{"as_of":"2026-08-18T20:02:00Z","caps":{"database_statements":6,"inbound":100,"outbound":100},"context_digest":"sha256:30c6d78eea9bbae074abc9f070dd2a3ec1155dec6bf393ee54703d08ab16f7f1","coverage":[{"denominator":27,"lane":"reference_resolution","note":"Typed states for the displayed outbound observations.","records_observed":27,"source":"paper_references, paper_reference_links","source_observed_at":"2026-08-10T20:32:41.742289Z","state":"measured"},{"denominator":29,"lane":"standing_notices","note":"One-hop event checks from named stored sources.","records_observed":29,"source":"scholarly_work_events, retraction_status_cache","source_observed_at":"2026-08-18T06:34:40.430872+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":"2026-08-12T11:45:09.565323Z","state":"measured"},{"denominator":1,"lane":"external_citation_measurements","note":"A source-named dated measurement, never combined with another source.","records_observed":0,"source":"pith","source_observed_at":"2026-08-10T20:32:41.908336Z","state":"measured"}],"external_citation_measurements":[],"inbound":[{"citation":{"cited_paper":{"arxiv_id":"2501.08137","last_updated":"2025-03-13T11:02:33Z","snapshot_observed_at":"2026-08-18T15:04:45.742915Z","submitted_at":"2025-01-14T14:15:10Z","title":"Audio-Visual Deepfake Detection With Local Temporal Inconsistencies","version":4},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2501.08137","snapshot_observed_at":"2026-08-12T11:45:09.565323Z","title":null,"venue":null,"work_id":null,"year":2025},"citing_paper":{"arxiv_id":"2411.17911","last_updated":"2025-04-05T18:48:12Z","snapshot_observed_at":"2026-08-16T08:29:38.727403Z","submitted_at":"2024-11-26T22:04:49Z","title":"Passive Deepfake Detection Across Multi-modalities: A Comprehensive Survey","version":2},"reference_index":6,"source":"pdf_text","source_observed_at":"2026-08-12T11:45:09.565323Z"},"links":{"cited_paper":"/paper/2501.08137","citing_paper":"/paper/2411.17911"},"observation_digest":"sha256:4743c5b1ec55ec50c01d54a312fa564477b83bcdf2cfdd29e414d21b34e9406d","observation_id":"0b9e89db-2a3d-4f2b-b99a-d9c557148618","resolution":{"observed_at":"2026-08-12T11:45:09.565323Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2501.08137","last_updated":"2025-03-13T11:02:33Z","snapshot_observed_at":"2026-08-18T15:04:45.742915Z","submitted_at":"2025-01-14T14:15:10Z","title":"Audio-Visual Deepfake Detection With Local Temporal Inconsistencies","version":4},"cited_work":{"arxiv_id":"2501.08137","doi":null,"metadata_source":"pith","pith_arxiv_id":"2501.08137","snapshot_observed_at":"2026-08-10T20:32:41.908336Z","title":"Audio-Visual Deepfake Detection With Local Temporal Inconsistencies","venue":"cs.CV","work_id":"0aa41a41-4c3a-46be-8c1a-41649da19840","year":2025},"citing_paper":{"arxiv_id":"2501.08137","last_updated":"2025-03-13T11:02:33Z","snapshot_observed_at":"2026-08-18T15:04:45.742915Z","submitted_at":"2025-01-14T14:15:10Z","title":"Audio-Visual Deepfake Detection With Local Temporal Inconsistencies","version":4},"reference_index":2,"source":"pdf_text","source_observed_at":"2026-08-10T20:32:41.596032Z"},"links":{"cited_paper":"/paper/2501.08137","citing_paper":"/paper/2501.08137"},"observation_digest":"sha256:f9657fe74648a9ea52b285f83a08f4d2b2e52152da65713f70c09d85227868a8","observation_id":"60fc6975-ea46-46f0-8e98-bf6e35eef785","resolution":{"observed_at":"2026-08-10T20:32:41.915306Z","resolver_source":"local_arxiv","status":"verified_exact"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-18T06:34:40.430872+00:00","source":"crossref"},{"observed_at":"2026-08-18T06:34:34.496301+00:00","source":"retraction_watch"}],"state":"measured"}}],"links":{"evidence":"/evidence","html":"/paper/2501.08137/citation-record","integrity":"/paper/2501.08137/integrity","json":"/paper/2501.08137/citation-record.json","paper":"/paper/2501.08137"},"outbound":[{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":"is/1635335","doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-10T20:32:42.069834Z","title":"As their quality im- proves, distinguishing real from fake becomes increasingly difficult, highlighting the need for effective detection