{"as_of":"2026-08-08T11:17:00Z","caps":{"database_statements":6,"inbound":100,"outbound":100},"context_digest":"sha256:140394ec25a6ca63859e75894966323c47376446737ae638a81f5afc63aaec5c","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":"2026-08-05T18:14:42.674457Z","state":"measured"},{"denominator":22,"lane":"standing_notices","note":"One-hop event checks from named stored sources.","records_observed":22,"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/2508.14980/citation-record","integrity":"/paper/2508.14980/integrity","json":"/paper/2508.14980/citation-record.json","paper":"/paper/2508.14980"},"outbound":[{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-05T18:14:45.025543Z","title":"Unified physical-digital attack detection chal- lenge","venue":null,"work_id":"ec46c8e8-5a9d-489e-9120-e560c76c13cd","year":2024},"citing_paper":{"arxiv_id":"2508.14980","last_updated":"2025-08-20T18:05:49Z","snapshot_observed_at":"2026-08-05T18:14:39.389338Z","submitted_at":"2025-08-20T18:05:49Z","title":"Paired-Sampling Contrastive Framework for Joint Physical-Digital Face Attack Detection","version":1},"reference_index":1,"source":"pdf_text","source_observed_at":"2026-08-05T18:14:40.527613Z"},"links":{"citing_paper":"/paper/2508.14980"},"observation_digest":"sha256:6686cd91014576adefdd5b8aa6cdb4184447c339677bfd25186d304338d831df","observation_id":"1d4cc3e1-55b0-47f1-b4d9-d6b22b0123a7","resolution":{"observed_at":"2026-08-05T18:14:45.089487Z","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":"2026-08-05T18:14:44.867144Z","title":"Benchmarking joint face spoofing and forgery detection with visual and physiological cues.IEEE Transactions on Dependable and Secure Computing, 21(5): 4327–4342, 2024","venue":null,"work_id":"40c80f00-79ed-42c8-a535-12fc751985d2","year":2024},"citing_paper":{"arxiv_id":"2508.14980","last_updated":"2025-08-20T18:05:49Z","snapshot_observed_at":"2026-08-05T18:14:39.389338Z","submitted_at":"2025-08-20T18:05:49Z","title":"Paired-Sampling Contrastive Framework for Joint Physical-Digital Face Attack Detection","version":1},"reference_index":2,"source":"pdf_text","source_observed_at":"2026-08-05T18:14:40.639416Z"},"links":{"citing_paper":"/paper/2508.14980"},"observation_digest":"sha256:3b1dc9e71fb5f95cc6f7e5e1f766ea11cbab24a8c0ef143e23141cb43c4c18f2","observation_id":"161c9b23-b1e4-4eb4-b7fd-b942a1416bc9","resolution":{"observed_at":"2026-08-05T18:14:44.953644Z","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":"2026-08-05T18:14:40.734975Z","title":"Efficientnet: Rethinking model scaling for convolutional neural networks","venue":null,"work_id":null,"year":null},"citing_paper":{"arxiv_id":"2508.14980","last_updated":"2025-08-20T18:05:49Z","snapshot_observed_at":"2026-08-05T18:14:39.389338Z","submitted_at":"2025-08-20T18:05:49Z","title":"Paired-Sampling Contrastive Framework for Joint Physical-Digital Face Attack Detection","version":1},"reference_index":3,"source":"pdf_text","source_observed_at":"2026-08-05T18:14:40.734975Z"},"links":{"citing_paper":"/paper/2508.14980"},"observation_digest":"sha256:81086a40b768b630601ac4c54222784caa735ba1de83375b3994ed0399be58da","observation_id":"f6d45470-e2a6-49db-8b35-7d7accca4a2d","resolution":{"observed_at":"2026-08-05T18:14:40.734975Z","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":"2026-08-05T18:14:44.693824Z","title":"Bio- metric face presentation attack detection with multi-channel convolutional neural network.IEEE transactions on infor- mation forensics and security, 15:42–55, 