{"as_of":"2026-08-21T11:51:00Z","caps":{"database_statements":6,"inbound":100,"outbound":100},"context_digest":"sha256:1bf20adb665bbe34859234d2624208ca4d5eadb17a186abef16d8d531da4553b","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":"2026-08-21T06:32:19.484+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":"2026-06-30T21:25:08.141052Z","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":"2026-06-30T21:35:05.245909Z","state":"measured"}],"external_citation_measurements":[],"inbound":[{"citation":{"cited_paper":{"arxiv_id":"2210.08793","last_updated":"2022-10-17T07:16:44Z","snapshot_observed_at":"2026-08-19T19:10:42.199933Z","submitted_at":"2022-10-17T07:16:44Z","title":"Rethinking Trajectory Prediction via \"Team Game\"","version":1},"cited_work":{"arxiv_id":"2210.08793","doi":null,"metadata_source":"arxiv_reference","pith_arxiv_id":"2210.08793","snapshot_observed_at":"2026-06-30T21:35:05.245909Z","title":"Rethinking Trajectory Prediction via Team Game,","venue":null,"work_id":"691423de-0ca6-439f-8fcd-3f4f980aa400","year":2022},"citing_paper":{"arxiv_id":"2605.14855","last_updated":"2026-05-14T14:02:45Z","snapshot_observed_at":"2026-08-17T03:25:20.012992Z","submitted_at":"2026-05-14T14:02:45Z","title":"Exploitation of Hidden Context in Dynamic Movement Forecasting: A Neural Network Journey from Recurrent to Graph Neural Networks and General Purpose Transformers","version":1},"reference_index":12,"source":"pdf_text","source_observed_at":"2026-06-30T21:25:08.141052Z"},"links":{"cited_paper":"/paper/2210.08793","citing_paper":"/paper/2605.14855"},"observation_digest":"sha256:e0034e0aa50e8a6486727f7124dacd2286f866ee2fa57dd3c1767dc241161846","observation_id":"ad6d0a0b-819d-4903-b484-08b963efdf48","resolution":{"observed_at":"2026-06-30T21:35:05.247851Z","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/2210.08793/citation-record","integrity":"/paper/2210.08793/integrity","json":"/paper/2210.08793/citation-record.json","paper":"/paper/2210.08793"},"outbound":[],"paper":{"arxiv_id":"2210.08793","last_updated":"2022-10-17T07:16:44Z","latest_version":1,"primary_category":"cs.CV","snapshot_observed_at":"2026-08-19T19:10:42.199933Z","submitted_at":"2022-10-17T07:16:44Z","title":"Rethinking Trajectory Prediction via \"Team Game\""},"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 1 inbound Pith citation observation for arXiv:2210.08793."}