{"as_of":"2026-08-20T23:05:00Z","caps":{"database_statements":6,"inbound":100,"outbound":100},"context_digest":"sha256:318f8c1137dc58d972aac8df4e8e7213609e50e5ec7285afe45e544eac1061d3","coverage":[{"denominator":0,"lane":"reference_resolution","note":"Typed states for the displayed outbound observations.","records_observed":0,"source":"paper_references, paper_reference_links","source_observed_at":null,"state":"measured"},{"denominator":5,"lane":"standing_notices","note":"One-hop event checks from named stored sources.","records_observed":5,"source":"scholarly_work_events, retraction_status_cache","source_observed_at":"2026-08-20T06:33:59.587034+00:00","state":"measured"},{"denominator":5,"lane":"inbound_itemization","note":"Pith citing papers itemized under the disclosed page cap.","records_observed":5,"source":"paper_references, paper_reference_links","source_observed_at":"2026-08-12T14:57:46.910229Z","state":"measured"},{"denominator":1,"lane":"external_citation_measurements","note":"A source-named dated measurement, never combined with another source.","records_observed":0,"source":"arxiv_reference","source_observed_at":"2026-05-18T23:51:55.085616Z","state":"measured"}],"external_citation_measurements":[],"inbound":[{"citation":{"cited_paper":{"arxiv_id":"2109.05673","last_updated":"2021-09-13T02:36:25Z","snapshot_observed_at":"2026-08-16T17:57:09.597100Z","submitted_at":"2021-09-13T02:36:25Z","title":"FaceGuard: Proactive Deepfake Detection","version":1},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2109.05673","snapshot_observed_at":"2026-08-12T14:57:46.910229Z","title":"Faceguard: Proactive deepfake detection","venue":null,"work_id":null,"year":2021},"citing_paper":{"arxiv_id":"2411.14798","last_updated":"2024-11-22T08:49:08Z","snapshot_observed_at":"2026-08-18T02:18:15.420569Z","submitted_at":"2024-11-22T08:49:08Z","title":"Facial Features Matter: a Dynamic Watermark based Proactive Deepfake Detection Approach","version":1},"reference_index":41,"source":"pdf_text","source_observed_at":"2026-08-12T14:57:46.910229Z"},"links":{"cited_paper":"/paper/2109.05673","citing_paper":"/paper/2411.14798"},"observation_digest":"sha256:556d8f2d294a6f5d0574076f344ea46012ad6c76eb47782e9eb8bde10bc045a8","observation_id":"39cca91d-8fcd-496a-a50d-62e54a0a877a","resolution":{"observed_at":"2026-08-12T14:57:46.910229Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2109.05673","last_updated":"2021-09-13T02:36:25Z","snapshot_observed_at":"2026-08-16T17:57:09.597100Z","submitted_at":"2021-09-13T02:36:25Z","title":"FaceGuard: Proactive Deepfake Detection","version":1},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2109.05673","snapshot_observed_at":"2026-08-12T12:29:25.037834Z","title":null,"venue":null,"work_id":null,"year":2021},"citing_paper":{"arxiv_id":"2411.17209","last_updated":"2024-11-26T08:24:56Z","snapshot_observed_at":"2026-08-19T09:03:06.301772Z","submitted_at":"2024-11-26T08:24:56Z","title":"LampMark: Proactive Deepfake Detection via Training-Free Landmark Perceptual Watermarks","version":1},"reference_index":50,"source":"pdf_text","source_observed_at":"2026-08-12T12:29:25.037834Z"},"links":{"cited_paper":"/paper/2109.05673","citing_paper":"/paper/2411.17209"},"observation_digest":"sha256:b58bfd8c78fe5b6881441683c38def148d8476400b4ccc90784bdf8e2b79ef6f","observation_id":"e5c2b490-20af-41e9-8cc3-0049fc1d349d","resolution":{"observed_at":"2026-08-12T12:29:25.037834Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2109.05673","last_updated":"2021-09-13T02:36:25Z","snapshot_observed_at":"2026-08-16T17:57:09.597100Z","submitted_at":"2021-09-13T02:36:25Z","title":"FaceGuard: Proactive Deepfake Detection","version":1},"cited_work":{"arxiv_id":"2109.05673","doi":null,"metadata_source":"arxiv_reference","pith_arxiv_id":"2109.05673","snapshot_observed_at":"2026-06-05T21:23:00.469572Z","title":"Faceguard: Proactive deepfake detection","venue":null,"work_id":"4d411d94-e2f2-4176-a1cd-234960913186","year":2021},"citing_paper":{"arxiv_id":"2508.06248","last_updated":"2026-05-11T10:15:54Z","snapshot_observed_at":"2026-08-12T21:50:11.157315Z","submitted_at":"2025-08-08T12:03:56Z","title":"Deepfake Detection that Generalizes Across