{"as_of":"2026-08-11T04:31:00Z","caps":{"database_statements":6,"inbound":100,"outbound":100},"context_digest":"sha256:c10ca119f1e953d5ff3f4c7fa24ac71a2e7a68ae1feeb8663ce68d2a7249c501","coverage":[{"denominator":28,"lane":"reference_resolution","note":"Typed states for the displayed outbound observations.","records_observed":28,"source":"paper_references, paper_reference_links","source_observed_at":"2026-08-09T00:55:11.089125Z","state":"measured"},{"denominator":30,"lane":"standing_notices","note":"One-hop event checks from named stored sources.","records_observed":30,"source":"scholarly_work_events, retraction_status_cache","source_observed_at":"2026-08-10T06:31:04.303077+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":"2026-08-04T11:28:53.996348Z","state":"measured"},{"denominator":1,"lane":"external_citation_measurements","note":"A source-named dated measurement, never combined with another source.","records_observed":0,"source":"cited_works","source_observed_at":null,"state":"measured"}],"external_citation_measurements":[],"inbound":[{"citation":{"cited_paper":{"arxiv_id":"2502.04393","last_updated":"2025-02-06T03:56:11Z","snapshot_observed_at":"2026-08-10T09:02:00.534700Z","submitted_at":"2025-02-06T03:56:11Z","title":"UniCP: A Unified Caching and Pruning Framework for Efficient Video Generation","version":1},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2502.04393","snapshot_observed_at":"2026-08-04T11:28:53.996348Z","title":"UniCP : A Unified Caching and Pruning Framework for Efficient Video Generation , February 2025","venue":null,"work_id":null,"year":2025},"citing_paper":{"arxiv_id":"2510.04646","last_updated":"2026-06-22T07:44:29Z","snapshot_observed_at":"2026-08-07T23:52:55.636241Z","submitted_at":"2025-10-06T09:49:14Z","title":"Predictive Feature Caching for Training-free Acceleration of Molecular Geometry Generation","version":2},"reference_index":19,"source":"arxiv_source","source_observed_at":"2026-08-04T11:28:53.996348Z"},"links":{"cited_paper":"/paper/2502.04393","citing_paper":"/paper/2510.04646"},"observation_digest":"sha256:c0b943664c94b6e0395f8ee51ddb8af56a4ee296c5baaa622c406bf65804fb44","observation_id":"87746a17-fe88-4bc4-b53b-0a0f28d410c9","resolution":{"observed_at":"2026-08-04T11:28:53.996348Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2502.04393","last_updated":"2025-02-06T03:56:11Z","snapshot_observed_at":"2026-08-10T09:02:00.534700Z","submitted_at":"2025-02-06T03:56:11Z","title":"UniCP: A Unified Caching and Pruning Framework for Efficient Video Generation","version":1},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2502.04393","snapshot_observed_at":"2026-07-13T12:34:28.755596Z","title":"Unicp: A unified caching and pruning framework for efficient video generation.arXiv preprint arXiv:2502.04393,","venue":null,"work_id":null,"year":null},"citing_paper":{"arxiv_id":"2604.03674","last_updated":"2026-04-04T10:16:18Z","snapshot_observed_at":"2026-08-06T17:48:37.654091Z","submitted_at":"2026-04-04T10:16:18Z","title":"DiffSparse: Accelerating Diffusion Transformers with Learned Token Sparsity","version":1},"reference_index":17,"source":"pdf_text","source_observed_at":"2026-07-13T12:34:28.755596Z"},"links":{"cited_paper":"/paper/2502.04393","citing_paper":"/paper/2604.03674"},"observation_digest":"sha256:5c18b08232f296975f352fc6b2dd52a43992e1fb5498f19b2175df1f5f706c55","observation_id":"d6f58019-f4a1-40a6-8a13-94a2e15dfba5","resolution":{"observed_at":"2026-07-13T12:34:28.755596Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}}],"links":{"evidence":"/evidence","html":"/paper/2502.04393/citation-record","integrity":"/paper/2502.04393/integrity","json":"/paper/2502.04393/citation-record.json","paper":"/paper/2502.04393"},"outbound":[{"citation":{"cited_paper":{"arxiv_id":"2212.09748","last_updated":"2023-03-02T09:06:55Z","snapshot_observed_at":"2026-07-06T14:32:37.317828Z","submitted_at":"2022-12-19T18:59:58Z","title":"Scalable Diffusion Models with Transformers","version":2},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2212.09748","snapshot_observed_at":"2026-08-09T00:55:10.940996Z","title":"Scalable diffusion models with