{"as_of":"2026-08-05T05:54:00Z","caps":{"database_statements":6,"inbound":100,"outbound":100},"context_digest":"sha256:f93b9b43527c53307e5cc10207be461bfa78b140ffffabf3e7655cf044f7ab57","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":"2026-08-04T06:34:03.388597+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":"2026-08-01T13:56:39.152037Z","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":"2026-07-03T20:28:55.544053Z","state":"measured"}],"external_citation_measurements":[],"inbound":[{"citation":{"cited_paper":{"arxiv_id":"2502.12632","last_updated":"2025-07-08T04:03:03Z","snapshot_observed_at":"2026-07-06T20:38:25.164930Z","submitted_at":"2025-02-18T08:22:50Z","title":"MALT Diffusion: Memory-Augmented Latent Transformers for Any-Length Video Generation","version":3},"cited_work":{"arxiv_id":"2502.12632","doi":null,"metadata_source":"arxiv_reference","pith_arxiv_id":"2502.12632","snapshot_observed_at":"2026-07-03T20:28:55.544053Z","title":"arXiv preprint arXiv:2502.12632 , year=","venue":null,"work_id":"ab001ae6-4e24-4b25-99ee-c0961797eee1","year":2025},"citing_paper":{"arxiv_id":"2605.15042","last_updated":"2026-05-14T16:36:34Z","snapshot_observed_at":"2026-07-06T23:26:23.179482Z","submitted_at":"2026-05-14T16:36:34Z","title":"EverAnimate: Minute-Scale Human Animation via Latent Flow Restoration","version":1},"reference_index":53,"source":"pdf_text","source_observed_at":"2026-06-30T21:21:58.123630Z"},"links":{"cited_paper":"/paper/2502.12632","citing_paper":"/paper/2605.15042"},"observation_digest":"sha256:4e37fa457dd5af34b91d31016cf633f517ba9be230c99e861e5f29a570433d0e","observation_id":"daba8c2c-5cae-4f5a-855c-1b2a9740a0e6","resolution":{"observed_at":"2026-06-30T21:25:04.914794Z","resolver_source":"arxiv_id","status":"verified_exact"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-04T06:34:03.388597+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-04T06:34:03.388597+00:00","source":"crossref"},{"observed_at":"2026-08-04T06:33:57.428241+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"2502.12632","last_updated":"2025-07-08T04:03:03Z","snapshot_observed_at":"2026-07-06T20:38:25.164930Z","submitted_at":"2025-02-18T08:22:50Z","title":"MALT Diffusion: Memory-Augmented Latent Transformers for Any-Length Video Generation","version":3},"cited_work":{"arxiv_id":"2502.12632","doi":null,"metadata_source":"arxiv_reference","pith_arxiv_id":"2502.12632","snapshot_observed_at":"2026-07-03T20:28:55.544053Z","title":"arXiv preprint arXiv:2502.12632 , year=","venue":null,"work_id":"ab001ae6-4e24-4b25-99ee-c0961797eee1","year":2025},"citing_paper":{"arxiv_id":"2606.17590","last_updated":"2026-06-16T06:52:52Z","snapshot_observed_at":"2026-08-02T16:55:34.840902Z","submitted_at":"2026-06-16T06:52:52Z","title":"TivTok: Broadcasting Time-Invariant Tokens for Scalable Video Tokenization","version":1},"reference_index":125,"source":"arxiv_source","source_observed_at":"2026-06-27T01:20:32.508409Z"},"links":{"cited_paper":"/paper/2502.12632","citing_paper":"/paper/2606.17590"},"observation_digest":"sha256:4ef826e8868509abd0fa32ece52e5f7c33474a355372b02b2281a0a25e1db0d9","observation_id":"738b7e8a-2b16-4c5b-850e-81cdedaf2d91","resolution":{"observed_at":"2026-07-03T20:28:55.545765Z","resolver_source":"arxiv_id","status":"verified_exact"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-04T06:34:03.388597+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-04T06:34:03.388597+00:00","source":"crossref"},{"observed_at":"2026-08-04T06:33:57.428241+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"2502.12632","last_updated":"2025-07-08T04:03:03Z","snapshot_observed_at":"2026-07-06T20:38:25.164930Z","submitted_at":"2025-02-18T08:22:50Z","title":"MALT Diffusion: Memory-Augmented Latent Transformers for Any-Length Video Generation","version":3},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2502.12632","snapshot_observed_at":"2026-08-01T13:56:39.152037Z","title":"arXiv preprint arXiv:2502.12632 , year=","venue":null,"work_id":null,"year":null},"citing_paper":{"arxiv_id":"2607.26529","last_updated":"2026-07-29T06:48:11Z","snapshot_observed_at":"2026-08-01T23:26:45.323335Z","submitted_at":"2026-07-29T06:48:11Z","title":"CineWeaver: Training-Free Reference-Controllable Multi-Shot Long Video Generation for Cinematic Storytelling","version":1},"reference_index":96,"source":"arxiv_source","source_observed_at":"2026-08-01T13:56:39.152037Z"},"links":{"cited_paper":"/paper/2502.12632","citing_paper":"/paper/2607.26529"},"observation_digest":"sha256:dc75073301fad2140b4c57187d75144ac5799a14288c7889a721362fff99ca2d","observation_id":"045d70b9-34d4-4700-b91d-80cb3c76f2d6","resolution":{"observed_at":"2026-08-01T13:56:39.152037Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}}],"links":{"evidence":"/evidence","html":"/paper/2502.12632/citation-record","integrity":"/paper/2502.12632/integrity","json":"/paper/2502.12632/citation-record.json","paper":"/paper/2502.12632"},"outbound":[],"paper":{"arxiv_id":"2502.12632","last_updated":"2025-07-08T04:03:03Z","latest_version":3,"primary_category":"cs.CV","snapshot_observed_at":"2026-07-06T20:38:25.164930Z","submitted_at":"2025-02-18T08:22:50Z","title":"MALT Diffusion: Memory-Augmented Latent Transformers for Any-Length Video Generation"},"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":"2026-08-04T06:34:03.388597+00:00","source":"crossref"},{"observed_at":"2026-08-04T06:33:57.428241+00:00","source":"retraction_watch"}],"thesis":"As of 5 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 3 inbound Pith citation observations for arXiv:2502.12632."}