{"as_of":"2026-08-05T20:44:00Z","caps":{"database_statements":6,"inbound":100,"outbound":100},"context_digest":"sha256:8be7ea486c0fa10268a2848f8a9c2340cf749e8b848efd3b771193f7af310e1f","coverage":[{"denominator":53,"lane":"reference_resolution","note":"Typed states for the displayed outbound observations.","records_observed":53,"source":"paper_references, paper_reference_links","source_observed_at":"2026-05-22T18:46:35.684340Z","state":"measured"},{"denominator":55,"lane":"standing_notices","note":"One-hop event checks from named stored sources.","records_observed":55,"source":"scholarly_work_events, retraction_status_cache","source_observed_at":"2026-08-05T06:32:48.257954+00:00","state":"measured"},{"denominator":2,"lane":"inbound_itemization","note":"Pith citing papers itemized under the disclosed page cap.","records_observed":2,"source":"paper_references, paper_reference_links","source_observed_at":"2026-08-01T21:04:40.669683Z","state":"measured"},{"denominator":1,"lane":"external_citation_measurements","note":"A source-named dated measurement, never combined with another source.","records_observed":0,"source":"pith","source_observed_at":"2026-05-10T23:55:49.444793Z","state":"measured"}],"external_citation_measurements":[],"inbound":[{"citation":{"cited_paper":{"arxiv_id":"2504.18015","last_updated":"2026-05-01T02:03:47Z","snapshot_observed_at":"2026-08-02T11:34:45.251281Z","submitted_at":"2025-04-25T01:53:27Z","title":"DiffMI: Breaking Face Recognition Privacy via Diffusion-Driven Training-Free Model Inversion","version":4},"cited_work":{"arxiv_id":"2504.18015","doi":null,"metadata_source":"pith","pith_arxiv_id":"2504.18015","snapshot_observed_at":"2026-06-05T21:23:00.469572Z","title":"DiffMI: Breaking Face Recognition Privacy via Diffusion-Driven Training-Free Model Inversion","venue":"cs.CR","work_id":"9939f7b8-356a-430f-87ba-f3c9ba8d87d0","year":2025},"citing_paper":{"arxiv_id":"2604.05296","last_updated":"2026-04-07T01:03:51Z","snapshot_observed_at":"2026-08-02T08:04:40.750705Z","submitted_at":"2026-04-07T01:03:51Z","title":"From Measurement to Mitigation: Quantifying and Reducing Identity Leakage in Image Representation Encoders with Linear Subspace Removal","version":1},"reference_index":30,"source":"pdf_text","source_observed_at":"2026-05-10T18:49:31.678501Z"},"links":{"cited_paper":"/paper/2504.18015","citing_paper":"/paper/2604.05296"},"observation_digest":"sha256:e3c4656153aab51c194699e32635cf8c4503aa401f616a94a3377b800c5e504d","observation_id":"e25b7f6c-06f6-4992-88fb-3d7604bd4aff","resolution":{"observed_at":"2026-05-10T23:55:49.457633Z","resolver_source":"local_arxiv","status":"verified_exact"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-05T06:32:48.257954+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-05T06:32:48.257954+00:00","source":"crossref"},{"observed_at":"2026-08-05T06:32:44.755628+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"2504.18015","last_updated":"2026-05-01T02:03:47Z","snapshot_observed_at":"2026-08-02T11:34:45.251281Z","submitted_at":"2025-04-25T01:53:27Z","title":"DiffMI: Breaking Face Recognition Privacy via Diffusion-Driven Training-Free Model Inversion","version":4},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2504.18015","snapshot_observed_at":"2026-08-01T21:04:40.669683Z","title":"arXiv preprint arXiv:2504.18015 (2025)","venue":null,"work_id":null,"year":2025},"citing_paper":{"arxiv_id":"2607.16414","last_updated":"2026-07-17T18:05:47Z","snapshot_observed_at":"2026-08-01T21:04:37.305788Z","submitted_at":"2026-07-17T18:05:47Z","title":"Signal-based Model Access Risk Analysis for AI System Operations Security","version":1},"reference_index":34,"source":"pdf_text","source_observed_at":"2026-08-01T21:04:40.669683Z"},"links":{"cited_paper":"/paper/2504.18015","citing_paper":"/paper/2607.16414"},"observation_digest":"sha256:a801058f05a9d19ea5132c035e8c35e24618e8179df17e2b7a7392d2c82bcc6b","observation_id":"1128aa0d-e70f-40e2-99c9-0ba8b684ec23","resolution":{"observed_at":"2026-08-01T21:04:40.669683Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}}],"links":{"evidence":"/evidence","html":"/paper/2504.18015/citation-record","integrity":"/paper/2504.18015/integrity","json":"/paper/2504.18015/citation-record.json","paper":"/paper/2504.18015"},"outbound":[{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-06-05T21:23:00.469572Z","title":"Review of cbp’s major cybersecurity incident during a 2019 biometric pilot","venue":null,"work_id":"0bae5c9d-725e-40b7-8974-8e47d46196ef","year":2019},"citing_paper":{"arxiv_id":"2504.18015","last_updated":"2026-05-01T02:03:47Z","snapshot_observed_at":"2026-08-02T11:34:45.251281Z","submitted_at":"2025-04-25T01:53:27Z","title":"DiffMI: Breaking Face Recognition Privacy via Diffusion-Driven Training-Free Model Inversion","version":4},"reference_index":1,"source":"pdf_text","source_observed_at":"2026-05-22T18:46:35.684340Z"},"links":{"citing_paper":"/paper/2504.18015"},"observation_digest":"sha256:a44e1ca33809a20191e7670aca95a71ca8cb836ada0792e3181e5273d39408cd","observation_id":"076afbcc-3adb-433f-a3f0-cd38cc7f256d","resolution":{"observed_at":"2026-05-22T18:47:04.905504Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-05T06:32:48.257954+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-05T06:32:48.257954+00:00","source":"crossref"},{"observed_at":"2026-08-05T06:32:44.755628+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":"2026-06-05T21:23:00.469572Z","title":"Major breach found in biometrics system used by banks, uk police and defence firms","venue":null,"work_id":"4d020ec5-2437-446c-8736-a178ab0e36ed","year":2019},"citing_paper":{"arxiv_id":"2504.18015","last_updated":"2026-05-01T02:03:47Z","snapshot_observed_at":"2026-08-02T11:34:45.251281Z","submitted_at":"2025-04-25T01:53:27Z","title":"DiffMI: Breaking Face Recognition Privacy via Diffusion-Driven Training-Free Model Inversion","version":4},"reference_index":2,"source":"pdf_text","source_observed_at":"2026-05-22T18:46:35.684340Z"},"links":{"citing_paper":"/paper/2504.18015"},"observation_digest":"sha256:9f9324963d6f1952c4a5dc6992c73a241952ce7cac30e2b15b18b958f350858b","observation_id":"89fb42b8-8da2-4ff0-878c-a9aceb6e9a89","resolution":{"observed_at":"2026-05-22T18:47:04.899804Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-05T06:32:48.257954+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-05T06:32:48.257954+00:00","source":"crossref"},{"observed_at":"2026-08-05T06:32:44.755628+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":"2026-06-05T21:23:00.469572Z","title":"The shanghai data leak shows china’s state surveillance was inevitable","venue":null,"work_id":"9dca4adb-5e12-40cd-840f-9120a621abf2","year":2022},"citing_paper":{"arxiv_id":"2504.18015","last_updated":"2026-05-01T02:03:47Z","snapshot_observed_at":"2026-08-02T11:34:45.251281Z","submitted_at":"2025-04-25T01:53:27Z","title":"DiffMI: Breaking Face Recognition Privacy via Diffusion-Driven Training-Free Model Inversion","version":4},"reference_index":3,"source":"pdf_text","source_observed_at":"2026-05-22T18:46:35.684340Z"},"links":{"citing_paper":"/paper/2504.18015"},"observation_digest":"sha256:db5e2768a20d3edbc35b7f5a3c46041fc16baeda24f14259c0cf6c27c518f951","observation_id":"fc8a82b6-ae4d-49cf-8cef-578fb672cf77","resolution":{"observed_at":"2026-05-22T18:47:04.896217Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-05T06:32:48.257954+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-05T06:32:48.257954+00:00","source":"crossref"},{"observed_at":"2026-08-05T06:32:44.755628+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":"2026-06-05T21:23:00.469572Z","title":"Reported australian biometric data breach prompts arrest and hysteria","venue":null,"work_id":"d1b76696-f877-48c6-84c4-3176e9271040","year":2024},"citing_paper":{"arxiv_id":"2504.18015","last_updated":"2026-05-01T02:03:47Z","snapshot_observed_at":"2026-08-02T11:34:45.251281Z","submitted_at":"2025-04-25T01:53:27Z","title":"DiffMI: Breaking Face Recognition Privacy via Diffusion-Driven Training-Free Model Inversion","version":4},"reference_index":4,"source":"pdf_text","source_observed_at":"2026-05-22T18:46:35.684340Z"},"links":{"citing_paper":"/paper/2504.18015"},"observation_digest":"sha256:33a5954d578d67a8107982f59237c356f0a3f1668d91e74253131697899dfe5b","observation_id":"aed560ac-02e4-4295-b4d1-a747dd6f11e0","resolution":{"observed_at":"2026-05-22T18:47:04.887011Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-05T06:32:48.257954+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-05T06:32:48.257954+00:00","source":"crossref"},{"observed_at":"2026-08-05T06:32:44.755628+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":"2026-06-05T21:23:00.469572Z","title":"Data leak exposes personal data of indian military and police","venue":null,"work_id":"de7be9bf-f5e8-48b9-8748-bff6f84484fa","year":2024},"citing_paper":{"arxiv_id":"2504.18015","last_updated":"2026-05-01T02:03:47Z","snapshot_observed_at":"2026-08-02T11:34:45.251281Z","submitted_at":"2025-04-25T01:53:27Z","title":"DiffMI: Breaking Face Recognition Privacy via Diffusion-Driven Training-Free Model Inversion","version":4},"reference_index":5,"source":"pdf_text","source_observed_at":"2026-05-22T18:46:35.684340Z"},"links":{"citing_paper":"/paper/2504.18015"},"observation_digest":"sha256:c011201b5767f4aa5aa5306f101d370a42edb2af109624b1f75b87fa8ec47456","observation_id":"b6ed767e-650b-4bab-ada3-23254cff6397","resolution":{"observed_at":"2026-05-22T18:47:04.876963Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-05T06:32:48.257954+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-05T06:32:48.257954+00:00","source":"crossref"},{"observed_at":"2026-08-05T06:32:44.755628+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":"2026-06-05T21:23:00.469572Z","title":"Azure AI Services Documenta- tion","venue":null,"work_id":"719de63d-6b9a-4a39-80fe-4c43dfd9a5d5","year":2024},"citing_paper":{"arxiv_id":"2504.18015","last_updated":"2026-05-01T02:03:47Z","snapshot_observed_at":"2026-08-02T11:34:45.251281Z","submitted_at":"2025-04-25T01:53:27Z","title":"DiffMI: Breaking Face Recognition Privacy via Diffusion-Driven Training-Free Model Inversion","version":4},"reference_index":6,"source":"pdf_text","source_observed_at":"2026-05-22T18:46:35.684340Z"},"links":{"citing_paper":"/paper/2504.18015"},"observation_digest":"sha256:3aed53b5930beb1e245c3eaad175427d68d49dd2eed284d3ead027df130b4c28","observation_id":"2a774cb1-3b82-4412-981c-7f153c57a0ea","resolution":{"observed_at":"2026-05-22T18:47:04.869865Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-05T06:32:48.257954+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-05T06:32:48.257954+00:00","source":"crossref"},{"observed_at":"2026-08-05T06:32:44.755628+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":"2026-06-05T21:23:00.469572Z","title":null,"venue":null,"work_id":"c0e34b0b-fd31-4f92-abf9-69276015d81c","year":2024},"citing_paper":{"arxiv_id":"2504.18015","last_updated":"2026-05-01T02:03:47Z","snapshot_observed_at":"2026-08-02T11:34:45.251281Z","submitted_at":"2025-04-25T01:53:27Z","title":"DiffMI: Breaking Face Recognition Privacy via Diffusion-Driven Training-Free Model Inversion","version":4},"reference_index":7,"source":"pdf_text","source_observed_at":"2026-05-22T18:46:35.684340Z"},"links":{"citing_paper":"/paper/2504.18015"},"observation_digest":"sha256:dd7793405154629974308f666eec6ac37246f251e5c092bf68c727e01bfc50c1","observation_id":"489f3101-f63e-4427-9be2-671538939e34","resolution":{"observed_at":"2026-05-22T18:47:04.862039Z","resolver_source":"raw_fallback","status":"unresolved"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-05T06:32:48.257954+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-05T06:32:48.257954+00:00","source":"crossref"},{"observed_at":"2026-08-05T06:32:44.755628+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":"2026-06-05T21:23:00.469572Z","title":"Cloud,Cloud Vision Documentation","venue":null,"work_id":"78d32abe-86cb-4828-8640-81cddca7f6ab","year":2024},"citing_paper":{"arxiv_id":"2504.18015","last_updated":"2026-05-01T02:03:47Z","snapshot_observed_at":"2026-08-02T11:34:45.251281Z","submitted_at":"2025-04-25T01:53:27Z","title":"DiffMI: Breaking Face Recognition Privacy via Diffusion-Driven Training-Free Model Inversion","version":4},"reference_index":8,"source":"pdf_text","source_observed_at":"2026-05-22T18:46:35.684340Z"},"links":{"citing_paper":"/paper/2504.18015"},"observation_digest":"sha256:68ba07841f4d08e118a6a5bd5575108fc1c4d655b89cc0912633528e964f8413","observation_id":"21b2bece-6d48-4daa-95cc-281e5c9d1196","resolution":{"observed_at":"2026-05-22T18:47:04.850433Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-05T06:32:48.257954+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-05T06:32:48.257954+00:00","source":"crossref"},{"observed_at":"2026-08-05T06:32:44.755628+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":"2026-06-05T21:23:00.469572Z","title":"Face++ Official Documentation","venue":null,"work_id":"76871dce-b251-4d8b-a7c8-dd6085edf4de","year":2024},"citing_paper":{"arxiv_id":"2504.18015","last_updated":"2026-05-01T02:03:47Z","snapshot_observed_at":"2026-08-02T11:34:45.251281Z","submitted_at":"2025-04-25T01:53:27Z","title":"DiffMI: Breaking Face Recognition Privacy via Diffusion-Driven Training-Free Model Inversion","version":4},"reference_index":9,"source":"pdf_text","source_observed_at":"2026-05-22T18:46:35.684340Z"},"links":{"citing_paper":"/paper/2504.18015"},"observation_digest":"sha256:62c498846a3f1b08d9e478ecd063d112c05d2e7dae22f6ab6dd2fc34faf20b28","observation_id":"9a68e0e9-f363-4f90-b079-9be7ff811145","resolution":{"observed_at":"2026-05-22T18:47:04.842566Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-05T06:32:48.257954+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-05T06:32:48.257954+00:00","source":"crossref"},{"observed_at":"2026-08-05T06:32:44.755628+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":"2026-06-05T21:23:00.469572Z","title":"Facenet: A unified em- bedding for face recognition and clustering","venue":null,"work_id":"d2dfbbe2-aebd-4446-9988-bc63163dea1d","year":2015},"citing_paper":{"arxiv_id":"2504.18015","last_updated":"2026-05-01T02:03:47Z","snapshot_observed_at":"2026-08-02T11:34:45.251281Z","submitted_at":"2025-04-25T01:53:27Z","title":"DiffMI: Breaking Face Recognition Privacy via Diffusion-Driven Training-Free Model Inversion","version":4},"reference_index":10,"source":"pdf_text","source_observed_at":"2026-05-22T18:46:35.684340Z"},"links":{"citing_paper":"/paper/2504.18015"},"observation_digest":"sha256:62e0eef7e3747682e0b30bfe651e98c47b29c6bf0c755144637b6d26c33e3f9a","observation_id":"923ec7cf-075d-4a9f-8cd3-fd9cbcfe5ab0","resolution":{"observed_at":"2026-05-22T18:47:04.836619Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-05T06:32:48.257954+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-05T06:32:48.257954+00:00","source":"crossref"},{"observed_at":"2026-08-05T06:32:44.755628+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":"2026-06-05T21:23:00.469572Z","title":"Arcface: Additive angular margin loss for deep face recognition","venue":null,"work_id":"e1b6d830-c33a-4fdf-a658-24be8a63d8b6","year":2019},"citing_paper":{"arxiv_id":"2504.18015","last_updated":"2026-05-01T02:03:47Z","snapshot_observed_at":"2026-08-02T11:34:45.251281Z","submitted_at":"2025-04-25T01:53:27Z","title":"DiffMI: Breaking Face Recognition Privacy via Diffusion-Driven Training-Free Model