transformers,","venue":null,"work_id":null,"year":2022},"citing_paper":{"arxiv_id":"2502.04393","last_updated":"2025-02-06T03:56:11Z","snapshot_observed_at":"2026-08-10T09:02:00.534700Z","submitted_at":"2025-02-06T03:56:11Z","title":"UniCP: A Unified Caching and Pruning Framework for Efficient Video Generation","version":1},"reference_index":1,"source":"pdf_text","source_observed_at":"2026-08-09T00:55:10.940996Z"},"links":{"cited_paper":"/paper/2212.09748","citing_paper":"/paper/2502.04393"},"observation_digest":"sha256:35f3a4a442745939bd54cbcf55c27c729d8925e5cf0c60e5a2350bc557b77e70","observation_id":"11e8607f-a759-4f62-ae10-81c5eb9e7abc","resolution":{"observed_at":"2026-08-09T00:55:10.940996Z","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":"2026-08-09T00:55:11.667850Z","title":"Ditfastattn: Attention compression for diffusion transformer models,","venue":null,"work_id":"e7adcf12-db0b-4360-8723-16ba2920c49d","year":2024},"citing_paper":{"arxiv_id":"2502.04393","last_updated":"2025-02-06T03:56:11Z","snapshot_observed_at":"2026-08-10T09:02:00.534700Z","submitted_at":"2025-02-06T03:56:11Z","title":"UniCP: A Unified Caching and Pruning Framework for Efficient Video Generation","version":1},"reference_index":2,"source":"pdf_text","source_observed_at":"2026-08-09T00:55:10.947185Z"},"links":{"citing_paper":"/paper/2502.04393"},"observation_digest":"sha256:7df85a8e98ba7256bba620587ff7d267a6afb715596fd398fa22af2d068d87c0","observation_id":"3c6e7cc3-6841-4f7e-830d-8610e76a5d67","resolution":{"observed_at":"2026-08-09T00:55:11.673005Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"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"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-09T00:55:11.652342Z","title":"Denoising dif- fusion probabilistic models,","venue":null,"work_id":"23f96f64-6346-49a6-966f-4ed184ed7f41","year":2020},"citing_paper":{"arxiv_id":"2502.04393","last_updated":"2025-02-06T03:56:11Z","snapshot_observed_at":"2026-08-10T09:02:00.534700Z","submitted_at":"2025-02-06T03:56:11Z","title":"UniCP: A Unified Caching and Pruning Framework for Efficient Video Generation","version":1},"reference_index":3,"source":"pdf_text","source_observed_at":"2026-08-09T00:55:10.953332Z"},"links":{"citing_paper":"/paper/2502.04393"},"observation_digest":"sha256:52ec7ece26e855a8b30e93d8d002ca1fedf337d9dfc91f303bcb6f00729a4aed","observation_id":"66613ba7-6979-4520-b117-a0c3d3fba1c9","resolution":{"observed_at":"2026-08-09T00:55:11.657632Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"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"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-09T00:55:11.634716Z","title":"High-resolution image synthesis with latent diffusion models,","venue":null,"work_id":"073d8de5-18aa-4717-babf-5bfaeeb2d5f8","year":2022},"citing_paper":{"arxiv_id":"2502.04393","last_updated":"2025-02-06T03:56:11Z","snapshot_observed_at":"2026-08-10T09:02:00.534700Z","submitted_at":"2025-02-06T03:56:11Z","title":"UniCP: A Unified Caching and Pruning Framework for Efficient Video Generation","version":1},"reference_index":4,"source":"pdf_text","source_observed_at":"2026-08-09T00:55:10.959442Z"},"links":{"citing_paper":"/paper/2502.04393"},"observation_digest":"sha256:5e073d85a5838a9d6e97b07c2487daaccefb1971eca9378323037a90efb7913a","observation_id":"bdb76bc5-916b-47db-87e9-4e739030f75c","resolution":{"observed_at":"2026-08-09T00:55:11.641193Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"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"}},{"citation":{"cited_paper":{"arxiv_id":"2311.15127","last_updated":"2023-11-25T22:28:38Z","snapshot_observed_at":"2026-08-07T21:47:08.589400Z","submitted_at":"2023-11-25T22:28:38Z","title":"Stable Video Diffusion: Scaling Latent Video Diffusion Models to Large Datasets","version":1},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2311.15127","snapshot_observed_at":"2026-08-09T00:55:10.964837Z","title":"Stable video diffusion: Scaling latent video diffusion models to large datasets,","venue":null,"work_id":null,"year":2023},"citing_paper":{"arxiv_id":"2502.04393","last_updated":"2025-02-06T03:56:11Z","snapshot_observed_at":"2026-08-10T09:02:00.534700Z","submitted_at":"2025-02-06T03:56:11Z","title":"UniCP: A Unified Caching and Pruning Framework for Efficient Video Generation","version":1},"reference_index":5,"source":"pdf_text","source_observed_at":"2026-08-09T00:55:10.964837Z"},"links":{"cited_paper":"/paper/2311.15127","citing_paper":"/paper/2502.04393"},"observation_digest":"sha256:1565372e78c62d46b10e3bd4be1c6b637e9e94ed7b3ff117844e1528ca2dda42","observation_id":"6c230ac4-ba51-4aed-8ca0-636d8ac636e2","resolution":{"observed_at":"2026-08-09T00:55:10.964837Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2010.02502","last_updated":"2022-10-05T20:19:21Z","snapshot_observed_at":"2026-07-06T10:01:50.133383Z","submitted_at":"2020-10-06T06:15:51Z","title":"Denoising Diffusion Implicit Models","version":4},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2010.02502","snapshot_observed_at":"2026-08-09T00:55:10.970203Z","title":"Denoising diffusion implicit models,","venue":null,"work_id":null,"year":2010},"citing_paper":{"arxiv_id":"2502.04393","last_updated":"2025-02-06T03:56:11Z","snapshot_observed_at":"2026-08-10T09:02:00.534700Z","submitted_at":"2025-02-06T03:56:11Z","title":"UniCP: A Unified Caching and Pruning Framework for Efficient Video Generation","version":1},"reference_index":6,"source":"pdf_text","source_observed_at":"2026-08-09T00:55:10.970203Z"},"links":{"cited_paper":"/paper/2010.02502","citing_paper":"/paper/2502.04393"},"observation_digest":"sha256:60b58b0bb0fa732597c2ddfd75a685a2c6b990902a48e3c3f23aee300cb43603","observation_id":"5726f6bb-2516-4924-af6f-a6f6a48366d5","resolution":{"observed_at":"2026-08-09T00:55:10.970203Z","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":"2026-08-09T00:55:11.618723Z","title":"Deepcache: Accelerating diffusion models for free,","venue":null,"work_id":"8df1f534-1523-4d4f-8782-d341e8f5b8f2","year":2024},"citing_paper":{"arxiv_id":"2502.04393","last_updated":"2025-02-06T03:56:11Z","snapshot_observed_at":"2026-08-10T09:02:00.534700Z","submitted_at":"2025-02-06T03:56:11Z","title":"UniCP: A Unified Caching and Pruning Framework for Efficient Video Generation","version":1},"reference_index":7,"source":"pdf_text","source_observed_at":"2026-08-09T00:55:10.976312Z"},"links":{"citing_paper":"/paper/2502.04393"},"observation_digest":"sha256:1bab36550d008d51040bbbcc28604663a7725beb26d398881a6dd93e09c6e7a5","observation_id":"05b07109-69e2-4f7e-bb83-a4042894592e","resolution":{"observed_at":"2026-08-09T00:55:11.623927Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"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"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-09T00:55:11.602107Z","title":"Faster diffusion: Rethinking the role of unet encoder in diffusion models,","venue":null,"work_id":"be15cc3b-2a55-46c4-a021-76b3a687e852","year":2023},"citing_paper":{"arxiv_id":"2502.04393","last_updated":"2025-02-06T03:56:11Z","snapshot_observed_at":"2026-08-10T09:02:00.534700Z","submitted_at":"2025-02-06T03:56:11Z","title":"UniCP: A Unified Caching and Pruning Framework for Efficient Video Generation","version":1},"reference_index":8,"source":"pdf_text","source_observed_at":"2026-08-09T00:55:10.981937Z"},"links":{"citing_paper":"/paper/2502.04393"},"observation_digest":"sha256:a87de6fa7b731426e72d04fa01e026db859785dc672a8037ee1f21ff907c7fcb","observation_id":"4d19086c-f678-42ba-b8d5-a38979316e46","resolution":{"observed_at":"2026-08-09T00:55:11.607537Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"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"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-09T00:55:11.583483Z","title":"Real- time video generation with pyramid attention broadcast,","venue":null,"work_id":"8fcdf262-1602-4d0a-ba38-ed96fd592708","year":2024},"citing_paper":{"arxiv_id":"2502.04393","last_updated":"2025-02-06T03:56:11Z","snapshot_observed_at":"2026-08-10T09:02:00.534700Z","submitted_at":"2025-02-06T03:56:11Z","title":"UniCP: A Unified Caching and Pruning Framework for Efficient Video