{"as_of":"2026-08-11T20:36:00Z","caps":{"database_statements":6,"inbound":100,"outbound":100},"context_digest":"sha256:bce570aad701bfaabc0392b467bf5b91e1cfb000ce48fc4987a4765018099453","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":4,"lane":"standing_notices","note":"One-hop event checks from named stored sources.","records_observed":4,"source":"scholarly_work_events, retraction_status_cache","source_observed_at":"2026-08-11T06:34:44.6726+00:00","state":"measured"},{"denominator":4,"lane":"inbound_itemization","note":"Pith citing papers itemized under the disclosed page cap.","records_observed":4,"source":"paper_references, paper_reference_links","source_observed_at":"2026-08-10T19:54:05.634114Z","state":"measured"},{"denominator":1,"lane":"external_citation_measurements","note":"A source-named dated measurement, never combined with another source.","records_observed":1,"source":"arxiv_reference","source_observed_at":"2026-08-05T02:28:24.338817Z","state":"measured"}],"external_citation_measurements":[{"count":46,"observed_at":"2026-08-05T02:28:24.338817Z","source":"arxiv_reference"}],"inbound":[{"citation":{"cited_paper":{"arxiv_id":"2101.09258","last_updated":"2021-10-21T00:06:11Z","snapshot_observed_at":"2026-08-11T17:48:14.000794Z","submitted_at":"2021-01-22T18:22:29Z","title":"Maximum Likelihood Training of Score-Based Diffusion Models","version":4},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2101.09258","snapshot_observed_at":"2026-08-10T19:54:05.634114Z","title":"Maximum likelihood training of score-based diffusion models, 2021 a","venue":null,"work_id":null,"year":2021},"citing_paper":{"arxiv_id":"2501.09659","last_updated":"2025-06-05T10:28:30Z","snapshot_observed_at":"2026-08-11T03:17:56.151122Z","submitted_at":"2025-01-16T16:54:40Z","title":"Fokker-Planck to Callan-Symanzik: evolution of weight matrices under training","version":2},"reference_index":40,"source":"arxiv_source","source_observed_at":"2026-08-10T19:54:05.634114Z"},"links":{"cited_paper":"/paper/2101.09258","citing_paper":"/paper/2501.09659"},"observation_digest":"sha256:53996d3529cece4b70b2d527de2aab8ccb1e32b3d7b8a7b0a090789026f6967a","observation_id":"258a19a6-42c3-48d1-a77d-364ab9256632","resolution":{"observed_at":"2026-08-10T19:54:05.634114Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2101.09258","last_updated":"2021-10-21T00:06:11Z","snapshot_observed_at":"2026-08-11T17:48:14.000794Z","submitted_at":"2021-01-22T18:22:29Z","title":"Maximum Likelihood Training of Score-Based Diffusion Models","version":4},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2101.09258","snapshot_observed_at":"2026-08-04T13:16:06.720996Z","title":null,"venue":null,"work_id":null,"year":null},"citing_paper":{"arxiv_id":"2510.01328","last_updated":"2025-10-01T18:00:34Z","snapshot_observed_at":"2026-08-06T11:35:15.530650Z","submitted_at":"2025-10-01T18:00:34Z","title":"Combining complex Langevin dynamics with score-based and energy-based diffusion models","version":1},"reference_index":41,"source":"pdf_text","source_observed_at":"2026-08-04T13:16:06.720996Z"},"links":{"cited_paper":"/paper/2101.09258","citing_paper":"/paper/2510.01328"},"observation_digest":"sha256:6de72a1cd7a86c1f996845d589515a318f191674527d02bb23b138c045a5523f","observation_id":"6223f5da-1571-483f-b6b8-ac2df0cf690d","resolution":{"observed_at":"2026-08-04T13:16:06.720996Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2101.09258","last_updated":"2021-10-21T00:06:11Z","snapshot_observed_at":"2026-08-11T17:48:14.000794Z","submitted_at":"2021-01-22T18:22:29Z","title":"Maximum