Inversion","version":4},"reference_index":11,"source":"pdf_text","source_observed_at":"2026-05-22T18:46:35.684340Z"},"links":{"citing_paper":"/paper/2504.18015"},"observation_digest":"sha256:ffb818504c6d431f0d26b3d461dd41c677fac95e77a6d453b8ddadad08093ee2","observation_id":"7830038d-a964-472e-9776-5feb60fd038c","resolution":{"observed_at":"2026-05-22T18:47:04.830737Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-05T06:32:48.257954+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-05T06:32:48.257954+00:00","source":"crossref"},{"observed_at":"2026-08-05T06:32:44.755628+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":"2026-06-05T21:23:00.469572Z","title":"Privacy-preserving face recognition with learnable privacy budgets in frequency domain","venue":null,"work_id":"c88d6dd9-2717-4d2e-b37b-40024bfc3c7f","year":2022},"citing_paper":{"arxiv_id":"2504.18015","last_updated":"2026-05-01T02:03:47Z","snapshot_observed_at":"2026-08-02T11:34:45.251281Z","submitted_at":"2025-04-25T01:53:27Z","title":"DiffMI: Breaking Face Recognition Privacy via Diffusion-Driven Training-Free Model Inversion","version":4},"reference_index":12,"source":"pdf_text","source_observed_at":"2026-05-22T18:46:35.684340Z"},"links":{"citing_paper":"/paper/2504.18015"},"observation_digest":"sha256:c13d0d2d01eb175dedc7aa1e114e85a202739128e6bbaff9b3809b14e59d7a46","observation_id":"bef6d832-6a60-4d5e-9472-b6e1bd45c77d","resolution":{"observed_at":"2026-05-22T18:47:04.822507Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-05T06:32:48.257954+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-05T06:32:48.257954+00:00","source":"crossref"},{"observed_at":"2026-08-05T06:32:44.755628+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":"2026-06-05T21:23:00.469572Z","title":"Privacy-preserving face recognition using random frequency components","venue":null,"work_id":"3972f0c7-a8e3-4a10-8029-0c5bf77a3d60","year":2023},"citing_paper":{"arxiv_id":"2504.18015","last_updated":"2026-05-01T02:03:47Z","snapshot_observed_at":"2026-08-02T11:34:45.251281Z","submitted_at":"2025-04-25T01:53:27Z","title":"DiffMI: Breaking Face Recognition Privacy via Diffusion-Driven Training-Free Model Inversion","version":4},"reference_index":13,"source":"pdf_text","source_observed_at":"2026-05-22T18:46:35.684340Z"},"links":{"citing_paper":"/paper/2504.18015"},"observation_digest":"sha256:11bd16a64696923175957c9eef94ea19f062269417625e877f75b2161de7881e","observation_id":"4da96be4-3d33-4dc2-bf93-78fcbede2377","resolution":{"observed_at":"2026-05-22T18:47:04.815144Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-05T06:32:48.257954+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-05T06:32:48.257954+00:00","source":"crossref"},{"observed_at":"2026-08-05T06:32:44.755628+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":"2026-06-05T21:23:00.469572Z","title":"Validating privacy-preserving face recognition under a minimum assumption","venue":null,"work_id":"92ac33f7-6a5c-44c8-b30f-6c6922ca9cb4","year":2024},"citing_paper":{"arxiv_id":"2504.18015","last_updated":"2026-05-01T02:03:47Z","snapshot_observed_at":"2026-08-02T11:34:45.251281Z","submitted_at":"2025-04-25T01:53:27Z","title":"DiffMI: Breaking Face Recognition Privacy via Diffusion-Driven Training-Free Model Inversion","version":4},"reference_index":14,"source":"pdf_text","source_observed_at":"2026-05-22T18:46:35.684340Z"},"links":{"citing_paper":"/paper/2504.18015"},"observation_digest":"sha256:350a435ddc49125ec002c044786654d39af866a5b2f61676dba5294ef80f4d79","observation_id":"cf30b8d4-0c2d-445c-9b00-4ea297e52873","resolution":{"observed_at":"2026-05-22T18:47:04.806592Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-05T06:32:48.257954+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-05T06:32:48.257954+00:00","source":"crossref"},{"observed_at":"2026-08-05T06:32:44.755628+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":"2026-06-05T21:23:00.469572Z","title":"Vulnerability of state- of-the-art face recognition models to template inversion attack","venue":null,"work_id":"2cfb9c8f-275b-48ca-b7a0-95ceb7c0d054","year":2024},"citing_paper":{"arxiv_id":"2504.18015","last_updated":"2026-05-01T02:03:47Z","snapshot_observed_at":"2026-08-02T11:34:45.251281Z","submitted_at":"2025-04-25T01:53:27Z","title":"DiffMI: Breaking Face Recognition Privacy via Diffusion-Driven Training-Free Model Inversion","version":4},"reference_index":15,"source":"pdf_text","source_observed_at":"2026-05-22T18:46:35.684340Z"},"links":{"citing_paper":"/paper/2504.18015"},"observation_digest":"sha256:b9b8ff91d060152e091c2b4d32864323f9bae1239acd5d7e338fd7993ff55f97","observation_id":"3d5f22cf-0cef-41ce-87e5-e82ffec52b19","resolution":{"observed_at":"2026-05-22T18:47:04.802681Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-05T06:32:48.257954+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-05T06:32:48.257954+00:00","source":"crossref"},{"observed_at":"2026-08-05T06:32:44.755628+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":"2026-06-05T21:23:00.469572Z","title":"Face reconstruction from facial templates by learning latent space of a generator network","venue":null,"work_id":"48e8acd0-fe2c-4144-9089-7772d5982384","year":2023},"citing_paper":{"arxiv_id":"2504.18015","last_updated":"2026-05-01T02:03:47Z","snapshot_observed_at":"2026-08-02T11:34:45.251281Z","submitted_at":"2025-04-25T01:53:27Z","title":"DiffMI: Breaking Face Recognition Privacy via Diffusion-Driven Training-Free Model Inversion","version":4},"reference_index":16,"source":"pdf_text","source_observed_at":"2026-05-22T18:46:35.684340Z"},"links":{"citing_paper":"/paper/2504.18015"},"observation_digest":"sha256:6911a91cdf337206e80d1908dd87812a72dafdd10d60e95b8c14bb9e9a272665","observation_id":"6aef895b-f9bf-4b36-a760-e22cdbd85290","resolution":{"observed_at":"2026-05-22T18:47:04.799662Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-05T06:32:48.257954+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-05T06:32:48.257954+00:00","source":"crossref"},{"observed_at":"2026-08-05T06:32:44.755628+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":"2026-06-05T21:23:00.469572Z","title":"Template inversion attack using synthetic face images against real face recognition systems","venue":null,"work_id":"796f96c4-0f8d-4197-be97-09574b7936eb","year":2024},"citing_paper":{"arxiv_id":"2504.18015","last_updated":"2026-05-01T02:03:47Z","snapshot_observed_at":"2026-08-02T11:34:45.251281Z","submitted_at":"2025-04-25T01:53:27Z","title":"DiffMI: Breaking Face Recognition Privacy via Diffusion-Driven Training-Free Model Inversion","version":4},"reference_index":17,"source":"pdf_text","source_observed_at":"2026-05-22T18:46:35.684340Z"},"links":{"citing_paper":"/paper/2504.18015"},"observation_digest":"sha256:66b70d7a4358e2da58b9df6f9eb5d33dbc4b25d4435be8420c3879133a67dcc5","observation_id":"45a9fa44-e910-4e55-b20a-acee0f306767","resolution":{"observed_at":"2026-05-22T18:47:04.792257Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-05T06:32:48.257954+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-05T06:32:48.257954+00:00","source":"crossref"},{"observed_at":"2026-08-05T06:32:44.755628+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":"2026-06-05T21:23:00.469572Z","title":"Reconstruct face from features based on genetic algorithm using gan generator as a distribution constraint","venue":null,"work_id":"f1f12c75-55a5-4706-8006-7d8312490200","year":2023},"citing_paper":{"arxiv_id":"2504.18015","last_updated":"2026-05-01T02:03:47Z","snapshot_observed_at":"2026-08-02T11:34:45.251281Z","submitted_at":"2025-04-25T01:53:27Z","title":"DiffMI: Breaking Face Recognition Privacy via Diffusion-Driven Training-Free Model Inversion","version":4},"reference_index":18,"source":"pdf_text","source_observed_at":"2026-05-22T18:46:35.684340Z"},"links":{"citing_paper":"/paper/2504.18015"},"observation_digest":"sha256:46c5342d223a482f3f58ef30231bcd4843b03b0bda3b0e9ce06da68a20274f49","observation_id":"67419300-9650-4365-bb42-212d64a528e7","resolution":{"observed_at":"2026-05-22T18:47:04.784795Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-05T06:32:48.257954+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-05T06:32:48.257954+00:00","source":"crossref"},{"observed_at":"2026-08-05T06:32:44.755628+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":"2026-06-05T21:23:00.469572Z","title":"Model