{"as_of":"2026-08-07T20:55:00Z","caps":{"database_statements":6,"inbound":100,"outbound":100},"context_digest":"sha256:70fc5d1f1e28b8dce779590f6e55370149355b3e09e461c5e7a040238159f823","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":6,"lane":"standing_notices","note":"One-hop event checks from named stored sources.","records_observed":6,"source":"scholarly_work_events, retraction_status_cache","source_observed_at":"2026-08-07T06:34:17.273281+00:00","state":"measured"},{"denominator":6,"lane":"inbound_itemization","note":"Pith citing papers itemized under the disclosed page cap.","records_observed":6,"source":"paper_references, paper_reference_links","source_observed_at":"2026-08-04T16:39:59.495180Z","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":"2026-05-17T05:44:07.331652Z","state":"measured"}],"external_citation_measurements":[],"inbound":[{"citation":{"cited_paper":{"arxiv_id":"2101.12072","last_updated":"2021-02-02T12:32:30Z","snapshot_observed_at":"2026-08-07T01:30:33.258981Z","submitted_at":"2021-01-28T15:46:10Z","title":"Autoregressive Denoising Diffusion Models for Multivariate Probabilistic Time Series Forecasting","version":2},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2101.12072","snapshot_observed_at":"2026-08-04T16:39:59.495180Z","title":null,"venue":null,"work_id":null,"year":null},"citing_paper":{"arxiv_id":"2509.13374","last_updated":"2026-08-02T17:28:24Z","snapshot_observed_at":"2026-08-06T23:23:56.446413Z","submitted_at":"2025-09-16T06:00:43Z","title":"Conditional Deep Levy Models for Exotic Derivatives: History-Aware Path Generation and P-Q Payoff Diagnostics","version":2},"reference_index":19,"source":"pdf_text","source_observed_at":"2026-08-04T16:39:59.495180Z"},"links":{"cited_paper":"/paper/2101.12072","citing_paper":"/paper/2509.13374"},"observation_digest":"sha256:37d2fa1dd57cc405d6d61baecacf1f2437d631d50c6eaf9090fc77e099a4284d","observation_id":"976928e4-fa54-43d8-8750-53088cbd5144","resolution":{"observed_at":"2026-08-04T16:39:59.495180Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2101.12072","last_updated":"2021-02-02T12:32:30Z","snapshot_observed_at":"2026-08-07T01:30:33.258981Z","submitted_at":"2021-01-28T15:46:10Z","title":"Autoregressive Denoising Diffusion Models for Multivariate Probabilistic Time Series Forecasting","version":2},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2101.12072","snapshot_observed_at":"2026-08-04T10:13:19.945980Z","title":"Autoregressive denoising diffusion models for multivariate probabilistic time series forecasting,","venue":null,"work_id":null,"year":2021},"citing_paper":{"arxiv_id":"2510.11214","last_updated":"2026-07-29T13:48:59Z","snapshot_observed_at":"2026-08-06T21:51:21.107646Z","submitted_at":"2025-10-13T09:50:51Z","title":"CSI Prediction Using Diffusion Models","version":2},"reference_index":16,"source":"pdf_text","source_observed_at":"2026-08-04T10:13:19.945980Z"},"links":{"cited_paper":"/paper/2101.12072","citing_paper":"/paper/2510.11214"},"observation_digest":"sha256:442985b3b03787436cd10f3aabac98e2e7d87b073f359173840f2c0397be3407","observation_id":"884100ef-83b0-4cfb-a1c2-2aade4c0325f","resolution":{"observed_at":"2026-08-04T10:13:19.945980Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2101.12072","last_updated":"2021-02-02T12:32:30Z","snapshot_observed_at":"2026-08-07T01:30:33.258981Z","submitted_at":"2021-01-28T15:46:10Z","title":"Autoregressive Denoising Diffusion Models for Multivariate Probabilistic Time Series Forecasting","version":2},"cited_work":{"arxiv_id":"2101.12072","doi":null,"metadata_source":"arxiv_reference","pith_arxiv_id":"2101.12072","snapshot_observed_at":"2026-06-05T21:23:00.469572Z","title":"Autoregressive denoising diffusion models for multivariate probabilistic time series forecasting.CoRR, abs/2101.12072","venue":null,"work_id":"8f120a0e-67eb-470f-9b03-39b73cf94b79","year":2021},"citing_paper":{"arxiv_id":"2511.18539","last_updated":"2026-04-23T05:21:00Z","snapshot_observed_at":"2026-08-01T01:15:05.827466Z","submitted_at":"2025-11-23T17:10:07Z","title":"TimePre: Bridging Accuracy, Efficiency, and Stability in Probabilistic Time-Series Forecasting","version":2},"reference_index":50,"source":"pdf_text","source_observed_at":"2026-05-17T05:42:45.075521Z"},"links":{"cited_paper":"/paper/2101.12072","citing_paper":"/paper/2511.18539"},"observation_digest":"sha256:b4027e9ae9b06df3231ca1b4ec4b65be522e682d82b8b9609ccaabba7f99b343","observation_id":"6a79f625-4000-4f32-8f5b-89f2286938a4","resolution":{"observed_at":"2026-05-17T05:44:07.334699Z","resolver_source":"arxiv_id","status":"verified_exact"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-07T06:34:17.273281+00:00","source":"crossref"},{"observed_at":"2026-08-07T06:34:11.927384+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"2101.12072","last_updated":"2021-02-02T12:32:30Z","snapshot_observed_at":"2026-08-07T01:30:33.258981Z","submitted_at":"2021-01-28T15:46:10Z","title":"Autoregressive Denoising Diffusion Models