systems","venue":null,"work_id":"e5a8fab5-4596-4b11-b029-a4338716b4c8","year":null},"citing_paper":{"arxiv_id":"2501.08137","last_updated":"2025-03-13T11:02:33Z","snapshot_observed_at":"2026-08-18T15:04:45.742915Z","submitted_at":"2025-01-14T14:15:10Z","title":"Audio-Visual Deepfake Detection With Local Temporal Inconsistencies","version":4},"reference_index":1,"source":"pdf_text","source_observed_at":"2026-08-10T20:32:41.589663Z"},"links":{"citing_paper":"/paper/2501.08137"},"observation_digest":"sha256:619746008b86e8794d8ce9287f9fa8a978b24b995a736462cae582ccfbd64c23","observation_id":"c4a9b1d7-92e4-410a-b166-042ed83550f2","resolution":{"observed_at":"2026-08-10T20:32:42.080613Z","resolver_source":"raw_fallback","status":"verified_exact"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-18T06:34:40.430872+00:00","source":"crossref"},{"observed_at":"2026-08-18T06:34:34.496301+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"2501.08137","last_updated":"2025-03-13T11:02:33Z","snapshot_observed_at":"2026-08-18T15:04:45.742915Z","submitted_at":"2025-01-14T14:15:10Z","title":"Audio-Visual Deepfake Detection With Local Temporal Inconsistencies","version":4},"cited_work":{"arxiv_id":"2501.08137","doi":null,"metadata_source":"pith","pith_arxiv_id":"2501.08137","snapshot_observed_at":"2026-08-10T20:32:41.908336Z","title":"Audio-Visual Deepfake Detection With Local Temporal Inconsistencies","venue":"cs.CV","work_id":"0aa41a41-4c3a-46be-8c1a-41649da19840","year":2025},"citing_paper":{"arxiv_id":"2501.08137","last_updated":"2025-03-13T11:02:33Z","snapshot_observed_at":"2026-08-18T15:04:45.742915Z","submitted_at":"2025-01-14T14:15:10Z","title":"Audio-Visual Deepfake Detection With Local Temporal Inconsistencies","version":4},"reference_index":2,"source":"pdf_text","source_observed_at":"2026-08-10T20:32:41.596032Z"},"links":{"cited_paper":"/paper/2501.08137","citing_paper":"/paper/2501.08137"},"observation_digest":"sha256:f9657fe74648a9ea52b285f83a08f4d2b2e52152da65713f70c09d85227868a8","observation_id":"60fc6975-ea46-46f0-8e98-bf6e35eef785","resolution":{"observed_at":"2026-08-10T20:32:41.915306Z","resolver_source":"local_arxiv","status":"verified_exact"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-18T06:34:40.430872+00:00","source":"crossref"},{"observed_at":"2026-08-18T06:34:34.496301+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":"2026-08-10T20:32:42.448850Z","title":"This method, depicted in Fig","venue":null,"work_id":"dcbc84e8-1417-4a90-80c7-a3669bc41b27","year":null},"citing_paper":{"arxiv_id":"2501.08137","last_updated":"2025-03-13T11:02:33Z","snapshot_observed_at":"2026-08-18T15:04:45.742915Z","submitted_at":"2025-01-14T14:15:10Z","title":"Audio-Visual Deepfake Detection With Local Temporal Inconsistencies","version":4},"reference_index":3,"source":"pdf_text","source_observed_at":"2026-08-10T20:32:41.601937Z"},"links":{"citing_paper":"/paper/2501.08137"},"observation_digest":"sha256:205c67074bb49bea7d42ef2ad1d9740cd0aa6f072997734a369c487925921b35","observation_id":"152bfadc-dbde-418f-99f2-cf5de6c72373","resolution":{"observed_at":"2026-08-10T20:32:42.454473Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-18T06:34:40.430872+00:00","source":"crossref"},{"observed_at":"2026-08-18T06:34:34.496301+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":"2026-08-10T20:32:42.431223Z","title":"In the example of Fig","venue":null,"work_id":"394c161d-5512-45ac-9266-5d97210f71f7","year":null},"citing_paper":{"arxiv_id":"2501.08137","last_updated":"2025-03-13T11:02:33Z","snapshot_observed_at":"2026-08-18T15:04:45.742915Z","submitted_at":"2025-01-14T14:15:10Z","title":"Audio-Visual Deepfake Detection With Local Temporal Inconsistencies","version":4},"reference_index":4,"source":"pdf_text","source_observed_at":"2026-08-10T20:32:41.607706Z"},"links":{"citing_paper":"/paper/2501.08137"},"observation_digest":"sha256:8189dbd1385c54faead0407a6aa4e7d52ead210bbc35428ba87ba3c3bcf179b8","observation_id":"76e7a971-f6fc-48cd-a364-12b3d5967d7e","resolution":{"observed_at":"2026-08-10T20:32:42.437035Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-18T06:34:40.430872+00:00","source":"crossref"},{"observed_at":"2026-08-18T06:34:34.496301+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":"2026-08-10T20:32:42.413355Z","title":"In