2019","venue":null,"work_id":"22628f99-c217-4dc5-95d3-9ba3478b30d2","year":2019},"citing_paper":{"arxiv_id":"2508.14980","last_updated":"2025-08-20T18:05:49Z","snapshot_observed_at":"2026-08-05T18:14:39.389338Z","submitted_at":"2025-08-20T18:05:49Z","title":"Paired-Sampling Contrastive Framework for Joint Physical-Digital Face Attack Detection","version":1},"reference_index":4,"source":"pdf_text","source_observed_at":"2026-08-05T18:14:40.860697Z"},"links":{"citing_paper":"/paper/2508.14980"},"observation_digest":"sha256:34b446fe4c15b6e8dc3b468e7f4d94fbaf348a1d8573762f90ea0cf838fe650c","observation_id":"9efdf0f4-79e0-433e-a7b9-a0a6f9e017b9","resolution":{"observed_at":"2026-08-05T18:14:44.760080Z","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":"2010.11929","last_updated":"2021-06-03T13:08:56Z","snapshot_observed_at":"2026-07-06T02:11:23.670680Z","submitted_at":"2020-10-22T17:55:59Z","title":"An Image is Worth 16x16 Words: Transformers for Image Recognition at Scale","version":2},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2010.11929","snapshot_observed_at":"2026-08-05T18:14:41.000849Z","title":"An image is worth 16x16 words: Trans- formers for image recognition at scale.arXiv preprint arXiv:2010.11929, 2020","venue":null,"work_id":null,"year":2010},"citing_paper":{"arxiv_id":"2508.14980","last_updated":"2025-08-20T18:05:49Z","snapshot_observed_at":"2026-08-05T18:14:39.389338Z","submitted_at":"2025-08-20T18:05:49Z","title":"Paired-Sampling Contrastive Framework for Joint Physical-Digital Face Attack Detection","version":1},"reference_index":5,"source":"pdf_text","source_observed_at":"2026-08-05T18:14:41.000849Z"},"links":{"cited_paper":"/paper/2010.11929","citing_paper":"/paper/2508.14980"},"observation_digest":"sha256:b265a17b977f8876cfd4809c341927b3e817dfc75fac3fd5b14522a0b854f257","observation_id":"266b8765-4900-4330-8141-eb08ee0bcca3","resolution":{"observed_at":"2026-08-05T18:14:41.000849Z","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":"2026-08-05T18:14:44.524668Z","title":"Forgery-aware adaptive learning with vision transformer for generalized face forgery detection.IEEE Transactions on Circuits and Systems for Video Technology, 2024","venue":null,"work_id":"71b00909-95f4-4e71-9799-641f2127636d","year":2024},"citing_paper":{"arxiv_id":"2508.14980","last_updated":"2025-08-20T18:05:49Z","snapshot_observed_at":"2026-08-05T18:14:39.389338Z","submitted_at":"2025-08-20T18:05:49Z","title":"Paired-Sampling Contrastive Framework for Joint Physical-Digital Face Attack Detection","version":1},"reference_index":6,"source":"pdf_text","source_observed_at":"2026-08-05T18:14:41.107783Z"},"links":{"citing_paper":"/paper/2508.14980"},"observation_digest":"sha256:c23e7aff130e5c2f8443412a6445e1bb527b6c77b924e94d2fc7455f77167c4b","observation_id":"cd16e83b-ca36-4285-85d6-e637a86b6c25","resolution":{"observed_at":"2026-08-05T18:14:44.625307Z","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":"2026-08-05T18:14:44.409161Z","title":"Laa-net: Localized artifact attention network for quality-agnostic and generalizable deepfake de- tection","venue":null,"work_id":"1eda90b2-2213-441c-b3f7-395a35bcacea","year":2024},"citing_paper":{"arxiv_id":"2508.14980","last_updated":"2025-08-20T18:05:49Z","snapshot_observed_at":"2026-08-05T18:14:39.389338Z","submitted_at":"2025-08-20T18:05:49Z","title":"Paired-Sampling Contrastive Framework for Joint Physical-Digital Face Attack Detection","version":1},"reference_index":7,"source":"pdf_text","source_observed_at":"2026-08-05T18:14:41.237055Z"},"links":{"citing_paper":"/paper/2508.14980"},"observation_digest":"sha256:72538e1a91c9a2976672126aa2d239000865b0496cb39e6dd8d310301ce90983","observation_id":"9d31a2d5-3a1d-4480-b043-5573650655fc","resolution":{"observed_at":"2026-08-05T18:14:44.456437Z","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":"2026-08-05T18:14:41.346375Z","title":"Trufor: Leveraging all-round clues for trustworthy image forgery detection and localiza- tion","venue":null,"work_id":null,"year":null},"citing_paper":{"arxiv_id":"2508.14980","last_updated":"2025-08-20T18:05:49Z","snapshot_observed_at":"2026-08-05T18:14:39.389338Z","submitted_at":"2025-08-20T18:05:49Z","title":"Paired-Sampling Contrastive Framework for Joint Physical-Digital Face Attack Detection","version":1},"reference_index":8,"source":"pdf_text","source_observed_at":"2026-08-05T18:14:41.346375Z"},"links":{"citing_paper":"/paper/2508.14980"},"observation_digest":"sha256:08804149253b832c5cccf054f85d1d21045e86f8ad7e7520df3b502c69b332c2","observation_id":"003d9a29-39df-4b14-b1e9-cc87d6c59880","resolution":{"observed_at":"2026-08-05T18:14:41.346375Z","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":"2026-08-05T18:14:44.229043Z","title":"Implicit identity leakage: The stum- bling block to improving deepfake detection generalization","venue":null,"work_id":"e1ef5f21-c1cb-46a1-a115-2f92b796bd46","year":2023},"citing_paper":{"arxiv_id":"2508.14980","last_updated":"2025-08-20T18:05:49Z","snapshot_observed_at":"2026-08-05T18:14:39.389338Z","submitted_at":"2025-08-20T18:05:49Z","title":"Paired-Sampling Contrastive Framework for Joint Physical-Digital Face Attack Detection","version":1},"reference_index":9,"source":"pdf_text","source_observed_at":"2026-08-05T18:14:41.461027Z"},"links":{"citing_paper":"/paper/2508.14980"},"observation_digest":"sha256:4d498b131719da90e0c568d8667ff15cefa561e304d4d69bc48852fe3a4388d3","observation_id":"06edd40f-17de-4494-a775-e9f2ff4f1cfd","resolution":{"observed_at":"2026-08-05T18:14:44.318841Z","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":"2026-08-05T18:14:44.082906Z","title":"Detecting deep- fakes with self-blended images","venue":null,"work_id":"ba365a92-6e79-422c-991d-a70d9b6b97fb","year":2022},"citing_paper":{"arxiv_id":"2508.14980","last_updated":"2025-08-20T18:05:49Z","snapshot_observed_at":"2026-08-05T18:14:39.389338Z","submitted_at":"2025-08-20T18:05:49Z","title":"Paired-Sampling Contrastive Framework for Joint Physical-Digital Face Attack Detection","version":1},"reference_index":10,"source":"pdf_text","source_observed_at":"2026-08-05T18:14:41.563358Z"},"links":{"citing_paper":"/paper/2508.14980"},"observation_digest":"sha256:2b1044d4e5cf1b7473bac82b8095321c97e5ee4ce36c8035a054cc34962e2cbe","observation_id":"b3b1998b-de0c-4342-853f-776295167263","resolution":{"observed_at":"2026-08-05T18:14:44.127922Z","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":"2026-08-05T18:14:43.936703Z","title":"Implicit identity driven deepfake face swapping detection","venue":null,"work_id":"25e60871-bb7c-47e7-9e24-1aa56dd9a963","year":2023},"citing_paper":{"arxiv_id":"2508.14980","last_updated":"2025-08-20T18:05:49Z","snapshot_observed_at":"2026-08-05T18:14:39.389338Z","submitted_at":"2025-08-20T18:05:49Z","title":"Paired-Sampling Contrastive Framework for Joint Physical-Digital Face Attack Detection","version":1},"reference_index":11,"source":"pdf_text","source_observed_at":"2026-08-05T18:14:41.656276Z"},"links":{"citing_paper":"/paper/2508.14980"},"observation_digest":"sha256:2a1c9a7203decb07c580f63226f6171411854a230317537effb4aebab929502e","observation_id":"dea6cc93-f62c-4c58-aa74-d68636dee50d","resolution":{"observed_at":"2026-08-05T18:14:43.998688Z","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":"2026-08-05T18:14:43.774688Z","title":"Faceforen- sics++: Learning to detect manipulated facial