{"as_of":"2026-08-10T19:12:00Z","caps":{"database_statements":6,"inbound":100,"outbound":100},"context_digest":"sha256:ddc6d1500dbca2ddaa7deaf15b0873b7ebaec0fa8bd345f8186b47e68ec5b516","coverage":[{"denominator":22,"lane":"reference_resolution","note":"Typed states for the displayed outbound observations.","records_observed":22,"source":"paper_references, paper_reference_links","source_observed_at":"2026-08-10T16:11:51.899245Z","state":"measured"},{"denominator":23,"lane":"standing_notices","note":"One-hop event checks from named stored sources.","records_observed":23,"source":"scholarly_work_events, retraction_status_cache","source_observed_at":"2026-08-10T06:31:04.303077+00:00","state":"measured"},{"denominator":1,"lane":"inbound_itemization","note":"Pith citing papers itemized under the disclosed page cap.","records_observed":1,"source":"paper_references, paper_reference_links","source_observed_at":"2026-07-14T09:16:37.881212Z","state":"measured"},{"denominator":1,"lane":"external_citation_measurements","note":"A source-named dated measurement, never combined with another source.","records_observed":0,"source":"cited_works","source_observed_at":null,"state":"measured"}],"external_citation_measurements":[],"inbound":[{"citation":{"cited_paper":{"arxiv_id":"2501.13435","last_updated":"2025-01-23T07:43:56Z","snapshot_observed_at":"2026-08-10T15:55:22.412630Z","submitted_at":"2025-01-23T07:43:56Z","title":"GC-ConsFlow: Leveraging Optical Flow Residuals and Global Context for Robust Deepfake Detection","version":1},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2501.13435","snapshot_observed_at":"2026-07-14T09:16:37.881212Z","title":"arXiv preprint arXiv:2501.13435 , year=","venue":null,"work_id":null,"year":null},"citing_paper":{"arxiv_id":"2607.10787","last_updated":"2026-07-12T14:25:04Z","snapshot_observed_at":"2026-08-06T13:12:11.216373Z","submitted_at":"2026-07-12T14:25:04Z","title":"Detecting AI-Generated Video: A Vision-Language Dual-View Survey","version":1},"reference_index":75,"source":"arxiv_source","source_observed_at":"2026-07-14T09:16:37.881212Z"},"links":{"cited_paper":"/paper/2501.13435","citing_paper":"/paper/2607.10787"},"observation_digest":"sha256:c7cc3fb5b8c1009f618bc8303b265683fa1ab9fe62b95108aeea99af28eaa9c6","observation_id":"497d868e-4bbb-4005-ab72-563229e7037b","resolution":{"observed_at":"2026-07-14T09:16:37.881212Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}}],"links":{"evidence":"/evidence","html":"/paper/2501.13435/citation-record","integrity":"/paper/2501.13435/integrity","json":"/paper/2501.13435/citation-record.json","paper":"/paper/2501.13435"},"outbound":[{"citation":{"cited_paper":{"arxiv_id":"2205.01373","last_updated":"2022-12-23T14:17:23Z","snapshot_observed_at":"2026-08-04T01:17:42.430010Z","submitted_at":"2022-05-03T08:45:22Z","title":"Copy Motion From One to Another: Fake Motion Video Generation","version":3},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2205.01373","snapshot_observed_at":"2026-08-10T16:11:51.819367Z","title":"Copy motion from one to another: Fake motion video generation,","venue":null,"work_id":null,"year":2022},"citing_paper":{"arxiv_id":"2501.13435","last_updated":"2025-01-23T07:43:56Z","snapshot_observed_at":"2026-08-10T15:55:22.412630Z","submitted_at":"2025-01-23T07:43:56Z","title":"GC-ConsFlow: Leveraging Optical Flow Residuals and Global Context for Robust Deepfake Detection","version":1},"reference_index":1,"source":"pdf_text","source_observed_at":"2026-08-10T16:11:51.819367Z"},"links":{"cited_paper":"/paper/2205.01373","citing_paper":"/paper/2501.13435"},"observation_digest":"sha256:c2f221acc1f516569e9a965aef9f125de3bca67bb723c51cfd3583e4d698a57f","observation_id":"eb650544-3f6c-4e2d-8f12-9c2ba0886153","resolution":{"observed_at":"2026-08-10T16:11:51.819367Z","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":"2026-08-10T16:11:52.167128Z","title":"Deepfakes: perspec- tives on the future “reality","venue":null,"work_id":"08da3376-4c4d-49b7-87a3-664c90510765","year":2021},"citing_paper":{"arxiv_id":"2501.13435","last_updated":"2025-01-23T07:43:56Z","snapshot_observed_at":"2026-08-10T15:55:22.412630Z","submitted_at":"2025-01-23T07:43:56Z","title":"GC-ConsFlow: Leveraging Optical Flow Residuals and Global Context for Robust Deepfake Detection","version":1},"reference_index":2,"source":"pdf_text","source_observed_at":"2026-08-10T16:11:51.823712Z"},"links":{"citing_paper":"/paper/2501.13435"},"observation_digest":"sha256:e8f349079743eb645882731ca194acb21f4d680d7ad7cb044b87475f74a0cc47","observation_id":"b5da031c-b3aa-4519-969c-03f980ae8bbd","resolution":{"observed_at":"2026-08-10T16:11:52.171989Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-10T06:31:04.303077+00:00","source":"crossref"},{"observed_at":"2026-08-10T06:30:57.382061+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-10T16:11:52.154477Z","title":"Detecting compressed deepfake videos in social networks using frame-temporality two-stream convolutional network,","venue":null,"work_id":"ddf75a01-a256-4aea-9f20-8ca3594a48dd","year":2021},"citing_paper":{"arxiv_id":"2501.13435","last_updated":"2025-01-23T07:43:56Z","snapshot_observed_at":"2026-08-10T15:55:22.412630Z","submitted_at":"2025-01-23T07:43:56Z","title":"GC-ConsFlow: Leveraging Optical Flow Residuals and Global Context for Robust Deepfake Detection","version":1},"reference_index":3,"source":"pdf_text","source_observed_at":"2026-08-10T16:11:51.827046Z"},"links":{"citing_paper":"/paper/2501.13435"},"observation_digest":"sha256:6925663e839946704542068e7b128ab275beb0022350ad5e0c73c08047f7ee47","observation_id":"41559f78-9c0e-4944-b8d9-20d452dd25d1","resolution":{"observed_at":"2026-08-10T16:11:52.159135Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-10T06:31:04.303077+00:00","source":"crossref"},{"observed_at":"2026-08-10T06:30:57.382061+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-10T16:11:52.142048Z","title":"Capsule- forensics: Using capsule networks to detect forged images and videos,","venue":null,"work_id":"3ddc0750-1cd9-4fd1-9fe8-69945c2a9c54","year":2019},"citing_paper":{"arxiv_id":"2501.13435","last_updated":"2025-01-23T07:43:56Z","snapshot_observed_at":"2026-08-10T15:55:22.412630Z","submitted_at":"2025-01-23T07:43:56Z","title":"GC-ConsFlow: Leveraging Optical Flow Residuals and Global Context for Robust Deepfake Detection","version":1},"reference_index":4,"source":"pdf_text","source_observed_at":"2026-08-10T16:11:51.831426Z"},"links":{"citing_paper":"/paper/2501.13435"},"observation_digest":"sha256:a7ae1f579add3b3e37e3363c858cde8b681951fce0894a0912e6eb187e9ba8a0","observation_id":"c3ceda49-386a-4eb9-8dd4-67be97414f05","resolution":{"observed_at":"2026-08-10T16:11:52.146716Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-10T06:31:04.303077+00:00","source":"crossref"},{"observed_at":"2026-08-10T06:30:57.382061+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-10T16:11:52.131858Z","title":"Mesonet: a compact facial video forgery detection network,","venue":null,"work_id":"b7f9348c-e912-4da1-8fbc-f0b585410fc8","year":2018},"citing_paper":{"arxiv_id":"2501.13435","last_updated":"2025-01-23T07:43:56Z","snapshot_observed_at":"2026-08-10T15:55:22.412630Z","submitted_at":"2025-01-23T07:43:56Z","title":"GC-ConsFlow: Leveraging Optical Flow Residuals and Global Context for Robust Deepfake