{"as_of":"2026-08-15T01:42:00Z","caps":{"database_statements":6,"inbound":100,"outbound":100},"context_digest":"sha256:08f196dfc246331a867a10bd79ae8063f02f01c94360d2e496c9b126d02ba23e","coverage":[{"denominator":17,"lane":"reference_resolution","note":"Typed states for the displayed outbound observations.","records_observed":17,"source":"paper_references, paper_reference_links","source_observed_at":"2026-08-10T22:02:04.349179Z","state":"measured"},{"denominator":18,"lane":"standing_notices","note":"One-hop event checks from named stored sources.","records_observed":18,"source":"scholarly_work_events, retraction_status_cache","source_observed_at":"2026-08-14T06:32:32.682623+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":"2026-08-11T16:34:49.429660Z","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":"2026-08-11T16:34:49.665302Z","state":"measured"}],"external_citation_measurements":[],"inbound":[{"citation":{"cited_paper":{"arxiv_id":"2501.03430","last_updated":"2025-01-06T23:23:24Z","snapshot_observed_at":"2026-08-13T04:17:31.132584Z","submitted_at":"2025-01-06T23:23:24Z","title":"A Self-supervised Diffusion Bridge for MRI Reconstruction","version":1},"cited_work":{"arxiv_id":"2501.03430","doi":null,"metadata_source":"pith","pith_arxiv_id":"2501.03430","snapshot_observed_at":"2026-08-11T16:34:49.665302Z","title":"A Self-supervised Diffusion Bridge for MRI Reconstruction","venue":"eess.IV","work_id":"067767dd-8a95-4ec4-8422-13a555572512","year":2025},"citing_paper":{"arxiv_id":"2412.09998","last_updated":"2025-04-28T02:56:06Z","snapshot_observed_at":"2026-08-11T16:25:28.170177Z","submitted_at":"2024-12-13T09:35:34Z","title":"Self-Consistent Nested Diffusion Bridge for Accelerated MRI Reconstruction","version":2},"reference_index":2025,"source":"pdf_text","source_observed_at":"2026-08-11T16:34:49.429660Z"},"links":{"cited_paper":"/paper/2501.03430","citing_paper":"/paper/2412.09998"},"observation_digest":"sha256:89cb423c4ccc32b0d95b61603285136b093ca465ebb9b972eec001daa582f36e","observation_id":"2bb733df-04ba-4e32-8aee-7a12e573cd7c","resolution":{"observed_at":"2026-08-11T16:34:49.671838Z","resolver_source":"local_arxiv","status":"metadata_mismatch"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-14T06:32:32.682623+00:00","source":"crossref"},{"observed_at":"2026-08-14T06:32:18.44784+00:00","source":"retraction_watch"}],"state":"measured"}}],"links":{"evidence":"/evidence","html":"/paper/2501.03430/citation-record","integrity":"/paper/2501.03430/integrity","json":"/paper/2501.03430/citation-record.json","paper":"/paper/2501.03430"},"outbound":[{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-10T22:02:04.615744Z","title":"Sparse MRI: The application of compressed sensing for rapid MR imaging,","venue":null,"work_id":"44ef76c1-c033-4b13-8d66-3a57e67d4b98","year":2007},"citing_paper":{"arxiv_id":"2501.03430","last_updated":"2025-01-06T23:23:24Z","snapshot_observed_at":"2026-08-13T04:17:31.132584Z","submitted_at":"2025-01-06T23:23:24Z","title":"A Self-supervised Diffusion Bridge for MRI Reconstruction","version":1},"reference_index":1,"source":"pdf_text","source_observed_at":"2026-08-10T22:02:04.266237Z"},"links":{"citing_paper":"/paper/2501.03430"},"observation_digest":"sha256:f700d248c658f8500ff09a122dc0383133911d52b42d0a1c7f406f93072a73e1","observation_id":"28f6d09b-4a5c-4636-8915-5bba4617a3ce","resolution":{"observed_at":"2026-08-10T22:02:04.620158Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-14T06:32:32.682623+00:00","source":"crossref"},{"observed_at":"2026-08-14T06:32:18.44784+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-10T22:02:04.602519Z","title":"Deep