inversion attacks that exploit confidence information and basic countermeasures","venue":null,"work_id":"aadabaf7-4af7-4e3b-8213-4918f880fceb","year":2015},"citing_paper":{"arxiv_id":"2504.18015","last_updated":"2026-05-01T02:03:47Z","snapshot_observed_at":"2026-08-02T11:34:45.251281Z","submitted_at":"2025-04-25T01:53:27Z","title":"DiffMI: Breaking Face Recognition Privacy via Diffusion-Driven Training-Free Model Inversion","version":4},"reference_index":19,"source":"pdf_text","source_observed_at":"2026-05-22T18:46:35.684340Z"},"links":{"citing_paper":"/paper/2504.18015"},"observation_digest":"sha256:dbba5e4a974ec8551758704319dcae7c9a5416c5f987febcc4d07ae12f8e41c7","observation_id":"83435a72-d6e7-41f9-a3de-42009aeaf679","resolution":{"observed_at":"2026-05-22T18:47:04.780592Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-05T06:32:48.257954+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-05T06:32:48.257954+00:00","source":"crossref"},{"observed_at":"2026-08-05T06:32:44.755628+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":"2026-06-05T21:23:00.469572Z","title":"On the reconstruction of face images from deep face templates","venue":null,"work_id":"e1b9a19a-33ad-4446-9ae0-dfbd31841e4d","year":2018},"citing_paper":{"arxiv_id":"2504.18015","last_updated":"2026-05-01T02:03:47Z","snapshot_observed_at":"2026-08-02T11:34:45.251281Z","submitted_at":"2025-04-25T01:53:27Z","title":"DiffMI: Breaking Face Recognition Privacy via Diffusion-Driven Training-Free Model Inversion","version":4},"reference_index":20,"source":"pdf_text","source_observed_at":"2026-05-22T18:46:35.684340Z"},"links":{"citing_paper":"/paper/2504.18015"},"observation_digest":"sha256:95fd95460c428727a8a1503f60d1c56c02d0053af146926fc0aadcc78623ef0f","observation_id":"b977f809-fc00-40d7-a8c0-2dd27ff8ef15","resolution":{"observed_at":"2026-05-22T18:47:04.856156Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-05T06:32:48.257954+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-05T06:32:48.257954+00:00","source":"crossref"},{"observed_at":"2026-08-05T06:32:44.755628+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":"2026-06-05T21:23:00.469572Z","title":"Analysis and utilization of hidden information in model inversion attacks","venue":null,"work_id":"5d1d7eab-2d94-4c0d-abb2-22e780de557f","year":2023},"citing_paper":{"arxiv_id":"2504.18015","last_updated":"2026-05-01T02:03:47Z","snapshot_observed_at":"2026-08-02T11:34:45.251281Z","submitted_at":"2025-04-25T01:53:27Z","title":"DiffMI: Breaking Face Recognition Privacy via Diffusion-Driven Training-Free Model Inversion","version":4},"reference_index":21,"source":"pdf_text","source_observed_at":"2026-05-22T18:46:35.684340Z"},"links":{"citing_paper":"/paper/2504.18015"},"observation_digest":"sha256:2e91f214a545ef5807cf1fac8830d2853bac250fd65068ec2c15f481e59174b4","observation_id":"2373cab3-44d6-4e06-9749-9ef099741645","resolution":{"observed_at":"2026-05-22T18:47:04.647328Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-05T06:32:48.257954+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-05T06:32:48.257954+00:00","source":"crossref"},{"observed_at":"2026-08-05T06:32:44.755628+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":"2026-06-05T21:23:00.469572Z","title":"Vec2face: Unveil human faces from their blackbox features in face recognition","venue":null,"work_id":"915a26d8-13d6-4071-bbaf-3a710deb5dbc","year":2020},"citing_paper":{"arxiv_id":"2504.18015","last_updated":"2026-05-01T02:03:47Z","snapshot_observed_at":"2026-08-02T11:34:45.251281Z","submitted_at":"2025-04-25T01:53:27Z","title":"DiffMI: Breaking Face Recognition Privacy via Diffusion-Driven Training-Free Model Inversion","version":4},"reference_index":22,"source":"pdf_text","source_observed_at":"2026-05-22T18:46:35.684340Z"},"links":{"citing_paper":"/paper/2504.18015"},"observation_digest":"sha256:ef4fdc8a5f9c50be438b2ba7dfb1a3867e31c0493410e531bc8ef9d59352f360","observation_id":"d8b17dc1-4a64-463b-8e90-3b1bd80ade9c","resolution":{"observed_at":"2026-05-22T18:47:04.768767Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-05T06:32:48.257954+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-05T06:32:48.257954+00:00","source":"crossref"},{"observed_at":"2026-08-05T06:32:44.755628+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":"2026-06-05T21:23:00.469572Z","title":"The secret revealer: Generative model-inversion attacks against deep neural networks","venue":null,"work_id":"8ca5808e-790c-4222-be5a-d9f6064bfb34","year":2020},"citing_paper":{"arxiv_id":"2504.18015","last_updated":"2026-05-01T02:03:47Z","snapshot_observed_at":"2026-08-02T11:34:45.251281Z","submitted_at":"2025-04-25T01:53:27Z","title":"DiffMI: Breaking Face Recognition Privacy via Diffusion-Driven Training-Free Model Inversion","version":4},"reference_index":23,"source":"pdf_text","source_observed_at":"2026-05-22T18:46:35.684340Z"},"links":{"citing_paper":"/paper/2504.18015"},"observation_digest":"sha256:c45b338fb98470c61697e994c78d0bfc539e9f0301d7441b0708fbed4d359e3d","observation_id":"20898722-ccbe-4cd2-aa2f-2859cd090a42","resolution":{"observed_at":"2026-05-22T18:47:04.758494Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-05T06:32:48.257954+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-05T06:32:48.257954+00:00","source":"crossref"},{"observed_at":"2026-08-05T06:32:44.755628+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":"2026-06-05T21:23:00.469572Z","title":"Model inversion attack by integration of deep generative models: Privacy-sensitive face generation from a face recognition system","venue":null,"work_id":"1cf4b470-0373-42fb-b8ab-5bf9e918b5df","year":2022},"citing_paper":{"arxiv_id":"2504.18015","last_updated":"2026-05-01T02:03:47Z","snapshot_observed_at":"2026-08-02T11:34:45.251281Z","submitted_at":"2025-04-25T01:53:27Z","title":"DiffMI: Breaking Face Recognition Privacy via Diffusion-Driven Training-Free Model Inversion","version":4},"reference_index":24,"source":"pdf_text","source_observed_at":"2026-05-22T18:46:35.684340Z"},"links":{"citing_paper":"/paper/2504.18015"},"observation_digest":"sha256:5091c272ea1518199bc9714ee147d0888551f74012a78e73ac3aa3e68af44a0f","observation_id":"786267eb-2f36-4714-b3f7-aa466b842bb1","resolution":{"observed_at":"2026-05-22T18:47:04.746726Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-05T06:32:48.257954+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-05T06:32:48.257954+00:00","source":"crossref"},{"observed_at":"2026-08-05T06:32:44.755628+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":"2026-06-05T21:23:00.469572Z","title":"Pseudo label-guided model inversion attack via conditional generative adver- sarial network","venue":null,"work_id":"4f8f0045-31f3-4a88-8348-50a8119556b7","year":2023},"citing_paper":{"arxiv_id":"2504.18015","last_updated":"2026-05-01T02:03:47Z","snapshot_observed_at":"2026-08-02T11:34:45.251281Z","submitted_at":"2025-04-25T01:53:27Z","title":"DiffMI: Breaking Face Recognition Privacy via Diffusion-Driven Training-Free Model Inversion","version":4},"reference_index":25,"source":"pdf_text","source_observed_at":"2026-05-22T18:46:35.684340Z"},"links":{"citing_paper":"/paper/2504.18015"},"observation_digest":"sha256:54f936a42e9c93c4c235fde2e6c7ad2f6ef65ca0d0f085c0a15148d303d4c351","observation_id":"e1987261-4e88-4351-85d3-7197fd8487d1","resolution":{"observed_at":"2026-05-22T18:47:04.634989Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-05T06:32:48.257954+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-05T06:32:48.257954+00:00","source":"crossref"},{"observed_at":"2026-08-05T06:32:44.755628+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":"2026-06-05T21:23:00.469572Z","title":"Label-only