the example of Fig","venue":null,"work_id":"e5667a7b-4c57-484e-bd0b-2dad91b5c1dd","year":null},"citing_paper":{"arxiv_id":"2501.08137","last_updated":"2025-03-13T11:02:33Z","snapshot_observed_at":"2026-08-18T15:04:45.742915Z","submitted_at":"2025-01-14T14:15:10Z","title":"Audio-Visual Deepfake Detection With Local Temporal Inconsistencies","version":4},"reference_index":5,"source":"pdf_text","source_observed_at":"2026-08-10T20:32:41.613495Z"},"links":{"citing_paper":"/paper/2501.08137"},"observation_digest":"sha256:c6828dc5dfb284cd2260378b1b3c400f50d2e4491f83844b2e0af923c73e3059","observation_id":"b6cced36-70c1-4f5d-9d8e-33d2129ec719","resolution":{"observed_at":"2026-08-10T20:32:42.419020Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-18T06:34:40.430872+00:00","source":"crossref"},{"observed_at":"2026-08-18T06:34:34.496301+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":"2026-08-10T20:32:42.394955Z","title":null,"venue":null,"work_id":"3c288f8c-224e-4e0a-ac16-ba11d903ad55","year":null},"citing_paper":{"arxiv_id":"2501.08137","last_updated":"2025-03-13T11:02:33Z","snapshot_observed_at":"2026-08-18T15:04:45.742915Z","submitted_at":"2025-01-14T14:15:10Z","title":"Audio-Visual Deepfake Detection With Local Temporal Inconsistencies","version":4},"reference_index":6,"source":"pdf_text","source_observed_at":"2026-08-10T20:32:41.619363Z"},"links":{"citing_paper":"/paper/2501.08137"},"observation_digest":"sha256:ca6a0ec3484097a5e4eb8a152dd254299a63636a4882d6ecd659032404cd786c","observation_id":"4b0fa63f-c298-4ff6-a961-516ef19d5100","resolution":{"observed_at":"2026-08-10T20:32:42.401127Z","resolver_source":"raw_fallback","status":"unresolved"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-18T06:34:40.430872+00:00","source":"crossref"},{"observed_at":"2026-08-18T06:34:34.496301+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":"2026-08-10T20:32:42.376950Z","title":"Experimental setup Dataset","venue":null,"work_id":"b3ff21f0-f62b-41dd-b355-32432ee580fc","year":null},"citing_paper":{"arxiv_id":"2501.08137","last_updated":"2025-03-13T11:02:33Z","snapshot_observed_at":"2026-08-18T15:04:45.742915Z","submitted_at":"2025-01-14T14:15:10Z","title":"Audio-Visual Deepfake Detection With Local Temporal Inconsistencies","version":4},"reference_index":7,"source":"pdf_text","source_observed_at":"2026-08-10T20:32:41.625058Z"},"links":{"citing_paper":"/paper/2501.08137"},"observation_digest":"sha256:0fb1e9fbee0ace0f9de5f806e1c22a05df4f0d97dc466eeb87c404254ebc04b9","observation_id":"712b05eb-2d3b-476f-b3cb-88628bca27d0","resolution":{"observed_at":"2026-08-10T20:32:42.382438Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-18T06:34:40.430872+00:00","source":"crossref"},{"observed_at":"2026-08-18T06:34:34.496301+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":"2026-08-10T20:32:42.359412Z","title":"Our approach includes both data augmentation and architectural design strategies","venue":null,"work_id":"d1cbfb85-334e-493b-859a-0eea56407914","year":null},"citing_paper":{"arxiv_id":"2501.08137","last_updated":"2025-03-13T11:02:33Z","snapshot_observed_at":"2026-08-18T15:04:45.742915Z","submitted_at":"2025-01-14T14:15:10Z","title":"Audio-Visual Deepfake Detection With Local Temporal Inconsistencies","version":4},"reference_index":8,"source":"pdf_text","source_observed_at":"2026-08-10T20:32:41.631374Z"},"links":{"citing_paper":"/paper/2501.08137"},"observation_digest":"sha256:720efde02e4ffec8772db6ba91ed45a398bbe46ac73574befce1f4aee8ca42c6","observation_id":"34cb30e0-7526-4021-ac3a-d15eeaecaff4","resolution":{"observed_at":"2026-08-10T20:32:42.364987Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-18T06:34:40.430872+00:00","source":"crossref"},{"observed_at":"2026-08-18T06:34:34.496301+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":"2026-08-10T20:32:42.341782Z","title":"Finance worker pays out $25 million after video call with deepfake ‘chief financial