learning techniques for inverse problems in imaging,","venue":null,"work_id":"d53dae16-2836-401e-bc1c-cd308c767dd0","year":2020},"citing_paper":{"arxiv_id":"2501.03430","last_updated":"2025-01-06T23:23:24Z","snapshot_observed_at":"2026-08-13T04:17:31.132584Z","submitted_at":"2025-01-06T23:23:24Z","title":"A Self-supervised Diffusion Bridge for MRI Reconstruction","version":1},"reference_index":2,"source":"pdf_text","source_observed_at":"2026-08-10T22:02:04.272665Z"},"links":{"citing_paper":"/paper/2501.03430"},"observation_digest":"sha256:310ae364b3317c6504a93e012a5017751e4b47a1c7563df997602b2021deed0b","observation_id":"9914e7c6-9505-4593-b924-03f6b2ff4976","resolution":{"observed_at":"2026-08-10T22:02:04.606907Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-14T06:32:32.682623+00:00","source":"crossref"},{"observed_at":"2026-08-14T06:32:18.44784+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-10T22:02:04.588597Z","title":"MoDL: Model-Based Deep Learning Architecture for Inverse Problems,","venue":null,"work_id":"d5343d0a-691e-49a4-a4a4-889875fac08a","year":2019},"citing_paper":{"arxiv_id":"2501.03430","last_updated":"2025-01-06T23:23:24Z","snapshot_observed_at":"2026-08-13T04:17:31.132584Z","submitted_at":"2025-01-06T23:23:24Z","title":"A Self-supervised Diffusion Bridge for MRI Reconstruction","version":1},"reference_index":3,"source":"pdf_text","source_observed_at":"2026-08-10T22:02:04.283815Z"},"links":{"citing_paper":"/paper/2501.03430"},"observation_digest":"sha256:d5317ee0f4cb64f9ee6ce887daeda3e18d307cef6a1a6ce1783d130f0461f4b6","observation_id":"2f24c7b3-58ba-4036-8df1-a104667fdb98","resolution":{"observed_at":"2026-08-10T22:02:04.593220Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-14T06:32:32.682623+00:00","source":"crossref"},{"observed_at":"2026-08-14T06:32:18.44784+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"2410.00083","last_updated":"2024-09-30T17:34:01Z","snapshot_observed_at":"2026-07-06T19:24:48.032228Z","submitted_at":"2024-09-30T17:34:01Z","title":"A Survey on Diffusion Models for Inverse Problems","version":1},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2410.00083","snapshot_observed_at":"2026-08-10T22:02:04.288737Z","title":"A Survey on Diffusion Models for Inverse Problems,","venue":null,"work_id":null,"year":2024},"citing_paper":{"arxiv_id":"2501.03430","last_updated":"2025-01-06T23:23:24Z","snapshot_observed_at":"2026-08-13T04:17:31.132584Z","submitted_at":"2025-01-06T23:23:24Z","title":"A Self-supervised Diffusion Bridge for MRI Reconstruction","version":1},"reference_index":4,"source":"pdf_text","source_observed_at":"2026-08-10T22:02:04.288737Z"},"links":{"cited_paper":"/paper/2410.00083","citing_paper":"/paper/2501.03430"},"observation_digest":"sha256:cacd107caee3db83cf43ca79a7eb8adcdd769a6f7038001518f387035fffae84","observation_id":"6a39416a-716c-4f8a-b6b2-3d846d9072ec","resolution":{"observed_at":"2026-08-10T22:02:04.288737Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-10T22:02:04.574777Z","title":"DOLCE: A model-based probabilistic diffusion framework