Likelihood Training of Score-Based Diffusion Models","version":4},"cited_work":{"arxiv_id":"2101.09258","doi":"10.48550/arxiv.2101.09258","metadata_source":"arxiv_reference","pith_arxiv_id":"2101.09258","snapshot_observed_at":"2026-08-05T02:28:24.338817Z","title":"Sun, J., Liu, Y ., Zhang, Z., and Schaeffer, H","venue":"arXiv (Cornell University)","work_id":"adf503c1-c4ac-4ca2-b94b-aef11ae5f65e","year":null},"citing_paper":{"arxiv_id":"2602.11229","last_updated":"2026-05-06T20:12:38Z","snapshot_observed_at":"2026-08-11T07:19:31.817761Z","submitted_at":"2026-02-11T15:34:52Z","title":"Latent Generative Solvers for Generalizable Long-Term Physics Simulation","version":2},"reference_index":32,"source":"pdf_text","source_observed_at":"2026-05-16T05:21:13.280286Z"},"links":{"cited_paper":"/paper/2101.09258","citing_paper":"/paper/2602.11229"},"observation_digest":"sha256:ecc64b859a18c32e3fa43f726ffa96bff811cdc6c2bb8366f7420c9e97ee10cf","observation_id":"6cc12e8d-ee24-4316-97ae-8ea134b8676b","resolution":{"observed_at":"2026-05-16T05:22:22.594612Z","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"}},{"citation":{"cited_paper":{"arxiv_id":"2101.09258","last_updated":"2021-10-21T00:06:11Z","snapshot_observed_at":"2026-08-11T17:48:14.000794Z","submitted_at":"2021-01-22T18:22:29Z","title":"Maximum Likelihood Training of Score-Based Diffusion Models","version":4},"cited_work":{"arxiv_id":"2101.09258","doi":"10.48550/arxiv.2101.09258","metadata_source":"arxiv_reference","pith_arxiv_id":"2101.09258","snapshot_observed_at":"2026-08-05T02:28:24.338817Z","title":"Sun, J., Liu, Y ., Zhang, Z., and Schaeffer, H","venue":"arXiv (Cornell University)","work_id":"adf503c1-c4ac-4ca2-b94b-aef11ae5f65e","year":null},"citing_paper":{"arxiv_id":"2605.07907","last_updated":"2026-05-08T15:45:34Z","snapshot_observed_at":"2026-08-11T10:10:11.685526Z","submitted_at":"2026-05-08T15:45:34Z","title":"Consistency Regularised Gradient Flows for Inverse Problems","version":1},"reference_index":60,"source":"arxiv_source","source_observed_at":"2026-05-11T03:21:35.082352Z"},"links":{"cited_paper":"/paper/2101.09258","citing_paper":"/paper/2605.07907"},"observation_digest":"sha256:6876a8824e38aa76101f3954b51b728e427a0bb4eb7a3e40c7f54560a9b8badc","observation_id":"2069f56d-aaef-4701-a4fa-b1dde4dad45f","resolution":{"observed_at":"2026-05-11T03:25:55.016431Z","resolver_source":"arxiv_id","status":"metadata_mismatch"},"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/2101.09258/citation-record","integrity":"/paper/2101.09258/integrity","json":"/paper/2101.09258/citation-record.json","paper":"/paper/2101.09258"},"outbound":[],"paper":{"arxiv_id":"2101.09258","last_updated":"2021-10-21T00:06:11Z","latest_version":4,"primary_category":"stat.ML","snapshot_observed_at":"2026-08-11T17:48:14.000794Z","submitted_at":"2021-01-22T18:22:29Z","title":"Maximum Likelihood Training of Score-Based Diffusion Models"},"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 4 inbound Pith citation observations for arXiv:2101.09258."}