{"as_of":"2026-08-10T23:07:00Z","caps":{"database_statements":6,"inbound":100,"outbound":100},"context_digest":"sha256:403187392fb24d89ad47f7d87141045ea8a6eae7a96f2f5f5390eeb23e5a1cd5","coverage":[{"denominator":65,"lane":"reference_resolution","note":"Typed states for the displayed outbound observations.","records_observed":65,"source":"paper_references, paper_reference_links","source_observed_at":"2026-08-10T22:05:27.097655Z","state":"measured"},{"denominator":69,"lane":"standing_notices","note":"One-hop event checks from named stored sources.","records_observed":69,"source":"scholarly_work_events, retraction_status_cache","source_observed_at":"2026-08-10T06:31:04.303077+00:00","state":"measured"},{"denominator":4,"lane":"inbound_itemization","note":"Pith citing papers itemized under the disclosed page cap.","records_observed":4,"source":"paper_references, paper_reference_links","source_observed_at":"2026-08-06T22:22:36.893017Z","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":"2026-05-10T06:56:47.191988Z","state":"measured"}],"external_citation_measurements":[],"inbound":[{"citation":{"cited_paper":{"arxiv_id":"2501.02892","last_updated":"2025-01-06T10:14:52Z","snapshot_observed_at":"2026-08-10T21:58:36.963226Z","submitted_at":"2025-01-06T10:14:52Z","title":"FoundPAD: Foundation Models Reloaded for Face Presentation Attack Detection","version":1},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2501.02892","snapshot_observed_at":"2026-08-06T22:22:36.893017Z","title":null,"venue":null,"work_id":null,"year":2025},"citing_paper":{"arxiv_id":"2506.21895","last_updated":"2025-06-27T04:28:29Z","snapshot_observed_at":"2026-08-06T22:14:08.147076Z","submitted_at":"2025-06-27T04:28:29Z","title":"Exploring Task-Solving Paradigm for Generalized Cross-Domain Face Anti-Spoofing via Reinforcement Fine-Tuning","version":1},"reference_index":40,"source":"arxiv_source","source_observed_at":"2026-08-06T22:22:36.893017Z"},"links":{"cited_paper":"/paper/2501.02892","citing_paper":"/paper/2506.21895"},"observation_digest":"sha256:434a731ab3aa1271d50557f6273b999c92c47ded82b729bad750b898b7165369","observation_id":"243913b9-0ffe-4f05-a5cd-65ae76555649","resolution":{"observed_at":"2026-08-06T22:22:36.893017Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2501.02892","last_updated":"2025-01-06T10:14:52Z","snapshot_observed_at":"2026-08-10T21:58:36.963226Z","submitted_at":"2025-01-06T10:14:52Z","title":"FoundPAD: Foundation Models Reloaded for Face Presentation Attack Detection","version":1},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2501.02892","snapshot_observed_at":"2026-08-06T15:43:10.801542Z","title":"FoundPAD: Foundation models reloaded for face presenta- tion attack detection,","venue":null,"work_id":null,"year":2025},"citing_paper":{"arxiv_id":"2507.15285","last_updated":"2025-07-21T06:35:46Z","snapshot_observed_at":"2026-08-08T20:20:51.804408Z","submitted_at":"2025-07-21T06:35:46Z","title":"In-context Learning of Vision Language Models for Detection of Physical and Digital Attacks against Face Recognition Systems","version":1},"reference_index":4,"source":"pdf_text","source_observed_at":"2026-08-06T15:43:10.801542Z"},"links":{"cited_paper":"/paper/2501.02892","citing_paper":"/paper/2507.15285"},"observation_digest":"sha256:a352f116c8775d8817344dfeb266be4a5a8bcf5b1154a99c5eb79b77f49bb31e","observation_id":"b0ece18f-ff03-4cd8-a497-492c0e87d9b3","resolution":{"observed_at":"2026-08-06T15:43:10.801542Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2501.02892","last_updated":"2025-01-06T10:14:52Z","snapshot_observed_at":"2026-08-10T21:58:36.963226Z","submitted_at":"2025-01-06T10:14:52Z","title":"FoundPAD: Foundation Models Reloaded for Face Presentation Attack Detection","version":1},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2501.02892","snapshot_observed_at":"2026-08-06T15:16:26.193352Z","title":"Ozgur, E","venue":null,"work_id":null,"year":2025},"citing_paper":{"arxiv_id":"2507.16393","last_updated":"2025-07-22T09:38:21Z","snapshot_observed_at":"2026-08-06T21:59:26.807153Z","submitted_at":"2025-07-22T09:38:21Z","title":"Are Foundation Models All You Need for Zero-shot Face Presentation Attack Detection?","version":1},"reference_index":41,"source":"pdf_text","source_observed_at":"2026-08-06T15:16:26.193352Z"},"links":{"cited_paper":"/paper/2501.02892","citing_paper":"/paper/2507.16393"},"observation_digest":"sha256:a19f127bc38fba2281416c82891b7e7c94f3a0e3ce766a89c3168d06852a6e7d","observation_id":"7bd550b4-777e-4afa-b534-44866e440351","resolution":{"observed_at":"2026-08-06T15:16:26.193352Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2501.02892","last_updated":"2025-01-06T10:14:52Z","snapshot_observed_at":"2026-08-10T21:58:36.963226Z","submitted_at":"2025-01-06T10:14:52Z","title":"FoundPAD: Foundation Models Reloaded for Face Presentation Attack Detection","version":1},"cited_work":{"arxiv_id":"2501.02892","doi":null,"metadata_source":"arxiv_reference","pith_arxiv_id":"2501.02892","snapshot_observed_at":"2026-06-05T21:23:00.469572Z","title":"Foundpad: Foundation models reloaded for face presentation attack detection","venue":null,"work_id":"b08b19e0-fcd0-4562-a219-3f15e8692ecc","year":2025},"citing_paper":{"arxiv_id":"2604.17321","last_updated":"2026-04-19T08:21:45Z","snapshot_observed_at":"2026-07-06T23:04:28.260463Z","submitted_at":"2026-04-19T08:21:45Z","title":"R-FLoRA: Residual-Statistic-Gated Low-Rank Adaptation for Single-Image Face Morphing Attack Detection","version":1},"reference_index":15,"source":"pdf_text","source_observed_at":"2026-05-10T06:56:28.212908Z"},"links":{"cited_paper":"/paper/2501.02892","citing_paper":"/paper/2604.17321"},"observation_digest":"sha256:92ccd4f4d0c129a0efb5ca865f1cc40ebc0ba02b859c6e8980d5dc036306d9bc","observation_id":"16068987-e881-4eee-8173-50b377141ce6","resolution":{"observed_at":"2026-05-10T06:56:47.193490Z","resolver_source":"arxiv_id","status":"verified_exact"},"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"}}],"links":{"evidence":"/evidence","html":"/paper/2501.02892/citation-record","integrity":"/paper/2501.02892/integrity","json":"/paper/2501.02892/citation-record.json","paper":"/paper/2501.02892"},"outbound":[{"citation":{"cited_paper":{"arxiv_id":"2012.13255","last_updated":"2020-12-22T07:42:30Z","snapshot_observed_at":"2026-08-08T07:37:46.709970Z","submitted_at":"2020-12-22T07:42:30Z","title":"Intrinsic Dimensionality Explains the Effectiveness of Language Model Fine-Tuning","version":1},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2012.13255","snapshot_observed_at":"2026-08-10T22:05:26.675087Z","title":"In - trinsic dimensionality explains the effectiveness of lang uage model fine-tuning","venue":null,"work_id":null,"year":2012},"citing_paper":{"arxiv_id":"2501.02892","last_updated":"2025-01-06T10:14:52Z","snapshot_observed_at":"2026-08-10T21:58:36.963226Z","submitted_at":"2025-01-06T10:14:52Z","title":"FoundPAD: Foundation Models Reloaded for Face Presentation Attack Detection","version":1},"reference_index":1,"source":"pdf_text","source_observed_at":"2026-08-10T22:05:26.675087Z"},"links":{"cited_paper":"/paper/2012.13255","citing_paper":"/paper/2501.02892"},"observation_digest":"sha256:07446d9cb0f44a7198a7a1fa7e035a6796f07816c341d3a971ef64ced3a35f07","observation_id":"d9805ca1-f0f9-4a8f-bc4d-15e2b49129bc","resolution":{"observed_at":"2026-08-10T22:05:26.675087Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2010.11929","last_updated":"2021-06-03T13:08:56Z","snapshot_observed_at":"2026-08-10T01:12:16.468283Z","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":"2026-08-10T22:05:26.681232Z","title":"An image is worth 16x16 words: Trans - formers for image recognition at scale","venue":null,"work_id":null,"year":2010},"citing_paper":{"arxiv_id":"2501.02892","last_updated":"2025-01-06T10:14:52Z","snapshot_observed_at":"2026-08-10T21:58:36.963226Z","submitted_at":"2025-01-06T10:14:52Z","title":"FoundPAD: Foundation Models Reloaded for Face Presentation Attack