Generation","version":1},"reference_index":9,"source":"pdf_text","source_observed_at":"2026-08-09T00:55:10.986945Z"},"links":{"citing_paper":"/paper/2502.04393"},"observation_digest":"sha256:5fc02a2538224fb6e059a50ac0e3bdfa9819acc951a696e281a30daf78ca164f","observation_id":"3a13ff19-a64a-41b3-b72c-4f5f1ecc4e65","resolution":{"observed_at":"2026-08-09T00:55:11.589072Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"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"}},{"citation":{"cited_paper":{"arxiv_id":"2406.01125","last_updated":"2024-06-03T09:10:44Z","snapshot_observed_at":"2026-08-10T10:06:50.769308Z","submitted_at":"2024-06-03T09:10:44Z","title":"$\\Delta$-DiT: A Training-Free Acceleration Method Tailored for Diffusion Transformers","version":1},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2406.01125","snapshot_observed_at":"2026-08-09T00:55:10.992313Z","title":"Delta-dit: A training-free acceleration method tailored for diffusion transformers,","venue":null,"work_id":null,"year":2024},"citing_paper":{"arxiv_id":"2502.04393","last_updated":"2025-02-06T03:56:11Z","snapshot_observed_at":"2026-08-10T09:02:00.534700Z","submitted_at":"2025-02-06T03:56:11Z","title":"UniCP: A Unified Caching and Pruning Framework for Efficient Video Generation","version":1},"reference_index":10,"source":"pdf_text","source_observed_at":"2026-08-09T00:55:10.992313Z"},"links":{"cited_paper":"/paper/2406.01125","citing_paper":"/paper/2502.04393"},"observation_digest":"sha256:3afe8768e65b33606c9d9c86c7e2dc36a3e4b9d1a16c70ab16e785aebc2bf130","observation_id":"7521bd65-b7a4-4356-a2d8-bd11b823c636","resolution":{"observed_at":"2026-08-09T00:55:10.992313Z","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":"2026-08-09T00:55:11.567090Z","title":"Temporal generative adversarial nets with singular value clipping,","venue":null,"work_id":"b70dd8f2-657a-4542-a4e6-4c5757ad8c14","year":2017},"citing_paper":{"arxiv_id":"2502.04393","last_updated":"2025-02-06T03:56:11Z","snapshot_observed_at":"2026-08-10T09:02:00.534700Z","submitted_at":"2025-02-06T03:56:11Z","title":"UniCP: A Unified Caching and Pruning Framework for Efficient Video Generation","version":1},"reference_index":11,"source":"pdf_text","source_observed_at":"2026-08-09T00:55:10.997262Z"},"links":{"citing_paper":"/paper/2502.04393"},"observation_digest":"sha256:2a502fd1a0694a89c212e461359a95e2f8816c23825044418b89bcf36d825fda","observation_id":"9ba4aeca-5f97-4993-aabb-b4394841be4c","resolution":{"observed_at":"2026-08-09T00:55:11.572258Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"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"}},{"citation":{"cited_paper":{"arxiv_id":"1808.06601","last_updated":"2018-12-03T15:12:44Z","snapshot_observed_at":"2026-07-06T06:56:30.962909Z","submitted_at":"2018-08-20T17:58:42Z","title":"Video-to-Video Synthesis","version":2},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"1808.06601","snapshot_observed_at":"2026-08-09T00:55:11.005137Z","title":"Video-to- video synthesis,","venue":null,"work_id":null,"year":2018},"citing_paper":{"arxiv_id":"2502.04393","last_updated":"2025-02-06T03:56:11Z","snapshot_observed_at":"2026-08-10T09:02:00.534700Z","submitted_at":"2025-02-06T03:56:11Z","title":"UniCP: A Unified Caching and Pruning Framework for Efficient Video Generation","version":1},"reference_index":12,"source":"pdf_text","source_observed_at":"2026-08-09T00:55:11.005137Z"},"links":{"cited_paper":"/paper/1808.06601","citing_paper":"/paper/2502.04393"},"observation_digest":"sha256:ed9507a67e422ce5819c07bebc0b159efa11e0e36e4eba4121f3e9aa7d07e805","observation_id":"23bf36d8-bc3c-4676-8c86-e365ba872d31","resolution":{"observed_at":"2026-08-09T00:55:11.005137Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"1906.02634","last_updated":"2020-02-10T19:29:56Z","snapshot_observed_at":"2026-08-10T11:43:04.991423Z","submitted_at":"2019-06-06T15:06:21Z","title":"Scaling Autoregressive Video Models","version":3},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"1906.02634","snapshot_observed_at":"2026-08-09T00:55:11.011088Z","title":"Scaling autoregressive video models,","venue":null,"work_id":null,"year":1906},"citing_paper":{"arxiv_id":"2502.04393","last_updated":"2025-02-06T03:56:11Z","snapshot_observed_at":"2026-08-10T09:02:00.534700Z","submitted_at":"2025-02-06T03:56:11Z","title":"UniCP: A Unified Caching and Pruning Framework for Efficient Video