images","venue":null,"work_id":"bb4c5529-2ae1-447a-a7a2-97fe55a89184","year":2019},"citing_paper":{"arxiv_id":"2508.14980","last_updated":"2025-08-20T18:05:49Z","snapshot_observed_at":"2026-08-05T18:14:39.389338Z","submitted_at":"2025-08-20T18:05:49Z","title":"Paired-Sampling Contrastive Framework for Joint Physical-Digital Face Attack Detection","version":1},"reference_index":12,"source":"pdf_text","source_observed_at":"2026-08-05T18:14:41.730288Z"},"links":{"citing_paper":"/paper/2508.14980"},"observation_digest":"sha256:6917bb7ffe62b6b794345053ffe4e52a091812a5a544077fb8cd1f767f34e8f3","observation_id":"9a706692-8c3b-4e4a-b6a2-c410012f99a4","resolution":{"observed_at":"2026-08-05T18:14:43.857472Z","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":"2026-08-05T18:14:43.616826Z","title":"Celeb-df: A large-scale challenging dataset for deep- fake forensics","venue":null,"work_id":"074e1685-47e4-4b5b-aa5b-a8091c72d485","year":2020},"citing_paper":{"arxiv_id":"2508.14980","last_updated":"2025-08-20T18:05:49Z","snapshot_observed_at":"2026-08-05T18:14:39.389338Z","submitted_at":"2025-08-20T18:05:49Z","title":"Paired-Sampling Contrastive Framework for Joint Physical-Digital Face Attack Detection","version":1},"reference_index":13,"source":"pdf_text","source_observed_at":"2026-08-05T18:14:41.856418Z"},"links":{"citing_paper":"/paper/2508.14980"},"observation_digest":"sha256:e2f24a994f982a229fb94411bcad550476694debc8ba55ba3190f1da75161f56","observation_id":"8d24bca9-0956-469c-b336-fccad8990bfe","resolution":{"observed_at":"2026-08-05T18:14:43.693652Z","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":"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":"2026-08-05T18:14:41.974082Z","title":"The deepfake detection challenge (dfdc) dataset.arXiv preprint arXiv:2006.07397, 2020","venue":null,"work_id":null,"year":2006},"citing_paper":{"arxiv_id":"2508.14980","last_updated":"2025-08-20T18:05:49Z","snapshot_observed_at":"2026-08-05T18:14:39.389338Z","submitted_at":"2025-08-20T18:05:49Z","title":"Paired-Sampling Contrastive Framework for Joint Physical-Digital Face Attack Detection","version":1},"reference_index":14,"source":"pdf_text","source_observed_at":"2026-08-05T18:14:41.974082Z"},"links":{"cited_paper":"/paper/2006.07397","citing_paper":"/paper/2508.14980"},"observation_digest":"sha256:b8d0d4579e9cdc8b44ad5d032f0db6c34a62a4b26a2cede931ebfd538853af97","observation_id":"1ec7e185-e745-4e1f-b071-41e17eae1585","resolution":{"observed_at":"2026-08-05T18:14:41.974082Z","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":"2026-08-05T18:14:43.498000Z","title":"Wilddeepfake: A challenging real-world dataset for deepfake detection","venue":null,"work_id":"035b3635-6124-4fa5-9bc0-4ce092d667bf","year":2020},"citing_paper":{"arxiv_id":"2508.14980","last_updated":"2025-08-20T18:05:49Z","snapshot_observed_at":"2026-08-05T18:14:39.389338Z","submitted_at":"2025-08-20T18:05:49Z","title":"Paired-Sampling Contrastive Framework for Joint Physical-Digital Face Attack Detection","version":1},"reference_index":15,"source":"pdf_text","source_observed_at":"2026-08-05T18:14:42.052828Z"},"links":{"citing_paper":"/paper/2508.14980"},"observation_digest":"sha256:be059a0625266fef010697f1b1b6ff1527935fb390e4cda3b30c4687776eb038","observation_id":"a32f5681-afe9-497a-956f-9f28d28cc768","resolution":{"observed_at":"2026-08-05T18:14:43.549264Z","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":"2026-08-05T18:14:43.410844Z","title":"Unified de- tection of digital and physical face