Detection","version":1},"reference_index":2,"source":"pdf_text","source_observed_at":"2026-08-10T22:05:26.681232Z"},"links":{"cited_paper":"/paper/2010.11929","citing_paper":"/paper/2501.02892"},"observation_digest":"sha256:f2cbaa535d48235c75171f970f2569b733dab2deb1ced5d469676440eb74e289","observation_id":"066983f4-2f04-4b9b-826c-17e51374d7f9","resolution":{"observed_at":"2026-08-10T22:05:26.681232Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2108.07258","last_updated":"2022-07-12T23:45:14Z","snapshot_observed_at":"2026-08-02T09:20:40.804790Z","submitted_at":"2021-08-16T17:50:08Z","title":"On the Opportunities and Risks of Foundation Models","version":3},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2108.07258","snapshot_observed_at":"2026-08-10T22:05:26.687300Z","title":"Hudson, Ehsan Adeli, Russ B","venue":null,"work_id":null,"year":2021},"citing_paper":{"arxiv_id":"2501.02892","last_updated":"2025-01-06T10:14:52Z","snapshot_observed_at":"2026-08-10T21:58:36.963226Z","submitted_at":"2025-01-06T10:14:52Z","title":"FoundPAD: Foundation Models Reloaded for Face Presentation Attack Detection","version":1},"reference_index":3,"source":"pdf_text","source_observed_at":"2026-08-10T22:05:26.687300Z"},"links":{"cited_paper":"/paper/2108.07258","citing_paper":"/paper/2501.02892"},"observation_digest":"sha256:cbccac2b0f4126d78cdc8112ed952fddebda7d730ed9547bf203a958786265d6","observation_id":"3aeaa3d8-09af-4f3d-bbba-446a585af03c","resolution":{"observed_at":"2026-08-10T22:05:26.687300Z","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":"2026-08-10T22:05:28.419025Z","title":"OULU-NPU: A mobile face presentation attack database with real-world variations","venue":null,"work_id":"ffe0de27-ceac-4c7a-8bfe-3de3ce362aeb","year":2017},"citing_paper":{"arxiv_id":"2501.02892","last_updated":"2025-01-06T10:14:52Z","snapshot_observed_at":"2026-08-10T21:58:36.963226Z","submitted_at":"2025-01-06T10:14:52Z","title":"FoundPAD: Foundation Models Reloaded for Face Presentation Attack Detection","version":1},"reference_index":4,"source":"pdf_text","source_observed_at":"2026-08-10T22:05:26.695712Z"},"links":{"citing_paper":"/paper/2501.02892"},"observation_digest":"sha256:e5e50b7dca9e45b2aabfe75b8eab61472a43843bf86edfb6e3815d44b6ba8660","observation_id":"bab9ac3f-d2ee-43ca-a456-95b1cd97ce19","resolution":{"observed_at":"2026-08-10T22:05:28.423960Z","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":"2026-08-10T22:05:28.401316Z","title":"Elasticface: Elastic margin loss for deep face recognition","venue":null,"work_id":"4210578f-eab7-4a09-8a07-8375f9a4125d","year":2022},"citing_paper":{"arxiv_id":"2501.02892","last_updated":"2025-01-06T10:14:52Z","snapshot_observed_at":"2026-08-10T21:58:36.963226Z","submitted_at":"2025-01-06T10:14:52Z","title":"FoundPAD: Foundation Models Reloaded for Face Presentation Attack Detection","version":1},"reference_index":5,"source":"pdf_text","source_observed_at":"2026-08-10T22:05:26.704527Z"},"links":{"citing_paper":"/paper/2501.02892"},"observation_digest":"sha256:6a4048773706144637eecdf609255c605fcbb3ff7e5d0946a80951476be2c7f1","observation_id":"429bff55-8cf7-4191-8fa7-0a8134aa743c","resolution":{"observed_at":"2026-08-10T22:05:28.408139Z","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":"2026-08-10T22:05:28.377491Z","title":"Cr-fiqa: Face image quality assessment by learning sample relative classifiability, 2023","venue":null,"work_id":"46fb781e-e995-4bc2-8a3e-c6f59a3e4884","year":2023},"citing_paper":{"arxiv_id":"2501.02892","last_updated":"2025-01-06T10:14:52Z","snapshot_observed_at":"2026-08-10T21:58:36.963226Z","submitted_at":"2025-01-06T10:14:52Z","title":"FoundPAD: Foundation Models Reloaded for Face Presentation Attack Detection","version":1},"reference_index":6,"source":"pdf_text","source_observed_at":"2026-08-10T22:05:26.709018Z"},"links":{"citing_paper":"/paper/2501.02892"},"observation_digest":"sha256:f3faa6e49e9110d4858c0d0da2bbe20d731dcedeba7ab283aded81929fb2e21f","observation_id":"5316276c-b5fe-4538-a37e-a9ac5bc6752f","resolution":{"observed_at":"2026-08-10T22:05:28.385341Z","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":"2026-08-10T22:05:28.354828Z","title":"Adapting vision foundation models for plant pheno- typing","venue":null,"work_id":"80636bbb-da0a-41d9-b761-e38531d58f9c","year":2023},"citing_paper":{"arxiv_id":"2501.02892","last_updated":"2025-01-06T10:14:52Z","snapshot_observed_at":"2026-08-10T21:58:36.963226Z","submitted_at":"2025-01-06T10:14:52Z","title":"FoundPAD: Foundation Models Reloaded for Face Presentation Attack Detection","version":1},"reference_index":7,"source":"pdf_text","source_observed_at":"2026-08-10T22:05:26.717614Z"},"links":{"citing_paper":"/paper/2501.02892"},"observation_digest":"sha256:1b2d3cc61a7abd67ed0b5dc17ede1f191039ffe0d0e04f759b357c4ed6e3bf78","observation_id":"0c032e15-475f-43e5-b7b2-a6c1dc59b67a","resolution":{"observed_at":"2026-08-10T22:05:28.360596Z","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":null,"pith_arxiv_id":null,"snapshot_observed_at":"2026-08-10T22:05:26.727324Z","title":"Adaptformer: Adapting vision transformers for scalable visual recogni- tion","venue":null,"work_id":null,"year":2022},"citing_paper":{"arxiv_id":"2501.02892","last_updated":"2025-01-06T10:14:52Z","snapshot_observed_at":"2026-08-10T21:58:36.963226Z","submitted_at":"2025-01-06T10:14:52Z","title":"FoundPAD: Foundation Models Reloaded for Face Presentation Attack Detection","version":1},"reference_index":8,"source":"pdf_text","source_observed_at":"2026-08-10T22:05:26.727324Z"},"links":{"citing_paper":"/paper/2501.02892"},"observation_digest":"sha256:73678540ef434ea49c4145ce70f47868b4b89fa55ae3ffd44461406954867137","observation_id":"35535fe8-67e2-4567-9aad-e74969fd8d53","resolution":{"observed_at":"2026-08-10T22:05:26.727324Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2205.08534","last_updated":"2023-02-13T15:50:22Z","snapshot_observed_at":"2026-08-07T21:44:39.930046Z","submitted_at":"2022-05-17T17:59:11Z","title":"Vision Transformer Adapter for Dense Predictions","version":4},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2205.08534","snapshot_observed_at":"2026-08-10T22:05:26.731722Z","title":"Vision transformer adapter for dense predictions","venue":null,"work_id":null,"year":2022},"citing_paper":{"arxiv_id":"2501.02892","last_updated":"2025-01-06T10:14:52Z","snapshot_observed_at":"2026-08-10T21:58:36.963226Z","submitted_at":"2025-01-06T10:14:52Z","title":"FoundPAD: Foundation Models Reloaded for Face Presentation Attack Detection","version":1},"reference_index":9,"source":"pdf_text","source_observed_at":"2026-08-10T22:05:26.731722Z"},"links":{"cited_paper":"/paper/2205.08534","citing_paper":"/paper/2501.02892"},"observation_digest":"sha256:5b07263953ee6186bea9d435bbfae537b3b83b6ab46f0e194da5d6a16e2882b4","observation_id":"228333d4-5b59-43e3-82a3-c26d06d16705","resolution":{"observed_at":"2026-08-10T22:05:26.731722Z","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":"2026-08-10T22:05:28.319917Z","title":"General- izable representation learning for mixture domain face ant i- spoofing","venue":null,"work_id":"9caafa83-0454-40d1-989a-72e9c228c2a2","year":2021},"citing_paper":{"arxiv_id":"2501.02892","last_updated":"2025-01-06T10:14:52Z","snapshot_observed_at":"2026-08-10T21:58:36.963226Z","submitted_at":"2025-01-06T10:14:52Z","title":"FoundPAD: Foundation Models Reloaded for Face Presentation Attack Detection","version":1},"reference_index":10,"source":"pdf_text","source_observed_at":"2026-08-10T22:05:26.737296Z"},"links":{"citing_paper":"/paper/2501.02892"},"observation_digest":"sha256:b0894f02ce1b0b6e83951540276f57a7aa1e8725b2c16cdd91f31ba06c009839","observation_id":"84a3f34f-7723-4e53-9786-348ccd375ead","resolution":{"observed_at":"2026-08-10T22:05:28.326585Z","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":"2410.23831","last_updated":"2025-02-07T09:44:41Z","snapshot_observed_at":"2026-08-09T15:33:50.084430Z","submitted_at":"2024-10-31T11:21:21Z","title":"FRoundation: Are Foundation Models Ready for Face Recognition?","version":3},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2410.23831","snapshot_observed_at":"2026-08-10T22:05:26.744869Z","title":"Froun- dation: Are foundation models ready for face recognition? arXiv preprint arXiv:2410.23831, 2024","venue":null,"work_id":null,"year":2024},"citing_paper":{"arxiv_id":"2501.02892","last_updated":"2025-01-06T10:14:52Z","snapshot_observed_at":"2026-08-10T21:58:36.963226Z","submitted_at":"2025-01-06T10:14:52Z","title":"FoundPAD: Foundation Models Reloaded for Face Presentation Attack