Generation","version":1},"reference_index":13,"source":"pdf_text","source_observed_at":"2026-08-09T00:55:11.011088Z"},"links":{"cited_paper":"/paper/1906.02634","citing_paper":"/paper/2502.04393"},"observation_digest":"sha256:cd414b081e58c094d79f29819f9efb91dc8575a1ed358ef6642fee670ebbb038","observation_id":"dd192a89-50fd-472c-86b0-06e7132d1bb2","resolution":{"observed_at":"2026-08-09T00:55:11.011088Z","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":"2026-08-09T00:55:11.550383Z","title":"Video diffusion models,","venue":null,"work_id":"28a00015-d66c-4ec3-bce8-aae5457a940b","year":2022},"citing_paper":{"arxiv_id":"2502.04393","last_updated":"2025-02-06T03:56:11Z","snapshot_observed_at":"2026-08-10T09:02:00.534700Z","submitted_at":"2025-02-06T03:56:11Z","title":"UniCP: A Unified Caching and Pruning Framework for Efficient Video Generation","version":1},"reference_index":14,"source":"pdf_text","source_observed_at":"2026-08-09T00:55:11.016373Z"},"links":{"citing_paper":"/paper/2502.04393"},"observation_digest":"sha256:78ae27eeda976c83bbb775bef4a63368a5c1ee254d9aacee155fa51bb206f8ac","observation_id":"0703cd7e-5c07-42a3-9169-23314da579e9","resolution":{"observed_at":"2026-08-09T00:55:11.556093Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"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"}},{"citation":{"cited_paper":{"arxiv_id":"2401.03048","last_updated":"2025-05-01T09:40:21Z","snapshot_observed_at":"2026-08-02T13:01:06.918463Z","submitted_at":"2024-01-05T19:55:15Z","title":"Latte: Latent Diffusion Transformer for Video Generation","version":3},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2401.03048","snapshot_observed_at":"2026-08-09T00:55:11.021821Z","title":"Latte: Latent diffusion transformer for video generation,","venue":null,"work_id":null,"year":2024},"citing_paper":{"arxiv_id":"2502.04393","last_updated":"2025-02-06T03:56:11Z","snapshot_observed_at":"2026-08-10T09:02:00.534700Z","submitted_at":"2025-02-06T03:56:11Z","title":"UniCP: A Unified Caching and Pruning Framework for Efficient Video Generation","version":1},"reference_index":15,"source":"pdf_text","source_observed_at":"2026-08-09T00:55:11.021821Z"},"links":{"cited_paper":"/paper/2401.03048","citing_paper":"/paper/2502.04393"},"observation_digest":"sha256:b28622e1a1839aff632a56b76b3e9fea1b90e9d23360697f0913e9cb17e1ea3e","observation_id":"adabfffa-d826-4b75-b844-3accc6a9a425","resolution":{"observed_at":"2026-08-09T00:55:11.021821Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2205.15868","last_updated":"2022-05-29T19:02:15Z","snapshot_observed_at":"2026-07-06T13:15:58.303738Z","submitted_at":"2022-05-29T19:02:15Z","title":"CogVideo: Large-scale Pretraining for Text-to-Video Generation via Transformers","version":1},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2205.15868","snapshot_observed_at":"2026-08-09T00:55:11.027649Z","title":"Cogvideo: Large-scale pretraining for text-to-video generation via transformers,","venue":null,"work_id":null,"year":2022},"citing_paper":{"arxiv_id":"2502.04393","last_updated":"2025-02-06T03:56:11Z","snapshot_observed_at":"2026-08-10T09:02:00.534700Z","submitted_at":"2025-02-06T03:56:11Z","title":"UniCP: A Unified Caching and Pruning Framework for Efficient Video Generation","version":1},"reference_index":16,"source":"pdf_text","source_observed_at":"2026-08-09T00:55:11.027649Z"},"links":{"cited_paper":"/paper/2205.15868","citing_paper":"/paper/2502.04393"},"observation_digest":"sha256:a386528d21200fce2965285e30589223aae05d5566f84593cfd59f0b4ce81612","observation_id":"19c6c18b-409c-4d19-8dba-94ce19d2ebd3","resolution":{"observed_at":"2026-08-09T00:55:11.027649Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2408.06072","last_updated":"2025-03-26T08:33:10Z","snapshot_observed_at":"2026-07-06T02:11:23.670680Z","submitted_at":"2024-08-12T11:47:11Z","title":"CogVideoX: Text-to-Video Diffusion Models with An Expert Transformer","version":3},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2408.06072","snapshot_observed_at":"2026-08-09T00:55:11.032454Z","title":"Cogvideox: Text-to-video diffusion models with an expert transformer,","venue":null,"work_id":null,"year":2024},"citing_paper":{"arxiv_id":"2502.04393","last_updated":"2025-02-06T03:56:11Z","snapshot_observed_at":"2026-08-10T09:02:00.534700Z","submitted_at":"2025-02-06T03:56:11Z","title":"UniCP: A Unified Caching and Pruning Framework for Efficient Video Generation","version":1},"reference_index":17,"source":"pdf_text","source_observed_at":"2026-08-09T00:55:11.032454Z"},"links":{"cited_paper":"/paper/2408.06072","citing_paper":"/paper/2502.04393"},"observation_digest":"sha256:b94565a5d6e01d98f9226f30fd37418b9c34d8b914e59e7525c2c7921ba72050","observation_id":"e28508bc-f175-4f86-a920-503ae042d334","resolution":{"observed_at":"2026-08-09T00:55:11.032454Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2404.10667","last_updated":"2024-10-31T07:43:14Z","snapshot_observed_at":"2026-08-10T11:43:43.946305Z","submitted_at":"2024-04-16T15:43:22Z","title":"VASA-1: Lifelike Audio-Driven Talking Faces Generated in Real Time","version":2},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2404.10667","snapshot_observed_at":"2026-08-09T00:55:11.037455Z","title":"Vasa-1: Lifelike audio-driven talking faces generated in real time,","venue":null,"work_id":null,"year":2024},"citing_paper":{"arxiv_id":"2502.04393","last_updated":"2025-02-06T03:56:11Z","snapshot_observed_at":"2026-08-10T09:02:00.534700Z","submitted_at":"2025-02-06T03:56:11Z","title":"UniCP: A Unified Caching and Pruning Framework for Efficient Video Generation","version":1},"reference_index":18,"source":"pdf_text","source_observed_at":"2026-08-09T00:55:11.037455Z"},"links":{"cited_paper":"/paper/2404.10667","citing_paper":"/paper/2502.04393"},"observation_digest":"sha256:4776cc16ebbd15ae9c20c1f25212632a07ca8553c8115e3325270ee165e1a69f","observation_id":"07af191c-a7ec-478a-8e45-b25668495004","resolution":{"observed_at":"2026-08-09T00:55:11.037455Z","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":"2026-08-09T00:55:11.533086Z","title":"Scaling rectified flow transformers for high-resolution image synthesis,","venue":null,"work_id":"c548a0a9-2439-4a22-899b-b271493f7491","year":2024},"citing_paper":{"arxiv_id":"2502.04393","last_updated":"2025-02-06T03:56:11Z","snapshot_observed_at":"2026-08-10T09:02:00.534700Z","submitted_at":"2025-02-06T03:56:11Z","title":"UniCP: A Unified Caching and Pruning Framework for Efficient Video Generation","version":1},"reference_index":19,"source":"pdf_text","source_observed_at":"2026-08-09T00:55:11.042847Z"},"links":{"citing_paper":"/paper/2502.04393"},"observation_digest":"sha256:372829e3613283092fe8b1eabc078850638ed9d8b5a876832c760d9eeec8558f","observation_id":"f464598e-ccfe-4716-b10a-12b0a4eed9ec","resolution":{"observed_at":"2026-08-09T00:55:11.538796Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"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"}},{"citation":{"cited_paper":{"arxiv_id":"2412.03603","last_updated":"2025-03-11T08:14:25Z","snapshot_observed_at":"2026-08-03T00:44:01.942521Z","submitted_at":"2024-12-03T23:52:37Z","title":"HunyuanVideo: A Systematic Framework For Large Video Generative Models","version":6},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2412.03603","snapshot_observed_at":"2026-08-09T00:55:11.047396Z","title":"Hunyuanvideo: A systematic framework for large video generative models,","venue":null,"work_id":null,"year":2024},"citing_paper":{"arxiv_id":"2502.04393","last_updated":"2025-02-06T03:56:11Z","snapshot_observed_at":"2026-08-10T09:02:00.534700Z","submitted_at":"2025-02-06T03:56:11Z","title":"UniCP: A Unified Caching and Pruning Framework for Efficient Video Generation","version":1},"reference_index":20,"source":"pdf_text","source_observed_at":"2026-08-09T00:55:11.047396Z"},"links":{"cited_paper":"/paper/2412.03603","citing_paper":"/paper/2502.04393"},"observation_digest":"sha256:2d051215e075d94d68c8ce1400475ae3ede7358ce71afd96652d178829ea06e2","observation_id":"b05299a4-1c54-4197-b072-71b16cbaf958","resolution":{"observed_at":"2026-08-09T00:55:11.047396Z","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":"2026-08-09T00:55:11.515684Z","title":"Dpm-solver: A fast ode solver for diffusion probabilistic model sampling in around 10 