for Multivariate Probabilistic Time Series Forecasting","version":2},"cited_work":{"arxiv_id":"2101.12072","doi":null,"metadata_source":"arxiv_reference","pith_arxiv_id":"2101.12072","snapshot_observed_at":"2026-06-05T21:23:00.469572Z","title":"Autoregressive denoising diffusion models for multivariate probabilistic time series forecasting.CoRR, abs/2101.12072","venue":null,"work_id":"8f120a0e-67eb-470f-9b03-39b73cf94b79","year":2021},"citing_paper":{"arxiv_id":"2512.23748","last_updated":"2026-04-14T19:54:35Z","snapshot_observed_at":"2026-08-03T02:33:30.910059Z","submitted_at":"2025-12-26T18:18:25Z","title":"A Review of Diffusion-based Simulation-Based Inference: Foundations and Applications in Non-Ideal Data Scenarios","version":2},"reference_index":71,"source":"pdf_text","source_observed_at":"2026-05-16T18:57:06.742017Z"},"links":{"cited_paper":"/paper/2101.12072","citing_paper":"/paper/2512.23748"},"observation_digest":"sha256:f78e9186e1de0e3fa3e9dd7966ab1a9faeb7cd8433951eb86be9bba3cfc44977","observation_id":"bbcf7734-c141-4b3a-9bca-03732730eedc","resolution":{"observed_at":"2026-05-16T18:58:18.886375Z","resolver_source":"arxiv_id","status":"metadata_mismatch"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-07T06:34:17.273281+00:00","source":"crossref"},{"observed_at":"2026-08-07T06:34:11.927384+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"2101.12072","last_updated":"2021-02-02T12:32:30Z","snapshot_observed_at":"2026-08-07T01:30:33.258981Z","submitted_at":"2021-01-28T15:46:10Z","title":"Autoregressive Denoising Diffusion Models for Multivariate Probabilistic Time Series Forecasting","version":2},"cited_work":{"arxiv_id":"2101.12072","doi":null,"metadata_source":"arxiv_reference","pith_arxiv_id":"2101.12072","snapshot_observed_at":"2026-06-05T21:23:00.469572Z","title":"Autoregressive denoising diffusion models for multivariate probabilistic time series forecasting.CoRR, abs/2101.12072","venue":null,"work_id":"8f120a0e-67eb-470f-9b03-39b73cf94b79","year":2021},"citing_paper":{"arxiv_id":"2603.28253","last_updated":"2026-04-08T03:27:07Z","snapshot_observed_at":"2026-07-06T22:51:05.074191Z","submitted_at":"2026-03-30T10:25:35Z","title":"MR-ImagenTime: Multi-Resolution Time Series Generation through Dual Image Representations","version":2},"reference_index":15,"source":"pdf_text","source_observed_at":"2026-05-14T21:16:39.851664Z"},"links":{"cited_paper":"/paper/2101.12072","citing_paper":"/paper/2603.28253"},"observation_digest":"sha256:774c65d3dc670f636b9ca9dacbbe961ff56a1ede731823f4d219f0510bc1f2d9","observation_id":"7116e1ee-27e8-4de3-b2b6-634203588730","resolution":{"observed_at":"2026-05-14T21:17:58.942507Z","resolver_source":"arxiv_id","status":"metadata_mismatch"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-07T06:34:17.273281+00:00","source":"crossref"},{"observed_at":"2026-08-07T06:34:11.927384+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"2101.12072","last_updated":"2021-02-02T12:32:30Z","snapshot_observed_at":"2026-08-07T01:30:33.258981Z","submitted_at":"2021-01-28T15:46:10Z","title":"Autoregressive Denoising Diffusion Models for Multivariate Probabilistic Time Series Forecasting","version":2},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2101.12072","snapshot_observed_at":"2026-08-02T06:58:55.038172Z","title":"Autoregressive denoising diffusion models for multivariate probabilistic time series forecasting, 2021","venue":null,"work_id":null,"year":2021},"citing_paper":{"arxiv_id":"2607.20545","last_updated":"2026-07-13T09:57:04Z","snapshot_observed_at":"2026-08-06T23:40:47.437511Z","submitted_at":"2026-07-13T09:57:04Z","title":"StrideDiffusion: Accelerating Diffusion Models for Time-series Generation","version":1},"reference_index":17,"source":"pdf_text","source_observed_at":"2026-08-02T06:58:55.038172Z"},"links":{"cited_paper":"/paper/2101.12072","citing_paper":"/paper/2607.20545"},"observation_digest":"sha256:ceac4d6e52dd038c0d1a15dc944697d0931f1269ee8e0ad4957369a1786b9d48","observation_id":"638567e5-b69c-42fe-a76c-4cc9408643a0","resolution":{"observed_at":"2026-08-02T06:58:55.038172Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}}],"links":{"evidence":"/evidence","html":"/paper/2101.12072/citation-record","integrity":"/paper/2101.12072/integrity","json":"/paper/2101.12072/citation-record.json","paper":"/paper/2101.12072"},"outbound":[],"paper":{"arxiv_id":"2101.12072","last_updated":"2021-02-02T12:32:30Z","latest_version":2,"primary_category":"cs.LG","snapshot_observed_at":"2026-08-07T01:30:33.258981Z","submitted_at":"2021-01-28T15:46:10Z","title":"Autoregressive Denoising Diffusion Models for Multivariate Probabilistic Time Series Forecasting"},"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":"2026-08-07T06:34:17.273281+00:00","source":"crossref"},{"observed_at":"2026-08-07T06:34:11.927384+00:00","source":"retraction_watch"}],"thesis":"As of 7 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 6 inbound Pith citation observations for arXiv:2101.12072."}