Detection","version":1},"reference_index":11,"source":"pdf_text","source_observed_at":"2026-08-10T22:05:26.744869Z"},"links":{"cited_paper":"/paper/2410.23831","citing_paper":"/paper/2501.02892"},"observation_digest":"sha256:561f56dd308f8200575bea4ccb4172326562b2119b6e5adde7b4ee8675f6b315","observation_id":"f57e15e8-63c7-4cef-a2dd-5135d991cded","resolution":{"observed_at":"2026-08-10T22:05:26.744869Z","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":"2026-08-10T22:05:28.301217Z","title":"On the effectiveness of local binary patterns in face anti- spoofing","venue":null,"work_id":"b1e89a2b-ed5f-49d2-9aed-61aa9e430d88","year":2012},"citing_paper":{"arxiv_id":"2501.02892","last_updated":"2025-01-06T10:14:52Z","snapshot_observed_at":"2026-08-10T21:58:36.963226Z","submitted_at":"2025-01-06T10:14:52Z","title":"FoundPAD: Foundation Models Reloaded for Face Presentation Attack Detection","version":1},"reference_index":12,"source":"pdf_text","source_observed_at":"2026-08-10T22:05:26.750021Z"},"links":{"citing_paper":"/paper/2501.02892"},"observation_digest":"sha256:0fe7ebb09b1a8ca7f59748a9e5c5009d69c7ad54c46edaea77d0f9b1e02a918c","observation_id":"4ef3968c-1f24-430a-9cf4-732243247b84","resolution":{"observed_at":"2026-08-10T22:05:28.306395Z","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":null,"pith_arxiv_id":null,"snapshot_observed_at":"2026-08-10T22:05:26.760874Z","title":"Arcface: Additive angular margin loss for deep face recognition","venue":null,"work_id":null,"year":2019},"citing_paper":{"arxiv_id":"2501.02892","last_updated":"2025-01-06T10:14:52Z","snapshot_observed_at":"2026-08-10T21:58:36.963226Z","submitted_at":"2025-01-06T10:14:52Z","title":"FoundPAD: Foundation Models Reloaded for Face Presentation Attack Detection","version":1},"reference_index":13,"source":"pdf_text","source_observed_at":"2026-08-10T22:05:26.760874Z"},"links":{"citing_paper":"/paper/2501.02892"},"observation_digest":"sha256:7f5cbd59c06c289b01dbb143b5bcecae5d348c93d56cd23c3dca5de4fa13185a","observation_id":"13ef82e1-74ca-4b0d-a0f9-2fe05e80eaea","resolution":{"observed_at":"2026-08-10T22:05:26.760874Z","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":"2026-08-10T22:05:28.270647Z","title":"An image is worth 16x16 words: Transformers for image recognition at scale, 2021","venue":null,"work_id":"149256e1-eab6-4bde-a5ac-57c4edddd2db","year":2021},"citing_paper":{"arxiv_id":"2501.02892","last_updated":"2025-01-06T10:14:52Z","snapshot_observed_at":"2026-08-10T21:58:36.963226Z","submitted_at":"2025-01-06T10:14:52Z","title":"FoundPAD: Foundation Models Reloaded for Face Presentation Attack Detection","version":1},"reference_index":14,"source":"pdf_text","source_observed_at":"2026-08-10T22:05:26.767733Z"},"links":{"citing_paper":"/paper/2501.02892"},"observation_digest":"sha256:9ab802ed64ae3f08d276822476c04c9cd608263440a4040fb5d0ec2257d2c8f4","observation_id":"452df1b8-7140-4e93-a79e-dec76500fd1d","resolution":{"observed_at":"2026-08-10T22:05:28.276502Z","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":"2026-08-10T22:05:28.244304Z","title":"Face presentation attack de- tection by excavating causal clues and adapting embedding statistics","venue":null,"work_id":"3f96e5d8-454a-4c71-b1a1-87ec0ae93e73","year":2024},"citing_paper":{"arxiv_id":"2501.02892","last_updated":"2025-01-06T10:14:52Z","snapshot_observed_at":"2026-08-10T21:58:36.963226Z","submitted_at":"2025-01-06T10:14:52Z","title":"FoundPAD: Foundation Models Reloaded for Face Presentation Attack Detection","version":1},"reference_index":15,"source":"pdf_text","source_observed_at":"2026-08-10T22:05:26.772329Z"},"links":{"citing_paper":"/paper/2501.02892"},"observation_digest":"sha256:fea5ad7e70dfa3840eb32bbe590c7e06f6e94c3176a713f8002e4a8880e2ba8c","observation_id":"2acd3712-7787-4c73-a05d-959d934d75d8","resolution":{"observed_at":"2026-08-10T22:05:28.251307Z","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":"2026-08-10T22:05:28.225861Z","title":"Learnable multi-level frequency decomposi- tion and hierarchical attention mechanism for generalized face presentation attack detection","venue":null,"work_id":"b19158a6-a8ee-4a48-86e5-5c416501e807","year":2022},"citing_paper":{"arxiv_id":"2501.02892","last_updated":"2025-01-06T10:14:52Z","snapshot_observed_at":"2026-08-10T21:58:36.963226Z","submitted_at":"2025-01-06T10:14:52Z","title":"FoundPAD: Foundation Models Reloaded for Face Presentation Attack Detection","version":1},"reference_index":16,"source":"pdf_text","source_observed_at":"2026-08-10T22:05:26.776529Z"},"links":{"citing_paper":"/paper/2501.02892"},"observation_digest":"sha256:2021908885a2a5b9cda18861c74bdca48f46932fd3abe9bc95a6277df64827f3","observation_id":"7ff1e3f1-6226-4fdd-981f-2fe6a179581f","resolution":{"observed_at":"2026-08-10T22:05:28.231607Z","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":"2026-08-10T22:05:28.209895Z","title":"Real masks and spoof faces: On the masked face presentation attack detection","venue":null,"work_id":"a828cd5e-558b-49e1-9430-12fb7ee89bb1","year":2022},"citing_paper":{"arxiv_id":"2501.02892","last_updated":"2025-01-06T10:14:52Z","snapshot_observed_at":"2026-08-10T21:58:36.963226Z","submitted_at":"2025-01-06T10:14:52Z","title":"FoundPAD: Foundation Models Reloaded for Face Presentation Attack Detection","version":1},"reference_index":17,"source":"pdf_text","source_observed_at":"2026-08-10T22:05:26.781165Z"},"links":{"citing_paper":"/paper/2501.02892"},"observation_digest":"sha256:db3a7898319aa23aa654743399866cdab01c47b9743b11b63aca1f1edf83cc00","observation_id":"98d5e953-7493-4202-aceb-6e91954ee75c","resolution":{"observed_at":"2026-08-10T22:05:28.215848Z","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":"2026-08-10T22:05:28.191248Z","title":"Syn- thaspoof: Developing face presentation attack detection based on privacy-friendly synthetic data","venue":null,"work_id":"1d49dad9-0f45-4ef5-a134-f27f605d2507","year":2023},"citing_paper":{"arxiv_id":"2501.02892","last_updated":"2025-01-06T10:14:52Z","snapshot_observed_at":"2026-08-10T21:58:36.963226Z","submitted_at":"2025-01-06T10:14:52Z","title":"FoundPAD: Foundation Models Reloaded for Face Presentation Attack Detection","version":1},"reference_index":18,"source":"pdf_text","source_observed_at":"2026-08-10T22:05:26.787201Z"},"links":{"citing_paper":"/paper/2501.02892"},"observation_digest":"sha256:50550e1a85327930fcd992d368b56552b34e26719972377fbbf3e97c58a31060","observation_id":"63585ff5-7bed-4093-b13d-c66d6f6114a7","resolution":{"observed_at":"2026-08-10T22:05:28.196024Z","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":"2026-08-10T22:05:28.173825Z","title":"Tapia, L´ azaro J","venue":null,"work_id":"a55f0d5a-6121-476f-af57-1edea2b5f015","year":2023},"citing_paper":{"arxiv_id":"2501.02892","last_updated":"2025-01-06T10:14:52Z","snapshot_observed_at":"2026-08-10T21:58:36.963226Z","submitted_at":"2025-01-06T10:14:52Z","title":"FoundPAD: Foundation Models Reloaded for Face Presentation Attack Detection","version":1},"reference_index":19,"source":"pdf_text","source_observed_at":"2026-08-10T22:05:26.794728Z"},"links":{"citing_paper":"/paper/2501.02892"},"observation_digest":"sha256:a7e947b6f090bed0f5a4ca86b1f6133c1a1bdd792a45e550dbe285bcc06d8617","observation_id":"e6f8cf87-f388-4988-97bd-66a060a4439c","resolution":{"observed_at":"2026-08-10T22:05:28.179056Z","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":"2402.06497","last_updated":"2024-05-31T01:58:44Z","snapshot_observed_at":"2026-08-09T21:00:33.503916Z","submitted_at":"2024-02-09T16:08:16Z","title":"Iris-SAM: Iris Segmentation Using a Foundation Model","version":3},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2402.06497","snapshot_observed_at":"2026-08-10T22:05:26.800176Z","title":"Iris-sam: Iris seg- mentation using a foundational model","venue":null,"work_id":null,"year":2024},"citing_paper":{"arxiv_id":"2501.02892","last_updated":"2025-01-06T10:14:52Z","snapshot_observed_at":"2026-08-10T21:58:36.963226Z","submitted_at":"2025-01-06T10:14:52Z","title":"FoundPAD: Foundation Models Reloaded for Face Presentation Attack