steps,","venue":null,"work_id":"8e2cb7f4-71b4-4f4a-8b21-edea5a8ce7d4","year":2022},"citing_paper":{"arxiv_id":"2502.04393","last_updated":"2025-02-06T03:56:11Z","snapshot_observed_at":"2026-08-10T09:02:00.534700Z","submitted_at":"2025-02-06T03:56:11Z","title":"UniCP: A Unified Caching and Pruning Framework for Efficient Video Generation","version":1},"reference_index":21,"source":"pdf_text","source_observed_at":"2026-08-09T00:55:11.053470Z"},"links":{"citing_paper":"/paper/2502.04393"},"observation_digest":"sha256:2aedb1c3c42dcf20494313ae6500f5e3cb3e4596b45abf773e6331d95964490f","observation_id":"cde69964-c74f-4efb-a3ff-d8792edbb668","resolution":{"observed_at":"2026-08-09T00:55:11.521753Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"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"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-09T00:55:11.497444Z","title":"One- step diffusion with distribution matching distillation,","venue":null,"work_id":"11fa5d1a-e895-4acf-810c-2ecf4e1f7654","year":2024},"citing_paper":{"arxiv_id":"2502.04393","last_updated":"2025-02-06T03:56:11Z","snapshot_observed_at":"2026-08-10T09:02:00.534700Z","submitted_at":"2025-02-06T03:56:11Z","title":"UniCP: A Unified Caching and Pruning Framework for Efficient Video Generation","version":1},"reference_index":22,"source":"pdf_text","source_observed_at":"2026-08-09T00:55:11.058369Z"},"links":{"citing_paper":"/paper/2502.04393"},"observation_digest":"sha256:3b0adb06aae03d01f4682ff8ae8e2ba5c1f8d14b6203e7cc2eecbf847e1bb0a9","observation_id":"bff71e79-c0fb-483d-b6a7-8e8255e23d6b","resolution":{"observed_at":"2026-08-09T00:55:11.503537Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"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"}},{"citation":{"cited_paper":{"arxiv_id":"2401.15024","last_updated":"2024-02-09T17:59:40Z","snapshot_observed_at":"2026-07-06T17:21:01.918787Z","submitted_at":"2024-01-26T17:35:45Z","title":"SliceGPT: Compress Large Language Models by Deleting Rows and Columns","version":2},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2401.15024","snapshot_observed_at":"2026-08-09T00:55:11.063169Z","title":"Slicegpt: Compress large language models by deleting rows and columns,","venue":null,"work_id":null,"year":2024},"citing_paper":{"arxiv_id":"2502.04393","last_updated":"2025-02-06T03:56:11Z","snapshot_observed_at":"2026-08-10T09:02:00.534700Z","submitted_at":"2025-02-06T03:56:11Z","title":"UniCP: A Unified Caching and Pruning Framework for Efficient Video Generation","version":1},"reference_index":23,"source":"pdf_text","source_observed_at":"2026-08-09T00:55:11.063169Z"},"links":{"cited_paper":"/paper/2401.15024","citing_paper":"/paper/2502.04393"},"observation_digest":"sha256:e4c475a5fa146a0de45533dd27a5b94ea5ce06d5b6e03b4e36f445223c69f5b7","observation_id":"ae26e4db-668b-4407-b2ff-58c77fe4098a","resolution":{"observed_at":"2026-08-09T00:55:11.063169Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2410.19355","last_updated":"2025-03-12T03:40:38Z","snapshot_observed_at":"2026-08-10T13:43:10.288098Z","submitted_at":"2024-10-25T07:24:38Z","title":"FasterCache: Training-Free Video Diffusion Model Acceleration with High Quality","version":2},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2410.19355","snapshot_observed_at":"2026-08-09T00:55:11.068026Z","title":"Fastercache: Training-free video diffusion model acceleration with high quality,","venue":null,"work_id":null,"year":2024},"citing_paper":{"arxiv_id":"2502.04393","last_updated":"2025-02-06T03:56:11Z","snapshot_observed_at":"2026-08-10T09:02:00.534700Z","submitted_at":"2025-02-06T03:56:11Z","title":"UniCP: A Unified Caching and Pruning Framework for Efficient Video Generation","version":1},"reference_index":24,"source":"pdf_text","source_observed_at":"2026-08-09T00:55:11.068026Z"},"links":{"cited_paper":"/paper/2410.19355","citing_paper":"/paper/2502.04393"},"observation_digest":"sha256:a6b7901672c964fbde2f87dffc3b0f16665b20f361f60a34f5798a10f05714e6","observation_id":"49c4a0e9-080d-4dc2-911e-1b8bd634781f","resolution":{"observed_at":"2026-08-09T00:55:11.068026Z","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":"2026-08-09T00:55:11.480071Z","title":"Vbench: Comprehensive benchmark suite for video generative