{"as_of":"2026-08-10T08:25:00Z","caps":{"database_statements":6,"inbound":100,"outbound":100},"context_digest":"sha256:dd40b48ef1d281ba96554dc2c4bd7711452a649c15988c2bb61f1b8068a9e495","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":3,"lane":"standing_notices","note":"One-hop event checks from named stored sources.","records_observed":3,"source":"scholarly_work_events, retraction_status_cache","source_observed_at":"2026-08-10T06:31:04.303077+00:00","state":"measured"},{"denominator":3,"lane":"inbound_itemization","note":"Pith citing papers itemized under the disclosed page cap.","records_observed":3,"source":"paper_references, paper_reference_links","source_observed_at":"2026-08-07T13:32:48.042452Z","state":"measured"},{"denominator":1,"lane":"external_citation_measurements","note":"A source-named dated measurement, never combined with another source.","records_observed":0,"source":"pith","source_observed_at":"2026-08-06T18:05:55.361868Z","state":"measured"}],"external_citation_measurements":[],"inbound":[{"citation":{"cited_paper":{"arxiv_id":"2302.03018","last_updated":"2023-02-06T18:56:39Z","snapshot_observed_at":"2026-08-05T14:29:55.368812Z","submitted_at":"2023-02-06T18:56:39Z","title":"DDM$^2$: Self-Supervised Diffusion MRI Denoising with Generative Diffusion Models","version":1},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2302.03018","snapshot_observed_at":"2026-08-07T13:32:48.042452Z","title":"Ddm ˆ2: Self- supervised diffusion mri denoising with generative diffusion models.arXiv preprint arXiv:2302.03018, 2023","venue":null,"work_id":null,"year":2023},"citing_paper":{"arxiv_id":"2505.21742","last_updated":"2025-05-27T20:32:28Z","snapshot_observed_at":"2026-08-07T13:21:41.109845Z","submitted_at":"2025-05-27T20:32:28Z","title":"What is Adversarial Training for Diffusion Models?","version":1},"reference_index":63,"source":"pdf_text","source_observed_at":"2026-08-07T13:32:48.042452Z"},"links":{"cited_paper":"/paper/2302.03018","citing_paper":"/paper/2505.21742"},"observation_digest":"sha256:15aa2edeabb1aed64c929eba28f729075506e069d1903423c56c08cf57e74174","observation_id":"12573fee-9605-469a-9dd6-525625f6e748","resolution":{"observed_at":"2026-08-07T13:32:48.042452Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2302.03018","last_updated":"2023-02-06T18:56:39Z","snapshot_observed_at":"2026-08-05T14:29:55.368812Z","submitted_at":"2023-02-06T18:56:39Z","title":"DDM$^2$: Self-Supervised Diffusion MRI Denoising with Generative Diffusion Models","version":1},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2302.03018","snapshot_observed_at":"2026-08-06T21:52:25.090070Z","title":"arXiv preprint arXiv:2302.03018 (2023)","venue":null,"work_id":null,"year":2023},"citing_paper":{"arxiv_id":"2506.23184","last_updated":"2025-06-29T11:02:45Z","snapshot_observed_at":"2026-08-09T05:30:23.870174Z","submitted_at":"2025-06-29T11:02:45Z","title":"Score-based Diffusion Model for Unpaired Virtual Histology Staining","version":1},"reference_index":25,"source":"pdf_text","source_observed_at":"2026-08-06T21:52:25.090070Z"},"links":{"cited_paper":"/paper/2302.03018","citing_paper":"/paper/2506.23184"},"observation_digest":"sha256:451cc0eecf8ae75c62c3145ce27faf093c294b021ec874d735f2c49c9437e864","observation_id":"dbc3a4b9-128e-4781-aab8-7b33bc37644b","resolution":{"observed_at":"2026-08-06T21:52:25.090070Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2302.03018","last_updated":"2023-02-06T18:56:39Z","snapshot_observed_at":"2026-08-05T14:29:55.368812Z","submitted_at":"2023-02-06T18:56:39Z","title":"DDM$^2$: Self-Supervised Diffusion MRI Denoising with Generative Diffusion Models","version":1},"cited_work":{"arxiv_id":"2302.03018","doi":null,"metadata_source":"pith","pith_arxiv_id":"2302.03018","snapshot_observed_at":"2026-08-06T18:05:55.361868Z","title":"DDM$^2$: Self-Supervised Diffusion MRI Denoising with Generative Diffusion Models","venue":"eess.IV","work_id":"901cf1ec-4269-44be-8f36-a999f860e5b8","year":2023},"citing_paper":{"arxiv_id":"2507.09230","last_updated":"2025-07-12T09:59:31Z","snapshot_observed_at":"2026-08-08T23:17:10.616344Z","submitted_at":"2025-07-12T09:59:31Z","title":"EgoAnimate: Generating Human Animations from Egocentric top-down Views","version":1},"reference_index":83,"source":"pdf_text","source_observed_at":"2026-08-06T18:05:54.203716Z"},"links":{"cited_paper":"/paper/2302.03018","citing_paper":"/paper/2507.09230"},"observation_digest":"sha256:2ccb1b4bb215e03013490a7ae8fc77146841d87dcd5e31fe42ed45a11add2333","observation_id":"556de8b7-6eaa-4983-bb28-52517a264c55","resolution":{"observed_at":"2026-08-06T18:05:55.400751Z","resolver_source":"local_arxiv","status":"metadata_mismatch"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-10T06:31:04.303077+00:00","source":"crossref"},{"observed_at":"2026-08-10T06:30:57.382061+00:00","source":"retraction_watch"}],"state":"measured"}}],"links":{"evidence":"/evidence","html":"/paper/2302.03018/citation-record","integrity":"/paper/2302.03018/integrity","json":"/paper/2302.03018/citation-record.json","paper":"/paper/2302.03018"},"outbound":[],"paper":{"arxiv_id":"2302.03018","last_updated":"2023-02-06T18:56:39Z","latest_version":1,"primary_category":"eess.IV","snapshot_observed_at":"2026-08-05T14:29:55.368812Z","submitted_at":"2023-02-06T18:56:39Z","title":"DDM$^2$: Self-Supervised Diffusion MRI Denoising with Generative 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":"2026-08-10T06:31:04.303077+00:00","source":"crossref"},{"observed_at":"2026-08-10T06:30:57.382061+00:00","source":"retraction_watch"}],"thesis":"As of 10 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 3 inbound Pith citation observations for arXiv:2302.03018."}