{"as_of":"2026-08-08T04:40:00Z","caps":{"database_statements":6,"inbound":100,"outbound":100},"context_digest":"sha256:913fcf6c6f6ab36208acb2d8bf9f58e73d4c1187a868b73d300c70b1f63cea6b","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":9,"lane":"standing_notices","note":"One-hop event checks from named stored sources.","records_observed":9,"source":"scholarly_work_events, retraction_status_cache","source_observed_at":"2026-08-07T06:34:17.273281+00:00","state":"measured"},{"denominator":9,"lane":"inbound_itemization","note":"Pith citing papers itemized under the disclosed page cap.","records_observed":9,"source":"paper_references, paper_reference_links","source_observed_at":"2026-08-07T23:34:11.209457Z","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":"2026-05-24T06:44:02.528967Z","state":"measured"}],"external_citation_measurements":[],"inbound":[{"citation":{"cited_paper":{"arxiv_id":"2403.00564","last_updated":"2024-09-12T08:37:27Z","snapshot_observed_at":"2026-08-07T10:40:27.250156Z","submitted_at":"2024-03-01T14:42:25Z","title":"EfficientZero V2: Mastering Discrete and Continuous Control with Limited Data","version":2},"cited_work":{"arxiv_id":"2403.00564","doi":null,"metadata_source":"arxiv_reference","pith_arxiv_id":"2403.00564","snapshot_observed_at":"2026-06-05T21:23:00.469572Z","title":"Efficientzero v2: Mastering discrete and continuous control with limited data.arXiv preprint arXiv:2403.00564","venue":null,"work_id":"f72d0f2d-94ec-4ee4-93c8-23453fd783cd","year":2024},"citing_paper":{"arxiv_id":"2310.02635","last_updated":"2026-04-23T15:06:38Z","snapshot_observed_at":"2026-07-06T02:11:23.670680Z","submitted_at":"2023-10-04T07:56:42Z","title":"Reinforcement Learning with Foundation Priors: Let the Embodied Agent Efficiently Learn on Its Own","version":5},"reference_index":58,"source":"pdf_text","source_observed_at":"2026-05-24T06:40:00.328012Z"},"links":{"cited_paper":"/paper/2403.00564","citing_paper":"/paper/2310.02635"},"observation_digest":"sha256:fc9f14b870b1a86c5d114d9aa5f502203ab303bedf6f91ae0a0832bca998471f","observation_id":"a5b275f5-1d60-47cb-93c2-0cfc2a6acf76","resolution":{"observed_at":"2026-05-24T06:44:02.532376Z","resolver_source":"arxiv_id","status":"verified_exact"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-07T06:34:17.273281+00:00","source":"crossref"},{"observed_at":"2026-08-07T06:34:11.927384+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"2403.00564","last_updated":"2024-09-12T08:37:27Z","snapshot_observed_at":"2026-08-07T10:40:27.250156Z","submitted_at":"2024-03-01T14:42:25Z","title":"EfficientZero V2: Mastering Discrete and Continuous Control with Limited Data","version":2},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2403.00564","snapshot_observed_at":"2026-08-07T23:34:11.209457Z","title":"Efficientzero v2: Mastering discrete and continuous control with limited data","venue":null,"work_id":null,"year":2024},"citing_paper":{"arxiv_id":"2502.08844","last_updated":"2025-02-12T23:30:01Z","snapshot_observed_at":"2026-08-07T23:27:22.713894Z","submitted_at":"2025-02-12T23:30:01Z","title":"MuJoCo Playground","version":1},"reference_index":64,"source":"pdf_text","source_observed_at":"2026-08-07T23:34:11.209457Z"},"links":{"cited_paper":"/paper/2403.00564","citing_paper":"/paper/2502.08844"},"observation_digest":"sha256:2a1eac6974b16005a3e3644b1efa0dfd3afd3fe66579ad24c90ee226ec86371f","observation_id":"add7841a-ae70-4bd3-9f32-7480d8d99c7c","resolution":{"observed_at":"2026-08-07T23:34:11.209457Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2403.00564","last_updated":"2024-09-12T08:37:27Z","snapshot_observed_at":"2026-08-07T10:40:27.250156Z","submitted_at":"2024-03-01T14:42:25Z","title":"EfficientZero