for limited-angle ct reconstruc- tion,","venue":null,"work_id":"3ce07278-c6df-420d-b2e6-f35a11c107f1","year":2023},"citing_paper":{"arxiv_id":"2501.03430","last_updated":"2025-01-06T23:23:24Z","snapshot_observed_at":"2026-08-13T04:17:31.132584Z","submitted_at":"2025-01-06T23:23:24Z","title":"A Self-supervised Diffusion Bridge for MRI Reconstruction","version":1},"reference_index":5,"source":"pdf_text","source_observed_at":"2026-08-10T22:02:04.294177Z"},"links":{"citing_paper":"/paper/2501.03430"},"observation_digest":"sha256:e4f306829a89b074c9ec2a03026dbe96d12dab0a7a637dde2cf3616c7a4012aa","observation_id":"70efc4de-de4e-41de-b17b-0abba1e1644f","resolution":{"observed_at":"2026-08-10T22:02:04.579760Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-14T06:32:32.682623+00:00","source":"crossref"},{"observed_at":"2026-08-14T06:32:18.44784+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-10T22:02:04.562465Z","title":"Denoising Diffusion Probabilistic Models,","venue":null,"work_id":"75ab408b-5f19-46b4-a817-de9df1c9074b","year":2020},"citing_paper":{"arxiv_id":"2501.03430","last_updated":"2025-01-06T23:23:24Z","snapshot_observed_at":"2026-08-13T04:17:31.132584Z","submitted_at":"2025-01-06T23:23:24Z","title":"A Self-supervised Diffusion Bridge for MRI Reconstruction","version":1},"reference_index":6,"source":"pdf_text","source_observed_at":"2026-08-10T22:02:04.299638Z"},"links":{"citing_paper":"/paper/2501.03430"},"observation_digest":"sha256:ef27c938ddcc54e2a8a095773e390bcf4788cf428392ccd4027bd3db5f7f1529","observation_id":"3e09d316-301f-4051-a126-ce4f54327946","resolution":{"observed_at":"2026-08-10T22:02:04.566543Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-14T06:32:32.682623+00:00","source":"crossref"},{"observed_at":"2026-08-14T06:32:18.44784+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-10T22:02:04.548521Z","title":"Diffusion Posterior Sampling for General Noisy Inverse Problems,","venue":null,"work_id":"e3890ab0-f702-45b6-bd86-1054bda26979","year":2023},"citing_paper":{"arxiv_id":"2501.03430","last_updated":"2025-01-06T23:23:24Z","snapshot_observed_at":"2026-08-13T04:17:31.132584Z","submitted_at":"2025-01-06T23:23:24Z","title":"A Self-supervised Diffusion Bridge for MRI Reconstruction","version":1},"reference_index":7,"source":"pdf_text","source_observed_at":"2026-08-10T22:02:04.305183Z"},"links":{"citing_paper":"/paper/2501.03430"},"observation_digest":"sha256:93d9b0188019948fc1827431967858283bc812cc9e7040db7de23d45ce507778","observation_id":"ce48094e-05e1-43cd-9f3e-88a4565a4782","resolution":{"observed_at":"2026-08-10T22:02:04.553811Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-14T06:32:32.682623+00:00","source":"crossref"},{"observed_at":"2026-08-14T06:32:18.44784+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-10T22:02:04.535710Z","title":"DisC-Diff: Disentangled Conditional Diffusion Model for Multi-Contrast MRI Super- Resolution,","venue":null,"work_id":"82029ac4-7ae2-4032-808b-9f35d2934804","year":2023},"citing_paper":{"arxiv_id":"2501.03430","last_updated":"2025-01-06T23:23:24Z","snapshot_observed_at":"2026-08-13T04:17:31.132584Z","submitted_at":"2025-01-06T23:23:24Z","title":"A Self-supervised Diffusion Bridge for MRI