Detection","version":1},"reference_index":20,"source":"pdf_text","source_observed_at":"2026-08-10T22:05:26.800176Z"},"links":{"cited_paper":"/paper/2402.06497","citing_paper":"/paper/2501.02892"},"observation_digest":"sha256:777159bc53c7187f2ada1d3a9dc1b0c0788c1245dec1115d94f1c65eca9e957a","observation_id":"84fd9867-df68-4d65-b802-744138ecc66c","resolution":{"observed_at":"2026-08-10T22:05:26.800176Z","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":"2026-08-10T22:05:28.154402Z","title":"Lempitsky","venue":null,"work_id":"45cb4315-2559-42f7-81b5-86fd13df6ffc","year":null},"citing_paper":{"arxiv_id":"2501.02892","last_updated":"2025-01-06T10:14:52Z","snapshot_observed_at":"2026-08-10T21:58:36.963226Z","submitted_at":"2025-01-06T10:14:52Z","title":"FoundPAD: Foundation Models Reloaded for Face Presentation Attack Detection","version":1},"reference_index":21,"source":"pdf_text","source_observed_at":"2026-08-10T22:05:26.806940Z"},"links":{"citing_paper":"/paper/2501.02892"},"observation_digest":"sha256:e034253571d16d2821e4231fc057ee6b3889a2d8b5941ef5a1644b6eb208b85b","observation_id":"0a2a51fb-45b0-4699-9cf7-f4b855b28b17","resolution":{"observed_at":"2026-08-10T22:05:28.161538Z","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":"2106.09685","last_updated":"2021-10-16T18:40:34Z","snapshot_observed_at":"2026-08-07T07:43:16.294957Z","submitted_at":"2021-06-17T17:37:18Z","title":"LoRA: Low-Rank Adaptation of Large Language Models","version":2},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2106.09685","snapshot_observed_at":"2026-08-10T22:05:26.815537Z","title":"Lora: Low-rank adaptation of large language models","venue":null,"work_id":null,"year":2021},"citing_paper":{"arxiv_id":"2501.02892","last_updated":"2025-01-06T10:14:52Z","snapshot_observed_at":"2026-08-10T21:58:36.963226Z","submitted_at":"2025-01-06T10:14:52Z","title":"FoundPAD: Foundation Models Reloaded for Face Presentation Attack Detection","version":1},"reference_index":22,"source":"pdf_text","source_observed_at":"2026-08-10T22:05:26.815537Z"},"links":{"cited_paper":"/paper/2106.09685","citing_paper":"/paper/2501.02892"},"observation_digest":"sha256:eee10b72cc22ae8d5f79f25abe3a4808709afe927cbe030fb88fb716ad7ce36b","observation_id":"7952acb2-79e1-4e47-af11-44a2f43570cb","resolution":{"observed_at":"2026-08-10T22:05:26.815537Z","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":"2026-08-10T22:05:28.140392Z","title":"Adaptive transformers for robust few-shot cross-domain face anti-spoofing","venue":null,"work_id":"ae4bb3d3-1fac-40d4-acd3-2d349bf389a4","year":2022},"citing_paper":{"arxiv_id":"2501.02892","last_updated":"2025-01-06T10:14:52Z","snapshot_observed_at":"2026-08-10T21:58:36.963226Z","submitted_at":"2025-01-06T10:14:52Z","title":"FoundPAD: Foundation Models Reloaded for Face Presentation Attack Detection","version":1},"reference_index":23,"source":"pdf_text","source_observed_at":"2026-08-10T22:05:26.825321Z"},"links":{"citing_paper":"/paper/2501.02892"},"observation_digest":"sha256:66414adcb77978c711f0038326b92b2a74d24a78729389d209a79c08228c2480","observation_id":"07d9daf2-8e24-47cd-90db-e110d1bd2737","resolution":{"observed_at":"2026-08-10T22:05:28.145223Z","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":"2026-08-10T22:05:28.120490Z","title":"Adaptive transformers for robust few-shot cross-domain face anti-spoofing","venue":null,"work_id":"1bb81197-cf24-4d29-a54f-1c7d02ed5276","year":2022},"citing_paper":{"arxiv_id":"2501.02892","last_updated":"2025-01-06T10:14:52Z","snapshot_observed_at":"2026-08-10T21:58:36.963226Z","submitted_at":"2025-01-06T10:14:52Z","title":"FoundPAD: Foundation Models Reloaded for Face Presentation Attack Detection","version":1},"reference_index":24,"source":"pdf_text","source_observed_at":"2026-08-10T22:05:26.830335Z"},"links":{"citing_paper":"/paper/2501.02892"},"observation_digest":"sha256:8cc99e06dd26da42d2d579bd2859dfed529c43c15b77c0f006626cf3c343994c","observation_id":"e72268fe-cf4c-422f-a094-e02b99debea3","resolution":{"observed_at":"2026-08-10T22:05:28.125727Z","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":"2026-08-10T22:05:28.098421Z","title":"ISO /IEC DIS 30107-3:2016: Information Technology – Biometric presen- tation attack detection – P","venue":null,"work_id":"19da7896-2012-4389-88c1-874426deaab4","year":2016},"citing_paper":{"arxiv_id":"2501.02892","last_updated":"2025-01-06T10:14:52Z","snapshot_observed_at":"2026-08-10T21:58:36.963226Z","submitted_at":"2025-01-06T10:14:52Z","title":"FoundPAD: Foundation Models Reloaded for Face Presentation Attack Detection","version":1},"reference_index":25,"source":"pdf_text","source_observed_at":"2026-08-10T22:05:26.835857Z"},"links":{"citing_paper":"/paper/2501.02892"},"observation_digest":"sha256:c472a14bcd4f555aa9672676e0106b9d594a2181d79448267454941a171179dd","observation_id":"f06964e1-fc54-4846-b724-a3328a3abfa3","resolution":{"observed_at":"2026-08-10T22:05:28.107965Z","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":"2026-08-10T22:05:28.081745Z","title":"ISO /IEC 2382-37:2022: Information technology — V ocabulary — Part 37: Biometrics, 2022","venue":null,"work_id":"5537d5fa-b897-4112-8457-f64f07e21ab7","year":2022},"citing_paper":{"arxiv_id":"2501.02892","last_updated":"2025-01-06T10:14:52Z","snapshot_observed_at":"2026-08-10T21:58:36.963226Z","submitted_at":"2025-01-06T10:14:52Z","title":"FoundPAD: Foundation Models Reloaded for Face Presentation Attack Detection","version":1},"reference_index":26,"source":"pdf_text","source_observed_at":"2026-08-10T22:05:26.840374Z"},"links":{"citing_paper":"/paper/2501.02892"},"observation_digest":"sha256:ffab867e4901de97163d10ac9c0468251dc11cccee1857639ed72a2c50449631","observation_id":"b88f4f40-bd42-4b73-aac6-f740b00be390","resolution":{"observed_at":"2026-08-10T22:05:28.087675Z","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":"2026-08-10T22:05:28.062540Z","title":"Single-side domain generalization for face anti-spoofing","venue":null,"work_id":"96948abd-b9a9-47a5-96f9-b4e534f207cb","year":2020},"citing_paper":{"arxiv_id":"2501.02892","last_updated":"2025-01-06T10:14:52Z","snapshot_observed_at":"2026-08-10T21:58:36.963226Z","submitted_at":"2025-01-06T10:14:52Z","title":"FoundPAD: Foundation Models Reloaded for Face Presentation Attack Detection","version":1},"reference_index":27,"source":"pdf_text","source_observed_at":"2026-08-10T22:05:26.846531Z"},"links":{"citing_paper":"/paper/2501.02892"},"observation_digest":"sha256:18cf808bcf742ad21cead8154f638d557b678eaa456226c4b92b96714972cf11","observation_id":"bffbda8d-f959-4121-8088-c46f17fd5967","resolution":{"observed_at":"2026-08-10T22:05:28.070140Z","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":"2312.03732","last_updated":"2023-11-28T03:23:20Z","snapshot_observed_at":"2026-08-08T21:34:35.024914Z","submitted_at":"2023-11-28T03:23:20Z","title":"A Rank Stabilization Scaling Factor for Fine-Tuning with LoRA","version":1},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2312.03732","snapshot_observed_at":"2026-08-10T22:05:26.852077Z","title":"A rank stabilization scaling fa ctor for fine-tuning with lora","venue":null,"work_id":null,"year":null},"citing_paper":{"arxiv_id":"2501.02892","last_updated":"2025-01-06T10:14:52Z","snapshot_observed_at":"2026-08-10T21:58:36.963226Z","submitted_at":"2025-01-06T10:14:52Z","title":"FoundPAD: Foundation Models Reloaded for Face Presentation Attack Detection","version":1},"reference_index":28,"source":"pdf_text","source_observed_at":"2026-08-10T22:05:26.852077Z"},"links":{"cited_paper":"/paper/2312.03732","citing_paper":"/paper/2501.02892"},"observation_digest":"sha256:23db1a74334271915082378033cd7d5132cf22893070850e54685e95035274e4","observation_id":"2c19ebcd-f4c4-4d5b-a960-da4eabc8daae","resolution":{"observed_at":"2026-08-10T22:05:26.852077Z","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":"2026-08-10T22:05:28.044151Z","title":"Training generative adver- sarial networks with limited data, 2020","venue":null,"work_id":"ab1e26f2-1081-4bce-baf8-71dc08dcc65c","year":2020},"citing_paper":{"arxiv_id":"2501.02892","last_updated":"2025-01-06T10:14:52Z","snapshot_observed_at":"2026-08-10T21:58:36.963226Z","submitted_at":"2025-01-06T10:14:52Z","title":"FoundPAD: Foundation Models Reloaded for Face Presentation Attack