{"as_of":"2026-08-14T23:54:00Z","caps":{"database_statements":6,"inbound":100,"outbound":100},"context_digest":"sha256:8c2f80c7ae505bc753e3b433a312c1c8f04be5933a616a683ef2f1b698f1c331","coverage":[{"denominator":61,"lane":"reference_resolution","note":"Typed states for the displayed outbound observations.","records_observed":61,"source":"paper_references, paper_reference_links","source_observed_at":"2026-08-10T20:33:11.000621Z","state":"measured"},{"denominator":61,"lane":"standing_notices","note":"One-hop event checks from named stored sources.","records_observed":61,"source":"scholarly_work_events, retraction_status_cache","source_observed_at":"2026-08-14T06:32:32.682623+00:00","state":"measured"},{"denominator":0,"lane":"inbound_itemization","note":"Pith citing papers itemized under the disclosed page cap.","records_observed":0,"source":"paper_references, paper_reference_links","source_observed_at":null,"state":"measured"},{"denominator":1,"lane":"external_citation_measurements","note":"A source-named dated measurement, never combined with another source.","records_observed":0,"source":"cited_works","source_observed_at":null,"state":"measured"}],"external_citation_measurements":[],"inbound":[],"links":{"evidence":"/evidence","html":"/paper/2501.08258/citation-record","integrity":"/paper/2501.08258/integrity","json":"/paper/2501.08258/citation-record.json","paper":"/paper/2501.08258"},"outbound":[{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-10T20:33:12.031161Z","title":"Enhanc- ing object detection in smart video surveillance: A survey of occlusion-handling approaches,","venue":null,"work_id":"8924170d-a103-4377-ac76-d29b540f40fb","year":2024},"citing_paper":{"arxiv_id":"2501.08258","last_updated":"2025-01-16T10:55:41Z","snapshot_observed_at":"2026-08-14T11:47:29.738378Z","submitted_at":"2025-01-14T17:10:02Z","title":"Towards an End-to-End (E2E) Adversarial Learning and Application in the Physical World","version":2},"reference_index":1,"source":"pdf_text","source_observed_at":"2026-08-10T20:33:10.700594Z"},"links":{"citing_paper":"/paper/2501.08258"},"observation_digest":"sha256:8c1298b3cec61ad3143d222bfcc8703a8c3e9c61b995a21c26ed7f74a7ac1c85","observation_id":"78267256-017d-4aa4-90f8-81dc60e6dd8e","resolution":{"observed_at":"2026-08-10T20:33:12.036326Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-14T06:32:32.682623+00:00","source":"crossref"},{"observed_at":"2026-08-14T06:32:18.44784+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":"2026-08-10T20:33:12.015321Z","title":"Automatic number plate recognition: A detailed survey of relevant algo- rithms,","venue":null,"work_id":"1943fcf1-9432-4017-9d00-69553acb3446","year":2021},"citing_paper":{"arxiv_id":"2501.08258","last_updated":"2025-01-16T10:55:41Z","snapshot_observed_at":"2026-08-14T11:47:29.738378Z","submitted_at":"2025-01-14T17:10:02Z","title":"Towards an End-to-End (E2E) Adversarial Learning and Application in the Physical World","version":2},"reference_index":2,"source":"pdf_text","source_observed_at":"2026-08-10T20:33:10.705963Z"},"links":{"citing_paper":"/paper/2501.08258"},"observation_digest":"sha256:9b72896c305fc0de513c23c23b2e389a9729b7204452a12b3260fecb47d88320","observation_id":"c0867823-cbdd-4bde-8aba-00f4661d14a1","resolution":{"observed_at":"2026-08-10T20:33:12.020801Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-14T06:32:32.682623+00:00","source":"crossref"},{"observed_at":"2026-08-14T06:32:18.44784+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":"2026-08-10T20:33:12.000082Z","title":"Deep learning meth- ods for object detection in autonomous vehicles,","venue":null,"work_id":"27c899aa-ca7e-4517-a7d3-39c9eab94972","year":2021},"citing_paper":{"arxiv_id":"2501.08258","last_updated":"2025-01-16T10:55:41Z","snapshot_observed_at":"2026-08-14T11:47:29.738378Z","submitted_at":"2025-01-14T17:10:02Z","title":"Towards an End-to-End (E2E) Adversarial Learning and Application in the Physical World","version":2},"reference_index":3,"source":"pdf_text","source_observed_at":"2026-08-10T20:33:10.710615Z"},"links":{"citing_paper":"/paper/2501.08258"},"observation_digest":"sha256:8eb86075702895d3d6a01df34f11be68cd3ebe2cc4eae82219d156cca183ae3b","observation_id":"02bb3d08-92fd-487d-87de-2bdde3a74dec","resolution":{"observed_at":"2026-08-10T20:33:12.004814Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-14T06:32:32.682623+00:00","source":"crossref"},{"observed_at":"2026-08-14T06:32:18.44784+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":"2026-08-10T20:33:11.984635Z","title":"Naturalistic physical ad- versarial patch for object detectors,","venue":null,"work_id":"ec310d73-e7c7-4941-86d7-7b49c52b363e","year":2021},"citing_paper":{"arxiv_id":"2501.08258","last_updated":"2025-01-16T10:55:41Z","snapshot_observed_at":"2026-08-14T11:47:29.738378Z","submitted_at":"2025-01-14T17:10:02Z","title":"Towards an End-to-End (E2E) Adversarial Learning and Application in the Physical