attacks","venue":null,"work_id":"644c7c84-1b59-4d91-ae81-248390ba72cd","year":2023},"citing_paper":{"arxiv_id":"2508.14980","last_updated":"2025-08-20T18:05:49Z","snapshot_observed_at":"2026-08-05T18:14:39.389338Z","submitted_at":"2025-08-20T18:05:49Z","title":"Paired-Sampling Contrastive Framework for Joint Physical-Digital Face Attack Detection","version":1},"reference_index":16,"source":"pdf_text","source_observed_at":"2026-08-05T18:14:42.129049Z"},"links":{"citing_paper":"/paper/2508.14980"},"observation_digest":"sha256:11ef8728eff68245fb563a951931218f5f01faa26e49ce90059509838cfcc724","observation_id":"50d9f9da-83e4-424f-a57e-9bdc5e6635be","resolution":{"observed_at":"2026-08-05T18:14:43.451618Z","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":"1602.07261","last_updated":"2016-08-23T16:42:29Z","snapshot_observed_at":"2026-07-06T04:47:06.608643Z","submitted_at":"2016-02-23T18:44:39Z","title":"Inception-v4, Inception-ResNet and the Impact of Residual Connections on Learning","version":2},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"1602.07261","snapshot_observed_at":"2026-08-05T18:14:42.193505Z","title":null,"venue":null,"work_id":null,"year":2017},"citing_paper":{"arxiv_id":"2508.14980","last_updated":"2025-08-20T18:05:49Z","snapshot_observed_at":"2026-08-05T18:14:39.389338Z","submitted_at":"2025-08-20T18:05:49Z","title":"Paired-Sampling Contrastive Framework for Joint Physical-Digital Face Attack Detection","version":1},"reference_index":17,"source":"pdf_text","source_observed_at":"2026-08-05T18:14:42.193505Z"},"links":{"cited_paper":"/paper/1602.07261","citing_paper":"/paper/2508.14980"},"observation_digest":"sha256:40f4e96e7de0cc56ffe6884337684273c11df9d96a62701714e0f6cfc29821e3","observation_id":"e2289dec-c0c5-4185-b1b3-9a56a9a489f8","resolution":{"observed_at":"2026-08-05T18:14:42.193505Z","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":"2016.26033","doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-05T18:14:42.942829Z","title":"Joint face detection and alignment using multi-task cascaded convolutional networks.IEEE Signal Processing Letters, 23 (10):1499–1503, 2016","venue":null,"work_id":"7c5d21f8-5076-4e0d-9d0e-bd68442177f8","year":2016},"citing_paper":{"arxiv_id":"2508.14980","last_updated":"2025-08-20T18:05:49Z","snapshot_observed_at":"2026-08-05T18:14:39.389338Z","submitted_at":"2025-08-20T18:05:49Z","title":"Paired-Sampling Contrastive Framework for Joint Physical-Digital Face Attack Detection","version":1},"reference_index":18,"source":"pdf_text","source_observed_at":"2026-08-05T18:14:42.287496Z"},"links":{"citing_paper":"/paper/2508.14980"},"observation_digest":"sha256:a8ccd2788d9f4f70872818690d0fc2557bca6b338c9877e6ef738d74d734befe","observation_id":"907e3f77-0904-47cf-bb08-0de6ca2b230b","resolution":{"observed_at":"2026-08-05T18:14:43.010421Z","resolver_source":"raw_fallback","status":"metadata_mismatch"},"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":"2026-08-05T18:14:43.260009Z","title":"Focal loss for dense object detection","venue":null,"work_id":"26bd087b-eb4e-4092-ad06-fc45be37fef1","year":2017},"citing_paper":{"arxiv_id":"2508.14980","last_updated":"2025-08-20T18:05:49Z","snapshot_observed_at":"2026-08-05T18:14:39.389338Z","submitted_at":"2025-08-20T18:05:49Z","title":"Paired-Sampling Contrastive Framework for Joint Physical-Digital Face Attack Detection","version":1},"reference_index":19,"source":"pdf_text","source_observed_at":"2026-08-05T18:14:42.404955Z"},"links":{"citing_paper":"/paper/2508.14980"},"observation_digest":"sha256:d95baf9b729252741d6179a71ef080e0cc718a89184303158df39c45b3043a2f","observation_id":"f150cf5a-ffc0-4086-a596-3ddb28c15301","resolution":{"observed_at":"2026-08-05T18:14:43.343392Z","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":"2004.11362","last_updated":"2021-03-10T19:11:45Z","snapshot_observed_at":"2026-08-07T05:29:45.126060Z","submitted_at":"2020-04-23T17:58:56Z","title":"Supervised