{"as_of":"2026-07-27T16:07:00Z","caps":{"database_statements":6,"inbound":100,"outbound":100},"context_digest":"sha256:c1e81f0b7a05030c5bc5ee7ffe7cc22a008bc20ac686e3cbff5e4bb9aec82f78","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":"2026-07-27T06:30:09.085275+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":"2026-05-18T03:30:22.025578Z","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":"2026-05-18T03:30:22.312229Z","state":"measured"}],"external_citation_measurements":[],"inbound":[{"citation":{"cited_paper":{"arxiv_id":"2205.13554","last_updated":"2022-10-24T08:39:05Z","snapshot_observed_at":"2026-07-06T13:14:26.331614Z","submitted_at":"2022-05-26T18:00:02Z","title":"Training and Inference on Any-Order Autoregressive Models the Right Way","version":2},"cited_work":{"arxiv_id":"2205.13554","doi":null,"metadata_source":"arxiv_reference","pith_arxiv_id":"2205.13554","snapshot_observed_at":"2026-06-05T21:23:00.469572Z","title":null,"venue":null,"work_id":"e7c9c076-0450-40fb-a1e9-93d8b7385f4a","year":2022},"citing_paper":{"arxiv_id":"2211.15089","last_updated":"2022-12-15T14:27:19Z","snapshot_observed_at":"2026-07-06T14:23:43.235725Z","submitted_at":"2022-11-28T06:08:54Z","title":"Continuous diffusion for categorical data","version":3},"reference_index":78,"source":"arxiv_source","source_observed_at":"2026-05-18T03:30:22.025578Z"},"links":{"cited_paper":"/paper/2205.13554","citing_paper":"/paper/2211.15089"},"observation_digest":"sha256:a50fb49c0a469224ccb466e881c5162c21653a8de6ed9df75ec1dbf339693333","observation_id":"dc42792e-9651-44ca-a868-0e0b2695c52e","resolution":{"observed_at":"2026-05-18T03:30:22.315157Z","resolver_source":"arxiv_id","status":"verified_exact"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-07-27T06:30:09.085275+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-07-27T06:30:09.085275+00:00","source":"crossref"},{"observed_at":"2026-07-27T06:30:01.563335+00:00","source":"retraction_watch"}],"state":"measured"}}],"links":{"evidence":"/evidence","html":"/paper/2205.13554/citation-record","integrity":"/paper/2205.13554/integrity","json":"/paper/2205.13554/citation-record.json","paper":"/paper/2205.13554"},"outbound":[],"paper":{"arxiv_id":"2205.13554","last_updated":"2022-10-24T08:39:05Z","latest_version":2,"primary_category":"cs.LG","snapshot_observed_at":"2026-07-06T13:14:26.331614Z","submitted_at":"2022-05-26T18:00:02Z","title":"Training and Inference on Any-Order Autoregressive Models the Right Way"},"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":"2026-07-27T06:30:09.085275+00:00","source":"crossref"},{"observed_at":"2026-07-27T06:30:01.563335+00:00","source":"retraction_watch"}],"thesis":"As of 27 July 2026, this Paper Citation Record lists 0 of 0 outbound references and 1 inbound Pith citation observation for arXiv:2205.13554."}