Reconstruction","version":1},"reference_index":8,"source":"pdf_text","source_observed_at":"2026-08-10T22:02:04.309770Z"},"links":{"citing_paper":"/paper/2501.03430"},"observation_digest":"sha256:493f0a82fef1c4075fb1e2cb75d7db6116f52523acbc4ebe4663e205ca53bc80","observation_id":"4f02cca6-e158-4f6d-b680-c57bd27212f5","resolution":{"observed_at":"2026-08-10T22:02:04.540033Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-14T06:32:32.682623+00:00","source":"crossref"},{"observed_at":"2026-08-14T06:32:18.44784+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-10T22:02:04.521969Z","title":"Direct Diffusion Bridge using Data Consistency for Inverse Problems,","venue":null,"work_id":"d5023c48-8323-4e84-aa3c-bd4f3880837b","year":2023},"citing_paper":{"arxiv_id":"2501.03430","last_updated":"2025-01-06T23:23:24Z","snapshot_observed_at":"2026-08-13T04:17:31.132584Z","submitted_at":"2025-01-06T23:23:24Z","title":"A Self-supervised Diffusion Bridge for MRI Reconstruction","version":1},"reference_index":9,"source":"pdf_text","source_observed_at":"2026-08-10T22:02:04.314256Z"},"links":{"citing_paper":"/paper/2501.03430"},"observation_digest":"sha256:55bf2e33cb3f313318891c21c1a3b19c2f06dff6f62199647ef04e3aae8844f7","observation_id":"069971ef-e0bc-48db-a57d-9bd74c56e63e","resolution":{"observed_at":"2026-08-10T22:02:04.526712Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-14T06:32:32.682623+00:00","source":"crossref"},{"observed_at":"2026-08-14T06:32:18.44784+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-10T22:02:04.507753Z","title":"Inversion by Direct Iteration: An Alternative to Denoising Diffusion for Image Restoration,","venue":null,"work_id":"a249290a-474b-4b75-9b08-7137fa813a66","year":2024},"citing_paper":{"arxiv_id":"2501.03430","last_updated":"2025-01-06T23:23:24Z","snapshot_observed_at":"2026-08-13T04:17:31.132584Z","submitted_at":"2025-01-06T23:23:24Z","title":"A Self-supervised Diffusion Bridge for MRI Reconstruction","version":1},"reference_index":10,"source":"pdf_text","source_observed_at":"2026-08-10T22:02:04.318496Z"},"links":{"citing_paper":"/paper/2501.03430"},"observation_digest":"sha256:f9e0a0674751d1f2d72988441d15345ba501bc653c4d962d75b8bc4c4d63ee2b","observation_id":"0cd7c48c-b7a8-4c5a-a5bc-b728f6849553","resolution":{"observed_at":"2026-08-10T22:02:04.512688Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-14T06:32:32.682623+00:00","source":"crossref"},{"observed_at":"2026-08-14T06:32:18.44784+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-10T22:02:04.493913Z","title":"Self-supervised learning of physics-guided reconstruction neural networks without fully sampled reference data,","venue":null,"work_id":"4db83411-5272-40a5-b854-a96949b7df0c","year":2020},"citing_paper":{"arxiv_id":"2501.03430","last_updated":"2025-01-06T23:23:24Z","snapshot_observed_at":"2026-08-13T04:17:31.132584Z","submitted_at":"2025-01-06T23:23:24Z","title":"A Self-supervised Diffusion Bridge for MRI Reconstruction","version":1},"reference_index":11,"source":"pdf_text","source_observed_at":"2026-08-10T22:02:04.323218Z"},"links":{"citing_paper":"/paper/2501.03430"},"observation_digest":"sha256:e239b3762e8d73bd3bd0c09618c7f2bf7dc599550784c29005ea0860c551e99a","observation_id":"faec3e57-cbab-47cd-8f02-dd053d4ebd30","resolution":{"observed_at":"2026-08-10T22:02:04.498818Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-14T06:32:32.682623+00:00","source":"crossref"},{"observed_at":"2026-08-14T06:32:18.44784+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-10T22:02:04.479272Z","title":"Self-Supervised