{"as_of":"2026-08-21T10:04:00Z","caps":{"database_statements":6,"inbound":100,"outbound":100},"context_digest":"sha256:988b1ae4137d2980d97e6a073bac690f04c1cec3a185f8685ffb0cac3983d98a","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":4,"lane":"standing_notices","note":"One-hop event checks from named stored sources.","records_observed":4,"source":"scholarly_work_events, retraction_status_cache","source_observed_at":"2026-08-21T06:32:19.484+00:00","state":"measured"},{"denominator":4,"lane":"inbound_itemization","note":"Pith citing papers itemized under the disclosed page cap.","records_observed":4,"source":"paper_references, paper_reference_links","source_observed_at":"2026-07-03T17:42:44.309030Z","state":"measured"},{"denominator":1,"lane":"external_citation_measurements","note":"A source-named dated measurement, never combined with another source.","records_observed":1,"source":"arxiv_reference","source_observed_at":"2026-08-05T02:28:24.338817Z","state":"measured"}],"external_citation_measurements":[{"count":0,"observed_at":"2026-08-05T02:28:24.338817Z","source":"arxiv_reference"}],"inbound":[{"citation":{"cited_paper":{"arxiv_id":"2508.04280","last_updated":"2025-08-06T10:08:48Z","snapshot_observed_at":"2026-08-21T05:22:30.436981Z","submitted_at":"2025-08-06T10:08:48Z","title":"Enhancing Vision-Language Model Training with Reinforcement Learning in Synthetic Worlds for Real-World Success","version":1},"cited_work":{"arxiv_id":"2508.04280","doi":"10.48550/arxiv.2508.04280","metadata_source":"arxiv_reference","pith_arxiv_id":"2508.04280","snapshot_observed_at":"2026-08-05T02:28:24.338817Z","title":"Enhancing vision- language model training with reinforcement learning in synthetic worlds for real-world success","venue":"arXiv (Cornell University)","work_id":"cfe1bd59-605f-45d6-8901-1d1df2cafda0","year":2025},"citing_paper":{"arxiv_id":"2604.07774","last_updated":"2026-04-09T04:01:27Z","snapshot_observed_at":"2026-07-06T22:57:00.904627Z","submitted_at":"2026-04-09T04:01:27Z","title":"RoboAgent: Chaining Basic Capabilities for Embodied Task Planning","version":1},"reference_index":8,"source":"pdf_text","source_observed_at":"2026-05-10T18:15:08.727921Z"},"links":{"cited_paper":"/paper/2508.04280","citing_paper":"/paper/2604.07774"},"observation_digest":"sha256:fb8f905411d3b9bc986ea1b92a276c997d951c7c602f6ab269f5ca8a3782f05a","observation_id":"19e7b882-6f75-4a32-bb56-3598f81b3658","resolution":{"observed_at":"2026-05-11T05:15:57.383961Z","resolver_source":"arxiv_id","status":"verified_exact"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-21T06:32:19.484+00:00","source":"crossref"},{"observed_at":"2026-08-21T06:32:16.066871+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"2508.04280","last_updated":"2025-08-06T10:08:48Z","snapshot_observed_at":"2026-08-21T05:22:30.436981Z","submitted_at":"2025-08-06T10:08:48Z","title":"Enhancing Vision-Language Model Training with Reinforcement Learning in Synthetic Worlds for Real-World Success","version":1},"cited_work":{"arxiv_id":"2508.04280","doi":"10.48550/arxiv.2508.04280","metadata_source":"arxiv_reference","pith_arxiv_id":"2508.04280","snapshot_observed_at":"2026-08-05T02:28:24.338817Z","title":"Enhancing vision- language model training with reinforcement learning in synthetic worlds for real-world success","venue":"arXiv (Cornell University)","work_id":"cfe1bd59-605f-45d6-8901-1d1df2cafda0","year":2025},"citing_paper":{"arxiv_id":"2605.09965","last_updated":"2026-05-12T15:54:46Z","snapshot_observed_at":"2026-07-06T23:21:59.096464Z","submitted_at":"2026-05-11T04:16:41Z","title":"Towards Generalist Game Players: An Investigation of Foundation Models in the Game Multiverse","version":1},"reference_index":14,"source":"pdf_text","source_observed_at":"2026-05-12T03:25:24.844859Z"},"links":{"cited_paper":"/paper/2508.04280","citing_paper":"/paper/2605.09965"},"observation_digest":"sha256:0a1e44eea66d5ea364bb8993588a9c4181230476780b440af41e736054200c7d","observation_id":"4a08a957-9eef-4af8-af76-05c23cfe80cf","resolution":{"observed_at":"2026-05-12T03:26:19.046031Z","resolver_source":"arxiv_id","status":"verified_exact"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-21T06:32:19.484+00:00","source":"crossref"},{"observed_at":"2026-08-21T06:32:16.066871+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"2508.04280","last_updated":"2025-08-06T10:08:48Z","snapshot_observed_at":"2026-08-21T05:22:30.436981Z","submitted_at":"2025-08-06T10:08:48Z","title":"Enhancing