officer’,","venue":null,"work_id":"3f91dd7f-5faa-441e-9ef3-67969b300859","year":null},"citing_paper":{"arxiv_id":"2501.08137","last_updated":"2025-03-13T11:02:33Z","snapshot_observed_at":"2026-08-18T15:04:45.742915Z","submitted_at":"2025-01-14T14:15:10Z","title":"Audio-Visual Deepfake Detection With Local Temporal Inconsistencies","version":4},"reference_index":9,"source":"pdf_text","source_observed_at":"2026-08-10T20:32:41.636521Z"},"links":{"citing_paper":"/paper/2501.08137"},"observation_digest":"sha256:58a074b6a8f457b4510ae6e3880ed3797c342380a94ae24044dc9976b5fa5ffc","observation_id":"2335501e-be0c-42f3-800d-d902b2b3978e","resolution":{"observed_at":"2026-08-10T20:32:42.347321Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-18T06:34:40.430872+00:00","source":"crossref"},{"observed_at":"2026-08-18T06:34:34.496301+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":"2026-08-10T20:32:42.323513Z","title":"Deepfake video targeting zelen- sky’s wife linked to russian disinformation campaign, cnn analysis shows,","venue":null,"work_id":"096ceac2-da9e-43f6-87b1-eea7314fc5f7","year":null},"citing_paper":{"arxiv_id":"2501.08137","last_updated":"2025-03-13T11:02:33Z","snapshot_observed_at":"2026-08-18T15:04:45.742915Z","submitted_at":"2025-01-14T14:15:10Z","title":"Audio-Visual Deepfake Detection With Local Temporal Inconsistencies","version":4},"reference_index":10,"source":"pdf_text","source_observed_at":"2026-08-10T20:32:41.641701Z"},"links":{"citing_paper":"/paper/2501.08137"},"observation_digest":"sha256:0c2fe303666c4c5bede250650d2b3b150069451cd6b0f48c79af8fe3acf2d236","observation_id":"8f8d2677-3478-497f-a87c-2b2570e86834","resolution":{"observed_at":"2026-08-10T20:32:42.329538Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-18T06:34:40.430872+00:00","source":"crossref"},{"observed_at":"2026-08-18T06:34:34.496301+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":"2026-08-10T20:32:42.305395Z","title":"Not made for each other- audio-visual dissonance-based deepfake detection and localization,","venue":null,"work_id":"b6a1b0c8-81f1-4598-954d-d558a6bae112","year":2020},"citing_paper":{"arxiv_id":"2501.08137","last_updated":"2025-03-13T11:02:33Z","snapshot_observed_at":"2026-08-18T15:04:45.742915Z","submitted_at":"2025-01-14T14:15:10Z","title":"Audio-Visual Deepfake Detection With Local Temporal Inconsistencies","version":4},"reference_index":11,"source":"pdf_text","source_observed_at":"2026-08-10T20:32:41.647509Z"},"links":{"citing_paper":"/paper/2501.08137"},"observation_digest":"sha256:8b14d25098aae3e5086fb8b698c642647fd6d4d48177a0042e4be9871113478e","observation_id":"d6c42971-8305-4bb8-be73-2db60a1b7b04","resolution":{"observed_at":"2026-08-10T20:32:42.311370Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-18T06:34:40.430872+00:00","source":"crossref"},{"observed_at":"2026-08-18T06:34:34.496301+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":"2026-08-10T20:32:42.287012Z","title":"Deepfake video detection using audio-visual con- sistency,","venue":null,"work_id":"92bb3865-32c2-413d-bcee-38883b1d3c76","year":2020},"citing_paper":{"arxiv_id":"2501.08137","last_updated":"2025-03-13T11:02:33Z","snapshot_observed_at":"2026-08-18T15:04:45.742915Z","submitted_at":"2025-01-14T14:15:10Z","title":"Audio-Visual Deepfake Detection With Local Temporal Inconsistencies","version":4},"reference_index":12,"source":"pdf_text","source_observed_at":"2026-08-10T20:32:41.653065Z"},"links":{"citing_paper":"/paper/2501.08137"},"observation_digest":"sha256:e373d5ed3cdd9cd916779e36f297c0e3d142ad6e3558b165b8dcef850b69b4cf","observation_id":"9f623f6c-2292-48e1-a361-e09014518b0c","resolution":{"observed_at":"2026-08-10T20:32:42.292530Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-18T06:34:40.430872+00:00","source":"crossref"},{"observed_at":"2026-08-18T06:34:34.496301+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":"2026-08-10T20:32:42.269798Z","title":"Self- supervised video forensics by audio-visual anomaly de- tection,","venue":null,"work_id":"abe2c8c8-8bc3-4693-a0ba-974baab8b3ad","year":2023},"citing_paper":{"arxiv_id":"2501.08137","last_updated":"2025-03-13T11:02:33Z","snapshot_observed_at":"2026-08-18T15:04:45.742915Z","submitted_at":"2025-01-14T14:15:10Z","title":"Audio-Visual Deepfake Detection With Local Temporal