Deep Equilibrium Models With Theoretical Guarantees and Applications to MRI Reconstruction,","venue":null,"work_id":"5bb94625-987d-48e5-b0cc-67a7ba9bc9f0","year":2023},"citing_paper":{"arxiv_id":"2501.03430","last_updated":"2025-01-06T23:23:24Z","snapshot_observed_at":"2026-08-13T04:17:31.132584Z","submitted_at":"2025-01-06T23:23:24Z","title":"A Self-supervised Diffusion Bridge for MRI Reconstruction","version":1},"reference_index":12,"source":"pdf_text","source_observed_at":"2026-08-10T22:02:04.327577Z"},"links":{"citing_paper":"/paper/2501.03430"},"observation_digest":"sha256:8dd6562aa55b090b646b8ddebdc6b19a34befaf8b99e4a56e2846f35853e71c3","observation_id":"5210df06-b008-4106-8b82-073053141d19","resolution":{"observed_at":"2026-08-10T22:02:04.484354Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-14T06:32:32.682623+00:00","source":"crossref"},{"observed_at":"2026-08-14T06:32:18.44784+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-10T22:02:04.461939Z","title":"Equivariant Imaging: Learning Beyond the Range Space,","venue":null,"work_id":"48c14f43-b723-455d-b767-7a129ae06c99","year":2021},"citing_paper":{"arxiv_id":"2501.03430","last_updated":"2025-01-06T23:23:24Z","snapshot_observed_at":"2026-08-13T04:17:31.132584Z","submitted_at":"2025-01-06T23:23:24Z","title":"A Self-supervised Diffusion Bridge for MRI Reconstruction","version":1},"reference_index":13,"source":"pdf_text","source_observed_at":"2026-08-10T22:02:04.331473Z"},"links":{"citing_paper":"/paper/2501.03430"},"observation_digest":"sha256:02535346091de42dea87b1a94d040de0c3047be3b5d5b9ef802a321f8e0eeaa5","observation_id":"d5a193f6-bbda-4acf-b9f0-937c6e27124d","resolution":{"observed_at":"2026-08-10T22:02:04.467844Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-14T06:32:32.682623+00:00","source":"crossref"},{"observed_at":"2026-08-14T06:32:18.44784+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-10T22:02:04.444889Z","title":"Ambient diffusion: Learning clean distributions from corrupted data,","venue":null,"work_id":"c40000fb-8ef1-48ac-96bb-032eb8ba505f","year":2023},"citing_paper":{"arxiv_id":"2501.03430","last_updated":"2025-01-06T23:23:24Z","snapshot_observed_at":"2026-08-13T04:17:31.132584Z","submitted_at":"2025-01-06T23:23:24Z","title":"A Self-supervised Diffusion Bridge for MRI Reconstruction","version":1},"reference_index":14,"source":"pdf_text","source_observed_at":"2026-08-10T22:02:04.336034Z"},"links":{"citing_paper":"/paper/2501.03430"},"observation_digest":"sha256:a0375ad8184714e6cc174a3afe160ace7b23b8a8f07f512622f25152f6850e03","observation_id":"8985d4a7-c47a-4770-9a27-1ab4eebd3408","resolution":{"observed_at":"2026-08-10T22:02:04.449280Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-14T06:32:32.682623+00:00","source":"crossref"},{"observed_at":"2026-08-14T06:32:18.44784+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-10T22:02:04.430449Z","title":"Image Super-Resolution via Iterative Refinement,","venue":null,"work_id":"13d75d5e-3222-46c2-b19e-0b58b2033fc7","year":2022},"citing_paper":{"arxiv_id":"2501.03430","last_updated":"2025-01-06T23:23:24Z","snapshot_observed_at":"2026-08-13T04:17:31.132584Z","submitted_at":"2025-01-06T23:23:24Z","title":"A Self-supervised Diffusion Bridge for MRI