V2: Mastering Discrete and Continuous Control with Limited Data","version":2},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2403.00564","snapshot_observed_at":"2026-08-07T15:23:19.855001Z","title":null,"venue":null,"work_id":null,"year":2024},"citing_paper":{"arxiv_id":"2505.15345","last_updated":"2025-05-23T11:18:10Z","snapshot_observed_at":"2026-08-07T20:34:34.327158Z","submitted_at":"2025-05-21T10:19:49Z","title":"Hadamax Encoding: Elevating Performance in Model-Free Atari","version":2},"reference_index":54,"source":"pdf_text","source_observed_at":"2026-08-07T15:23:19.855001Z"},"links":{"cited_paper":"/paper/2403.00564","citing_paper":"/paper/2505.15345"},"observation_digest":"sha256:957e192aacb133af50e0c3470911b728a92e90b64f34a48ec70837910acb4dd4","observation_id":"7f475519-402d-4448-a1d0-0408ec7e3b91","resolution":{"observed_at":"2026-08-07T15:23:19.855001Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2403.00564","last_updated":"2024-09-12T08:37:27Z","snapshot_observed_at":"2026-08-07T10:40:27.250156Z","submitted_at":"2024-03-01T14:42:25Z","title":"EfficientZero V2: Mastering Discrete and Continuous Control with Limited Data","version":2},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2403.00564","snapshot_observed_at":"2026-08-07T12:22:31.561924Z","title":"Efficientzero v2: Mastering discrete and continuous control with limited data,","venue":null,"work_id":null,"year":2024},"citing_paper":{"arxiv_id":"2505.24784","last_updated":"2025-05-30T16:46:20Z","snapshot_observed_at":"2026-08-07T12:11:21.784704Z","submitted_at":"2025-05-30T16:46:20Z","title":"AXIOM: Learning to Play Games in Minutes with Expanding Object-Centric Models","version":1},"reference_index":41,"source":"pdf_text","source_observed_at":"2026-08-07T12:22:31.561924Z"},"links":{"cited_paper":"/paper/2403.00564","citing_paper":"/paper/2505.24784"},"observation_digest":"sha256:804a7cdf66962548ea3a7def93d4b7ee040c5c41bc36cf35e109d9607856c628","observation_id":"6f97b101-dad6-4ca4-b742-00c24dd48d38","resolution":{"observed_at":"2026-08-07T12:22:31.561924Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2403.00564","last_updated":"2024-09-12T08:37:27Z","snapshot_observed_at":"2026-08-07T10:40:27.250156Z","submitted_at":"2024-03-01T14:42:25Z","title":"EfficientZero V2: Mastering Discrete and Continuous Control with Limited Data","version":2},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2403.00564","snapshot_observed_at":"2026-08-06T19:12:58.951885Z","title":"Efficientzero v2: Mastering discrete and continuous control with limited data,","venue":null,"work_id":null,"year":2024},"citing_paper":{"arxiv_id":"2507.06326","last_updated":"2025-07-08T18:30:26Z","snapshot_observed_at":"2026-08-06T19:05:09.848320Z","submitted_at":"2025-07-08T18:30:26Z","title":"Sample-Efficient Reinforcement Learning Controller for Deep Brain Stimulation in Parkinson's