model inversion attacks via knowledge transfer","venue":null,"work_id":"4007f40b-ad5f-40ca-ba1e-6724684712f4","year":2023},"citing_paper":{"arxiv_id":"2504.18015","last_updated":"2026-05-01T02:03:47Z","snapshot_observed_at":"2026-08-02T11:34:45.251281Z","submitted_at":"2025-04-25T01:53:27Z","title":"DiffMI: Breaking Face Recognition Privacy via Diffusion-Driven Training-Free Model Inversion","version":4},"reference_index":26,"source":"pdf_text","source_observed_at":"2026-05-22T18:46:35.684340Z"},"links":{"citing_paper":"/paper/2504.18015"},"observation_digest":"sha256:4518fad60d39f41555567b2a8985e3b213c4a7acfdc6b4d4ba68297169a1740c","observation_id":"d47a6e48-7fc6-4bd0-aebe-92397a3affff","resolution":{"observed_at":"2026-05-22T18:47:04.738788Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-05T06:32:48.257954+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-05T06:32:48.257954+00:00","source":"crossref"},{"observed_at":"2026-08-05T06:32:44.755628+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":"2026-06-05T21:23:00.469572Z","title":"Label-only model inversion attacks: Adaptive boundary exclusion for limited queries","venue":null,"work_id":"b49428a3-7282-447a-b950-84f38578f127","year":2025},"citing_paper":{"arxiv_id":"2504.18015","last_updated":"2026-05-01T02:03:47Z","snapshot_observed_at":"2026-08-02T11:34:45.251281Z","submitted_at":"2025-04-25T01:53:27Z","title":"DiffMI: Breaking Face Recognition Privacy via Diffusion-Driven Training-Free Model Inversion","version":4},"reference_index":27,"source":"pdf_text","source_observed_at":"2026-05-22T18:46:35.684340Z"},"links":{"citing_paper":"/paper/2504.18015"},"observation_digest":"sha256:b3ace85b46e4754b198d0cc43b7bc228cffaea895dc052b29babc6314e26826f","observation_id":"3ae1c8a1-bbbd-4884-81b3-c67819435790","resolution":{"observed_at":"2026-05-22T18:47:04.732445Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-05T06:32:48.257954+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-05T06:32:48.257954+00:00","source":"crossref"},{"observed_at":"2026-08-05T06:32:44.755628+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":"2026-06-05T21:23:00.469572Z","title":"Controllable inversion of black-box face recognition models via diffusion","venue":null,"work_id":"3917252b-af73-4260-bc21-74f6363efb7e","year":2023},"citing_paper":{"arxiv_id":"2504.18015","last_updated":"2026-05-01T02:03:47Z","snapshot_observed_at":"2026-08-02T11:34:45.251281Z","submitted_at":"2025-04-25T01:53:27Z","title":"DiffMI: Breaking Face Recognition Privacy via Diffusion-Driven Training-Free Model Inversion","version":4},"reference_index":28,"source":"pdf_text","source_observed_at":"2026-05-22T18:46:35.684340Z"},"links":{"citing_paper":"/paper/2504.18015"},"observation_digest":"sha256:ad7bb423251c583161e25bcfaeb5178b40d53037b1d4bed9b459b10a6aeae960","observation_id":"e85c2bc5-e9ac-4bd5-ac83-48160d27c3f1","resolution":{"observed_at":"2026-05-22T18:47:04.727648Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-05T06:32:48.257954+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-05T06:32:48.257954+00:00","source":"crossref"},{"observed_at":"2026-08-05T06:32:44.755628+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":"2026-06-05T21:23:00.469572Z","title":"Un- stoppable attack: Label-only model inversion via conditional diffusion model","venue":null,"work_id":"a24cca43-56c7-4258-a202-0d97fac31eef","year":2024},"citing_paper":{"arxiv_id":"2504.18015","last_updated":"2026-05-01T02:03:47Z","snapshot_observed_at":"2026-08-02T11:34:45.251281Z","submitted_at":"2025-04-25T01:53:27Z","title":"DiffMI: Breaking Face Recognition Privacy via Diffusion-Driven Training-Free Model Inversion","version":4},"reference_index":29,"source":"pdf_text","source_observed_at":"2026-05-22T18:46:35.684340Z"},"links":{"citing_paper":"/paper/2504.18015"},"observation_digest":"sha256:14d7193cdfef4533f4f51a0011e75bc9dcffe2f968a73447bd5287c31ae5d178","observation_id":"01c1190f-b7a1-4538-934e-7a77f58adec0","resolution":{"observed_at":"2026-05-22T18:47:04.691301Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-05T06:32:48.257954+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-05T06:32:48.257954+00:00","source":"crossref"},{"observed_at":"2026-08-05T06:32:44.755628+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":"2026-06-05T21:23:00.469572Z","title":"Plug & play attacks: Towards robust and flexible model inversion attacks","venue":null,"work_id":"3a1ce5a3-0e2f-433f-81dc-1cdfb52a284f","year":2022},"citing_paper":{"arxiv_id":"2504.18015","last_updated":"2026-05-01T02:03:47Z","snapshot_observed_at":"2026-08-02T11:34:45.251281Z","submitted_at":"2025-04-25T01:53:27Z","title":"DiffMI: Breaking Face Recognition Privacy via Diffusion-Driven Training-Free Model Inversion","version":4},"reference_index":30,"source":"pdf_text","source_observed_at":"2026-05-22T18:46:35.684340Z"},"links":{"citing_paper":"/paper/2504.18015"},"observation_digest":"sha256:44fc85c5b9d80a4d6c8c578ef05dc745039a6f1ac26dd12b4a803aed47dd9abd","observation_id":"61a23e8f-fd8d-4d39-8fc4-f850ba385e93","resolution":{"observed_at":"2026-05-22T18:47:04.725646Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-05T06:32:48.257954+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-05T06:32:48.257954+00:00","source":"crossref"},{"observed_at":"2026-08-05T06:32:44.755628+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":"2026-06-05T21:23:00.469572Z","title":"A closer look at gan priors: Exploiting intermediate features for enhanced model inversion attacks","venue":null,"work_id":"ee34de80-462c-4236-9ebf-3547714e9705","year":2024},"citing_paper":{"arxiv_id":"2504.18015","last_updated":"2026-05-01T02:03:47Z","snapshot_observed_at":"2026-08-02T11:34:45.251281Z","submitted_at":"2025-04-25T01:53:27Z","title":"DiffMI: Breaking Face Recognition Privacy via Diffusion-Driven Training-Free Model Inversion","version":4},"reference_index":31,"source":"pdf_text","source_observed_at":"2026-05-22T18:46:35.684340Z"},"links":{"citing_paper":"/paper/2504.18015"},"observation_digest":"sha256:15601a8d92fdfb4f39f3f9d8ac97c8671ec8b0eda2b801a09a0124d2ef202515","observation_id":"f58df2f8-b896-4278-85c8-93c01208487c","resolution":{"observed_at":"2026-05-22T18:47:04.722971Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-05T06:32:48.257954+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-05T06:32:48.257954+00:00","source":"crossref"},{"observed_at":"2026-08-05T06:32:44.755628+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":"2026-06-05T21:23:00.469572Z","title":"Pridm: Effective and universal private data recovery via diffusion models","venue":null,"work_id":"5511e382-d515-40a5-9667-b3e768e24f58","year":2025},"citing_paper":{"arxiv_id":"2504.18015","last_updated":"2026-05-01T02:03:47Z","snapshot_observed_at":"2026-08-02T11:34:45.251281Z","submitted_at":"2025-04-25T01:53:27Z","title":"DiffMI: Breaking Face Recognition Privacy via Diffusion-Driven Training-Free Model Inversion","version":4},"reference_index":32,"source":"pdf_text","source_observed_at":"2026-05-22T18:46:35.684340Z"},"links":{"citing_paper":"/paper/2504.18015"},"observation_digest":"sha256:f1a6b1c798125b2a883d230f204123b7381b4b50f66445235bc48ccd7e3aa5ec","observation_id":"4071f086-571f-4343-ae4d-68058fd0876e","resolution":{"observed_at":"2026-05-22T18:47:04.720862Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-05T06:32:48.257954+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-05T06:32:48.257954+00:00","source":"crossref"},{"observed_at":"2026-08-05T06:32:44.755628+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":"2026-06-05T21:23:00.469572Z","title":"Oulu-npu: A mobile face presentation attack database with real-world variations","venue":null,"work_id":"25df303e-4357-44d7-bb4b-7e1c75ae5ba2","year":2017},"citing_paper":{"arxiv_id":"2504.18015","last_updated":"2026-05-01T02:03:47Z","snapshot_observed_at":"2026-08-02T11:34:45.251281Z","submitted_at":"2025-04-25T01:53:27Z","title":"DiffMI: