{"as_of":"2026-08-09T05:25:00Z","caps":{"database_statements":6,"inbound":100,"outbound":100},"context_digest":"sha256:bac09129a48de730fae09ff0c9744b3a324bb60412032a635125138f9b5c21dd","coverage":[{"denominator":62,"lane":"reference_resolution","note":"Typed states for the displayed outbound observations.","records_observed":62,"source":"paper_references, paper_reference_links","source_observed_at":"2026-08-06T13:57:04.663532Z","state":"measured"},{"denominator":62,"lane":"standing_notices","note":"One-hop event checks from named stored sources.","records_observed":62,"source":"scholarly_work_events, retraction_status_cache","source_observed_at":"2026-08-08T06:32:00.761636+00:00","state":"measured"},{"denominator":0,"lane":"inbound_itemization","note":"Pith citing papers itemized under the disclosed page cap.","records_observed":0,"source":"paper_references, paper_reference_links","source_observed_at":null,"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":[],"links":{"evidence":"/evidence","html":"/paper/2507.19924/citation-record","integrity":"/paper/2507.19924/integrity","json":"/paper/2507.19924/citation-record.json","paper":"/paper/2507.19924"},"outbound":[{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-06T13:57:05.956497Z","title":"https://vchitect.intern-ai.org.cn, 2024","venue":null,"work_id":"43ed4b2a-73c3-4272-9dbd-19b908119fee","year":2024},"citing_paper":{"arxiv_id":"2507.19924","last_updated":"2025-08-01T12:25:21Z","snapshot_observed_at":"2026-08-07T14:18:30.406157Z","submitted_at":"2025-07-26T12:03:47Z","title":"HumanSAM: Classifying Human-centric Forgery Videos in Human Spatial, Appearance, and Motion Anomaly","version":2},"reference_index":1,"source":"pdf_text","source_observed_at":"2026-08-06T13:57:04.231984Z"},"links":{"citing_paper":"/paper/2507.19924"},"observation_digest":"sha256:758f89515fabe7cf1704914b2f277c5f2480f597e26f580352f6a06a837f9c7d","observation_id":"0915f7ee-f875-4ff9-b9cf-3f917bc2c231","resolution":{"observed_at":"2026-08-06T13:57:05.960988Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"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"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-06T13:57:05.941145Z","title":"AI-generated video detection via spatial-temporal anomaly learning","venue":null,"work_id":"8ab721f6-1150-489d-852d-0e61fdd8bc55","year":2024},"citing_paper":{"arxiv_id":"2507.19924","last_updated":"2025-08-01T12:25:21Z","snapshot_observed_at":"2026-08-07T14:18:30.406157Z","submitted_at":"2025-07-26T12:03:47Z","title":"HumanSAM: Classifying Human-centric Forgery Videos in Human Spatial, Appearance, and Motion Anomaly","version":2},"reference_index":2,"source":"pdf_text","source_observed_at":"2026-08-06T13:57:04.317902Z"},"links":{"citing_paper":"/paper/2507.19924"},"observation_digest":"sha256:90aefefc4b349c05231e02ac361e766b4d6fef73501d5d50f802d73083c888bd","observation_id":"10179ea4-7f1d-4d91-bec3-c5f71a2f6b6a","resolution":{"observed_at":"2026-08-06T13:57:05.945740Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"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"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-06T13:57:05.925684Z","title":"Is space-time attention all you need for video understanding? InICML, page 4, 2021","venue":null,"work_id":"a4457644-84c3-41df-b0d1-e3b7c9a37311","year":2021},"citing_paper":{"arxiv_id":"2507.19924","last_updated":"2025-08-01T12:25:21Z","snapshot_observed_at":"2026-08-07T14:18:30.406157Z","submitted_at":"2025-07-26T12:03:47Z","title":"HumanSAM: Classifying Human-centric Forgery Videos in Human Spatial, Appearance, and Motion Anomaly","version":2},"reference_index":3,"source":"pdf_text","source_observed_at":"2026-08-06T13:57:04.355601Z"},"links":{"citing_paper":"/paper/2507.19924"},"observation_digest":"sha256:c9acba9a5dfe547ed574d22122ad665ef8ae7b0372de4bce48343fcb15a2d946","observation_id":"65254c27-10b5-49a2-9846-910733f694b1","resolution":{"observed_at":"2026-08-06T13:57:05.930302Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"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"}},{"citation":{"cited_paper":{"arxiv_id":"2410.02073","last_updated":"2025-04-21T12:09:08Z","snapshot_observed_at":"2026-08-02T06:32:26.688405Z","submitted_at":"2024-10-02T22:42:20Z","title":"Depth Pro: Sharp Monocular Metric Depth in Less Than a Second","version":2},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2410.02073","snapshot_observed_at":"2026-08-06T13:57:04.360584Z","title":"Depth pro: Sharp monocular metric depth in less than a second.arXiv preprint arXiv:2410.02073, 2024","venue":null,"work_id":null,"year":2024},"citing_paper":{"arxiv_id":"2507.19924","last_updated":"2025-08-01T12:25:21Z","snapshot_observed_at":"2026-08-07T14:18:30.406157Z","submitted_at":"2025-07-26T12:03:47Z","title":"HumanSAM: Classifying Human-centric Forgery Videos in Human Spatial, Appearance, and Motion Anomaly","version":2},"reference_index":4,"source":"pdf_text","source_observed_at":"2026-08-06T13:57:04.360584Z"},"links":{"cited_paper":"/paper/2410.02073","citing_paper":"/paper/2507.19924"},"observation_digest":"sha256:152b0afe610311435b422830ba12dfd514ff4530871a9da79dca5abcc58260c5","observation_id":"5520d5e9-52c5-4aeb-ac23-c505e5722a34","resolution":{"observed_at":"2026-08-06T13:57:04.360584Z","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":null,"pith_arxiv_id":null,"snapshot_observed_at":"2026-08-06T13:57:04.367406Z","title":"Video generation models as world simulators","venue":null,"work_id":null,"year":null},"citing_paper":{"arxiv_id":"2507.19924","last_updated":"2025-08-01T12:25:21Z","snapshot_observed_at":"2026-08-07T14:18:30.406157Z","submitted_at":"2025-07-26T12:03:47Z","title":"HumanSAM: Classifying Human-centric Forgery Videos in Human Spatial, Appearance, and Motion Anomaly","version":2},"reference_index":5,"source":"pdf_text","source_observed_at":"2026-08-06T13:57:04.367406Z"},"links":{"citing_paper":"/paper/2507.19924"},"observation_digest":"sha256:5b3a8108aaa1e97b5ec3db62bafdb9e9e3c087307aee8d6dcf9e176fbf13a793","observation_id":"2e64a08b-e971-46f7-8353-420bfabf7d71","resolution":{"observed_at":"2026-08-06T13:57:04.367406Z","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":"2026-08-06T13:57:05.899465Z","title":"Emerg- ing properties in self-supervised vision transformers","venue":null,"work_id":"3861cf1e-cd90-46d9-bf84-2cf5126752ed","year":2021},"citing_paper":{"arxiv_id":"2507.19924","last_updated":"2025-08-01T12:25:21Z","snapshot_observed_at":"2026-08-07T14:18:30.406157Z","submitted_at":"2025-07-26T12:03:47Z","title":"HumanSAM: Classifying Human-centric Forgery Videos in Human Spatial, Appearance, and Motion Anomaly","version":2},"reference_index":6,"source":"pdf_text","source_observed_at":"2026-08-06T13:57:04.375813Z"},"links":{"citing_paper":"/paper/2507.19924"},"observation_digest":"sha256:97569b778aa09bac6bf96cbeefa8ac110537d02ed90554bd5a82d9fba09b700a","observation_id":"7f250038-88a4-4643-8ea2-14b9c1edab8f","resolution":{"observed_at":"2026-08-06T13:57:05.903863Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"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"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":null,"snapshot_observed_at":"2026-08-06T13:57:04.382597Z","title":"What matters in detecting ai-generated videos like sora? arXiv preprint arXiv:2406.19568, 2024","venue":null,"work_id":null,"year":2024},"citing_paper":{"arxiv_id":"2507.19924","last_updated":"2025-08-01T12:25:21Z","snapshot_observed_at":"2026-08-07T14:18:30.406157Z","submitted_at":"2025-07-26T12:03:47Z","title":"HumanSAM: Classifying Human-centric Forgery Videos in Human Spatial, Appearance, and Motion Anomaly","version":2},"reference_index":7,"source":"pdf_text","source_observed_at":"2026-08-06T13:57:04.382597Z"},"links":{"citing_paper":"/paper/2507.19924"},"observation_digest":"sha256:eab4322d1ebbe4d8793c32e8f0a23dfbb71048b1d46142dfdfb185885e292504","observation_id":"64bb309a-7cb6-4182-9dd9-658e6ad1a9ed","resolution":{"observed_at":"2026-08-06T13:57:04.382597Z","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":"2026-08-06T13:57:05.885005Z","title":"Multi-view clustering