1ed23624a7da3b744647a9641bfbfa25a07757280057e59adde30","observation_id":"f2d30702-5654-451e-a9d5-872b374fdef9","resolution":{"observed_at":"2026-08-07T19:25:38.695370Z","resolver_source":"local_arxiv","status":"verified_exact"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-09T06:31:02.800959+00:00","source":"crossref"},{"observed_at":"2026-08-09T06:30:57.326959+00:00","source":"retraction_watch"}],"state":"measured"}}],"links":{"evidence":"/evidence","html":"/paper/2505.10861/citation-record","integrity":"/paper/2505.10861/integrity","json":"/paper/2505.10861/citation-record.json","paper":"/paper/2505.10861"},"outbound":[],"paper":{"arxiv_id":"2505.10861","last_updated":"2025-05-16T05:03:39Z","latest_version":1,"primary_category":"cs.LG","snapshot_observed_at":"2026-08-07T15:44:50.684850Z","submitted_at":"2025-05-16T05:03:39Z","title":"Improving the Data-efficiency of Reinforcement Learning by Warm-starting with LLM"},"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":"2026-08-09T06:31:02.800959+00:00","source":"crossref"},{"observed_at":"2026-08-09T06:30:57.326959+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:2505.10861."}