{"as_of":"2026-08-24T00:22:00Z","caps":{"database_statements":6,"inbound":100,"outbound":100},"context_digest":"sha256:8625f65b918596314b5993c18cad6faef28c793b51e51f0db4f3a5b6ee29f2a9","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":"2026-08-23T06:30:58.430688+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":"2026-08-07T11:27:01.890915Z","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":"2026-08-07T11:27:02.051986Z","state":"measured"}],"external_citation_measurements":[],"inbound":[{"citation":{"cited_paper":{"arxiv_id":"2202.13388","last_updated":"2022-11-29T14:16:05Z","snapshot_observed_at":"2026-08-16T17:18:19.353823Z","submitted_at":"2022-02-27T16:03:38Z","title":"PanoFlow: Learning 360{\\deg} Optical Flow for Surrounding Temporal Understanding","version":3},"cited_work":{"arxiv_id":"2202.13388","doi":null,"metadata_source":"pith","pith_arxiv_id":"2202.13388","snapshot_observed_at":"2026-08-07T11:27:02.051986Z","title":"PanoFlow: Learning 360{\\deg} Optical Flow for Surrounding Temporal Understanding","venue":"cs.CV","work_id":"78cd9262-be5f-43c8-966b-b2a79468ce1d","year":2022},"citing_paper":{"arxiv_id":"2506.14803","last_updated":"2025-06-03T05:59:21Z","snapshot_observed_at":"2026-08-16T01:35:12.734150Z","submitted_at":"2025-06-03T05:59:21Z","title":"Omnidirectional Video Super-Resolution using Deep Learning","version":1},"reference_index":31,"source":"pdf_text","source_observed_at":"2026-08-07T11:27:01.890915Z"},"links":{"cited_paper":"/paper/2202.13388","citing_paper":"/paper/2506.14803"},"observation_digest":"sha256:018872a918497b86431781642fa80aaa9d9bddcdc97f46d6d1e19858508fbf8c","observation_id":"f2b8682c-46fe-4c11-9176-69d2873d5e2c","resolution":{"observed_at":"2026-08-07T11:27:02.055447Z","resolver_source":"local_arxiv","status":"verified_exact"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-23T06:30:58.430688+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-23T06:30:58.430688+00:00","source":"crossref"},{"observed_at":"2026-08-23T06:30:53.778098+00:00","source":"retraction_watch"}],"state":"measured"}}],"links":{"evidence":"/evidence","html":"/paper/2202.13388/citation-record","integrity":"/paper/2202.13388/integrity","json":"/paper/2202.13388/citation-record.json","paper":"/paper/2202.13388"},"outbound":[],"paper":{"arxiv_id":"2202.13388","last_updated":"2022-11-29T14:16:05Z","latest_version":3,"primary_category":"cs.CV","snapshot_observed_at":"2026-08-16T17:18:19.353823Z","submitted_at":"2022-02-27T16:03:38Z","title":"PanoFlow: Learning 360{\\deg} Optical Flow for Surrounding Temporal Understanding"},"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":"2026-08-23T06:30:58.430688+00:00","source":"crossref"},{"observed_at":"2026-08-23T06:30:53.778098+00:00","source":"retraction_watch"}],"thesis":"As of 24 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 1 inbound Pith citation observation for arXiv:2202.13388."}