{"as_of":"2026-08-09T19:30:00Z","caps":{"database_statements":6,"inbound":100,"outbound":100},"context_digest":"sha256:59d11d7874d2909cb4a3ddd5672579fef3ee61510133ec68aa1b81a2c90b5d56","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":"2026-08-09T06:31:02.800959+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":"2026-08-08T12:32:20.142069Z","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":"2026-08-06T04:39:11.292081Z","state":"measured"}],"external_citation_measurements":[],"inbound":[{"citation":{"cited_paper":{"arxiv_id":"2410.08896","last_updated":"2025-04-02T18:17:24Z","snapshot_observed_at":"2026-08-04T20:57:43.814693Z","submitted_at":"2024-10-11T15:13:17Z","title":"MAD-TD: Model-Augmented Data stabilizes High Update Ratio RL","version":2},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2410.08896","snapshot_observed_at":"2026-08-08T12:32:20.142069Z","title":"Mad-td: Model-augmented data stabilizes high update ratio rl, 2025","venue":null,"work_id":null,"year":2025},"citing_paper":{"arxiv_id":"2502.07523","last_updated":"2025-05-22T12:39:27Z","snapshot_observed_at":"2026-08-08T12:25:21.333969Z","submitted_at":"2025-02-11T12:55:32Z","title":"Scaling Off-Policy Reinforcement Learning with Batch and Weight Normalization","version":2},"reference_index":44,"source":"pdf_text","source_observed_at":"2026-08-08T12:32:20.142069Z"},"links":{"cited_paper":"/paper/2410.08896","citing_paper":"/paper/2502.07523"},"observation_digest":"sha256:1a26a5143591040fd7c288433d1a09d9a65ede7dc1f89940bf66ad61dd42be6b","observation_id":"e034f50a-2aff-4ba1-806d-58df997a9bee","resolution":{"observed_at":"2026-08-08T12:32:20.142069Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2410.08896","last_updated":"2025-04-02T18:17:24Z","snapshot_observed_at":"2026-08-04T20:57:43.814693Z","submitted_at":"2024-10-11T15:13:17Z","title":"MAD-TD: Model-Augmented Data stabilizes High Update Ratio RL","version":2},"cited_work":{"arxiv_id":"2410.08896","doi":null,"metadata_source":"pith","pith_arxiv_id":"2410.08896","snapshot_observed_at":"2026-08-06T04:39:11.292081Z","title":"MAD-TD: Model-Augmented Data stabilizes High Update Ratio RL","venue":"cs.LG","work_id":"919b31fe-603b-4e7a-9d39-339c96d5f6e9","year":2024},"citing_paper":{"arxiv_id":"2508.03194","last_updated":"2025-08-05T08:03:12Z","snapshot_observed_at":"2026-08-06T11:32:36.516059Z","submitted_at":"2025-08-05T08:03:12Z","title":"Scaling DRL for Decision Making: A Survey on Data, Network, and Training Budget Strategies","version":1},"reference_index":50,"source":"pdf_text","source_observed_at":"2026-08-06T04:39:08.410191Z"},"links":{"cited_paper":"/paper/2410.08896","citing_paper":"/paper/2508.03194"},"observation_digest":"sha256:853ba5deca6b5b816f6dafc99db3666e984fb466ecd0aa38b0fbe582901548d9","observation_id":"7141075c-d58a-45f0-8b00-941519ddc798","resolution":{"observed_at":"2026-08-06T04:39:11.383388Z","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/2410.08896/citation-record","integrity":"/paper/2410.08896/integrity","json":"/paper/2410.08896/citation-record.json","paper":"/paper/2410.08896"},"outbound":[],"paper":{"arxiv_id":"2410.08896","last_updated":"2025-04-02T18:17:24Z","latest_version":2,"primary_category":"cs.LG","snapshot_observed_at":"2026-08-04T20:57:43.814693Z","submitted_at":"2024-10-11T15:13:17Z","title":"MAD-TD: Model-Augmented Data stabilizes High Update Ratio RL"},"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 2 inbound Pith citation observations for arXiv:2410.08896."}