Detection","version":1},"reference_index":5,"source":"pdf_text","source_observed_at":"2026-08-10T16:11:51.835314Z"},"links":{"citing_paper":"/paper/2501.13435"},"observation_digest":"sha256:c74b5eea19d9d702a14eaaf27357ca132aca702eca866c4d182074bdf363dffd","observation_id":"4460d715-cfc0-4d37-b885-1bbd364caa1e","resolution":{"observed_at":"2026-08-10T16:11:52.135450Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-10T06:31:04.303077+00:00","source":"crossref"},{"observed_at":"2026-08-10T06:30:57.382061+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-10T16:11:52.120651Z","title":"Beyond the prior forgery knowledge: Mining critical clues for general face forgery detection,","venue":null,"work_id":"13a7f44e-0348-4a58-9cc9-01d8c810c6d4","year":2023},"citing_paper":{"arxiv_id":"2501.13435","last_updated":"2025-01-23T07:43:56Z","snapshot_observed_at":"2026-08-10T15:55:22.412630Z","submitted_at":"2025-01-23T07:43:56Z","title":"GC-ConsFlow: Leveraging Optical Flow Residuals and Global Context for Robust Deepfake Detection","version":1},"reference_index":6,"source":"pdf_text","source_observed_at":"2026-08-10T16:11:51.839262Z"},"links":{"citing_paper":"/paper/2501.13435"},"observation_digest":"sha256:cc07e877516dd9ddc36f3e21d06210c35bd6d414a4bb82d27a15f7dc707f83c1","observation_id":"84d50538-4a91-48da-9d6d-0c73dd35bb8f","resolution":{"observed_at":"2026-08-10T16:11:52.125006Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-10T06:31:04.303077+00:00","source":"crossref"},{"observed_at":"2026-08-10T06:30:57.382061+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-10T16:11:52.107896Z","title":"Deepfake video detection using recurrent neural networks,","venue":null,"work_id":"16e2ec13-72f0-4d59-a854-a1c5a8a355c7","year":2018},"citing_paper":{"arxiv_id":"2501.13435","last_updated":"2025-01-23T07:43:56Z","snapshot_observed_at":"2026-08-10T15:55:22.412630Z","submitted_at":"2025-01-23T07:43:56Z","title":"GC-ConsFlow: Leveraging Optical Flow Residuals and Global Context for Robust Deepfake Detection","version":1},"reference_index":7,"source":"pdf_text","source_observed_at":"2026-08-10T16:11:51.843684Z"},"links":{"citing_paper":"/paper/2501.13435"},"observation_digest":"sha256:a2aeb231b127b15c0d2c5299a54c934e6d908cc21599f2f179079024543c80b2","observation_id":"a483e911-eda3-4346-9023-c2969445fd89","resolution":{"observed_at":"2026-08-10T16:11:52.113014Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-10T06:31:04.303077+00:00","source":"crossref"},{"observed_at":"2026-08-10T06:30:57.382061+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-10T16:11:52.096038Z","title":"In ictu oculi: Exposing ai created fake videos by detecting eye blinking,","venue":null,"work_id":"f609803f-d1f9-4fb1-a095-430c81914dc2","year":2018},"citing_paper":{"arxiv_id":"2501.13435","last_updated":"2025-01-23T07:43:56Z","snapshot_observed_at":"2026-08-10T15:55:22.412630Z","submitted_at":"2025-01-23T07:43:56Z","title":"GC-ConsFlow: Leveraging Optical Flow Residuals and Global Context for Robust Deepfake Detection","version":1},"reference_index":8,"source":"pdf_text","source_observed_at":"2026-08-10T16:11:51.848304Z"},"links":{"citing_paper":"/paper/2501.13435"},"observation_digest":"sha256:39d56e87c94a78390a5ff228ccc6c76be5ca345ae36f47d30701eb054e82145f","observation_id":"359432f9-c537-4c67-b0fb-11862765eadb","resolution":{"observed_at":"2026-08-10T16:11:52.100629Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-10T06:31:04.303077+00:00","source":"crossref"},{"observed_at":"2026-08-10T06:30:57.382061+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-10T16:11:52.085152Z","title":"Xception: Deep learning with depthwise separable convolutions,","venue":null,"work_id":"998d09e2-0286-4cfa-852f-3ef37e927403","year":2017},"citing_paper":{"arxiv_id":"2501.13435","last_updated":"2025-01-23T07:43:56Z","snapshot_observed_at":"2026-08-10T15:55:22.412630Z","submitted_at":"2025-01-23T07:43:56Z","title":"GC-ConsFlow: Leveraging Optical Flow