{"as_of":"2026-08-11T15:36:00Z","caps":{"database_statements":6,"inbound":100,"outbound":100},"context_digest":"sha256:b43a55b69f19cb4132d49f2fba28eb4324b58f48b9588663db683372e56947a7","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":"2026-08-11T06:34:44.6726+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":"2026-08-10T21:49:09.544095Z","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":"2026-05-23T02:55:19.670152Z","state":"measured"}],"external_citation_measurements":[],"inbound":[{"citation":{"cited_paper":{"arxiv_id":"2207.00493","last_updated":"2022-07-01T15:28:58Z","snapshot_observed_at":"2026-08-04T22:33:15.644259Z","submitted_at":"2022-07-01T15:28:58Z","title":"Simulating financial time series using attention","version":1},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2207.00493","snapshot_observed_at":"2026-08-10T21:49:09.544095Z","title":null,"venue":null,"work_id":null,"year":2022},"citing_paper":{"arxiv_id":"2501.03993","last_updated":"2026-07-18T12:33:41Z","snapshot_observed_at":"2026-08-11T15:30:39.651948Z","submitted_at":"2025-01-07T18:50:24Z","title":"Synthetic Data for Portfolios: A Throw of the Dice Will Never Abolish Chance","version":6},"reference_index":46,"source":"arxiv_source","source_observed_at":"2026-08-10T21:49:09.544095Z"},"links":{"cited_paper":"/paper/2207.00493","citing_paper":"/paper/2501.03993"},"observation_digest":"sha256:d2c7f8f904b4b950d0eea984c090afc1a25b947bc2496eaecdaec32c4fab0ec9","observation_id":"4ddb26bf-2dee-4e4d-a0b5-754dd6cabc32","resolution":{"observed_at":"2026-08-10T21:49:09.544095Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2207.00493","last_updated":"2022-07-01T15:28:58Z","snapshot_observed_at":"2026-08-04T22:33:15.644259Z","submitted_at":"2022-07-01T15:28:58Z","title":"Simulating financial time series using attention","version":1},"cited_work":{"arxiv_id":"2207.00493","doi":null,"metadata_source":"arxiv_reference","pith_arxiv_id":"2207.00493","snapshot_observed_at":"2026-06-05T21:23:00.469572Z","title":null,"venue":null,"work_id":"2a7bb9b0-a429-4d63-9f9f-9979a159b17a","year":2022},"citing_paper":{"arxiv_id":"2502.17011","last_updated":"2026-04-24T06:19:27Z","snapshot_observed_at":"2026-07-06T20:41:33.347753Z","submitted_at":"2025-02-24T09:46:37Z","title":"Predicting Liquidity-Aware Bond Yields using Causal GANs and Deep Reinforcement Learning with LLM Evaluation","version":2},"reference_index":8,"source":"arxiv_source","source_observed_at":"2026-05-23T02:54:08.887874Z"},"links":{"cited_paper":"/paper/2207.00493","citing_paper":"/paper/2502.17011"},"observation_digest":"sha256:cf619b36aecf8e40e6df3a915aba637490fa8331d359444dc14637ee7116b325","observation_id":"e261e36d-10a2-4e6d-98ac-e6b8ca66c99a","resolution":{"observed_at":"2026-05-23T02:55:19.672779Z","resolver_source":"arxiv_id","status":"verified_exact"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-11T06:34:44.6726+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-11T06:34:44.6726+00:00","source":"crossref"},{"observed_at":"2026-08-11T06:34:36.301508+00:00","source":"retraction_watch"}],"state":"measured"}}],"links":{"evidence":"/evidence","html":"/paper/2207.00493/citation-record","integrity":"/paper/2207.00493/integrity","json":"/paper/2207.00493/citation-record.json","paper":"/paper/2207.00493"},"outbound":[],"paper":{"arxiv_id":"2207.00493","last_updated":"2022-07-01T15:28:58Z","latest_version":1,"primary_category":"q-fin.ST","snapshot_observed_at":"2026-08-04T22:33:15.644259Z","submitted_at":"2022-07-01T15:28:58Z","title":"Simulating financial time series using attention"},"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":"2026-08-11T06:34:44.6726+00:00","source":"crossref"},{"observed_at":"2026-08-11T06:34:36.301508+00:00","source":"retraction_watch"}],"thesis":"As of 11 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 2 inbound Pith citation observations for arXiv:2207.00493."}