Detection","version":1},"reference_index":29,"source":"pdf_text","source_observed_at":"2026-08-10T22:05:26.859789Z"},"links":{"citing_paper":"/paper/2501.02892"},"observation_digest":"sha256:81e758b3fd24dea5b8604cf1521db4230bd7fdbf93c1ce9a6f4fbc30e58bc1c6","observation_id":"12d3a795-829f-4edf-b080-53f14fefa397","resolution":{"observed_at":"2026-08-10T22:05:28.049900Z","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":"2026-08-10T22:05:28.027089Z","title":"Segment any- thing","venue":null,"work_id":"336dac4f-ebe8-433f-bb7a-d66761dc8813","year":2023},"citing_paper":{"arxiv_id":"2501.02892","last_updated":"2025-01-06T10:14:52Z","snapshot_observed_at":"2026-08-10T21:58:36.963226Z","submitted_at":"2025-01-06T10:14:52Z","title":"FoundPAD: Foundation Models Reloaded for Face Presentation Attack Detection","version":1},"reference_index":30,"source":"pdf_text","source_observed_at":"2026-08-10T22:05:26.866282Z"},"links":{"citing_paper":"/paper/2501.02892"},"observation_digest":"sha256:bd8bea7c4f315a5336fa80accc7bd609b2dbf07278b4783b4124dfd05b2fec9a","observation_id":"2bd9e62f-29f3-467b-ba25-9616a7527964","resolution":{"observed_at":"2026-08-10T22:05:28.031974Z","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":"2026-08-10T22:05:28.007825Z","title":null,"venue":null,"work_id":"b593b760-695f-4e71-9782-225a553f14d5","year":2018},"citing_paper":{"arxiv_id":"2501.02892","last_updated":"2025-01-06T10:14:52Z","snapshot_observed_at":"2026-08-10T21:58:36.963226Z","submitted_at":"2025-01-06T10:14:52Z","title":"FoundPAD: Foundation Models Reloaded for Face Presentation Attack Detection","version":1},"reference_index":31,"source":"pdf_text","source_observed_at":"2026-08-10T22:05:26.871990Z"},"links":{"citing_paper":"/paper/2501.02892"},"observation_digest":"sha256:a0c70baf4c7579cb4bf6675dde3d7a95b66d25b218db2f51141e13c964b6c658","observation_id":"32fccb0c-5e60-45b4-b4d3-448ca71c7849","resolution":{"observed_at":"2026-08-10T22:05:28.014426Z","resolver_source":"raw_fallback","status":"unresolved"},"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":"2026-08-10T22:05:27.984141Z","title":null,"venue":null,"work_id":"14d40418-2d53-4c5c-9d43-af40fdd4a8a1","year":2018},"citing_paper":{"arxiv_id":"2501.02892","last_updated":"2025-01-06T10:14:52Z","snapshot_observed_at":"2026-08-10T21:58:36.963226Z","submitted_at":"2025-01-06T10:14:52Z","title":"FoundPAD: Foundation Models Reloaded for Face Presentation Attack Detection","version":1},"reference_index":32,"source":"pdf_text","source_observed_at":"2026-08-10T22:05:26.876418Z"},"links":{"citing_paper":"/paper/2501.02892"},"observation_digest":"sha256:c2a8e047ce6c02b07c9fc3ae5f02a3d5ad9cbff3e15b0cd831e7c1df97d9117c","observation_id":"911c068e-c28a-4953-a1b6-d01ce4efa24d","resolution":{"observed_at":"2026-08-10T22:05:27.990636Z","resolver_source":"raw_fallback","status":"unresolved"},"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":"2026-08-10T22:05:27.962489Z","title":"Causal intervention for general- izable face anti-spoofing","venue":null,"work_id":"3e10fd76-0168-45f2-99f5-8becd633f93f","year":2022},"citing_paper":{"arxiv_id":"2501.02892","last_updated":"2025-01-06T10:14:52Z","snapshot_observed_at":"2026-08-10T21:58:36.963226Z","submitted_at":"2025-01-06T10:14:52Z","title":"FoundPAD: Foundation Models Reloaded for Face Presentation Attack Detection","version":1},"reference_index":33,"source":"pdf_text","source_observed_at":"2026-08-10T22:05:26.881051Z"},"links":{"citing_paper":"/paper/2501.02892"},"observation_digest":"sha256:3ce5b0e4956691f115e2d8da0c307793ba253b4f5d3b72ea6082983b07061db5","observation_id":"779290d2-d178-4170-8a82-0f7f7d5e3fe3","resolution":{"observed_at":"2026-08-10T22:05:27.968005Z","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":"2026-08-10T22:05:27.943509Z","title":"Learning deep models for face anti-spoofing: Binary or auxiliary su- pervision","venue":null,"work_id":"ce66beb5-5044-4791-af60-87151f9213a2","year":2018},"citing_paper":{"arxiv_id":"2501.02892","last_updated":"2025-01-06T10:14:52Z","snapshot_observed_at":"2026-08-10T21:58:36.963226Z","submitted_at":"2025-01-06T10:14:52Z","title":"FoundPAD: Foundation Models Reloaded for Face Presentation Attack Detection","version":1},"reference_index":34,"source":"pdf_text","source_observed_at":"2026-08-10T22:05:26.886446Z"},"links":{"citing_paper":"/paper/2501.02892"},"observation_digest":"sha256:a79985fda16447887ba1fced3c9aadacc0000128b002a8fc23c8a187a4fdd32e","observation_id":"a6c1cdb3-981a-4a5e-a675-0a45b0649034","resolution":{"observed_at":"2026-08-10T22:05:27.952639Z","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":null,"pith_arxiv_id":null,"snapshot_observed_at":"2026-08-10T22:05:26.893066Z","title":"Decoupled weight de- cay regularization","venue":null,"work_id":null,"year":2019},"citing_paper":{"arxiv_id":"2501.02892","last_updated":"2025-01-06T10:14:52Z","snapshot_observed_at":"2026-08-10T21:58:36.963226Z","submitted_at":"2025-01-06T10:14:52Z","title":"FoundPAD: Foundation Models Reloaded for Face Presentation Attack Detection","version":1},"reference_index":35,"source":"pdf_text","source_observed_at":"2026-08-10T22:05:26.893066Z"},"links":{"citing_paper":"/paper/2501.02892"},"observation_digest":"sha256:bfd4eb28153713e0c8495a0ec77dddf81ca789a54e8c667b6cc7bf24adff6c27","observation_id":"c3fd2d69-e3b7-4d5d-a892-58dffae56a08","resolution":{"observed_at":"2026-08-10T22:05:26.893066Z","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":"2026-08-10T22:05:27.910392Z","title":"Face spoofing detection from single images using micro-texture analysis","venue":null,"work_id":"c649d072-677d-453f-911f-7d02a526b7b6","year":2011},"citing_paper":{"arxiv_id":"2501.02892","last_updated":"2025-01-06T10:14:52Z","snapshot_observed_at":"2026-08-10T21:58:36.963226Z","submitted_at":"2025-01-06T10:14:52Z","title":"FoundPAD: Foundation Models Reloaded for Face Presentation Attack Detection","version":1},"reference_index":36,"source":"pdf_text","source_observed_at":"2026-08-10T22:05:26.902549Z"},"links":{"citing_paper":"/paper/2501.02892"},"observation_digest":"sha256:2d4b2a8b8d1116c4b10ecb39d5a1f2231700c51eb70dcb03043c4923b7a2ec3f","observation_id":"17833922-7277-4a0f-b2e7-b313facffb88","resolution":{"observed_at":"2026-08-10T22:05:27.915563Z","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":"2026-08-10T22:05:27.891867Z","title":"A sur - vey on synthetic biometrics: Fingerprint, face, iris and va s- cular patterns","venue":null,"work_id":"34ca3571-2c0b-42bd-868a-e051700fe5f8","year":2023},"citing_paper":{"arxiv_id":"2501.02892","last_updated":"2025-01-06T10:14:52Z","snapshot_observed_at":"2026-08-10T21:58:36.963226Z","submitted_at":"2025-01-06T10:14:52Z","title":"FoundPAD: Foundation Models Reloaded for Face Presentation Attack Detection","version":1},"reference_index":37,"source":"pdf_text","source_observed_at":"2026-08-10T22:05:26.915251Z"},"links":{"citing_paper":"/paper/2501.02892"},"observation_digest":"sha256:d1815543b77edc6d2fc8d138164e17bba3b851f19fb8a06ea5ffc1355aaabe8b","observation_id":"2b8b29e0-796a-4fbf-b127-054ecb666242","resolution":{"observed_at":"2026-08-10T22:05:27.896398Z","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":"2026-08-10T22:05:27.874385Z","title":"Vitranspad: Video transformer using convolution and self- attention for face presentation attack detection","venue":null,"work_id":"336e7377-bb30-449a-b23a-73aa83aa41d8","year":2022},"citing_paper":{"arxiv_id":"2501.02892","last_updated":"2025-01-06T10:14:52Z","snapshot_observed_at":"2026-08-10T21:58:36.963226Z","submitted_at":"2025-01-06T10:14:52Z","title":"FoundPAD: Foundation Models Reloaded for Face Presentation Attack Detection","version":1},"reference_index":38,"source":"pdf_text","source_observed_at":"2026-08-10T22:05:26.922005Z"},"links":{"citing_paper":"/paper/2501.02892"},"observation_digest":"sha256:7e70e62b68cb1cd59a62a5a42f5b8df6c5e9d9746be4b0b143ba99a796e12fb2","observation_id":"357a6dba-13bf-40b2-93de-29f3ebb95a2f","resolution":{"observed_at":"2026-08-10T22:05:27.878713Z","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":"2304.07193","last_updated":"2024-02-02T10:24:09Z","snapshot_observed_at":"2026-08-09T18:02:17.307812Z","submitted_at":"2023-04-14T15:12:19Z","title":"DINOv2: Learning Robust Visual Features without Supervision","version":2},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2304.07193","snapshot_observed_at":"2026-08-10T22:05:26.931787Z","title":"Dinov2: Learning robust visual features without