{"as_of":"2026-08-11T19:01:00Z","caps":{"database_statements":6,"inbound":100,"outbound":100},"context_digest":"sha256:cb4bfbce74753b6cbc678b49666a2f7f75d7f5b2329ae4db269b4bfedf1ff2a3","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":"2026-07-01T06:59:07.294813Z","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":"2026-07-04T16:19:57.954258Z","state":"measured"}],"external_citation_measurements":[],"inbound":[{"citation":{"cited_paper":{"arxiv_id":"2503.14863","last_updated":"2025-03-19T03:41:56Z","snapshot_observed_at":"2026-08-08T19:45:50.229885Z","submitted_at":"2025-03-19T03:41:56Z","title":"Temporal-Consistent Video Restoration with Pre-trained Diffusion Models","version":1},"cited_work":{"arxiv_id":"2503.14863","doi":null,"metadata_source":"arxiv_reference","pith_arxiv_id":"2503.14863","snapshot_observed_at":"2026-07-04T16:19:57.954258Z","title":"Temporal-consistent video restoration with pre-trained diffusion models","venue":null,"work_id":"3213598f-668a-423f-9467-e3fa9c9cf15a","year":2025},"citing_paper":{"arxiv_id":"2511.16520","last_updated":"2026-05-12T03:36:08Z","snapshot_observed_at":"2026-07-06T22:36:30.947164Z","submitted_at":"2025-11-20T16:35:57Z","title":"Saving Foundation Flow-Matching Priors for Inverse Problems","version":3},"reference_index":25,"source":"pdf_text","source_observed_at":"2026-05-17T20:36:13.408128Z"},"links":{"cited_paper":"/paper/2503.14863","citing_paper":"/paper/2511.16520"},"observation_digest":"sha256:802ecd6a0453f0ff608d32b7ea1d4d1b8c5de755bdfe7b648f00d8a08a2746ee","observation_id":"0e7f98d9-2b19-4e24-beed-28b4b8238d32","resolution":{"observed_at":"2026-05-17T20:40:15.036803Z","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":"2503.14863","last_updated":"2025-03-19T03:41:56Z","snapshot_observed_at":"2026-08-08T19:45:50.229885Z","submitted_at":"2025-03-19T03:41:56Z","title":"Temporal-Consistent Video Restoration with Pre-trained Diffusion Models","version":1},"cited_work":{"arxiv_id":"2503.14863","doi":null,"metadata_source":"arxiv_reference","pith_arxiv_id":"2503.14863","snapshot_observed_at":"2026-07-04T16:19:57.954258Z","title":"Temporal-consistent video restoration with pre-trained diffusion models","venue":null,"work_id":"3213598f-668a-423f-9467-e3fa9c9cf15a","year":2025},"citing_paper":{"arxiv_id":"2512.23709","last_updated":"2026-04-04T08:31:26Z","snapshot_observed_at":"2026-08-02T10:50:10.466874Z","submitted_at":"2025-12-29T18:59:57Z","title":"Stream-DiffVSR: Low-Latency Streamable Video Super-Resolution via Auto-Regressive Diffusion","version":2},"reference_index":76,"source":"pdf_text","source_observed_at":"2026-05-16T19:14:15.240218Z"},"links":{"cited_paper":"/paper/2503.14863","citing_paper":"/paper/2512.23709"},"observation_digest":"sha256:6c285fbf058b131e4d6c47c5ed24f053d0bfa945a6dcf139d2b9726d2a85f33e","observation_id":"c2ac595b-8a07-437d-880e-24e9e981572f","resolution":{"observed_at":"2026-05-16T19:18:19.568094Z","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":"2503.14863","last_updated":"2025-03-19T03:41:56Z","snapshot_observed_at":"2026-08-08T19:45:50.229885Z","submitted_at":"2025-03-19T03:41:56Z","title":"Temporal-Consistent Video Restoration with Pre-trained Diffusion Models","version":1},"cited_work":{"arxiv_id":"2503.14863","doi":null,"metadata_source":"arxiv_reference","pith_arxiv_id":"2503.14863","snapshot_observed_at":"2026-07-04T16:19:57.954258Z","title":"Temporal-consistent video restoration with pre-trained diffusion models","venue":null,"work_id":"3213598f-668a-423f-9467-e3fa9c9cf15a","year":2025},"citing_paper":{"arxiv_id":"2606.24336","last_updated":"2026-06-30T03:40:24Z","snapshot_observed_at":"2026-07-06T23:58:54.018557Z","submitted_at":"2026-06-23T09:21:36Z","title":"TIGER: Taming Identity, Geometry, and Generative Priors for High-Quality Face Video Restoration","version":1},"reference_index":29,"source":"pdf_text","source_observed_at":"2026-06-26T00:45:05.681548Z"},"links":{"cited_paper":"/paper/2503.14863","citing_paper":"/paper/2606.24336"},"observation_digest":"sha256:d71813859aa1ab16db8a26657cd0926d5756c80523cd0b40d48d6a358fa5b3a9","observation_id":"67211d17-3f7e-4cc6-bd9f-13881c515525","resolution":{"observed_at":"2026-07-04T16:19:57.955768Z","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":"2503.14863","last_updated":"2025-03-19T03:41:56Z","snapshot_observed_at":"2026-08-08T19:45:50.229885Z","submitted_at":"2025-03-19T03:41:56Z","title":"Temporal-Consistent Video Restoration with Pre-trained Diffusion Models","version":1},"cited_work":{"arxiv_id":"2503.14863","doi":null,"metadata_source":"arxiv_reference","pith_arxiv_id":"2503.14863","snapshot_observed_at":"2026-07-04T16:19:57.954258Z","title":"Temporal-consistent video restoration with pre-trained diffusion models","venue":null,"work_id":"3213598f-668a-423f-9467-e3fa9c9cf15a","year":2025},"citing_paper":{"arxiv_id":"2606.24336","last_updated":"2026-06-30T03:40:24Z","snapshot_observed_at":"2026-07-06T23:58:54.018557Z","submitted_at":"2026-06-23T09:21:36Z","title":"TIGER: Taming Identity, Geometry, and Generative Priors for High-Quality Face Video Restoration","version":2},"reference_index":29,"source":"pdf_text","source_observed_at":"2026-07-01T06:59:07.294813Z"},"links":{"cited_paper":"/paper/2503.14863","citing_paper":"/paper/2606.24336"},"observation_digest":"sha256:9d9298da2e98158e0e6e33ea9cdc9f399f98cb206d66549f4bea75bf2e66bc6e","observation_id":"586c320e-a4f9-445b-897c-be5415ef22d8","resolution":{"observed_at":"2026-07-01T08:55:35.626201Z","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"}}],"links":{"evidence":"/evidence","html":"/paper/2503.14863/citation-record","integrity":"/paper/2503.14863/integrity","json":"/paper/2503.14863/citation-record.json","paper":"/paper/2503.14863"},"outbound":[],"paper":{"arxiv_id":"2503.14863","last_updated":"2025-03-19T03:41:56Z","latest_version":1,"primary_category":"cs.CV","snapshot_observed_at":"2026-08-08T19:45:50.229885Z","submitted_at":"2025-03-19T03:41:56Z","title":"Temporal-Consistent Video Restoration with Pre-trained 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:2503.14863."}