Inconsistencies","version":4},"reference_index":13,"source":"pdf_text","source_observed_at":"2026-08-10T20:32:41.658930Z"},"links":{"citing_paper":"/paper/2501.08137"},"observation_digest":"sha256:cd2cb6c0589cad805c6017d7a4583a1d0e52ce71f13bc8dbe1d6cfc2bc808028","observation_id":"d30c7fb4-d297-4deb-b594-ae81ec70f382","resolution":{"observed_at":"2026-08-10T20:32:42.275437Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-18T06:34:40.430872+00:00","source":"crossref"},{"observed_at":"2026-08-18T06:34:34.496301+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"2407.11650","last_updated":"2024-07-17T11:41:59Z","snapshot_observed_at":"2026-08-16T13:33:48.074318Z","submitted_at":"2024-07-16T12:15:41Z","title":"Statistics-aware Audio-visual Deepfake Detector","version":2},"cited_work":{"arxiv_id":"2407.11650","doi":null,"metadata_source":"pith","pith_arxiv_id":"2407.11650","snapshot_observed_at":"2026-08-10T20:32:41.880902Z","title":"Statistics-aware Audio-visual Deepfake Detector","venue":"cs.CV","work_id":"3bd7e68e-4d00-45de-a086-8904f4c9d459","year":2024},"citing_paper":{"arxiv_id":"2501.08137","last_updated":"2025-03-13T11:02:33Z","snapshot_observed_at":"2026-08-18T15:04:45.742915Z","submitted_at":"2025-01-14T14:15:10Z","title":"Audio-Visual Deepfake Detection With Local Temporal Inconsistencies","version":4},"reference_index":14,"source":"pdf_text","source_observed_at":"2026-08-10T20:32:41.664921Z"},"links":{"cited_paper":"/paper/2407.11650","citing_paper":"/paper/2501.08137"},"observation_digest":"sha256:ad9284de458f5803859d7bfa3f768d7275cd9d3af5f7e833499f7eb7c11a39c4","observation_id":"42a9de0a-5c9f-4838-a624-07f35e618417","resolution":{"observed_at":"2026-08-10T20:32:41.887126Z","resolver_source":"local_arxiv","status":"verified_exact"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-18T06:34:40.430872+00:00","source":"crossref"},{"observed_at":"2026-08-18T06:34:34.496301+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":"2026-08-10T20:32:42.251913Z","title":"Laa-net: Localized artifact attention network for quality-agnostic and generalizable deepfake detection,","venue":null,"work_id":"134b016d-14eb-4956-987d-c483f04b1e4a","year":2024},"citing_paper":{"arxiv_id":"2501.08137","last_updated":"2025-03-13T11:02:33Z","snapshot_observed_at":"2026-08-18T15:04:45.742915Z","submitted_at":"2025-01-14T14:15:10Z","title":"Audio-Visual Deepfake Detection With Local Temporal Inconsistencies","version":4},"reference_index":15,"source":"pdf_text","source_observed_at":"2026-08-10T20:32:41.671138Z"},"links":{"citing_paper":"/paper/2501.08137"},"observation_digest":"sha256:dad872c75de78b3ae4b0996b2eb7f5a6486e6775c7bf425dc3bcc5e3ef9dce50","observation_id":"69ec3a67-d656-4b6c-a3dc-56b483f6806c","resolution":{"observed_at":"2026-08-10T20:32:42.257577Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-18T06:34:40.430872+00:00","source":"crossref"},{"observed_at":"2026-08-18T06:34:34.496301+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":"2026-08-10T20:32:42.233363Z","title":"Multi- attentional deepfake detection,","venue":null,"work_id":"7c37c1c7-ac32-484e-b414-8c556035105f","year":2021},"citing_paper":{"arxiv_id":"2501.08137","last_updated":"2025-03-13T11:02:33Z","snapshot_observed_at":"2026-08-18T15:04:45.742915Z","submitted_at":"2025-01-14T14:15:10Z","title":"Audio-Visual Deepfake Detection With Local Temporal Inconsistencies","version":4},"reference_index":16,"source":"pdf_text","source_observed_at":"2026-08-10T20:32:41.679253Z"},"links":{"citing_paper":"/paper/2501.08137"},"observation_digest":"sha256:162976b4c68efb7260eafbb4e95ab5433349c9249eca46b83e1ee2b7c735918e","observation_id":"d8ad9094-6ee8-447f-8d51-d0a23b17caf0","resolution":{"observed_at":"2026-08-10T20:32:42.239292Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-18T06:34:40.430872+00:00","source":"crossref"},{"observed_at":"2026-08-18T06:34:34.496301+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"2408.06753","last_updated":"2024-10-14T16:06:54Z","snapshot_observed_at":"2026-08-16T13:26:47.594376Z","submitted_at":"2024-08-13T09:19:59Z","title":"Detecting Audio-Visual Deepfakes with Fine-Grained