{"as_of":"2026-08-05T07:38:00Z","caps":{"database_statements":6,"inbound":100,"outbound":100},"context_digest":"sha256:5fffba7603e3415f5824406f785202d62cc99586b3519d4a01c9428d6063923f","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":"2026-08-05T06:32:48.257954+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":"2026-05-15T19:19:42.748573Z","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":"2026-05-15T19:19:42.923464Z","state":"measured"}],"external_citation_measurements":[],"inbound":[{"citation":{"cited_paper":{"arxiv_id":"2503.06260","last_updated":"2025-03-08T16:13:18Z","snapshot_observed_at":"2026-07-06T20:49:09.368757Z","submitted_at":"2025-03-08T16:13:18Z","title":"From Captions to Rewards (CAREVL): Leveraging Large Language Model Experts for Enhanced Reward Modeling in Large Vision-Language Models","version":1},"cited_work":{"arxiv_id":"2503.06260","doi":null,"metadata_source":"arxiv_reference","pith_arxiv_id":"2503.06260","snapshot_observed_at":"2026-06-05T21:23:00.469572Z","title":null,"venue":null,"work_id":"810e41f6-228e-4b18-9ec5-a1924a10f623","year":2025},"citing_paper":{"arxiv_id":"2505.17685","last_updated":"2025-11-11T01:31:25Z","snapshot_observed_at":"2026-08-02T20:06:32.255780Z","submitted_at":"2025-05-23T09:55:32Z","title":"FutureSightDrive: Thinking Visually with Spatio-Temporal CoT for Autonomous Driving","version":3},"reference_index":9,"source":"pdf_text","source_observed_at":"2026-05-15T19:19:42.748573Z"},"links":{"cited_paper":"/paper/2503.06260","citing_paper":"/paper/2505.17685"},"observation_digest":"sha256:3c3084787538cdb14d47740917dca37d78f522158df8575a672f7d35cc174e07","observation_id":"fa681bf3-4f34-420d-8caf-879593a290f3","resolution":{"observed_at":"2026-05-15T19:19:42.926469Z","resolver_source":"arxiv_id","status":"verified_exact"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-05T06:32:48.257954+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-05T06:32:48.257954+00:00","source":"crossref"},{"observed_at":"2026-08-05T06:32:44.755628+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"2503.06260","last_updated":"2025-03-08T16:13:18Z","snapshot_observed_at":"2026-07-06T20:49:09.368757Z","submitted_at":"2025-03-08T16:13:18Z","title":"From Captions to Rewards (CAREVL): Leveraging Large Language Model Experts for Enhanced Reward Modeling in Large Vision-Language Models","version":1},"cited_work":{"arxiv_id":"2503.06260","doi":null,"metadata_source":"arxiv_reference","pith_arxiv_id":"2503.06260","snapshot_observed_at":"2026-06-05T21:23:00.469572Z","title":null,"venue":null,"work_id":"810e41f6-228e-4b18-9ec5-a1924a10f623","year":2025},"citing_paper":{"arxiv_id":"2602.23827","last_updated":"2026-02-27T09:07:47Z","snapshot_observed_at":"2026-07-06T22:47:15.482910Z","submitted_at":"2026-02-27T09:07:47Z","title":"FedNSAM:Consistency of Local and Global Flatness for Federated Learning","version":1},"reference_index":5,"source":"pdf_text","source_observed_at":"2026-05-15T18:41:54.145958Z"},"links":{"cited_paper":"/paper/2503.06260","citing_paper":"/paper/2602.23827"},"observation_digest":"sha256:08e37b2a0fbd8b630902b09a28230cdd41764d6f2062e58cc1a0a3c612eb8e40","observation_id":"42e18603-d2fb-4269-86ed-a41c0f7ff6c7","resolution":{"observed_at":"2026-05-15T18:46:29.515806Z","resolver_source":"arxiv_id","status":"verified_exact"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-05T06:32:48.257954+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-05T06:32:48.257954+00:00","source":"crossref"},{"observed_at":"2026-08-05T06:32:44.755628+00:00","source":"retraction_watch"}],"state":"measured"}}],"links":{"evidence":"/evidence","html":"/paper/2503.06260/citation-record","integrity":"/paper/2503.06260/integrity","json":"/paper/2503.06260/citation-record.json","paper":"/paper/2503.06260"},"outbound":[],"paper":{"arxiv_id":"2503.06260","last_updated":"2025-03-08T16:13:18Z","latest_version":1,"primary_category":"cs.CV","snapshot_observed_at":"2026-07-06T20:49:09.368757Z","submitted_at":"2025-03-08T16:13:18Z","title":"From Captions to Rewards (CAREVL): Leveraging Large Language Model Experts for Enhanced Reward Modeling in Large Vision-Language Models"},"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":"2026-08-05T06:32:48.257954+00:00","source":"crossref"},{"observed_at":"2026-08-05T06:32:44.755628+00:00","source":"retraction_watch"}],"thesis":"As of 5 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 2 inbound Pith citation observations for arXiv:2503.06260."}