supervision","venue":null,"work_id":null,"year":2023},"citing_paper":{"arxiv_id":"2501.02892","last_updated":"2025-01-06T10:14:52Z","snapshot_observed_at":"2026-08-10T21:58:36.963226Z","submitted_at":"2025-01-06T10:14:52Z","title":"FoundPAD: Foundation Models Reloaded for Face Presentation Attack Detection","version":1},"reference_index":39,"source":"pdf_text","source_observed_at":"2026-08-10T22:05:26.931787Z"},"links":{"cited_paper":"/paper/2304.07193","citing_paper":"/paper/2501.02892"},"observation_digest":"sha256:1936d7e749f76332f9e012c5d92d7d96c082e1459e0bcb9c834d49e406a501dd","observation_id":"1476a565-2033-424c-ae46-8ad164152836","resolution":{"observed_at":"2026-08-10T22:05:26.931787Z","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":"2026-08-10T22:05:27.850132Z","title":"Unsupervised compound domain adaptation for face anti-spoofing","venue":null,"work_id":"9466ddcd-2f4b-43a5-9f7f-d21f713c3179","year":2021},"citing_paper":{"arxiv_id":"2501.02892","last_updated":"2025-01-06T10:14:52Z","snapshot_observed_at":"2026-08-10T21:58:36.963226Z","submitted_at":"2025-01-06T10:14:52Z","title":"FoundPAD: Foundation Models Reloaded for Face Presentation Attack Detection","version":1},"reference_index":40,"source":"pdf_text","source_observed_at":"2026-08-10T22:05:26.937190Z"},"links":{"citing_paper":"/paper/2501.02892"},"observation_digest":"sha256:8e9ecb13ebdd6367cb12d3458794acc7dbc4fe8e69cd1e19291dc3c3f4633a6a","observation_id":"bf85f53c-f970-4b25-97be-b6393fecd388","resolution":{"observed_at":"2026-08-10T22:05:27.856130Z","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":"2026-08-10T22:05:27.830086Z","title":"Arc2face: A foundation model for id-consistent human faces","venue":null,"work_id":"6e2f5080-2c12-43d1-84b4-439d211a94a9","year":2024},"citing_paper":{"arxiv_id":"2501.02892","last_updated":"2025-01-06T10:14:52Z","snapshot_observed_at":"2026-08-10T21:58:36.963226Z","submitted_at":"2025-01-06T10:14:52Z","title":"FoundPAD: Foundation Models Reloaded for Face Presentation Attack Detection","version":1},"reference_index":41,"source":"pdf_text","source_observed_at":"2026-08-10T22:05:26.946036Z"},"links":{"citing_paper":"/paper/2501.02892"},"observation_digest":"sha256:bc30a82bee010fe4d91856d82aa5f5dcb904f935bf2933c3c04368558e466cc7","observation_id":"ac5fe79a-f113-4a2c-95ad-0be1c20dc1f5","resolution":{"observed_at":"2026-08-10T22:05:27.836163Z","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":"2026-08-10T22:05:27.810486Z","title":"Learning transferable visual models from natural language supervi- sion","venue":null,"work_id":"2f53c550-d168-497a-ac89-0ef46faf1b87","year":2021},"citing_paper":{"arxiv_id":"2501.02892","last_updated":"2025-01-06T10:14:52Z","snapshot_observed_at":"2026-08-10T21:58:36.963226Z","submitted_at":"2025-01-06T10:14:52Z","title":"FoundPAD: Foundation Models Reloaded for Face Presentation Attack Detection","version":1},"reference_index":42,"source":"pdf_text","source_observed_at":"2026-08-10T22:05:26.950592Z"},"links":{"citing_paper":"/paper/2501.02892"},"observation_digest":"sha256:bc3658ccdb9acf5f9fa45dbcd2c5e07a36e9b01240adf9a95dd053417fdbe439","observation_id":"dd8ffa34-17ee-4344-aae4-d74fff6ab6fc","resolution":{"observed_at":"2026-08-10T22:05:27.815618Z","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":"2408.00714","last_updated":"2024-10-28T16:37:57Z","snapshot_observed_at":"2026-07-06T18:55:41.459417Z","submitted_at":"2024-08-01T17:00:08Z","title":"SAM 2: Segment Anything in Images and Videos","version":2},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2408.00714","snapshot_observed_at":"2026-08-10T22:05:26.956137Z","title":"Sam 2: Segment anything in images and videos","venue":null,"work_id":null,"year":2024},"citing_paper":{"arxiv_id":"2501.02892","last_updated":"2025-01-06T10:14:52Z","snapshot_observed_at":"2026-08-10T21:58:36.963226Z","submitted_at":"2025-01-06T10:14:52Z","title":"FoundPAD: Foundation Models Reloaded for Face Presentation Attack Detection","version":1},"reference_index":43,"source":"pdf_text","source_observed_at":"2026-08-10T22:05:26.956137Z"},"links":{"cited_paper":"/paper/2408.00714","citing_paper":"/paper/2501.02892"},"observation_digest":"sha256:ac18b95fc3535c84fe70424c7c87c6d369bf02f03a40935e1d846d2b372255f7","observation_id":"19711caf-0ce2-4e38-8360-c39dfa23e99a","resolution":{"observed_at":"2026-08-10T22:05:26.956137Z","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":"2026-08-10T22:05:27.791419Z","title":"Domain agnostic feature learning for image and video based face anti-spoofing","venue":null,"work_id":"d2966ce9-c3a8-452d-a966-165437642ec7","year":null},"citing_paper":{"arxiv_id":"2501.02892","last_updated":"2025-01-06T10:14:52Z","snapshot_observed_at":"2026-08-10T21:58:36.963226Z","submitted_at":"2025-01-06T10:14:52Z","title":"FoundPAD: Foundation Models Reloaded for Face Presentation Attack Detection","version":1},"reference_index":44,"source":"pdf_text","source_observed_at":"2026-08-10T22:05:26.962677Z"},"links":{"citing_paper":"/paper/2501.02892"},"observation_digest":"sha256:666f298941237778a877a9799c032b17353194d7969c84d9c6f9f4058a636168","observation_id":"6a9f9036-624b-433b-806e-3e5e1ee90e95","resolution":{"observed_at":"2026-08-10T22:05:27.797495Z","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":"2026-08-10T22:05:27.771386Z","title":null,"venue":null,"work_id":"a2d1f523-65c4-4305-847e-f53b1d80512e","year":2019},"citing_paper":{"arxiv_id":"2501.02892","last_updated":"2025-01-06T10:14:52Z","snapshot_observed_at":"2026-08-10T21:58:36.963226Z","submitted_at":"2025-01-06T10:14:52Z","title":"FoundPAD: Foundation Models Reloaded for Face Presentation Attack Detection","version":1},"reference_index":45,"source":"pdf_text","source_observed_at":"2026-08-10T22:05:26.967500Z"},"links":{"citing_paper":"/paper/2501.02892"},"observation_digest":"sha256:c8f3f10bc8063d1492f036385f46a9dfaf90ae9a55a99f7d6a21348c76a89822","observation_id":"3bec64b1-87f5-4bc3-9f82-9a25140fb15a","resolution":{"observed_at":"2026-08-10T22:05:27.779614Z","resolver_source":"raw_fallback","status":"unresolved"},"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":"2026-08-10T22:05:27.745595Z","title":null,"venue":null,"work_id":"4d6e5ed4-9371-435f-a351-b9fa853d9ec3","year":2020},"citing_paper":{"arxiv_id":"2501.02892","last_updated":"2025-01-06T10:14:52Z","snapshot_observed_at":"2026-08-10T21:58:36.963226Z","submitted_at":"2025-01-06T10:14:52Z","title":"FoundPAD: Foundation Models Reloaded for Face Presentation Attack Detection","version":1},"reference_index":46,"source":"pdf_text","source_observed_at":"2026-08-10T22:05:26.973508Z"},"links":{"citing_paper":"/paper/2501.02892"},"observation_digest":"sha256:66e5391adcdde782e4dec48096c21466ea2c211c12a2e13c1af2350c2d214764","observation_id":"318a5b2a-a717-4eaa-a6a9-61c9c3a08a9c","resolution":{"observed_at":"2026-08-10T22:05:27.753667Z","resolver_source":"raw_fallback","status":"unresolved"},"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":"2026-08-10T22:05:27.728133Z","title":"Fixing the train-test resolution discrepancy.Advances in neural information processing systems , 32, 2019","venue":null,"work_id":"9f6f22d3-12a5-4d20-88ce-34c95a2a3d34","year":2019},"citing_paper":{"arxiv_id":"2501.02892","last_updated":"2025-01-06T10:14:52Z","snapshot_observed_at":"2026-08-10T21:58:36.963226Z","submitted_at":"2025-01-06T10:14:52Z","title":"FoundPAD: Foundation Models Reloaded for Face Presentation Attack Detection","version":1},"reference_index":47,"source":"pdf_text","source_observed_at":"2026-08-10T22:05:26.980519Z"},"links":{"citing_paper":"/paper/2501.02892"},"observation_digest":"sha256:5e1043e0131f6778b13dbb799e57056fc90fa1530c39bbc5e7592784e49662ab","observation_id":"2b33d6bb-059a-4346-a104-f6b9d2cd2c68","resolution":{"observed_at":"2026-08-10T22:05:27.733535Z","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":"2026-08-10T22:05:27.707059Z","title":"Adversarial discriminative domain adaptation","venue":null,"work_id":"5aebd61b-c0bf-4039-b7b3-e6355c2228e0","year":2017},"citing_paper":{"arxiv_id":"2501.02892","last_updated":"2025-01-06T10:14:52Z","snapshot_observed_at":"2026-08-10T21:58:36.963226Z","submitted_at":"2025-01-06T10:14:52Z","title":"FoundPAD: Foundation Models Reloaded for Face Presentation Attack