via deep concept factorization","venue":null,"work_id":"31e2eb5e-3f5e-488a-930f-e2cc4af389de","year":2021},"citing_paper":{"arxiv_id":"2507.19924","last_updated":"2025-08-01T12:25:21Z","snapshot_observed_at":"2026-08-07T14:18:30.406157Z","submitted_at":"2025-07-26T12:03:47Z","title":"HumanSAM: Classifying Human-centric Forgery Videos in Human Spatial, Appearance, and Motion Anomaly","version":2},"reference_index":8,"source":"pdf_text","source_observed_at":"2026-08-06T13:57:04.389105Z"},"links":{"citing_paper":"/paper/2507.19924"},"observation_digest":"sha256:11a518c0b91f5a64f2fb91cebeee06cc3a330645d8241f57978cc096f93e8611","observation_id":"58b24c88-9f7e-4bb5-aec2-36f3b8728ba1","resolution":{"observed_at":"2026-08-06T13:57:05.889542Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"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"}},{"citation":{"cited_paper":{"arxiv_id":"2502.02492","last_updated":"2025-05-26T13:56:07Z","snapshot_observed_at":"2026-08-04T22:35:38.752893Z","submitted_at":"2025-02-04T17:07:10Z","title":"VideoJAM: Joint Appearance-Motion Representations for Enhanced Motion Generation in Video Models","version":2},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2502.02492","snapshot_observed_at":"2026-08-06T13:57:04.394521Z","title":"Videojam: Joint appearance-motion representations for en- hanced motion generation in video models.arXiv preprint arXiv:2502.02492, 2025","venue":null,"work_id":null,"year":2025},"citing_paper":{"arxiv_id":"2507.19924","last_updated":"2025-08-01T12:25:21Z","snapshot_observed_at":"2026-08-07T14:18:30.406157Z","submitted_at":"2025-07-26T12:03:47Z","title":"HumanSAM: Classifying Human-centric Forgery Videos in Human Spatial, Appearance, and Motion Anomaly","version":2},"reference_index":9,"source":"pdf_text","source_observed_at":"2026-08-06T13:57:04.394521Z"},"links":{"cited_paper":"/paper/2502.02492","citing_paper":"/paper/2507.19924"},"observation_digest":"sha256:761dc85d29472a7c1b841dd738614be9364e0f6804e242539693170d949dcff2","observation_id":"0280e3ab-442d-4bc2-b5e5-35c36b402062","resolution":{"observed_at":"2026-08-06T13:57:04.394521Z","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":"2026-08-06T13:57:05.870948Z","title":"https://research.runwayml.com/gen2, 2023","venue":null,"work_id":"0514ce2a-dd15-4615-a2bb-a74df313e89e","year":2023},"citing_paper":{"arxiv_id":"2507.19924","last_updated":"2025-08-01T12:25:21Z","snapshot_observed_at":"2026-08-07T14:18:30.406157Z","submitted_at":"2025-07-26T12:03:47Z","title":"HumanSAM: Classifying Human-centric Forgery Videos in Human Spatial, Appearance, and Motion Anomaly","version":2},"reference_index":10,"source":"pdf_text","source_observed_at":"2026-08-06T13:57:04.399408Z"},"links":{"citing_paper":"/paper/2507.19924"},"observation_digest":"sha256:6333f9635208174ef0213acb3693506250cc40e2ed6ab6c78b5a4fec4af6a448","observation_id":"845f37cf-0abe-4362-9e26-f0291c5ed0d5","resolution":{"observed_at":"2026-08-06T13:57:05.875448Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"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"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-06T13:57:05.856331Z","title":"https://runwayml.com/research/introducing- gen-3-alpha, 2024","venue":null,"work_id":"67d6e9c4-a3cf-41be-8ede-8cfaf21f5a9d","year":2024},"citing_paper":{"arxiv_id":"2507.19924","last_updated":"2025-08-01T12:25:21Z","snapshot_observed_at":"2026-08-07T14:18:30.406157Z","submitted_at":"2025-07-26T12:03:47Z","title":"HumanSAM: Classifying Human-centric Forgery Videos in Human Spatial, Appearance, and Motion Anomaly","version":2},"reference_index":11,"source":"pdf_text","source_observed_at":"2026-08-06T13:57:04.405471Z"},"links":{"citing_paper":"/paper/2507.19924"},"observation_digest":"sha256:45e89c9ef5605e9b87e75037f16fa24a9146d2bc89940c3b1c7039e25bc3d734","observation_id":"6da0cb16-ba7a-4cb8-a9d9-c5f1cfa77306","resolution":{"observed_at":"2026-08-06T13:57:05.860555Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"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"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-06T13:57:05.839729Z","title":"Hierarchical fine-grained im- age forgery detection and localization","venue":null,"work_id":"57ac93d3-ac00-446a-9dd8-ee1dba439b78","year":2023},"citing_paper":{"arxiv_id":"2507.19924","last_updated":"2025-08-01T12:25:21Z","snapshot_observed_at":"2026-08-07T14:18:30.406157Z","submitted_at":"2025-07-26T12:03:47Z","title":"HumanSAM: Classifying Human-centric Forgery Videos in Human Spatial, Appearance, and Motion Anomaly","version":2},"reference_index":12,"source":"pdf_text","source_observed_at":"2026-08-06T13:57:04.410182Z"},"links":{"citing_paper":"/paper/2507.19924"},"observation_digest":"sha256:9fb6a7f7b365e43f9ea1e5bb6d799f0aa45c727e4ac1a1a4b929d5b702ef97d7","observation_id":"70fe0df4-8f2f-41cf-aefd-1473eb84e09e","resolution":{"observed_at":"2026-08-06T13:57:05.844655Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"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"}},{"citation":{"cited_paper":{"arxiv_id":"2407.07667","last_updated":"2024-07-10T13:46:08Z","snapshot_observed_at":"2026-08-07T00:56:39.117883Z","submitted_at":"2024-07-10T13:46:08Z","title":"VEnhancer: Generative Space-Time Enhancement for Video Generation","version":1},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2407.07667","snapshot_observed_at":"2026-08-06T13:57:04.416575Z","title":"Venhancer: Generative space-time enhancement for video generation.arXiv preprint arXiv:2407.07667, 2024","venue":null,"work_id":null,"year":2024},"citing_paper":{"arxiv_id":"2507.19924","last_updated":"2025-08-01T12:25:21Z","snapshot_observed_at":"2026-08-07T14:18:30.406157Z","submitted_at":"2025-07-26T12:03:47Z","title":"HumanSAM: Classifying Human-centric Forgery Videos in Human Spatial, Appearance, and Motion Anomaly","version":2},"reference_index":13,"source":"pdf_text","source_observed_at":"2026-08-06T13:57:04.416575Z"},"links":{"cited_paper":"/paper/2407.07667","citing_paper":"/paper/2507.19924"},"observation_digest":"sha256:d78c87e413dd2b79cb90757dc015586a105ee8def44c4aba87e53c9a8b8e9cfd","observation_id":"94936ad9-d07b-4b78-8bd8-73b6e9c6391c","resolution":{"observed_at":"2026-08-06T13:57:04.416575Z","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":"2026-08-06T13:57:05.825928Z","title":"Video dif- fusion models.Advances in Neural Information Processing Systems, 35:8633–8646, 2022","venue":null,"work_id":"d315302a-b8c0-4671-8217-9335da8083aa","year":2022},"citing_paper":{"arxiv_id":"2507.19924","last_updated":"2025-08-01T12:25:21Z","snapshot_observed_at":"2026-08-07T14:18:30.406157Z","submitted_at":"2025-07-26T12:03:47Z","title":"HumanSAM: Classifying Human-centric Forgery Videos in Human Spatial, Appearance, and Motion Anomaly","version":2},"reference_index":14,"source":"pdf_text","source_observed_at":"2026-08-06T13:57:04.423504Z"},"links":{"citing_paper":"/paper/2507.19924"},"observation_digest":"sha256:49b8cf8309a17665d1a684e894d5f6161aa24f33d1f209d93c312684c4896592","observation_id":"7b8c3aaa-a584-46d6-bb68-22380bfc196d","resolution":{"observed_at":"2026-08-06T13:57:05.830261Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"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"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-06T13:57:05.809946Z","title":"Vbench: Comprehensive bench- mark suite for video generative models","venue":null,"work_id":"a4793f52-507f-4926-a037-8066ca1bfe66","year":2024},"citing_paper":{"arxiv_id":"2507.19924","last_updated":"2025-08-01T12:25:21Z","snapshot_observed_at":"2026-08-07T14:18:30.406157Z","submitted_at":"2025-07-26T12:03:47Z","title":"HumanSAM: Classifying Human-centric Forgery Videos in Human Spatial, Appearance, and Motion Anomaly","version":2},"reference_index":15,"source":"pdf_text","source_observed_at":"2026-08-06T13:57:04.428125Z"},"links":{"citing_paper":"/paper/2507.19924"},"observation_digest":"sha256:47d46a70e8eadde0952719153039cb1970adfb849e5760baf7ad1d94e5248b0d","observation_id":"da56d66e-7c5c-49fd-baf6-3679cf1c64c4","resolution":{"observed_at":"2026-08-06T13:57:05.815123Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"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"}},{"citation":{"cited_paper":{"arxiv_id":"2001.08361","last_updated":"2020-01-23T03:59:20Z","snapshot_observed_at":"2026-07-06T08:52:12.656082Z","submitted_at":"2020-01-23T03:59:20Z","title":"Scaling