Residuals and Global Context for Robust Deepfake Detection","version":1},"reference_index":9,"source":"pdf_text","source_observed_at":"2026-08-10T16:11:51.852988Z"},"links":{"citing_paper":"/paper/2501.13435"},"observation_digest":"sha256:f77139ab65e67f9bb5d71ea8bde6358a3c8da15fc38582c89f1650d1d39ca85c","observation_id":"87adc4c6-7d9f-4d78-8819-f6307ad13060","resolution":{"observed_at":"2026-08-10T16:11:52.088963Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-10T06:31:04.303077+00:00","source":"crossref"},{"observed_at":"2026-08-10T06:30:57.382061+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-10T16:11:52.073473Z","title":"Flownet: Learning optical flow with convolutional networks,","venue":null,"work_id":"627a984c-1003-41b7-903e-a0f3784d464d","year":2015},"citing_paper":{"arxiv_id":"2501.13435","last_updated":"2025-01-23T07:43:56Z","snapshot_observed_at":"2026-08-10T15:55:22.412630Z","submitted_at":"2025-01-23T07:43:56Z","title":"GC-ConsFlow: Leveraging Optical Flow Residuals and Global Context for Robust Deepfake Detection","version":1},"reference_index":10,"source":"pdf_text","source_observed_at":"2026-08-10T16:11:51.856654Z"},"links":{"citing_paper":"/paper/2501.13435"},"observation_digest":"sha256:c76409253237a53957f5360e91d20972355429e292f7c6ba7effd955d745b750","observation_id":"dc675d19-3ad9-4380-a4b4-8b4f3a0d5d5a","resolution":{"observed_at":"2026-08-10T16:11:52.077461Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-10T06:31:04.303077+00:00","source":"crossref"},{"observed_at":"2026-08-10T06:30:57.382061+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-10T16:11:52.062231Z","title":"Masked feature prediction for self-supervised visual pre-training,","venue":null,"work_id":"295cca28-6aba-49f7-b857-de9e07dcdc09","year":2022},"citing_paper":{"arxiv_id":"2501.13435","last_updated":"2025-01-23T07:43:56Z","snapshot_observed_at":"2026-08-10T15:55:22.412630Z","submitted_at":"2025-01-23T07:43:56Z","title":"GC-ConsFlow: Leveraging Optical Flow Residuals and Global Context for Robust Deepfake Detection","version":1},"reference_index":11,"source":"pdf_text","source_observed_at":"2026-08-10T16:11:51.860129Z"},"links":{"citing_paper":"/paper/2501.13435"},"observation_digest":"sha256:514a927eba016a80701d2ebce50c32dec66efae1ef0dd4b2dcb7ade2f472cd19","observation_id":"1774716b-cab2-49fc-b8a9-dd2e15d72abb","resolution":{"observed_at":"2026-08-10T16:11:52.066378Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-10T06:31:04.303077+00:00","source":"crossref"},{"observed_at":"2026-08-10T06:30:57.382061+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"1803.09179","last_updated":"2018-03-24T23:12:44Z","snapshot_observed_at":"2026-07-06T06:30:02.787977Z","submitted_at":"2018-03-24T23:12:44Z","title":"FaceForensics: A Large-scale Video Dataset for Forgery Detection in Human Faces","version":1},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"1803.09179","snapshot_observed_at":"2026-08-10T16:11:51.863719Z","title":"Faceforensics: A large-scale video dataset for forgery detection in human faces,","venue":null,"work_id":null,"year":2018},"citing_paper":{"arxiv_id":"2501.13435","last_updated":"2025-01-23T07:43:56Z","snapshot_observed_at":"2026-08-10T15:55:22.412630Z","submitted_at":"2025-01-23T07:43:56Z","title":"GC-ConsFlow: Leveraging Optical Flow Residuals and Global Context for Robust Deepfake Detection","version":1},"reference_index":12,"source":"pdf_text","source_observed_at":"2026-08-10T16:11:51.863719Z"},"links":{"cited_paper":"/paper/1803.09179","citing_paper":"/paper/2501.13435"},"observation_digest":"sha256:9d6b0f4c6fbbcdada57186c6db3416ab5b01d344a6e501c14a539fe9e15a82d4","observation_id":"a7456529-d530-42e6-bb7d-9808898f4bdd","resolution":{"observed_at":"2026-08-10T16:11:51.863719Z","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":"2026-08-10T16:11:52.052500Z","title":"Celeb-df: A large-scale challenging dataset for deepfake forensics,","venue":null,"work_id":"4d1c6364-ae43-4a1b-a643-e0ec23be8ff2","year":2020},"citing_paper":{"arxiv_id":"2501.13435","last_updated":"2025-01-23T07:43:56Z","snapshot_observed_at":"2026-08-10T15:55:22.412630Z","submitted_at":"2025-01-23T07:43:56Z","title":"GC-ConsFlow: Leveraging Optical Flow Residuals and Global Context for Robust Deepfake Detection","version":1},"reference_index":13,"source":"pdf_text","source_observed_at":"2026-08-10T16:11:51.868372Z"},"links":{"citing_paper":"/paper/2501.13435"},"observation_digest":"sha256:676110baa4e64d1067a9426868aca6507369a0f5442390d82d5e2c44d98929fd","observation_id":"bc5d06ad-6f3b-4fb2-8f2d-6e2ad110f2ac","resolution":{"observed_at":"2026-08-10T16:11:52.055942Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-10T06:31:04.303077+00:00","source":"crossref"},{"observed_at":"2026-08-10T06:30:57.382061+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-10T16:11:52.040315Z","title":"Temporal surface frame anomalies for deepfake video detection,","venue":null,"work_id":"79385214-c5df-49be-b7e3-cf4eae01fc80","year":2024},"citing_paper":{"arxiv_id":"2501.13435","last_updated":"2025-01-23T07:43:56Z","snapshot_observed_at":"2026-08-10T15:55:22.412630Z","submitted_at":"2025-01-23T07:43:56Z","title":"GC-ConsFlow: Leveraging Optical Flow Residuals and Global Context for Robust Deepfake Detection","version":1},"reference_index":14,"source":"pdf_text","source_observed_at":"2026-08-10T16:11:51.872127Z"},"links":{"citing_paper":"/paper/2501.13435"},"observation_digest":"sha256:cb42354ccdfaa6bc928aef214ebe12c0de575f4f65260c4764c5f246f271c33c","observation_id":"11d93ad9-7112-4d73-9319-74b2a9c39dbd","resolution":{"observed_at":"2026-08-10T16:11:52.044455Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-10T06:31:04.303077+00:00","source":"crossref"},{"observed_at":"2026-08-10T06:30:57.382061+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-10T16:11:52.029665Z","title":"Deepfake videos detection via spatiotemporal inconsistency learning and interactive fu- sion,","venue":null,"work_id":"a44b0bb5-a43e-45e4-b3c9-79911c306acb","year":2022},"citing_paper":{"arxiv_id":"2501.13435","last_updated":"2025-01-23T07:43:56Z","snapshot_observed_at":"2026-08-10T15:55:22.412630Z","submitted_at":"2025-01-23T07:43:56Z","title":"GC-ConsFlow: Leveraging Optical Flow Residuals and Global Context for Robust Deepfake Detection","version":1},"reference_index":15,"source":"pdf_text","source_observed_at":"2026-08-10T16:11:51.876078Z"},"links":{"citing_paper":"/paper/2501.13435"},"observation_digest":"sha256:82ea8318fe37c3afe54128a5ddeb23cc51245e250e8ae1c75f33e520052a5a17","observation_id":"bde2405d-cd25-4357-93a5-90793bb1694c","resolution":{"observed_at":"2026-08-10T16:11:52.033658Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-10T06:31:04.303077+00:00","source":"crossref"},{"observed_at":"2026-08-10T06:30:57.382061+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-10T16:11:52.018290Z","title":"Learning spatiotemporal features with 3d convolu- tional networks,","venue":null,"work_id":"8763d5be-cc04-4076-aae0-6db855eaf42b","year":2015},"citing_paper":{"arxiv_id":"2501.13435","last_updated":"2025-01-23T07:43:56Z","snapshot_observed_at":"2026-08-10T15:55:22.412630Z","submitted_at":"2025-01-23T07:43:56Z","title":"GC-ConsFlow: Leveraging Optical Flow Residuals and Global Context for Robust Deepfake