Reconstruction","version":1},"reference_index":15,"source":"pdf_text","source_observed_at":"2026-08-10T22:02:04.340168Z"},"links":{"citing_paper":"/paper/2501.03430"},"observation_digest":"sha256:37bbce4393c9ee74f93056e49d520a4e73ae23ad184d2570bf559f2b1e870047","observation_id":"b1987500-3bed-467c-a9d0-d474bf106dd0","resolution":{"observed_at":"2026-08-10T22:02:04.435055Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-14T06:32:32.682623+00:00","source":"crossref"},{"observed_at":"2026-08-14T06:32:18.44784+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-10T22:02:04.414090Z","title":"fastMRI: A publicly available raw k-space and DICOM dataset of knee images for accelerated MR image reconstruction using machine learning,","venue":null,"work_id":"554c618a-5d2b-4cc8-950e-1fd8b2b23787","year":2020},"citing_paper":{"arxiv_id":"2501.03430","last_updated":"2025-01-06T23:23:24Z","snapshot_observed_at":"2026-08-13T04:17:31.132584Z","submitted_at":"2025-01-06T23:23:24Z","title":"A Self-supervised Diffusion Bridge for MRI Reconstruction","version":1},"reference_index":16,"source":"pdf_text","source_observed_at":"2026-08-10T22:02:04.344002Z"},"links":{"citing_paper":"/paper/2501.03430"},"observation_digest":"sha256:f64a0f374e4bafc8ce84a36bc5857f62ae8fa5d817ecd9f46b3fa34161871395","observation_id":"93a75a5b-bcb1-4520-bb6b-f514c0df33c0","resolution":{"observed_at":"2026-08-10T22:02:04.419494Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-14T06:32:32.682623+00:00","source":"crossref"},{"observed_at":"2026-08-14T06:32:18.44784+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-10T22:02:04.398269Z","title":"ESPIRiT-an eigenvalue approach to autocalibrating parallel MRI: Where SENSE meets GRAPPA,","venue":null,"work_id":"8d85a959-b5ee-4484-a6f0-2337fc42e78d","year":2014},"citing_paper":{"arxiv_id":"2501.03430","last_updated":"2025-01-06T23:23:24Z","snapshot_observed_at":"2026-08-13T04:17:31.132584Z","submitted_at":"2025-01-06T23:23:24Z","title":"A Self-supervised Diffusion Bridge for MRI Reconstruction","version":1},"reference_index":17,"source":"pdf_text","source_observed_at":"2026-08-10T22:02:04.349179Z"},"links":{"citing_paper":"/paper/2501.03430"},"observation_digest":"sha256:69adb538715e14b98aeda85741cc0ff01f1ddcb17bef9e3593f9bd3ea4dae061","observation_id":"061b3edb-bf07-4b25-835c-493e88107f85","resolution":{"observed_at":"2026-08-10T22:02:04.404690Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-14T06:32:32.682623+00:00","source":"crossref"},{"observed_at":"2026-08-14T06:32:18.44784+00:00","source":"retraction_watch"}],"state":"measured"}}],"paper":{"arxiv_id":"2501.03430","last_updated":"2025-01-06T23:23:24Z","latest_version":1,"primary_category":"eess.IV","snapshot_observed_at":"2026-08-13T04:17:31.132584Z","submitted_at":"2025-01-06T23:23:24Z","title":"A Self-supervised Diffusion Bridge for MRI Reconstruction"},"reference_resolution":{"displayed":17,"state_counts":{"malformed_identifier":0,"metadata_mismatch":0,"parse_uncertain":0,"unresolved":1,"verified_exact":0,"verified_fuzzy":16},"total_outbound_references":17},"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":"2026-08-14T06:32:32.682623+00:00","source":"crossref"},{"observed_at":"2026-08-14T06:32:18.44784+00:00","source":"retraction_watch"}],"thesis":"As of 15 August 2026, this Paper Citation Record lists 17 of 17 outbound references and 1 inbound Pith citation observation for arXiv:2501.03430."}