Disease","version":1},"reference_index":34,"source":"pdf_text","source_observed_at":"2026-08-06T19:12:58.951885Z"},"links":{"cited_paper":"/paper/2403.00564","citing_paper":"/paper/2507.06326"},"observation_digest":"sha256:fb54648690eaa4671d980764268310f2d37f0f6d28882bfc08d1ff22de84e20d","observation_id":"e35030c9-fe47-45ee-9cb1-6cb81efdead9","resolution":{"observed_at":"2026-08-06T19:12:58.951885Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2403.00564","last_updated":"2024-09-12T08:37:27Z","snapshot_observed_at":"2026-08-07T10:40:27.250156Z","submitted_at":"2024-03-01T14:42:25Z","title":"EfficientZero V2: Mastering Discrete and Continuous Control with Limited Data","version":2},"cited_work":{"arxiv_id":"2403.00564","doi":null,"metadata_source":"arxiv_reference","pith_arxiv_id":"2403.00564","snapshot_observed_at":"2026-06-05T21:23:00.469572Z","title":"Efficientzero v2: Mastering discrete and continuous control with limited data.arXiv preprint arXiv:2403.00564","venue":null,"work_id":"f72d0f2d-94ec-4ee4-93c8-23453fd783cd","year":2024},"citing_paper":{"arxiv_id":"2509.26627","last_updated":"2026-05-20T11:23:00Z","snapshot_observed_at":"2026-07-06T22:31:15.349221Z","submitted_at":"2025-09-30T17:58:20Z","title":"TimeRewarder: Learning Dense Reward from Passive Videos via Frame-wise Temporal Distance","version":3},"reference_index":15,"source":"pdf_text","source_observed_at":"2026-05-21T21:57:15.285757Z"},"links":{"cited_paper":"/paper/2403.00564","citing_paper":"/paper/2509.26627"},"observation_digest":"sha256:af712eb4d4c4171413374c3e86d594324e227730448b6237accf97e9f66c3b64","observation_id":"a882eafa-457f-4ce9-81cb-f48bc3c77d8d","resolution":{"observed_at":"2026-05-21T22:00:41.897156Z","resolver_source":"arxiv_id","status":"verified_exact"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-07T06:34:17.273281+00:00","source":"crossref"},{"observed_at":"2026-08-07T06:34:11.927384+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"2403.00564","last_updated":"2024-09-12T08:37:27Z","snapshot_observed_at":"2026-08-07T10:40:27.250156Z","submitted_at":"2024-03-01T14:42:25Z","title":"EfficientZero V2: Mastering Discrete and Continuous Control with Limited Data","version":2},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2403.00564","snapshot_observed_at":"2026-08-04T08:03:21.010708Z","title":"Efficientzero v2: Mastering discrete and continuous control with limited data","venue":null,"work_id":null,"year":2024},"citing_paper":{"arxiv_id":"2510.23216","last_updated":"2026-06-02T10:40:21Z","snapshot_observed_at":"2026-08-04T08:03:02.093431Z","submitted_at":"2025-10-27T11:06:00Z","title":"Human-Like Goalkeeping in a Realistic Football Simulation: a Sample-Efficient Reinforcement Learning Approach","version":4},"reference_index":23,"source":"arxiv_source","source_observed_at":"2026-08-04T08:03:21.010708Z"},"links":{"cited_paper":"/paper/2403.00564","citing_paper":"/paper/2510.23216"},"observation_digest":"sha256:6bf2f79f8bfb1d5b4d710d180cbca067ccf2c5e3b1e899c689fa8a91cfbfee25","observation_id":"6f8f4fe2-d005-4344-b0da-8bb0316fa701","resolution":{"observed_at":"2026-08-04T08:03:21.010708Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2403.00564","last_updated":"2024-09-12T08:37:27Z","snapshot_observed_at":"2026-08-07T10:40:27.250156Z","submitted_at":"2024-03-01T14:42:25Z","title":"EfficientZero V2: Mastering Discrete and Continuous Control with Limited Data","version":2},"cited_work":{"arxiv_id":"2403.00564","doi":null,"metadata_source":"arxiv_reference","pith_arxiv_id":"2403.00564","snapshot_observed_at":"2026-06-05T21:23:00.469572Z","title":"Efficientzero v2: Mastering discrete and continuous