models,","venue":null,"work_id":"24eacf6a-1215-4194-832d-77259ad8601d","year":2024},"citing_paper":{"arxiv_id":"2502.04393","last_updated":"2025-02-06T03:56:11Z","snapshot_observed_at":"2026-08-10T09:02:00.534700Z","submitted_at":"2025-02-06T03:56:11Z","title":"UniCP: A Unified Caching and Pruning Framework for Efficient Video Generation","version":1},"reference_index":25,"source":"pdf_text","source_observed_at":"2026-08-09T00:55:11.073801Z"},"links":{"citing_paper":"/paper/2502.04393"},"observation_digest":"sha256:4fd07e7fef2cbe6c9af0349b1344fcd6d02622accd12035996cb48549636a416","observation_id":"f43f8ef1-e7d4-42f0-9c3f-97420b984390","resolution":{"observed_at":"2026-08-09T00:55:11.486182Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"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"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-09T00:55:11.463507Z","title":"The unreasonable effectiveness of deep features as a perceptual metric,","venue":null,"work_id":"1306f673-0c0d-47ef-aecf-837e44b7876a","year":2018},"citing_paper":{"arxiv_id":"2502.04393","last_updated":"2025-02-06T03:56:11Z","snapshot_observed_at":"2026-08-10T09:02:00.534700Z","submitted_at":"2025-02-06T03:56:11Z","title":"UniCP: A Unified Caching and Pruning Framework for Efficient Video Generation","version":1},"reference_index":26,"source":"pdf_text","source_observed_at":"2026-08-09T00:55:11.078727Z"},"links":{"citing_paper":"/paper/2502.04393"},"observation_digest":"sha256:9074e5cdad262df1de5d7470e9b5a0119941b9c40cd818b5ae4b3b42b2ea5e88","observation_id":"8df80e99-4b79-4d98-93ea-8e55a7c9671a","resolution":{"observed_at":"2026-08-09T00:55:11.468384Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"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"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":null,"snapshot_observed_at":"2026-08-09T00:55:11.083723Z","title":"Image quality assessment: from error visibility to structural similarity,","venue":null,"work_id":null,"year":2004},"citing_paper":{"arxiv_id":"2502.04393","last_updated":"2025-02-06T03:56:11Z","snapshot_observed_at":"2026-08-10T09:02:00.534700Z","submitted_at":"2025-02-06T03:56:11Z","title":"UniCP: A Unified Caching and Pruning Framework for Efficient Video Generation","version":1},"reference_index":27,"source":"pdf_text","source_observed_at":"2026-08-09T00:55:11.083723Z"},"links":{"citing_paper":"/paper/2502.04393"},"observation_digest":"sha256:a2d2ed979c2fe55cc2ec9791ada58bb7dca69d3fb881deec7f88333e55e1bc73","observation_id":"318b4ba5-c31f-412a-943c-fc394082fe63","resolution":{"observed_at":"2026-08-09T00:55:11.083723Z","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":"2026-08-09T00:55:11.430123Z","title":"Peak signal-to-noise ratio revisited: Is simple beautiful?,","venue":null,"work_id":"f6216391-7161-4896-b2d1-b8b823670032","year":2012},"citing_paper":{"arxiv_id":"2502.04393","last_updated":"2025-02-06T03:56:11Z","snapshot_observed_at":"2026-08-10T09:02:00.534700Z","submitted_at":"2025-02-06T03:56:11Z","title":"UniCP: A Unified Caching and Pruning Framework for Efficient Video Generation","version":1},"reference_index":28,"source":"pdf_text","source_observed_at":"2026-08-09T00:55:11.089125Z"},"links":{"citing_paper":"/paper/2502.04393"},"observation_digest":"sha256:78f1dec5664e65546e4379eb0a367eb14b05b6898b2edb06ee5c2a398fa923ea","observation_id":"b46d731e-1a60-4462-9c38-83e8b6251039","resolution":{"observed_at":"2026-08-09T00:55:11.439367Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"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"}}],"paper":{"arxiv_id":"2502.04393","last_updated":"2025-02-06T03:56:11Z","latest_version":1,"primary_category":"cs.CV","snapshot_observed_at":"2026-08-10T09:02:00.534700Z","submitted_at":"2025-02-06T03:56:11Z","title":"UniCP: A Unified Caching and Pruning Framework for Efficient Video Generation"},"reference_resolution":{"displayed":28,"state_counts":{"malformed_identifier":0,"metadata_mismatch":0,"parse_uncertain":0,"unresolved":14,"verified_exact":0,"verified_fuzzy":14},"total_outbound_references":28},"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 11 August 2026, this Paper Citation Record lists 28 of 28 outbound references and 2 inbound Pith citation observations for arXiv:2502.04393."}