Breaking Face Recognition Privacy via Diffusion-Driven Training-Free Model Inversion","version":4},"reference_index":33,"source":"pdf_text","source_observed_at":"2026-05-22T18:46:35.684340Z"},"links":{"citing_paper":"/paper/2504.18015"},"observation_digest":"sha256:15662ad560fcdbfecd4ea27ad765a11704ec1993b5b448bf8a49ff7d498cdd88","observation_id":"e48f21ad-6810-4eea-bf9a-5791d42c9077","resolution":{"observed_at":"2026-05-22T18:47:04.717788Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-05T06:32:48.257954+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-05T06:32:48.257954+00:00","source":"crossref"},{"observed_at":"2026-08-05T06:32:44.755628+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":"2026-06-05T21:23:00.469572Z","title":"The many-faced god: Attacking face veri- fication system with embedding and image recovery","venue":null,"work_id":"130a5559-5c0c-4b90-af7a-0a4fc49d5202","year":2021},"citing_paper":{"arxiv_id":"2504.18015","last_updated":"2026-05-01T02:03:47Z","snapshot_observed_at":"2026-08-02T11:34:45.251281Z","submitted_at":"2025-04-25T01:53:27Z","title":"DiffMI: Breaking Face Recognition Privacy via Diffusion-Driven Training-Free Model Inversion","version":4},"reference_index":34,"source":"pdf_text","source_observed_at":"2026-05-22T18:46:35.684340Z"},"links":{"citing_paper":"/paper/2504.18015"},"observation_digest":"sha256:afb3ab0a4fa9e35e85e19480f578df8c89555416cc152d4faccf189e9dfe603f","observation_id":"e3cf9c6a-d08b-4d7a-bee0-3e68de477e28","resolution":{"observed_at":"2026-05-22T18:47:04.715368Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-05T06:32:48.257954+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-05T06:32:48.257954+00:00","source":"crossref"},{"observed_at":"2026-08-05T06:32:44.755628+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":"2026-06-05T21:23:00.469572Z","title":"High- resolution image synthesis with latent diffusion models","venue":null,"work_id":"75579563-44bc-43c6-a0f5-fb91e119c8e8","year":2022},"citing_paper":{"arxiv_id":"2504.18015","last_updated":"2026-05-01T02:03:47Z","snapshot_observed_at":"2026-08-02T11:34:45.251281Z","submitted_at":"2025-04-25T01:53:27Z","title":"DiffMI: Breaking Face Recognition Privacy via Diffusion-Driven Training-Free Model Inversion","version":4},"reference_index":35,"source":"pdf_text","source_observed_at":"2026-05-22T18:46:35.684340Z"},"links":{"citing_paper":"/paper/2504.18015"},"observation_digest":"sha256:5b06d72a3336d395fed4e5bd73e13f5b033454c90906a2bd5f3580ea1dccfd9c","observation_id":"faf5b03b-bbe6-4279-9fce-82aa40e9b70a","resolution":{"observed_at":"2026-05-22T18:47:04.712453Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-05T06:32:48.257954+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-05T06:32:48.257954+00:00","source":"crossref"},{"observed_at":"2026-08-05T06:32:44.755628+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":"2026-06-05T21:23:00.469572Z","title":"An- alyzing and improving the image quality of stylegan","venue":null,"work_id":"d7fa2c35-4899-4d9b-9ebb-e7d2bf869c5f","year":2020},"citing_paper":{"arxiv_id":"2504.18015","last_updated":"2026-05-01T02:03:47Z","snapshot_observed_at":"2026-08-02T11:34:45.251281Z","submitted_at":"2025-04-25T01:53:27Z","title":"DiffMI: Breaking Face Recognition Privacy via Diffusion-Driven Training-Free Model Inversion","version":4},"reference_index":36,"source":"pdf_text","source_observed_at":"2026-05-22T18:46:35.684340Z"},"links":{"citing_paper":"/paper/2504.18015"},"observation_digest":"sha256:f5e5c6cc055c4d986936ecf06a13ee46019fd810b260bafbb0e8c0cfb5a29fc1","observation_id":"2799b668-f2f5-40cd-a3e0-e96c129ac73c","resolution":{"observed_at":"2026-05-22T18:47:04.710484Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-05T06:32:48.257954+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-05T06:32:48.257954+00:00","source":"crossref"},{"observed_at":"2026-08-05T06:32:44.755628+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":"2026-06-05T21:23:00.469572Z","title":"SDEdit: Guided image synthesis and editing with stochastic differential equations","venue":null,"work_id":"8c02a0c6-ecb3-434d-8363-cf84ab5b70f7","year":2022},"citing_paper":{"arxiv_id":"2504.18015","last_updated":"2026-05-01T02:03:47Z","snapshot_observed_at":"2026-08-02T11:34:45.251281Z","submitted_at":"2025-04-25T01:53:27Z","title":"DiffMI: Breaking Face Recognition Privacy via Diffusion-Driven Training-Free Model Inversion","version":4},"reference_index":37,"source":"pdf_text","source_observed_at":"2026-05-22T18:46:35.684340Z"},"links":{"citing_paper":"/paper/2504.18015"},"observation_digest":"sha256:bd14a3bbd23c06d32661238b3bca5ed35d3d7fdc591fd9f19d327bbad7afe487","observation_id":"d5805c18-27db-40db-9efc-fde4e2d92b93","resolution":{"observed_at":"2026-05-22T18:47:04.708254Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-05T06:32:48.257954+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-05T06:32:48.257954+00:00","source":"crossref"},{"observed_at":"2026-08-05T06:32:44.755628+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":"2026-06-05T21:23:00.469572Z","title":"Maskgan: Towards diverse and interactive facial image manipulation","venue":null,"work_id":"a0a02b66-b664-425a-9c59-e6564cd81831","year":2020},"citing_paper":{"arxiv_id":"2504.18015","last_updated":"2026-05-01T02:03:47Z","snapshot_observed_at":"2026-08-02T11:34:45.251281Z","submitted_at":"2025-04-25T01:53:27Z","title":"DiffMI: Breaking Face Recognition Privacy via Diffusion-Driven Training-Free Model Inversion","version":4},"reference_index":38,"source":"pdf_text","source_observed_at":"2026-05-22T18:46:35.684340Z"},"links":{"citing_paper":"/paper/2504.18015"},"observation_digest":"sha256:e889e6ffb6a180c08f7abac8386003aaaad7325f597eea9e87d05d04c8d7c3eb","observation_id":"b9f27c14-012d-4525-9e06-19aa46b79f31","resolution":{"observed_at":"2026-05-22T18:47:04.705269Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-05T06:32:48.257954+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-05T06:32:48.257954+00:00","source":"crossref"},{"observed_at":"2026-08-05T06:32:44.755628+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":"2026-06-05T21:23:00.469572Z","title":"Labeled faces in the wild: A database forstudying face recognition in unconstrained environments","venue":null,"work_id":"b43f245b-885d-463b-9262-3dfa95aadf52","year":2008},"citing_paper":{"arxiv_id":"2504.18015","last_updated":"2026-05-01T02:03:47Z","snapshot_observed_at":"2026-08-02T11:34:45.251281Z","submitted_at":"2025-04-25T01:53:27Z","title":"DiffMI: Breaking Face Recognition Privacy via Diffusion-Driven Training-Free Model Inversion","version":4},"reference_index":39,"source":"pdf_text","source_observed_at":"2026-05-22T18:46:35.684340Z"},"links":{"citing_paper":"/paper/2504.18015"},"observation_digest":"sha256:f796f886714dbea5f079239ccc8aa256eba412f3eee58a9a9accfacfdca24450","observation_id":"ee70c38e-58c8-4b14-8559-08a8bb66bd97","resolution":{"observed_at":"2026-05-22T18:47:04.643302Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-05T06:32:48.257954+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-05T06:32:48.257954+00:00","source":"crossref"},{"observed_at":"2026-08-05T06:32:44.755628+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":"2026-06-05T21:23:00.469572Z","title":"Transformation to normality of the null distribution ofg 1","venue":null,"work_id":"5b1ff001-889d-406a-b85f-e4c90b7c6118","year":1970},"citing_paper":{"arxiv_id":"2504.18015","last_updated":"2026-05-01T02:03:47Z","snapshot_observed_at":"2026-08-02T11:34:45.251281Z","submitted_at":"2025-04-25T01:53:27Z","title":"DiffMI: Breaking Face Recognition Privacy via Diffusion-Driven Training-Free Model