Detection","version":1},"reference_index":16,"source":"pdf_text","source_observed_at":"2026-08-10T16:11:51.880045Z"},"links":{"citing_paper":"/paper/2501.13435"},"observation_digest":"sha256:a83ac88e8a1a6b6ebad11975bb191052f0f48ca1dcb8f8ee9fe0f6f36c6972bb","observation_id":"17ca913a-2303-47e3-9c5e-0c423e574875","resolution":{"observed_at":"2026-08-10T16:11:52.022431Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-10T06:31:04.303077+00:00","source":"crossref"},{"observed_at":"2026-08-10T06:30:57.382061+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-10T16:11:52.006044Z","title":"Quo vadis, action recognition? a new model and the kinetics dataset,","venue":null,"work_id":"3b0fa890-af6e-4c58-b0b8-29a89bdc12db","year":2017},"citing_paper":{"arxiv_id":"2501.13435","last_updated":"2025-01-23T07:43:56Z","snapshot_observed_at":"2026-08-10T15:55:22.412630Z","submitted_at":"2025-01-23T07:43:56Z","title":"GC-ConsFlow: Leveraging Optical Flow Residuals and Global Context for Robust Deepfake Detection","version":1},"reference_index":17,"source":"pdf_text","source_observed_at":"2026-08-10T16:11:51.883642Z"},"links":{"citing_paper":"/paper/2501.13435"},"observation_digest":"sha256:705e612e52cda088821d6d5a1a4a8e642e24c28a1fc59690c5a90839f873362c","observation_id":"e8cd452f-086b-4e0b-bee6-52210b5d523d","resolution":{"observed_at":"2026-08-10T16:11:52.009760Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-10T06:31:04.303077+00:00","source":"crossref"},{"observed_at":"2026-08-10T06:30:57.382061+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-10T16:11:51.994852Z","title":"Wilddeepfake: A challenging real-world dataset for deepfake detection,","venue":null,"work_id":"b60f57f4-a492-418b-a3a8-5b28d5526e80","year":2020},"citing_paper":{"arxiv_id":"2501.13435","last_updated":"2025-01-23T07:43:56Z","snapshot_observed_at":"2026-08-10T15:55:22.412630Z","submitted_at":"2025-01-23T07:43:56Z","title":"GC-ConsFlow: Leveraging Optical Flow Residuals and Global Context for Robust Deepfake Detection","version":1},"reference_index":18,"source":"pdf_text","source_observed_at":"2026-08-10T16:11:51.887145Z"},"links":{"citing_paper":"/paper/2501.13435"},"observation_digest":"sha256:149fe8e53bfb6464d31a30bcfdf0dda85456626748317c90727d57bc99c99b62","observation_id":"087347ea-48be-4f5a-9b60-15a4b95c542d","resolution":{"observed_at":"2026-08-10T16:11:51.998680Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-10T06:31:04.303077+00:00","source":"crossref"},{"observed_at":"2026-08-10T06:30:57.382061+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-10T16:11:51.984086Z","title":"Msvt: Multiple spatiotemporal views transformer for deepfake video detection,","venue":null,"work_id":"359c38fa-c3a3-4115-8ca2-f638531c3896","year":2023},"citing_paper":{"arxiv_id":"2501.13435","last_updated":"2025-01-23T07:43:56Z","snapshot_observed_at":"2026-08-10T15:55:22.412630Z","submitted_at":"2025-01-23T07:43:56Z","title":"GC-ConsFlow: Leveraging Optical Flow Residuals and Global Context for Robust Deepfake Detection","version":1},"reference_index":19,"source":"pdf_text","source_observed_at":"2026-08-10T16:11:51.890012Z"},"links":{"citing_paper":"/paper/2501.13435"},"observation_digest":"sha256:7946a770c3c5a950b5ec04c4821a51b59932a6581153639b4c8d034845249db9","observation_id":"8a6d3b06-ca7e-422a-add5-79ccfdf7a5e1","resolution":{"observed_at":"2026-08-10T16:11:51.987494Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-10T06:31:04.303077+00:00","source":"crossref"},{"observed_at":"2026-08-10T06:30:57.382061+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-10T16:11:51.972566Z","title":"Famm: facial muscle motions for detecting compressed deepfake videos over social networks,","venue":null,"work_id":"42e6b3ea-bd85-4f03-80a6-1c71bbab11d4","year":2023},"citing_paper":{"arxiv_id":"2501.13435","last_updated":"2025-01-23T07:43:56Z","snapshot_observed_at":"2026-08-10T15:55:22.412630Z","submitted_at":"2025-01-23T07:43:56Z","title":"GC-ConsFlow: Leveraging Optical Flow Residuals and Global Context