Inconsistencies","version":3},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2408.06753","snapshot_observed_at":"2026-08-10T20:32:41.684775Z","title":"Detecting audio-visual deepfakes with fine-grained in- consistencies,","venue":null,"work_id":null,"year":2024},"citing_paper":{"arxiv_id":"2501.08137","last_updated":"2025-03-13T11:02:33Z","snapshot_observed_at":"2026-08-18T15:04:45.742915Z","submitted_at":"2025-01-14T14:15:10Z","title":"Audio-Visual Deepfake Detection With Local Temporal Inconsistencies","version":4},"reference_index":17,"source":"pdf_text","source_observed_at":"2026-08-10T20:32:41.684775Z"},"links":{"cited_paper":"/paper/2408.06753","citing_paper":"/paper/2501.08137"},"observation_digest":"sha256:eef28845b5baf8e3c88fa54ba8ea6fd95dd27b911eea6b434fb89750b2377982","observation_id":"1deb87d4-ea3b-4c8a-b05b-1fa369ae6f26","resolution":{"observed_at":"2026-08-10T20:32:41.684775Z","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":"2026-08-10T20:32:42.214503Z","title":"Avoid-df: Audio-visual joint learning for detecting deepfake,","venue":null,"work_id":"673f3b7f-a698-4a9a-9f5f-5e99462b2b9c","year":2015},"citing_paper":{"arxiv_id":"2501.08137","last_updated":"2025-03-13T11:02:33Z","snapshot_observed_at":"2026-08-18T15:04:45.742915Z","submitted_at":"2025-01-14T14:15:10Z","title":"Audio-Visual Deepfake Detection With Local Temporal Inconsistencies","version":4},"reference_index":18,"source":"pdf_text","source_observed_at":"2026-08-10T20:32:41.691250Z"},"links":{"citing_paper":"/paper/2501.08137"},"observation_digest":"sha256:df91fb21f527349ced0cc2e69da87fdc21b61c69f641a692a417ec2462f2b85c","observation_id":"6f9e54c1-0488-49f8-b311-48de190513e2","resolution":{"observed_at":"2026-08-10T20:32:42.220234Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-18T06:34:40.430872+00:00","source":"crossref"},{"observed_at":"2026-08-18T06:34:34.496301+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"2403.14974","last_updated":"2024-03-22T06:04:37Z","snapshot_observed_at":"2026-08-16T14:07:27.167214Z","submitted_at":"2024-03-22T06:04:37Z","title":"AVT2-DWF: Improving Deepfake Detection with Audio-Visual Fusion and Dynamic Weighting Strategies","version":1},"cited_work":{"arxiv_id":"2403.14974","doi":null,"metadata_source":"pith","pith_arxiv_id":"2403.14974","snapshot_observed_at":"2026-08-10T20:32:41.828901Z","title":"AVT2-DWF: Improving Deepfake Detection with Audio-Visual Fusion and Dynamic Weighting Strategies","venue":"cs.CV","work_id":"33ba964f-7314-4d7a-b606-bd2c06ffa5f8","year":2024},"citing_paper":{"arxiv_id":"2501.08137","last_updated":"2025-03-13T11:02:33Z","snapshot_observed_at":"2026-08-18T15:04:45.742915Z","submitted_at":"2025-01-14T14:15:10Z","title":"Audio-Visual Deepfake Detection With Local Temporal Inconsistencies","version":4},"reference_index":19,"source":"pdf_text","source_observed_at":"2026-08-10T20:32:41.696546Z"},"links":{"cited_paper":"/paper/2403.14974","citing_paper":"/paper/2501.08137"},"observation_digest":"sha256:8215f8bea1ed527b9798e7780c1fd9eab5e335b7c7fd8b9f9e8fe1282aa81496","observation_id":"b83bda80-400f-49fb-8a86-51787cb37d26","resolution":{"observed_at":"2026-08-10T20:32:41.838870Z","resolver_source":"local_arxiv","status":"verified_exact"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-18T06:34:40.430872+00:00","source":"crossref"},{"observed_at":"2026-08-18T06:34:34.496301+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":"2026-08-10T20:32:42.195840Z","title":"Avfakenet: A unified end-to-end dense swin trans- former deep learning model for audio–visual deepfakes detection,","venue":null,"work_id":"3eef0139-2eb8-4dad-b7ca-d4e5c747375f","year":2023},"citing_paper":{"arxiv_id":"2501.08137","last_updated":"2025-03-13T11:02:33Z","snapshot_observed_at":"2026-08-18T15:04:45.742915Z","submitted_at":"2025-01-14T14:15:10Z","title":"Audio-Visual Deepfake Detection With Local Temporal