Inversion","version":4},"reference_index":40,"source":"pdf_text","source_observed_at":"2026-05-22T18:46:35.684340Z"},"links":{"citing_paper":"/paper/2504.18015"},"observation_digest":"sha256:0e8ab92a1a4baf7a6e6003e65d22ff6c79911ccd83fa06e7188dd8d7d6ff028b","observation_id":"09a8785f-3d71-42dc-a988-5c60ffe3db24","resolution":{"observed_at":"2026-05-22T18:47:04.702871Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-05T06:32:48.257954+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-05T06:32:48.257954+00:00","source":"crossref"},{"observed_at":"2026-08-05T06:32:44.755628+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":"2026-06-05T21:23:00.469572Z","title":"Tests for departure from normality. empirical results for the distributions ofb 2 and √b1","venue":null,"work_id":"7fe627a9-ee7b-4410-be3b-3516bbad5d10","year":1973},"citing_paper":{"arxiv_id":"2504.18015","last_updated":"2026-05-01T02:03:47Z","snapshot_observed_at":"2026-08-02T11:34:45.251281Z","submitted_at":"2025-04-25T01:53:27Z","title":"DiffMI: Breaking Face Recognition Privacy via Diffusion-Driven Training-Free Model Inversion","version":4},"reference_index":41,"source":"pdf_text","source_observed_at":"2026-05-22T18:46:35.684340Z"},"links":{"citing_paper":"/paper/2504.18015"},"observation_digest":"sha256:f792c81c0e96206619992febf1a288c7173c73432e0fca3ff1c776f70bd34e5c","observation_id":"1fa0c36e-7f6d-40b2-a12b-9ba9a6da5665","resolution":{"observed_at":"2026-05-22T18:47:04.754450Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-05T06:32:48.257954+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-05T06:32:48.257954+00:00","source":"crossref"},{"observed_at":"2026-08-05T06:32:44.755628+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":"2026-06-05T21:23:00.469572Z","title":"A suggestion for using powerful and informative tests of normality","venue":null,"work_id":"33f0e714-0349-46a3-bed7-d4c2f12ac071","year":1990},"citing_paper":{"arxiv_id":"2504.18015","last_updated":"2026-05-01T02:03:47Z","snapshot_observed_at":"2026-08-02T11:34:45.251281Z","submitted_at":"2025-04-25T01:53:27Z","title":"DiffMI: Breaking Face Recognition Privacy via Diffusion-Driven Training-Free Model Inversion","version":4},"reference_index":42,"source":"pdf_text","source_observed_at":"2026-05-22T18:46:35.684340Z"},"links":{"citing_paper":"/paper/2504.18015"},"observation_digest":"sha256:47ccc072c298862705af4d4d6b97f969fe2af5304a79b78bb72928d3f7de85c8","observation_id":"64078ec8-e6c2-432d-bcb9-1761984a66e8","resolution":{"observed_at":"2026-05-22T18:47:04.700563Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-05T06:32:48.257954+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-05T06:32:48.257954+00:00","source":"crossref"},{"observed_at":"2026-08-05T06:32:44.755628+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":"2026-06-05T21:23:00.469572Z","title":"Joint face detection and alignment using multitask cascaded convolutional networks","venue":null,"work_id":"d7a6b02a-3d41-499e-86ea-3f0baed6f4f7","year":2016},"citing_paper":{"arxiv_id":"2504.18015","last_updated":"2026-05-01T02:03:47Z","snapshot_observed_at":"2026-08-02T11:34:45.251281Z","submitted_at":"2025-04-25T01:53:27Z","title":"DiffMI: Breaking Face Recognition Privacy via Diffusion-Driven Training-Free Model Inversion","version":4},"reference_index":43,"source":"pdf_text","source_observed_at":"2026-05-22T18:46:35.684340Z"},"links":{"citing_paper":"/paper/2504.18015"},"observation_digest":"sha256:aaf087da5ad8871b017250a1a4938d77c3e50d04e99c24b9853da576e9ce8f2e","observation_id":"1a75a45a-18a7-4b76-9144-9d2af04b2a65","resolution":{"observed_at":"2026-05-22T18:47:04.696816Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-05T06:32:48.257954+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-05T06:32:48.257954+00:00","source":"crossref"},{"observed_at":"2026-08-05T06:32:44.755628+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":"2501.14230","doi":null,"metadata_source":"arxiv_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-06-05T21:23:00.469572Z","title":"Greedyp- ixel: Fine-grained black-box adversarial attack via greedy algorithm","venue":null,"work_id":"d1290440-bdb4-4791-9c99-4ab719640d48","year":2025},"citing_paper":{"arxiv_id":"2504.18015","last_updated":"2026-05-01T02:03:47Z","snapshot_observed_at":"2026-08-02T11:34:45.251281Z","submitted_at":"2025-04-25T01:53:27Z","title":"DiffMI: Breaking Face Recognition Privacy via Diffusion-Driven Training-Free Model Inversion","version":4},"reference_index":44,"source":"pdf_text","source_observed_at":"2026-05-22T18:46:35.684340Z"},"links":{"citing_paper":"/paper/2504.18015"},"observation_digest":"sha256:da66ea4d36db1b93dcf75442a3c8943479f7a6bd2839d7b3455bab5a350bafd7","observation_id":"e122bb7c-db4a-4a75-8d19-c960e9a234ae","resolution":{"observed_at":"2026-05-22T18:46:56.743651Z","resolver_source":"arxiv_id","status":"verified_exact"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-05T06:32:48.257954+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-05T06:32:48.257954+00:00","source":"crossref"},{"observed_at":"2026-08-05T06:32:44.755628+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":"2026-06-05T21:23:00.469572Z","title":"Reliable evaluation of adversarial robustness with an ensemble of diverse parameter-free attacks","venue":null,"work_id":"9fbeb244-44b0-4ea6-a48e-5cf5a6c052f7","year":2020},"citing_paper":{"arxiv_id":"2504.18015","last_updated":"2026-05-01T02:03:47Z","snapshot_observed_at":"2026-08-02T11:34:45.251281Z","submitted_at":"2025-04-25T01:53:27Z","title":"DiffMI: Breaking Face Recognition Privacy via Diffusion-Driven Training-Free Model Inversion","version":4},"reference_index":45,"source":"pdf_text","source_observed_at":"2026-05-22T18:46:35.684340Z"},"links":{"citing_paper":"/paper/2504.18015"},"observation_digest":"sha256:891b435ce3f0661aa9719f013063eb1f41b9478ae0acb2aa39fb9130fb78a7a0","observation_id":"1585538e-71cf-4140-82e8-88f3170fcea3","resolution":{"observed_at":"2026-05-22T18:47:04.686001Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-05T06:32:48.257954+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-05T06:32:48.257954+00:00","source":"crossref"},{"observed_at":"2026-08-05T06:32:44.755628+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":"2026-06-05T21:23:00.469572Z","title":"Vggface2: A dataset for recognising faces across pose and age","venue":null,"work_id":"8349c9f5-ce4d-430d-96c2-84a8c82121eb","year":2018},"citing_paper":{"arxiv_id":"2504.18015","last_updated":"2026-05-01T02:03:47Z","snapshot_observed_at":"2026-08-02T11:34:45.251281Z","submitted_at":"2025-04-25T01:53:27Z","title":"DiffMI: Breaking Face Recognition Privacy via Diffusion-Driven Training-Free Model Inversion","version":4},"reference_index":46,"source":"pdf_text","source_observed_at":"2026-05-22T18:46:35.684340Z"},"links":{"citing_paper":"/paper/2504.18015"},"observation_digest":"sha256:93719f9dbe8a6ef89a37f46e913296d0f5f1e7fe8c2595bea1db2d8b424a2617","observation_id":"8152fa01-efe7-4378-a5e6-58f16ab00b75","resolution":{"observed_at":"2026-05-22T18:47:04.653665Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-05T06:32:48.257954+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-05T06:32:48.257954+00:00","source":"crossref"},{"observed_at":"2026-08-05T06:32:44.755628+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":"2026-06-05T21:23:00.469572Z","title":"Ms-celeb-1m: A dataset and benchmark for large-scale face recognition","venue":null,"work_id":"6cf90b94-8043-479c-972c-85ad389fb7d8","year":2016},"citing_paper":{"arxiv_id":"2504.18015","last_updated":"2026-05-01T02:03:47Z","snapshot_observed_at":"2026-08-02T11:34:45.251281Z","submitted_at":"2025-04-25T01:53:27Z","title":"DiffMI: Breaking Face Recognition Privacy via Diffusion-Driven Training-Free Model