{"as_of":"2026-08-19T19:49:00Z","caps":{"database_statements":6,"inbound":100,"outbound":100},"context_digest":"sha256:86a13f454027d9e5114eabb135d5650d209396d0b1494ed26b0729d2453b55ac","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":"2026-08-19T06:32:44.657259+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":"2026-08-15T20:58:56.171577Z","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":"2026-05-12T06:36:26.505003Z","state":"measured"}],"external_citation_measurements":[],"inbound":[{"citation":{"cited_paper":{"arxiv_id":"2503.06132","last_updated":"2025-07-22T00:51:02Z","snapshot_observed_at":"2026-08-19T18:41:37.620486Z","submitted_at":"2025-03-08T09:01:03Z","title":"USP: Unified Self-Supervised Pretraining for Image Generation and Understanding","version":3},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2503.06132","snapshot_observed_at":"2026-08-15T20:58:56.171577Z","title":"Usp: Unified self-supervised pretraining for image generation and understanding","venue":null,"work_id":null,"year":2025},"citing_paper":{"arxiv_id":"2505.11306","last_updated":"2025-05-16T14:32:34Z","snapshot_observed_at":"2026-08-17T22:06:55.361153Z","submitted_at":"2025-05-16T14:32:34Z","title":"Effective Probabilistic Time Series Forecasting with Fourier Adaptive Noise-Separated Diffusion","version":1},"reference_index":16,"source":"pdf_text","source_observed_at":"2026-08-15T20:58:56.171577Z"},"links":{"cited_paper":"/paper/2503.06132","citing_paper":"/paper/2505.11306"},"observation_digest":"sha256:a06bdf9679f08e250cc1c95206ba168efece9d9bc730cd7ed54b312cdd5afd95","observation_id":"0c186524-2e2d-4b84-bbc2-9294c4108528","resolution":{"observed_at":"2026-08-15T20:58:56.171577Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2503.06132","last_updated":"2025-07-22T00:51:02Z","snapshot_observed_at":"2026-08-19T18:41:37.620486Z","submitted_at":"2025-03-08T09:01:03Z","title":"USP: Unified Self-Supervised Pretraining for Image Generation and Understanding","version":3},"cited_work":{"arxiv_id":"2503.06132","doi":null,"metadata_source":"arxiv_reference","pith_arxiv_id":"2503.06132","snapshot_observed_at":"2026-06-05T21:23:00.469572Z","title":"Usp: Unified self-supervised pretraining for image generation and understanding","venue":null,"work_id":"05623020-b60c-45ff-a019-bec3e39c94cc","year":2025},"citing_paper":{"arxiv_id":"2605.10790","last_updated":"2026-05-11T16:21:45Z","snapshot_observed_at":"2026-08-16T03:31:11.715054Z","submitted_at":"2026-05-11T16:21:45Z","title":"Elucidating Representation Degradation Problem in Diffusion Model Training","version":1},"reference_index":4,"source":"pdf_text","source_observed_at":"2026-05-12T04:08:11.110912Z"},"links":{"cited_paper":"/paper/2503.06132","citing_paper":"/paper/2605.10790"},"observation_digest":"sha256:13d3d4fc348b07e3fa781b492a8a1d14bd66347dbbb432418d64e2f218b90ab4","observation_id":"0c4bd243-b568-4713-85f8-50dc1a6ebeb3","resolution":{"observed_at":"2026-05-12T06:36:26.512693Z","resolver_source":"arxiv_id","status":"verified_exact"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-19T06:32:44.657259+00:00","source":"crossref"},{"observed_at":"2026-08-19T06:32:39.956319+00:00","source":"retraction_watch"}],"state":"measured"}}],"links":{"evidence":"/evidence","html":"/paper/2503.06132/citation-record","integrity":"/paper/2503.06132/integrity","json":"/paper/2503.06132/citation-record.json","paper":"/paper/2503.06132"},"outbound":[],"paper":{"arxiv_id":"2503.06132","last_updated":"2025-07-22T00:51:02Z","latest_version":3,"primary_category":"cs.CV","snapshot_observed_at":"2026-08-19T18:41:37.620486Z","submitted_at":"2025-03-08T09:01:03Z","title":"USP: Unified Self-Supervised Pretraining for Image Generation and 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":"2026-08-19T06:32:44.657259+00:00","source":"crossref"},{"observed_at":"2026-08-19T06:32:39.956319+00:00","source":"retraction_watch"}],"thesis":"As of 19 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 2 inbound Pith citation observations for arXiv:2503.06132."}