Inconsistencies","version":4},"reference_index":20,"source":"pdf_text","source_observed_at":"2026-08-10T20:32:41.702849Z"},"links":{"citing_paper":"/paper/2501.08137"},"observation_digest":"sha256:703790e806ee1ae12e76b98c56303e3d04403e4c072e47e103b7b35d15743dcf","observation_id":"17a1bb0f-fb0f-4ea1-becb-636eaf3e2a39","resolution":{"observed_at":"2026-08-10T20:32:42.201494Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-18T06:34:40.430872+00:00","source":"crossref"},{"observed_at":"2026-08-18T06:34:34.496301+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":"2026-08-10T20:32:42.176644Z","title":"V oice-face homogene- ity tells deepfake,","venue":null,"work_id":"fbf37a52-c122-490f-8f6d-2e1b8643dc10","year":2023},"citing_paper":{"arxiv_id":"2501.08137","last_updated":"2025-03-13T11:02:33Z","snapshot_observed_at":"2026-08-18T15:04:45.742915Z","submitted_at":"2025-01-14T14:15:10Z","title":"Audio-Visual Deepfake Detection With Local Temporal Inconsistencies","version":4},"reference_index":21,"source":"pdf_text","source_observed_at":"2026-08-10T20:32:41.708898Z"},"links":{"citing_paper":"/paper/2501.08137"},"observation_digest":"sha256:d747c7ff841f94527b4f77e182100121f3c7dbbae9a16dd272be55fdcd1f68fa","observation_id":"6220e73e-4553-4c7f-8ff2-8aa5e3acee5a","resolution":{"observed_at":"2026-08-10T20:32:42.183127Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-18T06:34:40.430872+00:00","source":"crossref"},{"observed_at":"2026-08-18T06:34:34.496301+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":"2026-08-10T20:32:42.154432Z","title":"Do you really mean that? content driven audio- visual deepfake dataset and multimodal method for tem- poral forgery localization,","venue":null,"work_id":"7ddb1295-0eee-47f0-a02e-62f18cab3fbb","year":2022},"citing_paper":{"arxiv_id":"2501.08137","last_updated":"2025-03-13T11:02:33Z","snapshot_observed_at":"2026-08-18T15:04:45.742915Z","submitted_at":"2025-01-14T14:15:10Z","title":"Audio-Visual Deepfake Detection With Local Temporal Inconsistencies","version":4},"reference_index":22,"source":"pdf_text","source_observed_at":"2026-08-10T20:32:41.714437Z"},"links":{"citing_paper":"/paper/2501.08137"},"observation_digest":"sha256:c380955eb3707200ecc9dc1a8ad24383b8df2d31702bfb8ab62392be7b68e61d","observation_id":"c1f9eb82-e3a4-4fd9-993b-ccf0db4a80de","resolution":{"observed_at":"2026-08-10T20:32:42.161339Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-18T06:34:40.430872+00:00","source":"crossref"},{"observed_at":"2026-08-18T06:34:34.496301+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"2006.07397","last_updated":"2020-10-28T03:48:28Z","snapshot_observed_at":"2026-07-06T09:28:36.954658Z","submitted_at":"2020-06-12T18:15:55Z","title":"The DeepFake Detection Challenge (DFDC) Dataset","version":4},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2006.07397","snapshot_observed_at":"2026-08-10T20:32:41.719694Z","title":"The deepfake detection challenge (dfdc) dataset,","venue":null,"work_id":null,"year":2006},"citing_paper":{"arxiv_id":"2501.08137","last_updated":"2025-03-13T11:02:33Z","snapshot_observed_at":"2026-08-18T15:04:45.742915Z","submitted_at":"2025-01-14T14:15:10Z","title":"Audio-Visual Deepfake Detection With Local Temporal Inconsistencies","version":4},"reference_index":23,"source":"pdf_text","source_observed_at":"2026-08-10T20:32:41.719694Z"},"links":{"cited_paper":"/paper/2006.07397","citing_paper":"/paper/2501.08137"},"observation_digest":"sha256:38de19a5fa733a4f26667b66028c754c14f4e3cd0bfea8c3bf749eea0149ae64","observation_id":"3ff9eac8-3b0a-4755-b371-d7649cee5850","resolution":{"observed_at":"2026-08-10T20:32:41.719694Z","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":"2026-08-10T20:32:42.134143Z","title":"Fakeavceleb: A novel audio-video multimodal deepfake dataset,","venue":null,"work_id":"b3811349-0eb8-4275-8f22-bd0d6b519a42","year":2021},"citing_paper":{"arxiv_id":"2501.08137","last_updated":"2025-03-13T11:02:33Z","snapshot_observed_at":"2026-08-18T15:04:45.742915Z","submitted_at":"2025-01-14T14:15:10Z","title":"Audio-Visual Deepfake Detection With Local Temporal Inconsistencies","version":4},"reference_index":24,"source":"pdf_text","source_observed_at":"2026-08-10T20:32:41.725616Z"},"links":{"citing_paper":"/paper/2501.08137"},"observation_digest":"sha256:ba8f8d3f2c039a109ec2754213c10ab97eef2f79d7840cb8cc1b70836d2b2ce7","observation_id":"2a89de71-d258-40b9-ace4-9b11ae17bbfd","resolution":{"observed_at":"2026-08-10T20:32:42.141211Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-18T06:34:40.430872+00:00","source":"crossref"},{"observed_at":"2026-08-18T06:34:34.496301+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":"2026-08-10T20:32:42.116155Z","title":"Emotions