Detection","version":1},"reference_index":48,"source":"pdf_text","source_observed_at":"2026-08-10T22:05:26.987965Z"},"links":{"citing_paper":"/paper/2501.02892"},"observation_digest":"sha256:b129b8e45aae141df4e571a58911f76d7e4d012c9100b2106bd14c1338a29bf1","observation_id":"88f0b729-a1c5-42f0-bfe7-833b2c2716a8","resolution":{"observed_at":"2026-08-10T22:05:27.712781Z","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":"2308.07156","last_updated":"2023-08-14T14:09:41Z","snapshot_observed_at":"2026-07-06T16:05:58.986548Z","submitted_at":"2023-08-14T14:09:41Z","title":"SAM Meets Robotic Surgery: An Empirical Study on Generalization, Robustness and Adaptation","version":1},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2308.07156","snapshot_observed_at":"2026-08-10T22:05:26.992637Z","title":"SAM meets robotic surgery: An empirical study on generalization, robustness and adaptation","venue":null,"work_id":null,"year":2023},"citing_paper":{"arxiv_id":"2501.02892","last_updated":"2025-01-06T10:14:52Z","snapshot_observed_at":"2026-08-10T21:58:36.963226Z","submitted_at":"2025-01-06T10:14:52Z","title":"FoundPAD: Foundation Models Reloaded for Face Presentation Attack Detection","version":1},"reference_index":49,"source":"pdf_text","source_observed_at":"2026-08-10T22:05:26.992637Z"},"links":{"cited_paper":"/paper/2308.07156","citing_paper":"/paper/2501.02892"},"observation_digest":"sha256:0f2fa7caebd23ce648cc87354eb80da0b85c6dab0a1236aa2d27435b92306cb6","observation_id":"ce33ddd3-c78a-406b-83b9-da5de7b5e8d0","resolution":{"observed_at":"2026-08-10T22:05:26.992637Z","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":"2026-08-10T22:05:27.681273Z","title":"Patchnet: A simple face anti-spoofing framework via fine-grained patch recognition","venue":null,"work_id":"28eafffd-e55d-4ebb-ac00-a1b656ac611f","year":2022},"citing_paper":{"arxiv_id":"2501.02892","last_updated":"2025-01-06T10:14:52Z","snapshot_observed_at":"2026-08-10T21:58:36.963226Z","submitted_at":"2025-01-06T10:14:52Z","title":"FoundPAD: Foundation Models Reloaded for Face Presentation Attack Detection","version":1},"reference_index":50,"source":"pdf_text","source_observed_at":"2026-08-10T22:05:26.998154Z"},"links":{"citing_paper":"/paper/2501.02892"},"observation_digest":"sha256:201ae9a382e2182190a5ddf66662cfc31d061d99f71c0dcea159e898649d35df","observation_id":"bb78a3c5-f9a5-4d37-9829-fe177777ce8c","resolution":{"observed_at":"2026-08-10T22:05:27.694812Z","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":"2026-08-10T22:05:27.657593Z","title":"Improving cross-database face presentation attack detect ion via adversarial domain adaptation","venue":null,"work_id":"28c356ec-705c-4a24-a0bb-1972c6c864d7","year":null},"citing_paper":{"arxiv_id":"2501.02892","last_updated":"2025-01-06T10:14:52Z","snapshot_observed_at":"2026-08-10T21:58:36.963226Z","submitted_at":"2025-01-06T10:14:52Z","title":"FoundPAD: Foundation Models Reloaded for Face Presentation Attack Detection","version":1},"reference_index":51,"source":"pdf_text","source_observed_at":"2026-08-10T22:05:27.004981Z"},"links":{"citing_paper":"/paper/2501.02892"},"observation_digest":"sha256:ac5ff3e20d0d8fba1a24cf763891953c22e8f56747d6b85f503b7cb19202e912","observation_id":"c3ea788a-e0e4-4743-9fa0-da874c9a4781","resolution":{"observed_at":"2026-08-10T22:05:27.665935Z","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":"2026-08-10T22:05:27.636485Z","title":"Cross-domain face presentation attack detection via multi - domain disentangled representation learning","venue":null,"work_id":"2004c3e5-b607-40b1-b29a-5961309a2822","year":2020},"citing_paper":{"arxiv_id":"2501.02892","last_updated":"2025-01-06T10:14:52Z","snapshot_observed_at":"2026-08-10T21:58:36.963226Z","submitted_at":"2025-01-06T10:14:52Z","title":"FoundPAD: Foundation Models Reloaded for Face Presentation Attack Detection","version":1},"reference_index":52,"source":"pdf_text","source_observed_at":"2026-08-10T22:05:27.009972Z"},"links":{"citing_paper":"/paper/2501.02892"},"observation_digest":"sha256:6c79af5cae2f3d4cf80edbffca71cc152efd0e0707f5f6db9b5cd7700313687f","observation_id":"84805487-66b3-407c-9bdf-6c489c058c96","resolution":{"observed_at":"2026-08-10T22:05:27.642543Z","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":"2026-08-10T22:05:27.618258Z","title":"Unsupervised adversarial domain adaptation for cross- domain face presentation attack detection","venue":null,"work_id":"a82500cf-41a2-4306-ba67-25544deee3a5","year":2021},"citing_paper":{"arxiv_id":"2501.02892","last_updated":"2025-01-06T10:14:52Z","snapshot_observed_at":"2026-08-10T21:58:36.963226Z","submitted_at":"2025-01-06T10:14:52Z","title":"FoundPAD: Foundation Models Reloaded for Face Presentation Attack Detection","version":1},"reference_index":53,"source":"pdf_text","source_observed_at":"2026-08-10T22:05:27.015054Z"},"links":{"citing_paper":"/paper/2501.02892"},"observation_digest":"sha256:2fba611898b2a975f1c82ab675dc281f37549f88271f4ec9e1fe780397b58820","observation_id":"8274e5e2-e321-4440-a988-683c56f6dba0","resolution":{"observed_at":"2026-08-10T22:05:27.625039Z","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":"2026-08-10T22:05:27.597488Z","title":"Face anti-spoofing using transformers with relation-aware mechanism","venue":null,"work_id":"390fdd67-d28e-4974-a7d9-d721eef75356","year":2022},"citing_paper":{"arxiv_id":"2501.02892","last_updated":"2025-01-06T10:14:52Z","snapshot_observed_at":"2026-08-10T21:58:36.963226Z","submitted_at":"2025-01-06T10:14:52Z","title":"FoundPAD: Foundation Models Reloaded for Face Presentation Attack Detection","version":1},"reference_index":54,"source":"pdf_text","source_observed_at":"2026-08-10T22:05:27.019320Z"},"links":{"citing_paper":"/paper/2501.02892"},"observation_digest":"sha256:70c2cf8b400802e915b61af1f35fbf73ae96e354feb9c00fa3fa24f993f22c1b","observation_id":"17b37df6-cf6e-4224-9f68-1a0ae3f3f5e2","resolution":{"observed_at":"2026-08-10T22:05:27.605547Z","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":"2026-08-10T22:05:27.577952Z","title":null,"venue":null,"work_id":"98305e5e-1e7e-452c-b3b2-88b0be23a698","year":2015},"citing_paper":{"arxiv_id":"2501.02892","last_updated":"2025-01-06T10:14:52Z","snapshot_observed_at":"2026-08-10T21:58:36.963226Z","submitted_at":"2025-01-06T10:14:52Z","title":"FoundPAD: Foundation Models Reloaded for Face Presentation Attack Detection","version":1},"reference_index":55,"source":"pdf_text","source_observed_at":"2026-08-10T22:05:27.026562Z"},"links":{"citing_paper":"/paper/2501.02892"},"observation_digest":"sha256:4c0b175f0baa39444ef5387cb033af3630c0b04367861a1599bf6789bc433b19","observation_id":"5d531d22-3c6d-41e2-96f7-60fdc84f9149","resolution":{"observed_at":"2026-08-10T22:05:27.583097Z","resolver_source":"raw_fallback","status":"unresolved"},"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":"2026-08-10T22:05:27.558917Z","title":"Exploiting low- rank structure from latent domains for domain generaliza- tion","venue":null,"work_id":"8d7c96e7-ee3e-48df-81c4-6ea59245f4be","year":2014},"citing_paper":{"arxiv_id":"2501.02892","last_updated":"2025-01-06T10:14:52Z","snapshot_observed_at":"2026-08-10T21:58:36.963226Z","submitted_at":"2025-01-06T10:14:52Z","title":"FoundPAD: Foundation Models Reloaded for Face Presentation Attack Detection","version":1},"reference_index":56,"source":"pdf_text","source_observed_at":"2026-08-10T22:05:27.034926Z"},"links":{"citing_paper":"/paper/2501.02892"},"observation_digest":"sha256:20ae0c3fcbbcbbb840f6dae19b8dd7066aaaed5e06c5b5271db761f534d42e9f","observation_id":"d088e3bc-6319-4812-8a29-8b2e58db9c7f","resolution":{"observed_at":"2026-08-10T22:05:27.564456Z","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":"2026-08-10T22:05:27.532811Z","title":"Domain adver- sarial disentanglement network with cross-domain synthes is for generalized face anti-spoofing","venue":null,"work_id":"ade40816-3d41-4aa3-a759-d987ce672094","year":2022},"citing_paper":{"arxiv_id":"2501.02892","last_updated":"2025-01-06T10:14:52Z","snapshot_observed_at":"2026-08-10T21:58:36.963226Z","submitted_at":"2025-01-06T10:14:52Z","title":"FoundPAD: Foundation Models Reloaded for Face Presentation Attack