control with limited data.arXiv preprint arXiv:2403.00564","venue":null,"work_id":"f72d0f2d-94ec-4ee4-93c8-23453fd783cd","year":2024},"citing_paper":{"arxiv_id":"2603.07083","last_updated":"2026-04-14T13:41:32Z","snapshot_observed_at":"2026-07-06T22:48:13.053749Z","submitted_at":"2026-03-07T07:41:28Z","title":"Dreamer-CDP: Improving Reconstruction-free World Models Via Continuous Deterministic Representation Prediction","version":2},"reference_index":18,"source":"pdf_text","source_observed_at":"2026-05-15T14:46:18.645009Z"},"links":{"cited_paper":"/paper/2403.00564","citing_paper":"/paper/2603.07083"},"observation_digest":"sha256:e998df013d511dc55c82ba32b34d79b80fc58af6ea2c9431bd7077157bd289eb","observation_id":"84e6aab5-0b82-4a0d-94ad-dc9055f82126","resolution":{"observed_at":"2026-05-15T14:50:05.082907Z","resolver_source":"arxiv_id","status":"verified_exact"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-07T06:34:17.273281+00:00","source":"crossref"},{"observed_at":"2026-08-07T06:34:11.927384+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"2403.00564","last_updated":"2024-09-12T08:37:27Z","snapshot_observed_at":"2026-08-07T10:40:27.250156Z","submitted_at":"2024-03-01T14:42:25Z","title":"EfficientZero V2: Mastering Discrete and Continuous Control with Limited Data","version":2},"cited_work":{"arxiv_id":"2403.00564","doi":null,"metadata_source":"arxiv_reference","pith_arxiv_id":"2403.00564","snapshot_observed_at":"2026-06-05T21:23:00.469572Z","title":"Efficientzero v2: Mastering discrete and continuous control with limited data.arXiv preprint arXiv:2403.00564","venue":null,"work_id":"f72d0f2d-94ec-4ee4-93c8-23453fd783cd","year":2024},"citing_paper":{"arxiv_id":"2605.08019","last_updated":"2026-05-08T17:07:41Z","snapshot_observed_at":"2026-07-06T23:20:19.821342Z","submitted_at":"2026-05-08T17:07:41Z","title":"Reason to Play: Behavioral and Brain Alignment Between Frontier LRMs and Human Game Learners","version":1},"reference_index":8,"source":"pdf_text","source_observed_at":"2026-05-11T02:54:56.671883Z"},"links":{"cited_paper":"/paper/2403.00564","citing_paper":"/paper/2605.08019"},"observation_digest":"sha256:43e0b7665bb227c1c17f97a4dcebd0aeea20041987e4dad1c9e901de73e0f747","observation_id":"fd7b19ff-454d-454c-bcdc-ab72db07366f","resolution":{"observed_at":"2026-05-11T02:55:53.006650Z","resolver_source":"arxiv_id","status":"verified_exact"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-07T06:34:17.273281+00:00","source":"crossref"},{"observed_at":"2026-08-07T06:34:11.927384+00:00","source":"retraction_watch"}],"state":"measured"}}],"links":{"evidence":"/evidence","html":"/paper/2403.00564/citation-record","integrity":"/paper/2403.00564/integrity","json":"/paper/2403.00564/citation-record.json","paper":"/paper/2403.00564"},"outbound":[],"paper":{"arxiv_id":"2403.00564","last_updated":"2024-09-12T08:37:27Z","latest_version":2,"primary_category":"cs.LG","snapshot_observed_at":"2026-08-07T10:40:27.250156Z","submitted_at":"2024-03-01T14:42:25Z","title":"EfficientZero V2: Mastering Discrete and Continuous Control with Limited Data"},"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":"2026-08-07T06:34:17.273281+00:00","source":"crossref"},{"observed_at":"2026-08-07T06:34:11.927384+00:00","source":"retraction_watch"}],"thesis":"As of 8 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 9 inbound Pith citation observations for arXiv:2403.00564."}