don’t lie: An audio-visual deepfake detection method using affec- tive cues,","venue":null,"work_id":"74fa0d06-bada-40cc-9956-cb1f2c839eb2","year":2020},"citing_paper":{"arxiv_id":"2501.08137","last_updated":"2025-03-13T11:02:33Z","snapshot_observed_at":"2026-08-18T15:04:45.742915Z","submitted_at":"2025-01-14T14:15:10Z","title":"Audio-Visual Deepfake Detection With Local Temporal Inconsistencies","version":4},"reference_index":25,"source":"pdf_text","source_observed_at":"2026-08-10T20:32:41.731017Z"},"links":{"citing_paper":"/paper/2501.08137"},"observation_digest":"sha256:6714c60a2cc97ba4b430596f67ad71ec9121a15dcafd8e14ddef957f95dbaf25","observation_id":"d4e17fb1-a34c-4b1f-ab82-d3b0726626ef","resolution":{"observed_at":"2026-08-10T20:32:42.121882Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-18T06:34:40.430872+00:00","source":"crossref"},{"observed_at":"2026-08-18T06:34:34.496301+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":"2026-08-10T20:32:42.096088Z","title":"Evaluation of an audio-video multimodal deepfake dataset using unimodal and multimodal detec- tors,","venue":null,"work_id":"53da9268-c0ef-46ff-a796-ff708746e762","year":2021},"citing_paper":{"arxiv_id":"2501.08137","last_updated":"2025-03-13T11:02:33Z","snapshot_observed_at":"2026-08-18T15:04:45.742915Z","submitted_at":"2025-01-14T14:15:10Z","title":"Audio-Visual Deepfake Detection With Local Temporal Inconsistencies","version":4},"reference_index":26,"source":"pdf_text","source_observed_at":"2026-08-10T20:32:41.736818Z"},"links":{"citing_paper":"/paper/2501.08137"},"observation_digest":"sha256:602e1976e8365fc672ec048453edbc07575fe43c115af780529eea7335f3970e","observation_id":"e632d99a-4b3a-4e8e-8b55-3edf6b4c6a9f","resolution":{"observed_at":"2026-08-10T20:32:42.103167Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-18T06:34:40.430872+00:00","source":"crossref"},{"observed_at":"2026-08-18T06:34:34.496301+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"1412.6980","last_updated":"2017-01-30T01:27:54Z","snapshot_observed_at":"2026-08-17T19:26:44.032537Z","submitted_at":"2014-12-22T13:54:29Z","title":"Adam: A Method for Stochastic Optimization","version":9},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"1412.6980","snapshot_observed_at":"2026-08-10T20:32:41.742289Z","title":"Adam: A method for stochastic optimization,","venue":null,"work_id":null,"year":2014},"citing_paper":{"arxiv_id":"2501.08137","last_updated":"2025-03-13T11:02:33Z","snapshot_observed_at":"2026-08-18T15:04:45.742915Z","submitted_at":"2025-01-14T14:15:10Z","title":"Audio-Visual Deepfake Detection With Local Temporal Inconsistencies","version":4},"reference_index":27,"source":"pdf_text","source_observed_at":"2026-08-10T20:32:41.742289Z"},"links":{"cited_paper":"/paper/1412.6980","citing_paper":"/paper/2501.08137"},"observation_digest":"sha256:6b7c21c1a26717c4e301c803af9a6f4590434557fa0bab83d817dc618651e90e","observation_id":"63ca3b55-3047-42b1-9ffc-9851364eb4be","resolution":{"observed_at":"2026-08-10T20:32:41.742289Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}}],"paper":{"arxiv_id":"2501.08137","last_updated":"2025-03-13T11:02:33Z","latest_version":4,"primary_category":"cs.CV","snapshot_observed_at":"2026-08-18T15:04:45.742915Z","submitted_at":"2025-01-14T14:15:10Z","title":"Audio-Visual Deepfake Detection With Local Temporal Inconsistencies"},"reference_resolution":{"displayed":27,"state_counts":{"malformed_identifier":0,"metadata_mismatch":0,"parse_uncertain":0,"unresolved":4,"verified_exact":4,"verified_fuzzy":19},"total_outbound_references":27},"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":"2026-08-18T06:34:40.430872+00:00","source":"crossref"},{"observed_at":"2026-08-18T06:34:34.496301+00:00","source":"retraction_watch"}],"thesis":"As of 18 August 2026, this Paper Citation Record lists 27 of 27 outbound references and 2 inbound Pith citation observations for arXiv:2501.08137."}