Contrastive Learning","version":5},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2004.11362","snapshot_observed_at":"2026-08-05T18:14:42.476566Z","title":"Supervised contrastive learning","venue":null,"work_id":null,"year":2020},"citing_paper":{"arxiv_id":"2508.14980","last_updated":"2025-08-20T18:05:49Z","snapshot_observed_at":"2026-08-05T18:14:39.389338Z","submitted_at":"2025-08-20T18:05:49Z","title":"Paired-Sampling Contrastive Framework for Joint Physical-Digital Face Attack Detection","version":1},"reference_index":20,"source":"pdf_text","source_observed_at":"2026-08-05T18:14:42.476566Z"},"links":{"cited_paper":"/paper/2004.11362","citing_paper":"/paper/2508.14980"},"observation_digest":"sha256:0f5b6df84616496bffed0aafc7613f39b5575c4aedad6caf5edb1dc09db84fac","observation_id":"8c3e36a4-0f8b-44d2-823f-3d08cf834d60","resolution":{"observed_at":"2026-08-05T18:14:42.476566Z","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":"2026-08-05T18:14:42.567874Z","title":"Convnext v2: Co-designing and scaling convnets with masked autoen- coders","venue":null,"work_id":null,"year":2023},"citing_paper":{"arxiv_id":"2508.14980","last_updated":"2025-08-20T18:05:49Z","snapshot_observed_at":"2026-08-05T18:14:39.389338Z","submitted_at":"2025-08-20T18:05:49Z","title":"Paired-Sampling Contrastive Framework for Joint Physical-Digital Face Attack Detection","version":1},"reference_index":21,"source":"pdf_text","source_observed_at":"2026-08-05T18:14:42.567874Z"},"links":{"citing_paper":"/paper/2508.14980"},"observation_digest":"sha256:b1bdc9df60cb6e670202a097048ea2b73a8c9c539bc6ceb9458a8f0b48f1f908","observation_id":"21f3637a-ba81-4a7c-83b0-cfbe45129002","resolution":{"observed_at":"2026-08-05T18:14:42.567874Z","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":"2026-08-05T18:14:43.136906Z","title":"Imagenet: A large-scale hierarchical im- age database","venue":null,"work_id":"7ef4f9a5-7c0c-455d-a0fd-28a2b991d930","year":2009},"citing_paper":{"arxiv_id":"2508.14980","last_updated":"2025-08-20T18:05:49Z","snapshot_observed_at":"2026-08-05T18:14:39.389338Z","submitted_at":"2025-08-20T18:05:49Z","title":"Paired-Sampling Contrastive Framework for Joint Physical-Digital Face Attack Detection","version":1},"reference_index":22,"source":"pdf_text","source_observed_at":"2026-08-05T18:14:42.674457Z"},"links":{"citing_paper":"/paper/2508.14980"},"observation_digest":"sha256:1d2398104eae726a1f3a6a1c5214c322c609fba1ff9708c68e6f1c7c2c2527b3","observation_id":"d3cd7aa3-600f-4166-b724-cf640d9c38ac","resolution":{"observed_at":"2026-08-05T18:14:43.168315Z","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"}}],"paper":{"arxiv_id":"2508.14980","last_updated":"2025-08-20T18:05:49Z","latest_version":1,"primary_category":"cs.CV","snapshot_observed_at":"2026-08-05T18:14:39.389338Z","submitted_at":"2025-08-20T18:05:49Z","title":"Paired-Sampling Contrastive Framework for Joint Physical-Digital Face Attack Detection"},"reference_resolution":{"displayed":22,"state_counts":{"malformed_identifier":0,"metadata_mismatch":1,"parse_uncertain":0,"unresolved":7,"verified_exact":0,"verified_fuzzy":14},"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":"2026-08-08T06:32:00.761636+00:00","source":"crossref"},{"observed_at":"2026-08-08T06:31:55.24221+00:00","source":"retraction_watch"}],"thesis":"As of 8 August 2026, this Paper Citation Record lists 22 of 22 outbound references and 0 inbound Pith citation observations for arXiv:2508.14980."}