Laws for Neural Language Models","version":1},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2001.08361","snapshot_observed_at":"2026-08-06T13:57:04.433162Z","title":"Scaling laws for neural language models.arXiv preprint arXiv:2001.08361,","venue":null,"work_id":null,"year":2001},"citing_paper":{"arxiv_id":"2507.19924","last_updated":"2025-08-01T12:25:21Z","snapshot_observed_at":"2026-08-07T14:18:30.406157Z","submitted_at":"2025-07-26T12:03:47Z","title":"HumanSAM: Classifying Human-centric Forgery Videos in Human Spatial, Appearance, and Motion Anomaly","version":2},"reference_index":16,"source":"pdf_text","source_observed_at":"2026-08-06T13:57:04.433162Z"},"links":{"cited_paper":"/paper/2001.08361","citing_paper":"/paper/2507.19924"},"observation_digest":"sha256:d76e2ef8228673d5d0290cf74de785945b04c98387b7ed2e12edf5fb27e2318b","observation_id":"85f54177-4cf0-4f12-aa33-e0fa0fb4ffb3","resolution":{"observed_at":"2026-08-06T13:57:04.433162Z","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":"2026-08-06T13:57:05.793585Z","title":"Large-scale video classification with convolutional neural networks","venue":null,"work_id":"6f68f1ad-62a7-42f8-8fa0-e2dbc72b3dd0","year":2014},"citing_paper":{"arxiv_id":"2507.19924","last_updated":"2025-08-01T12:25:21Z","snapshot_observed_at":"2026-08-07T14:18:30.406157Z","submitted_at":"2025-07-26T12:03:47Z","title":"HumanSAM: Classifying Human-centric Forgery Videos in Human Spatial, Appearance, and Motion Anomaly","version":2},"reference_index":17,"source":"pdf_text","source_observed_at":"2026-08-06T13:57:04.437534Z"},"links":{"citing_paper":"/paper/2507.19924"},"observation_digest":"sha256:d1de3a8170a72e8ba1a6b93bc6221f899a2a6138010af2064cfb97e77433661d","observation_id":"4d053b37-c262-4f75-ad1d-a5ce7925aa9e","resolution":{"observed_at":"2026-08-06T13:57:05.799000Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"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"}},{"citation":{"cited_paper":{"arxiv_id":"1705.06950","last_updated":"2017-05-19T12:07:01Z","snapshot_observed_at":"2026-08-08T17:46:50.107463Z","submitted_at":"2017-05-19T12:07:01Z","title":"The Kinetics Human Action Video Dataset","version":1},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"1705.06950","snapshot_observed_at":"2026-08-06T13:57:04.441894Z","title":"The kinetics hu- man action video dataset.arXiv preprint arXiv:1705.06950,","venue":null,"work_id":null,"year":null},"citing_paper":{"arxiv_id":"2507.19924","last_updated":"2025-08-01T12:25:21Z","snapshot_observed_at":"2026-08-07T14:18:30.406157Z","submitted_at":"2025-07-26T12:03:47Z","title":"HumanSAM: Classifying Human-centric Forgery Videos in Human Spatial, Appearance, and Motion Anomaly","version":2},"reference_index":18,"source":"pdf_text","source_observed_at":"2026-08-06T13:57:04.441894Z"},"links":{"cited_paper":"/paper/1705.06950","citing_paper":"/paper/2507.19924"},"observation_digest":"sha256:fc661bd0f6a089b1bab9705ab3419b81394ee54b5235eb97386e716c53f43174","observation_id":"cfe64271-82bd-4516-be08-ccb7ba6da883","resolution":{"observed_at":"2026-08-06T13:57:04.441894Z","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":"2026-08-06T13:57:05.779349Z","title":"https://klingai.kuaishou.com/, 2024","venue":null,"work_id":"9e00c8c5-f999-4ee9-bfa7-f6b0c4f23230","year":2024},"citing_paper":{"arxiv_id":"2507.19924","last_updated":"2025-08-01T12:25:21Z","snapshot_observed_at":"2026-08-07T14:18:30.406157Z","submitted_at":"2025-07-26T12:03:47Z","title":"HumanSAM: Classifying Human-centric Forgery Videos in Human Spatial, Appearance, and Motion Anomaly","version":2},"reference_index":19,"source":"pdf_text","source_observed_at":"2026-08-06T13:57:04.446952Z"},"links":{"citing_paper":"/paper/2507.19924"},"observation_digest":"sha256:3858911f5d94e88a1d232e4d9b7e38886dafd06b349e4a7f9893582ec93df55e","observation_id":"b02b280a-75ac-4065-8944-5eab1635068e","resolution":{"observed_at":"2026-08-06T13:57:05.783357Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"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"}},{"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":"2026-08-06T13:57:04.450911Z","title":"Hunyuanvideo: A systematic framework for large video generative models.arXiv preprint arXiv:2412.03603, 2024","venue":null,"work_id":null,"year":2024},"citing_paper":{"arxiv_id":"2507.19924","last_updated":"2025-08-01T12:25:21Z","snapshot_observed_at":"2026-08-07T14:18:30.406157Z","submitted_at":"2025-07-26T12:03:47Z","title":"HumanSAM: Classifying Human-centric Forgery Videos in Human Spatial, Appearance, and Motion Anomaly","version":2},"reference_index":20,"source":"pdf_text","source_observed_at":"2026-08-06T13:57:04.450911Z"},"links":{"cited_paper":"/paper/2412.03603","citing_paper":"/paper/2507.19924"},"observation_digest":"sha256:b9376b6b6f103c854418a7f981d3f69dd21be48d5580eb26b0e18ea442bc7ce8","observation_id":"f421f113-060f-4d27-b2a3-9fed35ee963c","resolution":{"observed_at":"2026-08-06T13:57:04.450911Z","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":"2026-08-06T13:57:05.765190Z","title":"https://pika.art, 2024","venue":null,"work_id":"2505d537-db97-45e7-8c67-a4b8c38087b4","year":2024},"citing_paper":{"arxiv_id":"2507.19924","last_updated":"2025-08-01T12:25:21Z","snapshot_observed_at":"2026-08-07T14:18:30.406157Z","submitted_at":"2025-07-26T12:03:47Z","title":"HumanSAM: Classifying Human-centric Forgery Videos in Human Spatial, Appearance, and Motion Anomaly","version":2},"reference_index":21,"source":"pdf_text","source_observed_at":"2026-08-06T13:57:04.455497Z"},"links":{"citing_paper":"/paper/2507.19924"},"observation_digest":"sha256:9bf9cf515a43cf2472beed6b482c7e036ba87f93f593784bacddaae77d72c7d8","observation_id":"8c46eacd-70eb-4ad5-8560-117c253831ab","resolution":{"observed_at":"2026-08-06T13:57:05.769476Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"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"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-06T13:57:05.750450Z","title":"Learning blind video temporal consistency","venue":null,"work_id":"dec0cd9e-26b5-4868-8d7c-0258dcfc3157","year":2018},"citing_paper":{"arxiv_id":"2507.19924","last_updated":"2025-08-01T12:25:21Z","snapshot_observed_at":"2026-08-07T14:18:30.406157Z","submitted_at":"2025-07-26T12:03:47Z","title":"HumanSAM: Classifying Human-centric Forgery Videos in Human Spatial, Appearance, and Motion Anomaly","version":2},"reference_index":22,"source":"pdf_text","source_observed_at":"2026-08-06T13:57:04.461021Z"},"links":{"citing_paper":"/paper/2507.19924"},"observation_digest":"sha256:1175e7061e822cee12abd9c17a11bf938d34a7ce3543014c9df2b3d62a9b8748","observation_id":"7e64a9d5-23c8-487b-be20-3ef31ac4909a","resolution":{"observed_at":"2026-08-06T13:57:05.755560Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"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"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-06T13:57:05.736299Z","title":"Blind video temporal consistency via deep video prior.Advances in Neu- ral Information Processing Systems, 33:1083–1093, 2020","venue":null,"work_id":"cc93e253-8932-4a51-bbeb-418bfd6a9d71","year":2020},"citing_paper":{"arxiv_id":"2507.19924","last_updated":"2025-08-01T12:25:21Z","snapshot_observed_at":"2026-08-07T14:18:30.406157Z","submitted_at":"2025-07-26T12:03:47Z","title":"HumanSAM: Classifying Human-centric Forgery Videos in Human Spatial, Appearance, and Motion Anomaly","version":2},"reference_index":23,"source":"pdf_text","source_observed_at":"2026-08-06T13:57:04.465912Z"},"links":{"citing_paper":"/paper/2507.19924"},"observation_digest":"sha256:087541f69a6c7eb6ee38cd11f22495ba7716e3ef3a8ce7946e3834d56b1f88a2","observation_id":"c61b6694-e3d1-43af-a7b2-759fd2462bfb","resolution":{"observed_at":"2026-08-06T13:57:05.740997Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"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"}},{"citation":{"cited_paper":{"arxiv_id":"2407.08428","last_updated":"2024-07-11T12:09:05Z","snapshot_observed_at":"2026-08-04T00:06:53.740379Z","submitted_at":"2024-07-11T12:09:05Z","title":"A