Detection","version":1},"reference_index":57,"source":"pdf_text","source_observed_at":"2026-08-10T22:05:27.040567Z"},"links":{"citing_paper":"/paper/2501.02892"},"observation_digest":"sha256:f1d451cf2eb90e0f314dc7c4bf9a9178798c25fb7d08722d64e91383b8b12f4b","observation_id":"8ebb052a-9fd9-461a-bbfa-1200c3cd43e1","resolution":{"observed_at":"2026-08-10T22:05:27.544838Z","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":"1408.5601","last_updated":"2014-08-26T02:45:55Z","snapshot_observed_at":"2026-07-06T03:52:29.303959Z","submitted_at":"2014-08-24T13:08:19Z","title":"Learn Convolutional Neural Network for Face Anti-Spoofing","version":2},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"1408.5601","snapshot_observed_at":"2026-08-10T22:05:27.045256Z","title":null,"venue":null,"work_id":null,"year":null},"citing_paper":{"arxiv_id":"2501.02892","last_updated":"2025-01-06T10:14:52Z","snapshot_observed_at":"2026-08-10T21:58:36.963226Z","submitted_at":"2025-01-06T10:14:52Z","title":"FoundPAD: Foundation Models Reloaded for Face Presentation Attack Detection","version":1},"reference_index":58,"source":"pdf_text","source_observed_at":"2026-08-10T22:05:27.045256Z"},"links":{"cited_paper":"/paper/1408.5601","citing_paper":"/paper/2501.02892"},"observation_digest":"sha256:60e99abd76f3432bd1987147b35d6e2d3812f179fe6af43a50f4f98e7c7bcaae","observation_id":"be675a91-db8a-4a29-8a1e-688e38eaabf3","resolution":{"observed_at":"2026-08-10T22:05:27.045256Z","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":"2026-08-10T22:05:27.516914Z","title":"Revisiting pixel-wise supervision for face anti-spoofing","venue":null,"work_id":"1b1b3b7e-272e-4095-8311-681effea6512","year":2021},"citing_paper":{"arxiv_id":"2501.02892","last_updated":"2025-01-06T10:14:52Z","snapshot_observed_at":"2026-08-10T21:58:36.963226Z","submitted_at":"2025-01-06T10:14:52Z","title":"FoundPAD: Foundation Models Reloaded for Face Presentation Attack Detection","version":1},"reference_index":59,"source":"pdf_text","source_observed_at":"2026-08-10T22:05:27.050994Z"},"links":{"citing_paper":"/paper/2501.02892"},"observation_digest":"sha256:1ab98a791d2da41696ecc019600bd6e8e764ef699ed1cf24f1a6c1a422f5f710","observation_id":"68ab628e-5982-4b3d-9f9d-61393c9db554","resolution":{"observed_at":"2026-08-10T22:05:27.522315Z","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":"2026-08-10T22:05:27.497414Z","title":"Li, and Guoying Zhao","venue":null,"work_id":"e529e84c-d0c2-44bc-b068-9ef4b5a60c0f","year":2021},"citing_paper":{"arxiv_id":"2501.02892","last_updated":"2025-01-06T10:14:52Z","snapshot_observed_at":"2026-08-10T21:58:36.963226Z","submitted_at":"2025-01-06T10:14:52Z","title":"FoundPAD: Foundation Models Reloaded for Face Presentation Attack Detection","version":1},"reference_index":60,"source":"pdf_text","source_observed_at":"2026-08-10T22:05:27.056275Z"},"links":{"citing_paper":"/paper/2501.02892"},"observation_digest":"sha256:667c3ffb4183df82f67c2cbf18a7c7436d751d09da8dfdba7b9c00ad9fc917ba","observation_id":"57039fc9-5f7e-4956-b925-cda623620a6b","resolution":{"observed_at":"2026-08-10T22:05:27.502610Z","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":"2406.10508","last_updated":"2024-06-30T14:28:34Z","snapshot_observed_at":"2026-07-06T18:31:21.929350Z","submitted_at":"2024-06-15T05:21:33Z","title":"Learning to Adapt Foundation Model DINOv2 for Capsule Endoscopy Diagnosis","version":2},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2406.10508","snapshot_observed_at":"2026-08-10T22:05:27.061434Z","title":"Learning to adapt foundation model dinov2 for capsule en- doscopy diagnosis","venue":null,"work_id":null,"year":2024},"citing_paper":{"arxiv_id":"2501.02892","last_updated":"2025-01-06T10:14:52Z","snapshot_observed_at":"2026-08-10T21:58:36.963226Z","submitted_at":"2025-01-06T10:14:52Z","title":"FoundPAD: Foundation Models Reloaded for Face Presentation Attack Detection","version":1},"reference_index":61,"source":"pdf_text","source_observed_at":"2026-08-10T22:05:27.061434Z"},"links":{"cited_paper":"/paper/2406.10508","citing_paper":"/paper/2501.02892"},"observation_digest":"sha256:cfab00ec8aa525ee062b6b89ed7b2a65dfa148bc186ff0c4bffc529cde593244","observation_id":"3ecda140-5b5b-40b8-8e4b-5e08466f1edc","resolution":{"observed_at":"2026-08-10T22:05:27.061434Z","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":"2026-08-10T22:05:27.477448Z","title":"Generalized single-image-based morph- ing attack detection using deep representations from visio n transformer","venue":null,"work_id":"705b8ccc-4828-4f60-81c5-32490cbabffd","year":2024},"citing_paper":{"arxiv_id":"2501.02892","last_updated":"2025-01-06T10:14:52Z","snapshot_observed_at":"2026-08-10T21:58:36.963226Z","submitted_at":"2025-01-06T10:14:52Z","title":"FoundPAD: Foundation Models Reloaded for Face Presentation Attack Detection","version":1},"reference_index":62,"source":"pdf_text","source_observed_at":"2026-08-10T22:05:27.066914Z"},"links":{"citing_paper":"/paper/2501.02892"},"observation_digest":"sha256:ba96ee2e24a962d76b3cfc8da5aa496a6781c32a1810abe5dbb6a56f7e9b78cd","observation_id":"aedc3e68-0a66-4abb-98b8-c3c2f2859019","resolution":{"observed_at":"2026-08-10T22:05:27.482514Z","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":"2026-08-10T22:05:27.460235Z","title":"Joint face detection and alignment using multitask cascade d convolutional networks","venue":null,"work_id":"a8aeb1ab-312f-47b9-89c0-36456d2c5123","year":2016},"citing_paper":{"arxiv_id":"2501.02892","last_updated":"2025-01-06T10:14:52Z","snapshot_observed_at":"2026-08-10T21:58:36.963226Z","submitted_at":"2025-01-06T10:14:52Z","title":"FoundPAD: Foundation Models Reloaded for Face Presentation Attack Detection","version":1},"reference_index":63,"source":"pdf_text","source_observed_at":"2026-08-10T22:05:27.077388Z"},"links":{"citing_paper":"/paper/2501.02892"},"observation_digest":"sha256:8173a5d53cddb4a36ed1ec8f4fb8eff5c571dde5f1de8adbc80eb6360f5067d8","observation_id":"adaa351d-c5ff-4a8d-b5e2-7cb4b9d409b3","resolution":{"observed_at":"2026-08-10T22:05:27.466118Z","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":"2026-08-10T22:05:27.441999Z","title":"Celeba-spoof: Large-scale face anti-spoofing dataset with rich annotations","venue":null,"work_id":"2c00763e-36d0-41d6-8047-c2d35003b46b","year":2020},"citing_paper":{"arxiv_id":"2501.02892","last_updated":"2025-01-06T10:14:52Z","snapshot_observed_at":"2026-08-10T21:58:36.963226Z","submitted_at":"2025-01-06T10:14:52Z","title":"FoundPAD: Foundation Models Reloaded for Face Presentation Attack Detection","version":1},"reference_index":64,"source":"pdf_text","source_observed_at":"2026-08-10T22:05:27.091932Z"},"links":{"citing_paper":"/paper/2501.02892"},"observation_digest":"sha256:009d2a5064d099cdf21eab02b3d921ee402505efe5523e3589104ebea082ed8a","observation_id":"d887c307-5a7b-4d2b-b867-135337124871","resolution":{"observed_at":"2026-08-10T22:05:27.448299Z","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":"2026-08-10T22:05:27.421764Z","title":null,"venue":null,"work_id":"b9fecaf3-eb45-452e-b489-4b8f2a72dd0e","year":2012},"citing_paper":{"arxiv_id":"2501.02892","last_updated":"2025-01-06T10:14:52Z","snapshot_observed_at":"2026-08-10T21:58:36.963226Z","submitted_at":"2025-01-06T10:14:52Z","title":"FoundPAD: Foundation Models Reloaded for Face Presentation Attack Detection","version":1},"reference_index":65,"source":"pdf_text","source_observed_at":"2026-08-10T22:05:27.097655Z"},"links":{"citing_paper":"/paper/2501.02892"},"observation_digest":"sha256:f19919eecda9c604c51bbae912ad7556a340d10e438bb6b1c5816e4edb14227d","observation_id":"040bc408-91aa-4260-9187-6e685e8ecbd7","resolution":{"observed_at":"2026-08-10T22:05:27.429045Z","resolver_source":"raw_fallback","status":"unresolved"},"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"}}],"paper":{"arxiv_id":"2501.02892","last_updated":"2025-01-06T10:14:52Z","latest_version":1,"primary_category":"cs.CV","snapshot_observed_at":"2026-08-10T21:58:36.963226Z","submitted_at":"2025-01-06T10:14:52Z","title":"FoundPAD: Foundation Models Reloaded for Face Presentation Attack Detection"},"reference_resolution":{"displayed":65,"state_counts":{"malformed_identifier":0,"metadata_mismatch":0,"parse_uncertain":0,"unresolved":22,"verified_exact":0,"verified_fuzzy":43},"total_outbound_references":65},"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 65 of 65 outbound references and 4 inbound Pith citation observations for arXiv:2501.02892."}