{"as_of":"2026-08-08T21:27:00Z","caps":{"database_statements":6,"inbound":100,"outbound":100},"context_digest":"sha256:97ac0b964d382a53f01cd0b8ba98d532c7c29d059f2ffeccc4061de5067ad615","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":2,"lane":"standing_notices","note":"One-hop event checks from named stored sources.","records_observed":2,"source":"scholarly_work_events, retraction_status_cache","source_observed_at":"2026-08-08T06:32:00.761636+00:00","state":"measured"},{"denominator":2,"lane":"inbound_itemization","note":"Pith citing papers itemized under the disclosed page cap.","records_observed":2,"source":"paper_references, paper_reference_links","source_observed_at":"2026-08-07T13:00:57.039138Z","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":"2026-05-11T11:11:03.884231Z","state":"measured"}],"external_citation_measurements":[],"inbound":[{"citation":{"cited_paper":{"arxiv_id":"2311.00990","last_updated":"2025-04-14T02:18:19Z","snapshot_observed_at":"2026-07-06T16:42:00.138744Z","submitted_at":"2023-11-02T04:38:50Z","title":"VideoDreamer: Customized Multi-Subject Text-to-Video Generation with Disen-Mix Finetuning on Language-Video Foundation Models","version":2},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2311.00990","snapshot_observed_at":"2026-08-07T13:00:57.039138Z","title":"Videodreamer: Customized multi-subject text-to- video generation with disen-mix finetuning.arXiv preprint arXiv:2311.00990, 2023","venue":null,"work_id":null,"year":2023},"citing_paper":{"arxiv_id":"2505.22980","last_updated":"2025-05-29T01:41:10Z","snapshot_observed_at":"2026-08-08T15:15:33.938758Z","submitted_at":"2025-05-29T01:41:10Z","title":"MOVi: Training-free Text-conditioned Multi-Object Video Generation","version":1},"reference_index":7,"source":"pdf_text","source_observed_at":"2026-08-07T13:00:57.039138Z"},"links":{"cited_paper":"/paper/2311.00990","citing_paper":"/paper/2505.22980"},"observation_digest":"sha256:1316934025d78959de8d85ababb08220bf9b3f9df0c8f9534a6a68627d85088a","observation_id":"a7ccfdea-b328-485b-9aa7-2f6d59470f66","resolution":{"observed_at":"2026-08-07T13:00:57.039138Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2311.00990","last_updated":"2025-04-14T02:18:19Z","snapshot_observed_at":"2026-07-06T16:42:00.138744Z","submitted_at":"2023-11-02T04:38:50Z","title":"VideoDreamer: Customized Multi-Subject Text-to-Video Generation with Disen-Mix Finetuning on Language-Video Foundation Models","version":2},"cited_work":{"arxiv_id":"2311.00990","doi":null,"metadata_source":"arxiv_reference","pith_arxiv_id":"2311.00990","snapshot_observed_at":"2026-06-05T21:23:00.469572Z","title":"Videodreamer: Customized multi-subject text-to-video generation with disen-mix finetuning.arXiv preprint arXiv:2311.00990","venue":null,"work_id":"82d4e473-b72e-49df-b88e-d7a677060bf4","year":null},"citing_paper":{"arxiv_id":"2604.11244","last_updated":"2026-04-15T07:55:01Z","snapshot_observed_at":"2026-07-06T22:59:40.900521Z","submitted_at":"2026-04-13T09:50:36Z","title":"Script-a-Video: Deep Structured Audio-visual Captions via Factorized Streams and Relational Grounding","version":2},"reference_index":3,"source":"pdf_text","source_observed_at":"2026-05-10T15:07:45.595260Z"},"links":{"cited_paper":"/paper/2311.00990","citing_paper":"/paper/2604.11244"},"observation_digest":"sha256:49fecf03ffb9ecd17d3c8e75642f21ad8f82c6d81f1f49baaf5114bef5b7910b","observation_id":"faffe768-9282-4961-a062-2db305ea5b2b","resolution":{"observed_at":"2026-05-11T11:11:03.887978Z","resolver_source":"arxiv_id","status":"verified_exact"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-08T06:32:00.761636+00:00","source":"crossref"},{"observed_at":"2026-08-08T06:31:55.24221+00:00","source":"retraction_watch"}],"state":"measured"}}],"links":{"evidence":"/evidence","html":"/paper/2311.00990/citation-record","integrity":"/paper/2311.00990/integrity","json":"/paper/2311.00990/citation-record.json","paper":"/paper/2311.00990"},"outbound":[],"paper":{"arxiv_id":"2311.00990","last_updated":"2025-04-14T02:18:19Z","latest_version":2,"primary_category":"cs.CV","snapshot_observed_at":"2026-07-06T16:42:00.138744Z","submitted_at":"2023-11-02T04:38:50Z","title":"VideoDreamer: Customized Multi-Subject Text-to-Video Generation with Disen-Mix Finetuning on Language-Video Foundation 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":"2026-08-08T06:32:00.761636+00:00","source":"crossref"},{"observed_at":"2026-08-08T06:31:55.24221+00:00","source":"retraction_watch"}],"thesis":"As of 8 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 2 inbound Pith citation observations for arXiv:2311.00990."}