Comprehensive Survey on Human Video Generation: Challenges, Methods, and Insights","version":1},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2407.08428","snapshot_observed_at":"2026-08-06T13:57:04.471534Z","title":"A comprehensive survey on human video gener- ation: Challenges, methods, and insights.arXiv preprint arXiv:2407.08428, 2024","venue":null,"work_id":null,"year":2024},"citing_paper":{"arxiv_id":"2507.19924","last_updated":"2025-08-01T12:25:21Z","snapshot_observed_at":"2026-08-07T14:18:30.406157Z","submitted_at":"2025-07-26T12:03:47Z","title":"HumanSAM: Classifying Human-centric Forgery Videos in Human Spatial, Appearance, and Motion Anomaly","version":2},"reference_index":24,"source":"pdf_text","source_observed_at":"2026-08-06T13:57:04.471534Z"},"links":{"cited_paper":"/paper/2407.08428","citing_paper":"/paper/2507.19924"},"observation_digest":"sha256:ed93d26b218aa67d87a5f8a1aba3799b64f1405f6b3cebb58759314ab47b8556","observation_id":"dd1b183c-25e4-49d0-8094-ec7142a15b1c","resolution":{"observed_at":"2026-08-06T13:57:04.471534Z","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":"2026-08-06T13:57:05.721812Z","title":"Unmasked teacher: Towards training-efficient video foundation models","venue":null,"work_id":"6349829b-68fa-4c4f-aa70-d777d504b975","year":2023},"citing_paper":{"arxiv_id":"2507.19924","last_updated":"2025-08-01T12:25:21Z","snapshot_observed_at":"2026-08-07T14:18:30.406157Z","submitted_at":"2025-07-26T12:03:47Z","title":"HumanSAM: Classifying Human-centric Forgery Videos in Human Spatial, Appearance, and Motion Anomaly","version":2},"reference_index":25,"source":"pdf_text","source_observed_at":"2026-08-06T13:57:04.476938Z"},"links":{"citing_paper":"/paper/2507.19924"},"observation_digest":"sha256:f8fa3959bb16828ef4b1df7652b1ac46f5f0e439e5965bcb1c12266030f33522","observation_id":"f9dd9395-673c-4978-ae73-d7dcf938d604","resolution":{"observed_at":"2026-08-06T13:57:05.725849Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"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"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-06T13:57:05.706878Z","title":"Evalcrafter: Benchmarking and eval- uating large video generation models","venue":null,"work_id":"1eb6a7a1-c8d4-468e-bf31-e7beaebda47f","year":2024},"citing_paper":{"arxiv_id":"2507.19924","last_updated":"2025-08-01T12:25:21Z","snapshot_observed_at":"2026-08-07T14:18:30.406157Z","submitted_at":"2025-07-26T12:03:47Z","title":"HumanSAM: Classifying Human-centric Forgery Videos in Human Spatial, Appearance, and Motion Anomaly","version":2},"reference_index":26,"source":"pdf_text","source_observed_at":"2026-08-06T13:57:04.481328Z"},"links":{"citing_paper":"/paper/2507.19924"},"observation_digest":"sha256:11829df360b864fdeb32be9a5770bea6d0ae7a9a5ddf144a6cebf9f1c7ecbc23","observation_id":"8163d72d-4924-4546-803d-3539a645ca32","resolution":{"observed_at":"2026-08-06T13:57:05.711433Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"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"}},{"citation":{"cited_paper":{"arxiv_id":"2502.10248","last_updated":"2025-02-24T10:12:11Z","snapshot_observed_at":"2026-07-06T02:11:23.670680Z","submitted_at":"2025-02-14T15:58:10Z","title":"Step-Video-T2V Technical Report: The Practice, Challenges, and Future of Video Foundation Model","version":3},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2502.10248","snapshot_observed_at":"2026-08-06T13:57:04.485515Z","title":"Step-video-t2v technical re- port: The practice, challenges, and future of video founda- tion model.arXiv preprint arXiv:2502.10248, 2025","venue":null,"work_id":null,"year":2025},"citing_paper":{"arxiv_id":"2507.19924","last_updated":"2025-08-01T12:25:21Z","snapshot_observed_at":"2026-08-07T14:18:30.406157Z","submitted_at":"2025-07-26T12:03:47Z","title":"HumanSAM: Classifying Human-centric Forgery Videos in Human Spatial, Appearance, and Motion Anomaly","version":2},"reference_index":27,"source":"pdf_text","source_observed_at":"2026-08-06T13:57:04.485515Z"},"links":{"cited_paper":"/paper/2502.10248","citing_paper":"/paper/2507.19924"},"observation_digest":"sha256:caea79e271ce77adbcabf6205a9d0b3d41da42b88e3336bda9e5f611d34195fb","observation_id":"0e04851a-2b60-4801-93f4-3ca2c757aab9","resolution":{"observed_at":"2026-08-06T13:57:04.485515Z","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":"2026-08-06T13:57:05.692376Z","title":"https://hailuoai.com/video, 2024","venue":null,"work_id":"9eb8e10f-1b8f-4c7c-b080-789fa0f81fde","year":2024},"citing_paper":{"arxiv_id":"2507.19924","last_updated":"2025-08-01T12:25:21Z","snapshot_observed_at":"2026-08-07T14:18:30.406157Z","submitted_at":"2025-07-26T12:03:47Z","title":"HumanSAM: Classifying Human-centric Forgery Videos in Human Spatial, Appearance, and Motion Anomaly","version":2},"reference_index":28,"source":"pdf_text","source_observed_at":"2026-08-06T13:57:04.490662Z"},"links":{"citing_paper":"/paper/2507.19924"},"observation_digest":"sha256:b4744a6b086e5ed55fdeb2f51a53da88b966ce866d8838b23ab125170a477533","observation_id":"f47b92eb-aea3-42b5-b85d-bd2e01c2244f","resolution":{"observed_at":"2026-08-06T13:57:05.696641Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"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"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-06T13:57:05.678036Z","title":"Towards uni- versal fake image detectors that generalize across genera- tive models","venue":null,"work_id":"14aada96-30bd-462f-9778-ecba8cd105d4","year":2023},"citing_paper":{"arxiv_id":"2507.19924","last_updated":"2025-08-01T12:25:21Z","snapshot_observed_at":"2026-08-07T14:18:30.406157Z","submitted_at":"2025-07-26T12:03:47Z","title":"HumanSAM: Classifying Human-centric Forgery Videos in Human Spatial, Appearance, and Motion Anomaly","version":2},"reference_index":29,"source":"pdf_text","source_observed_at":"2026-08-06T13:57:04.495175Z"},"links":{"citing_paper":"/paper/2507.19924"},"observation_digest":"sha256:603afac7b4676a60bcfd87fc79bf5ddb9bc4659990f82b473c43c64315df6182","observation_id":"da026e46-ccdd-4afc-af0f-5b1396cef422","resolution":{"observed_at":"2026-08-06T13:57:05.682510Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"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"}},{"citation":{"cited_paper":{"arxiv_id":"2304.07193","last_updated":"2024-02-02T10:24:09Z","snapshot_observed_at":"2026-08-06T05:58:29.182448Z","submitted_at":"2023-04-14T15:12:19Z","title":"DINOv2: Learning Robust Visual Features without Supervision","version":2},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2304.07193","snapshot_observed_at":"2026-08-06T13:57:04.499775Z","title":"Dinov2: Learning robust visual features without supervision","venue":null,"work_id":null,"year":2023},"citing_paper":{"arxiv_id":"2507.19924","last_updated":"2025-08-01T12:25:21Z","snapshot_observed_at":"2026-08-07T14:18:30.406157Z","submitted_at":"2025-07-26T12:03:47Z","title":"HumanSAM: Classifying Human-centric Forgery Videos in Human Spatial, Appearance, and Motion Anomaly","version":2},"reference_index":30,"source":"pdf_text","source_observed_at":"2026-08-06T13:57:04.499775Z"},"links":{"cited_paper":"/paper/2304.07193","citing_paper":"/paper/2507.19924"},"observation_digest":"sha256:d275317fb85f7a58c882fbd31526e5248afe13218d4bd2dde67e7381cb678440","observation_id":"821ae6ed-6fa6-44a3-8b01-a803ae878be2","resolution":{"observed_at":"2026-08-06T13:57:04.499775Z","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":"2026-08-06T13:57:05.663937Z","title":"Fine-grained bipar- tite concept factorization for clustering","venue":null,"work_id":"28acfd74-2952-448c-9c01-3ac9a2e044d6","year":2024},"citing_paper":{"arxiv_id":"2507.19924","last_updated":"2025-08-01T12:25:21Z","snapshot_observed_at":"2026-08-07T14:18:30.406157Z","submitted_at":"2025-07-26T12:03:47Z","title":"HumanSAM: Classifying Human-centric Forgery Videos in Human Spatial, Appearance, and Motion