for Robust Deepfake Detection","version":1},"reference_index":20,"source":"pdf_text","source_observed_at":"2026-08-10T16:11:51.893084Z"},"links":{"citing_paper":"/paper/2501.13435"},"observation_digest":"sha256:417c1d954d073a05effb3e7d781b68fce122e3cbdf5485add31197f528c60694","observation_id":"953ef94b-6e75-4ba5-8259-1e40cf16789f","resolution":{"observed_at":"2026-08-10T16:11:51.976629Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-10T06:31:04.303077+00:00","source":"crossref"},{"observed_at":"2026-08-10T06:30:57.382061+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-10T16:11:51.957410Z","title":"Dynamic difference learning with spatio-temporal correlation for deepfake video detection,","venue":null,"work_id":"34f8afdb-a22b-4e61-8aea-2de173675af9","year":2023},"citing_paper":{"arxiv_id":"2501.13435","last_updated":"2025-01-23T07:43:56Z","snapshot_observed_at":"2026-08-10T15:55:22.412630Z","submitted_at":"2025-01-23T07:43:56Z","title":"GC-ConsFlow: Leveraging Optical Flow Residuals and Global Context for Robust Deepfake Detection","version":1},"reference_index":21,"source":"pdf_text","source_observed_at":"2026-08-10T16:11:51.896127Z"},"links":{"citing_paper":"/paper/2501.13435"},"observation_digest":"sha256:c6d9c08c4d13089f996742556702ec24ac400050de49c718caa59e93146e774a","observation_id":"ee52a7b3-3b44-4336-a4a0-ba5c5749599e","resolution":{"observed_at":"2026-08-10T16:11:51.963912Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-10T06:31:04.303077+00:00","source":"crossref"},{"observed_at":"2026-08-10T06:30:57.382061+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"2401.10113","last_updated":"2024-06-03T21:29:28Z","snapshot_observed_at":"2026-08-08T08:45:18.222048Z","submitted_at":"2024-01-18T16:35:37Z","title":"Exposing Lip-syncing Deepfakes from Mouth Inconsistencies","version":2},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2401.10113","snapshot_observed_at":"2026-08-10T16:11:51.899245Z","title":"Exposing lip- syncing deepfakes from mouth inconsistencies,","venue":null,"work_id":null,"year":2024},"citing_paper":{"arxiv_id":"2501.13435","last_updated":"2025-01-23T07:43:56Z","snapshot_observed_at":"2026-08-10T15:55:22.412630Z","submitted_at":"2025-01-23T07:43:56Z","title":"GC-ConsFlow: Leveraging Optical Flow Residuals and Global Context for Robust Deepfake Detection","version":1},"reference_index":22,"source":"pdf_text","source_observed_at":"2026-08-10T16:11:51.899245Z"},"links":{"cited_paper":"/paper/2401.10113","citing_paper":"/paper/2501.13435"},"observation_digest":"sha256:73797de5f211a138cf350ed8ac79afa0ff414b0ffd9346b83e368c1dcf9753f2","observation_id":"fc774a44-1770-415b-b112-5fa0b5eeec0f","resolution":{"observed_at":"2026-08-10T16:11:51.899245Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}}],"paper":{"arxiv_id":"2501.13435","last_updated":"2025-01-23T07:43:56Z","latest_version":1,"primary_category":"cs.CV","snapshot_observed_at":"2026-08-10T15:55:22.412630Z","submitted_at":"2025-01-23T07:43:56Z","title":"GC-ConsFlow: Leveraging Optical Flow Residuals and Global Context for Robust Deepfake Detection"},"reference_resolution":{"displayed":22,"state_counts":{"malformed_identifier":0,"metadata_mismatch":0,"parse_uncertain":0,"unresolved":3,"verified_exact":0,"verified_fuzzy":19},"total_outbound_references":22},"refusal":"A citation records a reference. It does not transfer a finding from one paper to another.","schema":"pith.paper-citation-record.v1","standing_sources":[{"observed_at":"2026-08-10T06:31:04.303077+00:00","source":"crossref"},{"observed_at":"2026-08-10T06:30:57.382061+00:00","source":"retraction_watch"}],"thesis":"As of 10 August 2026, this Paper Citation Record lists 22 of 22 outbound references and 1 inbound Pith citation observation for arXiv:2501.13435."}