Benchmarks","version":4},"reference_index":61,"source":"pdf_text","source_observed_at":"2026-05-18T23:47:27.729587Z"},"links":{"cited_paper":"/paper/2109.05673","citing_paper":"/paper/2508.06248"},"observation_digest":"sha256:6d9625efd0238af863f1417f48839457878ca448d9e18df273344adc2dd6d76d","observation_id":"f8bd274b-4e23-495e-b42a-af7d1d2529e7","resolution":{"observed_at":"2026-05-18T23:51:55.089298Z","resolver_source":"arxiv_id","status":"verified_exact"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-20T06:33:59.587034+00:00","source":"crossref"},{"observed_at":"2026-08-20T06:33:54.927442+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"2109.05673","last_updated":"2021-09-13T02:36:25Z","snapshot_observed_at":"2026-08-16T17:57:09.597100Z","submitted_at":"2021-09-13T02:36:25Z","title":"FaceGuard: Proactive Deepfake Detection","version":1},"cited_work":{"arxiv_id":"2109.05673","doi":null,"metadata_source":"arxiv_reference","pith_arxiv_id":"2109.05673","snapshot_observed_at":"2026-06-05T21:23:00.469572Z","title":"Faceguard: Proactive deepfake detection","venue":null,"work_id":"4d411d94-e2f2-4176-a1cd-234960913186","year":2021},"citing_paper":{"arxiv_id":"2604.26342","last_updated":"2026-06-27T10:35:57Z","snapshot_observed_at":"2026-08-15T01:53:34.017525Z","submitted_at":"2026-04-29T06:50:19Z","title":"Whether, Which, and Whose: Solving the Triple Challenge of Deepfake Proactive Forensics in Multi-Face Scenarios","version":1},"reference_index":45,"source":"pdf_text","source_observed_at":"2026-05-07T13:39:45.318346Z"},"links":{"cited_paper":"/paper/2109.05673","citing_paper":"/paper/2604.26342"},"observation_digest":"sha256:be1def44cfd34e8d5754bfe4bad5229ea94442ca692a35b75bdb2d6b167af9fc","observation_id":"ad9ee2c2-b716-4458-8db9-c431e01735ae","resolution":{"observed_at":"2026-05-12T08:51:24.333148Z","resolver_source":"arxiv_id","status":"verified_exact"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-20T06:33:59.587034+00:00","source":"crossref"},{"observed_at":"2026-08-20T06:33:54.927442+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"2109.05673","last_updated":"2021-09-13T02:36:25Z","snapshot_observed_at":"2026-08-16T17:57:09.597100Z","submitted_at":"2021-09-13T02:36:25Z","title":"FaceGuard: Proactive Deepfake Detection","version":1},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2109.05673","snapshot_observed_at":"2026-08-01T15:27:47.994989Z","title":null,"venue":null,"work_id":null,"year":2021},"citing_paper":{"arxiv_id":"2607.20564","last_updated":"2026-08-04T02:51:42Z","snapshot_observed_at":"2026-08-20T02:50:06.319425Z","submitted_at":"2026-07-20T19:05:20Z","title":"PhantomSeal: Proactive Deepfakes Defense with Identity/Context Protection and Forensic Tracing","version":1},"reference_index":100,"source":"pdf_text","source_observed_at":"2026-08-01T15:27:47.994989Z"},"links":{"cited_paper":"/paper/2109.05673","citing_paper":"/paper/2607.20564"},"observation_digest":"sha256:656147ec883f204d3dee85951a57085ab715ff574b37128f8c664fd31fedfc5c","observation_id":"7b527dff-c01c-48f0-8458-19a2a04368a0","resolution":{"observed_at":"2026-08-01T15:27:47.994989Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}}],"links":{"evidence":"/evidence","html":"/paper/2109.05673/citation-record","integrity":"/paper/2109.05673/integrity","json":"/paper/2109.05673/citation-record.json","paper":"/paper/2109.05673"},"outbound":[],"paper":{"arxiv_id":"2109.05673","last_updated":"2021-09-13T02:36:25Z","latest_version":1,"primary_category":"cs.CV","snapshot_observed_at":"2026-08-16T17:57:09.597100Z","submitted_at":"2021-09-13T02:36:25Z","title":"FaceGuard: Proactive Deepfake Detection"},"reference_resolution":{"displayed":0,"state_counts":{"malformed_identifier":0,"metadata_mismatch":0,"parse_uncertain":0,"unresolved":0,"verified_exact":0,"verified_fuzzy":0},"total_outbound_references":0},"refusal":"A citation records a reference. It does not transfer a finding from one paper to another.","schema":"pith.paper-citation-record.v1","standing_sources":[{"observed_at":"2026-08-20T06:33:59.587034+00:00","source":"crossref"},{"observed_at":"2026-08-20T06:33:54.927442+00:00","source":"retraction_watch"}],"thesis":"As of 20 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 5 inbound Pith citation observations for arXiv:2109.05673."}