Anomaly","version":2},"reference_index":31,"source":"pdf_text","source_observed_at":"2026-08-06T13:57:04.505202Z"},"links":{"citing_paper":"/paper/2507.19924"},"observation_digest":"sha256:728a988a9156c4cc710e36c3b598133e56d6ea9a0d8b09af419ba381d1dc9613","observation_id":"a9c22209-7f9e-4af3-8662-3a7373fd2ca7","resolution":{"observed_at":"2026-08-06T13:57:05.668269Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"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"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-06T13:57:05.649252Z","title":"Fatezero: Fus- ing attentions for zero-shot text-based video editing","venue":null,"work_id":"8468ce39-5ab3-4592-a40d-1628828abed0","year":2023},"citing_paper":{"arxiv_id":"2507.19924","last_updated":"2025-08-01T12:25:21Z","snapshot_observed_at":"2026-08-07T14:18:30.406157Z","submitted_at":"2025-07-26T12:03:47Z","title":"HumanSAM: Classifying Human-centric Forgery Videos in Human Spatial, Appearance, and Motion Anomaly","version":2},"reference_index":32,"source":"pdf_text","source_observed_at":"2026-08-06T13:57:04.509830Z"},"links":{"citing_paper":"/paper/2507.19924"},"observation_digest":"sha256:7c275d64ffbc46e93668b7df7d495ed24a6c0fc69051f7cc698e10abe4dc2b7a","observation_id":"93fb96ba-6863-449a-86d3-2301dd1a20c4","resolution":{"observed_at":"2026-08-06T13:57:05.654428Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"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"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-06T13:57:05.634154Z","title":"Thinking in frequency: Face forgery detection by min- ing frequency-aware clues","venue":null,"work_id":"a2d80c51-e89e-4916-b030-048928c981c6","year":2020},"citing_paper":{"arxiv_id":"2507.19924","last_updated":"2025-08-01T12:25:21Z","snapshot_observed_at":"2026-08-07T14:18:30.406157Z","submitted_at":"2025-07-26T12:03:47Z","title":"HumanSAM: Classifying Human-centric Forgery Videos in Human Spatial, Appearance, and Motion Anomaly","version":2},"reference_index":33,"source":"pdf_text","source_observed_at":"2026-08-06T13:57:04.516102Z"},"links":{"citing_paper":"/paper/2507.19924"},"observation_digest":"sha256:ef539aea5645ddf5db78b650e15f2955984022805f2023c324946d2eea2fea5f","observation_id":"fb886f94-cfd2-4bc8-9f3c-54366cba5604","resolution":{"observed_at":"2026-08-06T13:57:05.638996Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"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"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-06T13:57:05.618674Z","title":"Learning transferable visual models from natural language supervi- sion","venue":null,"work_id":"74476cf6-9148-44c7-8a65-02f5b674a8be","year":2021},"citing_paper":{"arxiv_id":"2507.19924","last_updated":"2025-08-01T12:25:21Z","snapshot_observed_at":"2026-08-07T14:18:30.406157Z","submitted_at":"2025-07-26T12:03:47Z","title":"HumanSAM: Classifying Human-centric Forgery Videos in Human Spatial, Appearance, and Motion Anomaly","version":2},"reference_index":34,"source":"pdf_text","source_observed_at":"2026-08-06T13:57:04.520890Z"},"links":{"citing_paper":"/paper/2507.19924"},"observation_digest":"sha256:4e6193e026943493b2532fb7db102d020ba0e474fae9945dddbe2a5db6437390","observation_id":"b1761874-bd64-4f16-ac63-fbdaafcbc9fb","resolution":{"observed_at":"2026-08-06T13:57:05.622912Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"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"}},{"citation":{"cited_paper":{"arxiv_id":"2408.00714","last_updated":"2024-10-28T16:37:57Z","snapshot_observed_at":"2026-07-06T18:55:41.459417Z","submitted_at":"2024-08-01T17:00:08Z","title":"SAM 2: Segment Anything in Images and Videos","version":2},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2408.00714","snapshot_observed_at":"2026-08-06T13:57:04.526479Z","title":"Sam 2: Segment anything in images and videos.arXiv preprint arXiv:2408.00714, 2024","venue":null,"work_id":null,"year":2024},"citing_paper":{"arxiv_id":"2507.19924","last_updated":"2025-08-01T12:25:21Z","snapshot_observed_at":"2026-08-07T14:18:30.406157Z","submitted_at":"2025-07-26T12:03:47Z","title":"HumanSAM: Classifying Human-centric Forgery Videos in Human Spatial, Appearance, and Motion Anomaly","version":2},"reference_index":35,"source":"pdf_text","source_observed_at":"2026-08-06T13:57:04.526479Z"},"links":{"cited_paper":"/paper/2408.00714","citing_paper":"/paper/2507.19924"},"observation_digest":"sha256:fdf5c11aa01c4bfe06a67e815da11a7decaba270558641fe64edc3e33d9a4662","observation_id":"f62dc0ff-c991-4cfa-84f2-0a928dc8319e","resolution":{"observed_at":"2026-08-06T13:57:04.526479Z","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":"2026-08-06T13:57:05.599971Z","title":"De-fake: Detection and attribution of fake images generated by text- to-image generation models","venue":null,"work_id":"c8d37edc-d63c-4a85-855e-88e80d15bbf8","year":2023},"citing_paper":{"arxiv_id":"2507.19924","last_updated":"2025-08-01T12:25:21Z","snapshot_observed_at":"2026-08-07T14:18:30.406157Z","submitted_at":"2025-07-26T12:03:47Z","title":"HumanSAM: Classifying Human-centric Forgery Videos in Human Spatial, Appearance, and Motion Anomaly","version":2},"reference_index":36,"source":"pdf_text","source_observed_at":"2026-08-06T13:57:04.532042Z"},"links":{"citing_paper":"/paper/2507.19924"},"observation_digest":"sha256:8521db210e63a9b075ba4e081bf0421508ce7fbcaa23f8ad15e1a827ce6266ea","observation_id":"870faa30-2263-46f5-bbcd-a907997c7f59","resolution":{"observed_at":"2026-08-06T13:57:05.607761Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"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"}},{"citation":{"cited_paper":{"arxiv_id":"2501.08994","last_updated":"2025-01-15T18:20:37Z","snapshot_observed_at":"2026-08-04T06:44:30.960627Z","submitted_at":"2025-01-15T18:20:37Z","title":"RepVideo: Rethinking Cross-Layer Representation for Video Generation","version":1},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2501.08994","snapshot_observed_at":"2026-08-06T13:57:04.536373Z","title":"Repvideo: Rethinking cross- layer representation for video generation.arXiv preprint arXiv:2501.08994, 2025","venue":null,"work_id":null,"year":2025},"citing_paper":{"arxiv_id":"2507.19924","last_updated":"2025-08-01T12:25:21Z","snapshot_observed_at":"2026-08-07T14:18:30.406157Z","submitted_at":"2025-07-26T12:03:47Z","title":"HumanSAM: Classifying Human-centric Forgery Videos in Human Spatial, Appearance, and Motion Anomaly","version":2},"reference_index":37,"source":"pdf_text","source_observed_at":"2026-08-06T13:57:04.536373Z"},"links":{"cited_paper":"/paper/2501.08994","citing_paper":"/paper/2507.19924"},"observation_digest":"sha256:a181e48eca245239bf10e0b65bdab77ec9f7491bb3c887033ffaf6bcb94f284d","observation_id":"9621853d-e808-4cbe-a1cf-788173b347ee","resolution":{"observed_at":"2026-08-06T13:57:04.536373Z","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":"2026-08-06T13:57:05.555085Z","title":"Two-stream con- volutional networks for action recognition in videos.Ad- vances in neural information processing systems, 27, 2014","venue":null,"work_id":"bb6c93d2-ad9b-49b4-b0fb-684fb8cd655a","year":2014},"citing_paper":{"arxiv_id":"2507.19924","last_updated":"2025-08-01T12:25:21Z","snapshot_observed_at":"2026-08-07T14:18:30.406157Z","submitted_at":"2025-07-26T12:03:47Z","title":"HumanSAM: Classifying Human-centric Forgery Videos in Human Spatial, Appearance, and Motion Anomaly","version":2},"reference_index":38,"source":"pdf_text","source_observed_at":"2026-08-06T13:57:04.541661Z"},"links":{"citing_paper":"/paper/2507.19924"},"observation_digest":"sha256:885e886757a7019839c4551e08ba034a005a74538a1c79ad7c1346d51754406d","observation_id":"7b48b4a7-df27-410b-9331-5871ccd1d82b","resolution":{"observed_at":"2026-08-06T13:57:05.573379Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"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"}},{"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":"2026-08-06T13:57:04.546640Z","title":"Denoising diffusion implicit models.arXiv preprint arXiv:2010.02502, 2020","venue":null,"work_id":null,"year":2010},"citing_paper":{"arxiv_id":"2507.19924","last_updated":"2025-08-01T12:25:21Z","snapshot_observed_at":"2026-08-07T14:18:30.406157Z","submitted_at":"2025-07-26T12:03:47Z","title":"HumanSAM: Classifying Human-centric Forgery Videos in Human Spatial, Appearance, and Motion Anomaly","version":2},"reference_index":39,"source":"pdf_text","source_observed_at":"2026-08-06T13:57:04.546640Z"},"links":{"cited_paper":"/paper/2010.02502","citing_paper":"/paper/2507.19924"},"observation_digest":"sha256:2e91753545ade9c9213fcbd29df62c82ca6ec824909aea5054b8afbc7e2e6941","observation_id":"b3b02bf2-9bb3-4da6-8583-009b74dded78","resolution":{"observed_at":"2026-08-06T13:57:04.546640Z","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":"2026-08-06T13:57:05.520954Z","title":"On learn- ing multi-modal forgery representation for diffusion gener- ated video detection","venue":null,"work_id":"59b7760d-abce-4cf5-a8a0-03d1783dd6bc","year":2024},"citing_paper":{"arxiv_id":"2507.19924","last_updated":"2025-08-01T12:25:21Z","snapshot_observed_at":"2026-08-07T14:18:30.406157Z","submitted_at":"2025-07-26T12:03:47Z","title":"HumanSAM: Classifying Human-centric Forgery Videos in Human Spatial, Appearance, and Motion Anomaly","version":2},"reference_index":40,"source":"pdf_text","source_observed_at":"2026-08-06T13:57:04.553144Z"},"links":{"citing_paper":"/paper/2507.19924"},"observation_digest":"sha256:41f071548d5fba93c58a92426b7084fc0d8047dc276203decac31198ed8a8d52","observation_id":"ff065fc5-aca2-4433-a52b-9422068c549c","resolution":{"observed_at":"2026-08-06T13:57:05.537567Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"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"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-06T13:57:05.477211Z","title":"Rethinking the up-sampling op- erations in cnn-based generative network for generalizable deepfake detection","venue":null,"work_id":"8203601c-862c-4660-87bf-d97ea8dc5326","year":2024},"citing_paper":{"arxiv_id":"2507.19924","last_updated":"2025-08-01T12:25:21Z","snapshot_observed_at":"2026-08-07T14:18:30.406157Z","submitted_at":"2025-07-26T12:03:47Z","title":"HumanSAM: Classifying Human-centric Forgery Videos in Human Spatial, Appearance, and Motion Anomaly","version":2},"reference_index":41,"source":"pdf_text","source_observed_at":"2026-08-06T13:57:04.557530Z"},"links":{"citing_paper":"/paper/2507.19924"},"observation_digest":"sha256:76b37fef4a7c85e89f9db8b3d909b0591b030a43c7da9872b51965322ab35027","observation_id":"ddf49aac-e658-4285-8aff-279af00150c0","resolution":{"observed_at":"2026-08-06T13:57:05.492029Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"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"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":null,"snapshot_observed_at":"2026-08-06T13:57:04.561628Z","title":"Raft: Recurrent all-pairs field transforms for optical flow","venue":null,"work_id":null,"year":2020},"citing_paper":{"arxiv_id":"2507.19924","last_updated":"2025-08-01T12:25:21Z","snapshot_observed_at":"2026-08-07T14:18:30.406157Z","submitted_at":"2025-07-26T12:03:47Z","title":"HumanSAM: Classifying Human-centric Forgery Videos in Human Spatial, Appearance, and Motion Anomaly","version":2},"reference_index":42,"source":"pdf_text","source_observed_at":"2026-08-06T13:57:04.561628Z"},"links":{"citing_paper":"/paper/2507.19924"},"observation_digest":"sha256:c1e39526ea8f0c0a0c9aabaf76fb352879c6d467ba88767626ed56b2fc19c7ef","observation_id":"13941333-9d54-41fb-9b57-feb3f5f9e977","resolution":{"observed_at":"2026-08-06T13:57:04.561628Z","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":null,"pith_arxiv_id":null,"snapshot_observed_at":"2026-08-06T13:57:04.567292Z","title":"Learning spatiotemporal features with 3d convolutional networks","venue":null,"work_id":null,"year":null},"citing_paper":{"arxiv_id":"2507.19924","last_updated":"2025-08-01T12:25:21Z","snapshot_observed_at":"2026-08-07T14:18:30.406157Z","submitted_at":"2025-07-26T12:03:47Z","title":"HumanSAM: Classifying Human-centric Forgery Videos in Human Spatial, Appearance, and Motion Anomaly","version":2},"reference_index":43,"source":"pdf_text","source_observed_at":"2026-08-06T13:57:04.567292Z"},"links":{"citing_paper":"/paper/2507.19924"},"observation_digest":"sha256:462a0a92d868bab2923458ad2328d8654000edd04aa9f3a10a134c7393dfbc94","observation_id":"4be8cc68-da9a-43cd-8a3e-857f7ec6dd84","resolution":{"observed_at":"2026-08-06T13:57:04.567292Z","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":"2026-08-06T13:57:05.427331Z","title":"https://wanxai.com/, 2025","venue":null,"work_id":"8d54fa6f-4aaa-41e1-874f-32790db7a54b","year":2025},"citing_paper":{"arxiv_id":"2507.19924","last_updated":"2025-08-01T12:25:21Z","snapshot_observed_at":"2026-08-07T14:18:30.406157Z","submitted_at":"2025-07-26T12:03:47Z","title":"HumanSAM: Classifying Human-centric Forgery Videos in Human Spatial, Appearance, and Motion Anomaly","version":2},"reference_index":44,"source":"pdf_text","source_observed_at":"2026-08-06T13:57:04.573144Z"},"links":{"citing_paper":"/paper/2507.19924"},"observation_digest":"sha256:1757bde568228a8d92863d2960de8b77ba9d4638c51a298776f09a15f2a36502","observation_id":"287fcf92-4dd3-43b5-9924-488cf36576a2","resolution":{"observed_at":"2026-08-06T13:57:05.433073Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"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"}},{"citation":{"cited_paper":{"arxiv_id":"2308.06571","last_updated":"2023-08-12T13:53:10Z","snapshot_observed_at":"2026-08-07T17:54:54.749604Z","submitted_at":"2023-08-12T13:53:10Z","title":"ModelScope Text-to-Video Technical Report","version":1},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2308.06571","snapshot_observed_at":"2026-08-06T13:57:04.577514Z","title":"Modelscope text-to-video technical report.arXiv preprint arXiv:2308.06571, 2023","venue":null,"work_id":null,"year":2023},"citing_paper":{"arxiv_id":"2507.19924","last_updated":"2025-08-01T12:25:21Z","snapshot_observed_at":"2026-08-07T14:18:30.406157Z","submitted_at":"2025-07-26T12:03:47Z","title":"HumanSAM: Classifying Human-centric Forgery Videos in Human Spatial, Appearance, and Motion Anomaly","version":2},"reference_index":45,"source":"pdf_text","source_observed_at":"2026-08-06T13:57:04.577514Z"},"links":{"cited_paper":"/paper/2308.06571","citing_paper":"/paper/2507.19924"},"observation_digest":"sha256:de87b2f1f7fdf729c561c34225bb2bf953585740dd3c717e996570efb7a72990","observation_id":"a54887a3-c13d-4434-864a-a3629b8b54ae","resolution":{"observed_at":"2026-08-06T13:57:04.577514Z","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":"2026-08-06T13:57:05.409648Z","title":"Cnn-generated images are surprisingly easy to spot","venue":null,"work_id":"79b118d4-49e6-4b61-9bac-99f8ad157128","year":2020},"citing_paper":{"arxiv_id":"2507.19924","last_updated":"2025-08-01T12:25:21Z","snapshot_observed_at":"2026-08-07T14:18:30.406157Z","submitted_at":"2025-07-26T12:03:47Z","title":"HumanSAM: Classifying Human-centric Forgery Videos in Human Spatial, Appearance, and Motion Anomaly","version":2},"reference_index":46,"source":"pdf_text","source_observed_at":"2026-08-06T13:57:04.582427Z"},"links":{"citing_paper":"/paper/2507.19924"},"observation_digest":"sha256:0b38c6eecec44e872e9de5bcc34543cb4fb68eba94e12dec42955c0b80c43288","observation_id":"576d992d-34f0-421b-9082-911fa33c8632","resolution":{"observed_at":"2026-08-06T13:57:05.414401Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"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"}},{"citation":{"cited_paper":{"arxiv_id":"2403.15377","last_updated":"2024-08-14T14:31:50Z","snapshot_observed_at":"2026-08-01T19:17:08.239976Z","submitted_at":"2024-03-22T17:57:42Z","title":"InternVideo2: Scaling Foundation Models for Multimodal Video Understanding","version":4},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2403.15377","snapshot_observed_at":"2026-08-06T13:57:04.588143Z","title":"Internvideo2: Scaling video foundation mod- els for multimodal video understanding.arXiv preprint arXiv:2403.15377, 2024","venue":null,"work_id":null,"year":2024},"citing_paper":{"arxiv_id":"2507.19924","last_updated":"2025-08-01T12:25:21Z","snapshot_observed_at":"2026-08-07T14:18:30.406157Z","submitted_at":"2025-07-26T12:03:47Z","title":"HumanSAM: Classifying Human-centric Forgery Videos in Human Spatial, Appearance, and Motion Anomaly","version":2},"reference_index":47,"source":"pdf_text","source_observed_at":"2026-08-06T13:57:04.588143Z"},"links":{"cited_paper":"/paper/2403.15377","citing_paper":"/paper/2507.19924"},"observation_digest":"sha256:b0a8800f3d8104afea45639044e77d2cae59588dcb4e7c0e59b5a57c57f2d824","observation_id":"49664a06-07a5-49c3-a551-aeaea6f87f3f","resolution":{"observed_at":"2026-08-06T13:57:04.588143Z","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":"2026-08-06T13:57:05.394267Z","title":"Dire for diffusion-generated image detection","venue":null,"work_id":"813b47f5-8d04-4620-870b-e2c917284b9f","year":2023},"citing_paper":{"arxiv_id":"2507.19924","last_updated":"2025-08-01T12:25:21Z","snapshot_observed_at":"2026-08-07T14:18:30.406157Z","submitted_at":"2025-07-26T12:03:47Z","title":"HumanSAM: Classifying Human-centric Forgery Videos in Human Spatial, Appearance, and Motion Anomaly","version":2},"reference_index":48,"source":"pdf_text","source_observed_at":"2026-08-06T13:57:04.592938Z"},"links":{"citing_paper":"/paper/2507.19924"},"observation_digest":"sha256:9aec6488cc18df179bceb2ac05990e0ef2b37e38f5836b44193b2238890e1eb3","observation_id":"0e70c6ca-39ac-40ef-883d-ea6abd2d7e81","resolution":{"observed_at":"2026-08-06T13:57:05.398528Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"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"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-06T13:57:05.380371Z","title":"Finepose: Fine- grained prompt-driven 3d human pose estimation via diffu- sion models","venue":null,"work_id":"3ff00d08-f0db-4b15-b6cc-5276137ea51c","year":2024},"citing_paper":{"arxiv_id":"2507.19924","last_updated":"2025-08-01T12:25:21Z","snapshot_observed_at":"2026-08-07T14:18:30.406157Z","submitted_at":"2025-07-26T12:03:47Z","title":"HumanSAM: Classifying Human-centric Forgery Videos in Human Spatial, Appearance, and Motion Anomaly","version":2},"reference_index":49,"source":"pdf_text","source_observed_at":"2026-08-06T13:57:04.599107Z"},"links":{"citing_paper":"/paper/2507.19924"},"observation_digest":"sha256:210037c012538adfcb30557273d9cb6821742270d4626a15fd2c43e974c2b139","observation_id":"090fe47b-0c5a-4758-9f2f-e54c96f3eafa","resolution":{"observed_at":"2026-08-06T13:57:05.384765Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"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"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-06T13:57:05.366216Z","title":"Fineparser: A fine-grained spatio-temporal action parser for human-centric action quality assessment","venue":null,"work_id":"50cb6cf2-2ef8-4ec6-b444-04a44cc24e03","year":2024},"citing_paper":{"arxiv_id":"2507.19924","last_updated":"2025-08-01T12:25:21Z","snapshot_observed_at":"2026-08-07T14:18:30.406157Z","submitted_at":"2025-07-26T12:03:47Z","title":"HumanSAM: Classifying Human-centric Forgery Videos in Human Spatial, Appearance, and Motion Anomaly","version":2},"reference_index":50,"source":"pdf_text","source_observed_at":"2026-08-06T13:57:04.603929Z"},"links":{"citing_paper":"/paper/2507.19924"},"observation_digest":"sha256:c9eef71355899c74006cdec4f13372046cde0a44393738d825c020eeca107858","observation_id":"19256ad0-f45e-466f-93aa-56d91f0e5c10","resolution":{"observed_at":"2026-08-06T13:57:05.370577Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"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"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-06T13:57:05.350949Z","title":"Human motion video genera- tion: A survey.Authorea Preprints, 2024","venue":null,"work_id":"af6a7fc5-2cff-4d47-ac43-2bc0cdaedb98","year":2024},"citing_paper":{"arxiv_id":"2507.19924","last_updated":"2025-08-01T12:25:21Z","snapshot_observed_at":"2026-08-07T14:18:30.406157Z","submitted_at":"2025-07-26T12:03:47Z","title":"HumanSAM: Classifying Human-centric Forgery Videos in Human Spatial, Appearance, and Motion Anomaly","version":2},"reference_index":51,"source":"pdf_text","source_observed_at":"2026-08-06T13:57:04.609892Z"},"links":{"citing_paper":"/paper/2507.19924"},"observation_digest":"sha256:35f2492919ec819173c01269132b3be2cd417be1cad60a9c9ae2ee27e8cef267","observation_id":"363e232b-631c-48df-87f7-df057363f3e8","resolution":{"observed_at":"2026-08-06T13:57:05.356199Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"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"}},{"citation":{"cited_paper":{"arxiv_id":"2412.14171","last_updated":"2025-07-02T21:00:36Z","snapshot_observed_at":"2026-07-06T02:11:23.670680Z","submitted_at":"2024-12-18T18:59:54Z","title":"Thinking in Space: How Multimodal Large Language Models See, Remember, and Recall Spaces","version":2},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2412.14171","snapshot_observed_at":"2026-08-06T13:57:04.614646Z","title":"Thinking in space: How mul- timodal large language models see, remember, and recall spaces.arXiv preprint arXiv:2412.14171, 2024","venue":null,"work_id":null,"year":2024},"citing_paper":{"arxiv_id":"2507.19924","last_updated":"2025-08-01T12:25:21Z","snapshot_observed_at":"2026-08-07T14:18:30.406157Z","submitted_at":"2025-07-26T12:03:47Z","title":"HumanSAM: Classifying Human-centric Forgery Videos in Human Spatial, Appearance, and Motion Anomaly","version":2},"reference_index":52,"source":"pdf_text","source_observed_at":"2026-08-06T13:57:04.614646Z"},"links":{"cited_paper":"/paper/2412.14171","citing_paper":"/paper/2507.19924"},"observation_digest":"sha256:da49db3839f56620157debe1238979e165b2e1f1f93465f2d6b6dd101c93509f","observation_id":"13aa1db2-34f6-40dc-a205-a5a4b6fae393","resolution":{"observed_at":"2026-08-06T13:57:04.614646Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2406.09414","last_updated":"2024-10-20T11:24:09Z","snapshot_observed_at":"2026-07-06T18:30:32.982860Z","submitted_at":"2024-06-13T17:59:56Z","title":"Depth Anything V2","version":2},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2406.09414","snapshot_observed_at":"2026-08-06T13:57:04.619264Z","title":"Depth any- thing v2.arXiv preprint arXiv:2406.09414, 2024","venue":null,"work_id":null,"year":2024},"citing_paper":{"arxiv_id":"2507.19924","last_updated":"2025-08-01T12:25:21Z","snapshot_observed_at":"2026-08-07T14:18:30.406157Z","submitted_at":"2025-07-26T12:03:47Z","title":"HumanSAM: Classifying Human-centric Forgery Videos in Human Spatial, Appearance, and Motion Anomaly","version":2},"reference_index":53,"source":"pdf_text","source_observed_at":"2026-08-06T13:57:04.619264Z"},"links":{"cited_paper":"/paper/2406.09414","citing_paper":"/paper/2507.19924"},"observation_digest":"sha256:89eae37caccf2948b4b9abe0c22ed44daf72ade75159f990f4f4fc95eb272840","observation_id":"b09e4455-06f3-4c0d-8aed-e113330ba988","resolution":{"observed_at":"2026-08-06T13:57:04.619264Z","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":"2026-08-06T13:57:04.624361Z","title":"Cogvideox: Text-to-video diffusion models with an expert transformer.arXiv preprint arXiv:2408.06072, 2024","venue":null,"work_id":null,"year":2024},"citing_paper":{"arxiv_id":"2507.19924","last_updated":"2025-08-01T12:25:21Z","snapshot_observed_at":"2026-08-07T14:18:30.406157Z","submitted_at":"2025-07-26T12:03:47Z","title":"HumanSAM: Classifying Human-centric Forgery Videos in Human Spatial, Appearance, and Motion Anomaly","version":2},"reference_index":54,"source":"pdf_text","source_observed_at":"2026-08-06T13:57:04.624361Z"},"links":{"cited_paper":"/paper/2408.06072","citing_paper":"/paper/2507.19924"},"observation_digest":"sha256:95aef889bbb36a701e7f787b930dc9a958005dd91586a42adfc996f7240499d0","observation_id":"f9c086cc-12cb-4a91-b418-29ca0d344268","resolution":{"observed_at":"2026-08-06T13:57:04.624361Z","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":"2026-08-06T13:57:05.335411Z","title":"Stedge: Self-training edge detection with multilayer teaching and regularization.IEEE Transactions on Neural Networks and Learning Systems, 2023","venue":null,"work_id":"5ed65f6a-d57c-401e-acca-4e6a95c83e03","year":2023},"citing_paper":{"arxiv_id":"2507.19924","last_updated":"2025-08-01T12:25:21Z","snapshot_observed_at":"2026-08-07T14:18:30.406157Z","submitted_at":"2025-07-26T12:03:47Z","title":"HumanSAM: Classifying Human-centric Forgery Videos in Human Spatial, Appearance, and Motion Anomaly","version":2},"reference_index":55,"source":"pdf_text","source_observed_at":"2026-08-06T13:57:04.629202Z"},"links":{"citing_paper":"/paper/2507.19924"},"observation_digest":"sha256:8e3a0de56f282a157aa8655d57a2310958d0c8865c8e55c67cfd819dc3762ace","observation_id":"d10aca95-b507-47c4-a89f-567b6b43f0d8","resolution":{"observed_at":"2026-08-06T13:57:05.340129Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"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"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-06T13:57:05.319616Z","title":"Diffusionedge: Diffusion probabilistic model for crisp edge detection","venue":null,"work_id":"14ef7781-adff-42d6-b6e8-6e7b0d0a86bd","year":2024},"citing_paper":{"arxiv_id":"2507.19924","last_updated":"2025-08-01T12:25:21Z","snapshot_observed_at":"2026-08-07T14:18:30.406157Z","submitted_at":"2025-07-26T12:03:47Z","title":"HumanSAM: Classifying Human-centric Forgery Videos in Human Spatial, Appearance, and Motion Anomaly","version":2},"reference_index":56,"source":"pdf_text","source_observed_at":"2026-08-06T13:57:04.633796Z"},"links":{"citing_paper":"/paper/2507.19924"},"observation_digest":"sha256:6f0c02f404a2b379ca2f046e44539d42f9ab1ddb8bf1f62fedbe8889bdbd50ee","observation_id":"17d2de94-5e86-40ab-8500-016ddbd3d6cf","resolution":{"observed_at":"2026-08-06T13:57:05.324381Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"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"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-06T13:57:05.304341Z","title":null,"venue":null,"work_id":"154e70e6-832e-4b46-988a-7849237d17a9","year":2024},"citing_paper":{"arxiv_id":"2507.19924","last_updated":"2025-08-01T12:25:21Z","snapshot_observed_at":"2026-08-07T14:18:30.406157Z","submitted_at":"2025-07-26T12:03:47Z","title":"HumanSAM: Classifying Human-centric Forgery Videos in Human Spatial, Appearance, and Motion Anomaly","version":2},"reference_index":57,"source":"pdf_text","source_observed_at":"2026-08-06T13:57:04.638325Z"},"links":{"citing_paper":"/paper/2507.19924"},"observation_digest":"sha256:76dcca2d350ec3b0d9910bf7cba57252a1da47433cf4df5323f251c241ccd2ab","observation_id":"0765e47d-901f-431b-8299-33569df632ae","resolution":{"observed_at":"2026-08-06T13:57:05.308841Z","resolver_source":"raw_fallback","status":"unresolved"},"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"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-06T13:57:05.286722Z","title":"Identity- preserving text-to-video generation by frequency decompo- sition","venue":null,"work_id":"fb7a0185-8b18-481d-ae76-50a46143e204","year":2025},"citing_paper":{"arxiv_id":"2507.19924","last_updated":"2025-08-01T12:25:21Z","snapshot_observed_at":"2026-08-07T14:18:30.406157Z","submitted_at":"2025-07-26T12:03:47Z","title":"HumanSAM: Classifying Human-centric Forgery Videos in Human Spatial, Appearance, and Motion Anomaly","version":2},"reference_index":58,"source":"pdf_text","source_observed_at":"2026-08-06T13:57:04.642650Z"},"links":{"citing_paper":"/paper/2507.19924"},"observation_digest":"sha256:07c7d1779aa7025742077d25692af3e8af4be6addfc0153f5dff6567a2e5049d","observation_id":"5c6c2acd-9100-4167-bd06-7298ef145230","resolution":{"observed_at":"2026-08-06T13:57:05.292534Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"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"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-06T13:57:05.270104Z","title":"Multi- scale video anomaly detection by multi-grained spatio- temporal representation learning","venue":null,"work_id":"880420dc-322d-4e5f-a5db-63992c2c51f0","year":2024},"citing_paper":{"arxiv_id":"2507.19924","last_updated":"2025-08-01T12:25:21Z","snapshot_observed_at":"2026-08-07T14:18:30.406157Z","submitted_at":"2025-07-26T12:03:47Z","title":"HumanSAM: Classifying Human-centric Forgery Videos in Human Spatial, Appearance, and Motion Anomaly","version":2},"reference_index":59,"source":"pdf_text","source_observed_at":"2026-08-06T13:57:04.648656Z"},"links":{"citing_paper":"/paper/2507.19924"},"observation_digest":"sha256:6ec489ba90a506f3f6cf8b07d809cbcd06f63303aae572ef9bf8b28f84d976cb","observation_id":"8519dfa5-1cfa-4702-ae7a-e0fc6614a987","resolution":{"observed_at":"2026-08-06T13:57:05.275307Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"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"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-06T13:57:05.253049Z","title":"Pose-guided transformer for fine-grained action quality assessment.IEEE Transactions on Circuits and Systems for Video Technology, pages 1–1,","venue":null,"work_id":"92702759-98d7-4113-8783-bf0bed9a9d44","year":null},"citing_paper":{"arxiv_id":"2507.19924","last_updated":"2025-08-01T12:25:21Z","snapshot_observed_at":"2026-08-07T14:18:30.406157Z","submitted_at":"2025-07-26T12:03:47Z","title":"HumanSAM: Classifying Human-centric Forgery Videos in Human Spatial, Appearance, and Motion Anomaly","version":2},"reference_index":60,"source":"pdf_text","source_observed_at":"2026-08-06T13:57:04.654218Z"},"links":{"citing_paper":"/paper/2507.19924"},"observation_digest":"sha256:240985bcd0b4b511c5a90e149c420193e6a6937cd39fa8f15105df73e8bc9c68","observation_id":"e922e64d-fe81-480c-8a33-011f79f2673c","resolution":{"observed_at":"2026-08-06T13:57:05.259296Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"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"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-06T13:57:05.220499Z","title":null,"venue":null,"work_id":"95609161-eefa-4069-8543-8200ce067a27","year":null},"citing_paper":{"arxiv_id":"2507.19924","last_updated":"2025-08-01T12:25:21Z","snapshot_observed_at":"2026-08-07T14:18:30.406157Z","submitted_at":"2025-07-26T12:03:47Z","title":"HumanSAM: Classifying Human-centric Forgery Videos in Human Spatial, Appearance, and Motion Anomaly","version":2},"reference_index":62,"source":"pdf_text","source_observed_at":"2026-08-06T13:57:04.663532Z"},"links":{"citing_paper":"/paper/2507.19924"},"observation_digest":"sha256:1269542b1d3b1595f6bc0ebc03ccbf39ff20274710100f563237b68696ec2085","observation_id":"095c8183-e70b-4959-a272-00087b909712","resolution":{"observed_at":"2026-08-06T13:57:05.226405Z","resolver_source":"raw_fallback","status":"unresolved"},"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"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-06T13:57:05.237392Z","title":null,"venue":null,"work_id":"9c7fb140-64be-4647-9ff1-071a1339d83d","year":null},"citing_paper":{"arxiv_id":"2507.19924","last_updated":"2025-08-01T12:25:21Z","snapshot_observed_at":"2026-08-07T14:18:30.406157Z","submitted_at":"2025-07-26T12:03:47Z","title":"HumanSAM: Classifying Human-centric Forgery Videos in Human Spatial, Appearance, and Motion Anomaly","version":2},"reference_index":2025,"source":"pdf_text","source_observed_at":"2026-08-06T13:57:04.658633Z"},"links":{"citing_paper":"/paper/2507.19924"},"observation_digest":"sha256:d1351cfeaa4cd25a010ed8bfa387d49298327d1044e91c01a3d208eb263f1623","observation_id":"0ec6af70-5789-49ae-8773-854f54d3f961","resolution":{"observed_at":"2026-08-06T13:57:05.242128Z","resolver_source":"raw_fallback","status":"unresolved"},"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"}}],"paper":{"arxiv_id":"2507.19924","last_updated":"2025-08-01T12:25:21Z","latest_version":2,"primary_category":"cs.CV","snapshot_observed_at":"2026-08-07T14:18:30.406157Z","submitted_at":"2025-07-26T12:03:47Z","title":"HumanSAM: Classifying Human-centric Forgery Videos in Human Spatial, Appearance, and Motion Anomaly"},"reference_resolution":{"displayed":62,"state_counts":{"malformed_identifier":0,"metadata_mismatch":0,"parse_uncertain":0,"unresolved":24,"verified_exact":0,"verified_fuzzy":38},"total_outbound_references":62},"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 9 August 2026, this Paper Citation Record lists 62 of 62 outbound references and 0 inbound Pith citation observations for arXiv:2507.19924."}