Vision-Language Model Training with Reinforcement Learning in Synthetic Worlds for Real-World Success","version":1},"cited_work":{"arxiv_id":"2508.04280","doi":"10.48550/arxiv.2508.04280","metadata_source":"arxiv_reference","pith_arxiv_id":"2508.04280","snapshot_observed_at":"2026-08-05T02:28:24.338817Z","title":"Enhancing vision- language model training with reinforcement learning in synthetic worlds for real-world success","venue":"arXiv (Cornell University)","work_id":"cfe1bd59-605f-45d6-8901-1d1df2cafda0","year":2025},"citing_paper":{"arxiv_id":"2605.09965","last_updated":"2026-05-12T15:54:46Z","snapshot_observed_at":"2026-07-06T23:21:59.096464Z","submitted_at":"2026-05-11T04:16:41Z","title":"Towards Generalist Game Players: An Investigation of Foundation Models in the Game Multiverse","version":2},"reference_index":14,"source":"pdf_text","source_observed_at":"2026-05-13T06:44:28.552513Z"},"links":{"cited_paper":"/paper/2508.04280","citing_paper":"/paper/2605.09965"},"observation_digest":"sha256:4fc705275bc32c58a26bd8c12a87f1696ba6e15b2d92cd94ef1af975c9d2d53b","observation_id":"84d25fb1-4d0e-44a8-aad1-bbf2cb477c99","resolution":{"observed_at":"2026-05-13T06:47:26.987221Z","resolver_source":"arxiv_id","status":"verified_exact"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-21T06:32:19.484+00:00","source":"crossref"},{"observed_at":"2026-08-21T06:32:16.066871+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"2508.04280","last_updated":"2025-08-06T10:08:48Z","snapshot_observed_at":"2026-08-21T05:22:30.436981Z","submitted_at":"2025-08-06T10:08:48Z","title":"Enhancing Vision-Language Model Training with Reinforcement Learning in Synthetic Worlds for Real-World Success","version":1},"cited_work":{"arxiv_id":"2508.04280","doi":"10.48550/arxiv.2508.04280","metadata_source":"arxiv_reference","pith_arxiv_id":"2508.04280","snapshot_observed_at":"2026-08-05T02:28:24.338817Z","title":"Enhancing vision- language model training with reinforcement learning in synthetic worlds for real-world success","venue":"arXiv (Cornell University)","work_id":"cfe1bd59-605f-45d6-8901-1d1df2cafda0","year":2025},"citing_paper":{"arxiv_id":"2607.01897","last_updated":"2026-07-02T08:50:32Z","snapshot_observed_at":"2026-08-13T06:18:38.670996Z","submitted_at":"2026-07-02T08:50:32Z","title":"Rank-Then-Act: Reward-Free Control from Frame-Order Progress","version":1},"reference_index":2,"source":"pdf_text","source_observed_at":"2026-07-03T17:42:44.309030Z"},"links":{"cited_paper":"/paper/2508.04280","citing_paper":"/paper/2607.01897"},"observation_digest":"sha256:3a38847d87cd24145ecbfe1c2904595e642d6a66cf6fd2e83815a7fc052291fd","observation_id":"85944475-3427-4f92-86fb-ef5f31ca9f26","resolution":{"observed_at":"2026-07-03T17:48:45.215393Z","resolver_source":"arxiv_id","status":"verified_exact"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-21T06:32:19.484+00:00","source":"crossref"},{"observed_at":"2026-08-21T06:32:16.066871+00:00","source":"retraction_watch"}],"state":"measured"}}],"links":{"evidence":"/evidence","html":"/paper/2508.04280/citation-record","integrity":"/paper/2508.04280/integrity","json":"/paper/2508.04280/citation-record.json","paper":"/paper/2508.04280"},"outbound":[],"paper":{"arxiv_id":"2508.04280","last_updated":"2025-08-06T10:08:48Z","latest_version":1,"primary_category":"cs.LG","snapshot_observed_at":"2026-08-21T05:22:30.436981Z","submitted_at":"2025-08-06T10:08:48Z","title":"Enhancing Vision-Language Model Training with Reinforcement Learning in Synthetic Worlds for Real-World Success"},"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":"2026-08-21T06:32:19.484+00:00","source":"crossref"},{"observed_at":"2026-08-21T06:32:16.066871+00:00","source":"retraction_watch"}],"thesis":"As of 21 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 4 inbound Pith citation observations for arXiv:2508.04280."}