Inversion","version":4},"reference_index":47,"source":"pdf_text","source_observed_at":"2026-05-22T18:46:35.684340Z"},"links":{"citing_paper":"/paper/2504.18015"},"observation_digest":"sha256:4857cee2182229fc5057389fbc8e66c1894204986f47a41563c26763d578715a","observation_id":"b80a2ef7-7148-47b4-9c31-44d2a6c70d86","resolution":{"observed_at":"2026-05-22T18:47:04.773329Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-05T06:32:48.257954+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-05T06:32:48.257954+00:00","source":"crossref"},{"observed_at":"2026-08-05T06:32:44.755628+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":"2026-06-05T21:23:00.469572Z","title":"A style-based generator architecture for generative adversarial networks","venue":null,"work_id":"e707cd67-23cb-4d21-817a-55ea3c3d5370","year":2019},"citing_paper":{"arxiv_id":"2504.18015","last_updated":"2026-05-01T02:03:47Z","snapshot_observed_at":"2026-08-02T11:34:45.251281Z","submitted_at":"2025-04-25T01:53:27Z","title":"DiffMI: Breaking Face Recognition Privacy via Diffusion-Driven Training-Free Model Inversion","version":4},"reference_index":48,"source":"pdf_text","source_observed_at":"2026-05-22T18:46:35.684340Z"},"links":{"citing_paper":"/paper/2504.18015"},"observation_digest":"sha256:2d43c06dc939647e66a622831edba9313e1802120f6b9d0cad1f02e3add612ef","observation_id":"42659101-0e0a-4c63-b656-94e9a438cfd3","resolution":{"observed_at":"2026-05-22T18:47:04.658646Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-05T06:32:48.257954+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-05T06:32:48.257954+00:00","source":"crossref"},{"observed_at":"2026-08-05T06:32:44.755628+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":"2026-06-05T21:23:00.469572Z","title":"Square attack: a query-efficient black-box adversarial attack via random search","venue":null,"work_id":"9075099d-03fa-45eb-bc74-4cc994bc9b05","year":2020},"citing_paper":{"arxiv_id":"2504.18015","last_updated":"2026-05-01T02:03:47Z","snapshot_observed_at":"2026-08-02T11:34:45.251281Z","submitted_at":"2025-04-25T01:53:27Z","title":"DiffMI: Breaking Face Recognition Privacy via Diffusion-Driven Training-Free Model Inversion","version":4},"reference_index":49,"source":"pdf_text","source_observed_at":"2026-05-22T18:46:35.684340Z"},"links":{"citing_paper":"/paper/2504.18015"},"observation_digest":"sha256:9d9b7556f283db5e17aa28dc9fd89bce479bfcb856b4e8287d8ee1efe827ff0a","observation_id":"a34958fc-056a-4c25-b534-c600287b3cbb","resolution":{"observed_at":"2026-05-22T18:47:04.664998Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-05T06:32:48.257954+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-05T06:32:48.257954+00:00","source":"crossref"},{"observed_at":"2026-08-05T06:32:44.755628+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":"2026-06-05T21:23:00.469572Z","title":"Brusleattack: Query- efficient score-based sparse adversarial attack","venue":null,"work_id":"7ef46e34-589f-4450-ae1e-aa592b6083ad","year":2024},"citing_paper":{"arxiv_id":"2504.18015","last_updated":"2026-05-01T02:03:47Z","snapshot_observed_at":"2026-08-02T11:34:45.251281Z","submitted_at":"2025-04-25T01:53:27Z","title":"DiffMI: Breaking Face Recognition Privacy via Diffusion-Driven Training-Free Model Inversion","version":4},"reference_index":50,"source":"pdf_text","source_observed_at":"2026-05-22T18:46:35.684340Z"},"links":{"citing_paper":"/paper/2504.18015"},"observation_digest":"sha256:f70040a1139531a09f97d2e28e584ec5075a871cb076bba39658fb573b24aaa3","observation_id":"7b10a633-a23a-49ea-ad1d-543f94cb6fcb","resolution":{"observed_at":"2026-05-22T18:47:04.681820Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-05T06:32:48.257954+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-05T06:32:48.257954+00:00","source":"crossref"},{"observed_at":"2026-08-05T06:32:44.755628+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":"2026-06-05T21:23:00.469572Z","title":"Billions of logins for apple, google, facebook, telegram, and more found exposed online","venue":null,"work_id":"d7905203-ffa8-403c-a0b6-9baac364eb66","year":2025},"citing_paper":{"arxiv_id":"2504.18015","last_updated":"2026-05-01T02:03:47Z","snapshot_observed_at":"2026-08-02T11:34:45.251281Z","submitted_at":"2025-04-25T01:53:27Z","title":"DiffMI: Breaking Face Recognition Privacy via Diffusion-Driven Training-Free Model Inversion","version":4},"reference_index":51,"source":"pdf_text","source_observed_at":"2026-05-22T18:46:35.684340Z"},"links":{"citing_paper":"/paper/2504.18015"},"observation_digest":"sha256:1739716cc1a312292f6e7c39570061fdafed68bb5a1497b6a3bcf2b859acaebf","observation_id":"0881c0ef-a08b-42d8-8f73-8a7f76f713ae","resolution":{"observed_at":"2026-05-22T18:47:04.677297Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-05T06:32:48.257954+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-05T06:32:48.257954+00:00","source":"crossref"},{"observed_at":"2026-08-05T06:32:44.755628+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":"2026-06-05T21:23:00.469572Z","title":"Similarity-based gray-box adversarial attack against deep face recogni- tion","venue":null,"work_id":"d185eca1-25c3-4320-bdc5-4e0fe69c274a","year":2021},"citing_paper":{"arxiv_id":"2504.18015","last_updated":"2026-05-01T02:03:47Z","snapshot_observed_at":"2026-08-02T11:34:45.251281Z","submitted_at":"2025-04-25T01:53:27Z","title":"DiffMI: Breaking Face Recognition Privacy via Diffusion-Driven Training-Free Model Inversion","version":4},"reference_index":52,"source":"pdf_text","source_observed_at":"2026-05-22T18:46:35.684340Z"},"links":{"citing_paper":"/paper/2504.18015"},"observation_digest":"sha256:b85f4a2c1df33d346774eecf1a4902d4eb74b170f13e97c4f329ca4d2d50c916","observation_id":"e9a6a0f3-1c5f-4246-bc11-ff8e121a09df","resolution":{"observed_at":"2026-05-22T18:47:04.671878Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-05T06:32:48.257954+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-05T06:32:48.257954+00:00","source":"crossref"},{"observed_at":"2026-08-05T06:32:44.755628+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":"2026-06-05T21:23:00.469572Z","title":"A multi- task adversarial attack against face authentication","venue":null,"work_id":"1180e4d3-5831-489c-8952-f58f89584b90","year":2024},"citing_paper":{"arxiv_id":"2504.18015","last_updated":"2026-05-01T02:03:47Z","snapshot_observed_at":"2026-08-02T11:34:45.251281Z","submitted_at":"2025-04-25T01:53:27Z","title":"DiffMI: Breaking Face Recognition Privacy via Diffusion-Driven Training-Free Model Inversion","version":4},"reference_index":53,"source":"pdf_text","source_observed_at":"2026-05-22T18:46:35.684340Z"},"links":{"citing_paper":"/paper/2504.18015"},"observation_digest":"sha256:30f61e5b50eb48b2e6c9b589c040168781485b993f8199de19f7c9a27f075b01","observation_id":"41ed034f-9599-4ae1-99dd-f3785d4712ee","resolution":{"observed_at":"2026-05-22T18:47:04.629033Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-05T06:32:48.257954+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-05T06:32:48.257954+00:00","source":"crossref"},{"observed_at":"2026-08-05T06:32:44.755628+00:00","source":"retraction_watch"}],"state":"measured"}}],"paper":{"arxiv_id":"2504.18015","last_updated":"2026-05-01T02:03:47Z","latest_version":4,"primary_category":"cs.CR","snapshot_observed_at":"2026-08-02T11:34:45.251281Z","submitted_at":"2025-04-25T01:53:27Z","title":"DiffMI: Breaking Face Recognition Privacy via Diffusion-Driven Training-Free Model Inversion"},"reference_resolution":{"displayed":53,"state_counts":{"malformed_identifier":0,"metadata_mismatch":0,"parse_uncertain":0,"unresolved":1,"verified_exact":1,"verified_fuzzy":51},"total_outbound_references":53},"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":"2026-08-05T06:32:48.257954+00:00","source":"crossref"},{"observed_at":"2026-08-05T06:32:44.755628+00:00","source":"retraction_watch"}],"thesis":"As of 5 August 2026, this Paper Citation Record lists 53 of 53 outbound references and 2 inbound Pith citation observations for arXiv:2504.18015."}