World","version":2},"reference_index":4,"source":"pdf_text","source_observed_at":"2026-08-10T20:33:10.715690Z"},"links":{"citing_paper":"/paper/2501.08258"},"observation_digest":"sha256:f7e453e6cfa83b5388f05492026c9624243ca408ad41399bffa1c13ac3df9c36","observation_id":"79de64b5-6cf0-4b26-8fea-8746a25b7c72","resolution":{"observed_at":"2026-08-10T20:33:11.989388Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-14T06:32:32.682623+00:00","source":"crossref"},{"observed_at":"2026-08-14T06:32:18.44784+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":"2026-08-10T20:33:11.968449Z","title":"Hop- skipjumpattack: A query-efficient decision-based attack,","venue":null,"work_id":"644d4ce2-d079-4be6-a043-b1a0a033e618","year":2020},"citing_paper":{"arxiv_id":"2501.08258","last_updated":"2025-01-16T10:55:41Z","snapshot_observed_at":"2026-08-14T11:47:29.738378Z","submitted_at":"2025-01-14T17:10:02Z","title":"Towards an End-to-End (E2E) Adversarial Learning and Application in the Physical World","version":2},"reference_index":5,"source":"pdf_text","source_observed_at":"2026-08-10T20:33:10.720198Z"},"links":{"citing_paper":"/paper/2501.08258"},"observation_digest":"sha256:fa29ce8c15422e7b0c524ce477635e79c8b2eead218b648ccf9dbdeb48a4f078","observation_id":"c8888f05-831a-4285-99d9-d911534c5b68","resolution":{"observed_at":"2026-08-10T20:33:11.973911Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-14T06:32:32.682623+00:00","source":"crossref"},{"observed_at":"2026-08-14T06:32:18.44784+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":"2026-08-10T20:33:11.951452Z","title":"Simple black-box adversarial attacks,","venue":null,"work_id":"c491bf60-6feb-45e5-ac0a-3008a31a2a14","year":2019},"citing_paper":{"arxiv_id":"2501.08258","last_updated":"2025-01-16T10:55:41Z","snapshot_observed_at":"2026-08-14T11:47:29.738378Z","submitted_at":"2025-01-14T17:10:02Z","title":"Towards an End-to-End (E2E) Adversarial Learning and Application in the Physical World","version":2},"reference_index":6,"source":"pdf_text","source_observed_at":"2026-08-10T20:33:10.724737Z"},"links":{"citing_paper":"/paper/2501.08258"},"observation_digest":"sha256:d164664c49f445eee22dc28270f7899835f53600e27abcf1c514e4c1a61e1fd0","observation_id":"1dc519d1-927c-4392-a981-b07fa9d9c5fa","resolution":{"observed_at":"2026-08-10T20:33:11.956934Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-14T06:32:32.682623+00:00","source":"crossref"},{"observed_at":"2026-08-14T06:32:18.44784+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"1712.04248","last_updated":"2018-02-16T14:40:42Z","snapshot_observed_at":"2026-08-14T20:04:31.854470Z","submitted_at":"2017-12-12T11:36:26Z","title":"Decision-Based Adversarial Attacks: Reliable Attacks Against Black-Box Machine Learning Models","version":2},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"1712.04248","snapshot_observed_at":"2026-08-10T20:33:10.729674Z","title":"Decision- based adversarial attacks: Reliable attacks against black-box machine learning models,","venue":null,"work_id":null,"year":2017},"citing_paper":{"arxiv_id":"2501.08258","last_updated":"2025-01-16T10:55:41Z","snapshot_observed_at":"2026-08-14T11:47:29.738378Z","submitted_at":"2025-01-14T17:10:02Z","title":"Towards an End-to-End (E2E) Adversarial Learning and Application in the Physical World","version":2},"reference_index":7,"source":"pdf_text","source_observed_at":"2026-08-10T20:33:10.729674Z"},"links":{"cited_paper":"/paper/1712.04248","citing_paper":"/paper/2501.08258"},"observation_digest":"sha256:60559c1e68252a80d11d2958558ce5c94041c43573fce0af2c0925482f513305","observation_id":"e62eb51d-515d-47f6-8fd5-98b674a5bf5c","resolution":{"observed_at":"2026-08-10T20:33:10.729674Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"1707.07397","last_updated":"2018-06-07T16:25:12Z","snapshot_observed_at":"2026-08-14T20:45:49.587140Z","submitted_at":"2017-07-24T04:17:33Z","title":"Synthesizing Robust Adversarial Examples","version":3},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"1707.07397","snapshot_observed_at":"2026-08-10T20:33:10.734328Z","title":"Synthesizing robust adversarial examples,","venue":null,"work_id":null,"year":2018},"citing_paper":{"arxiv_id":"2501.08258","last_updated":"2025-01-16T10:55:41Z","snapshot_observed_at":"2026-08-14T11:47:29.738378Z","submitted_at":"2025-01-14T17:10:02Z","title":"Towards an End-to-End (E2E) Adversarial Learning and Application in the Physical World","version":2},"reference_index":8,"source":"pdf_text","source_observed_at":"2026-08-10T20:33:10.734328Z"},"links":{"cited_paper":"/paper/1707.07397","citing_paper":"/paper/2501.08258"},"observation_digest":"sha256:053c209099d91f27f1d545ca2dbb4f058b393afde2f0f190e58ef8bd1b9aabfa","observation_id":"887b6d10-c300-4114-a53d-371e61b9b559","resolution":{"observed_at":"2026-08-10T20:33:10.734328Z","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":"2026-08-10T20:33:11.934946Z","title":"Phys- 14 ical adversarial examples for object detectors,","venue":null,"work_id":"9b8747c8-6a6b-4f12-9dda-c1d50cda8c8b","year":2018},"citing_paper":{"arxiv_id":"2501.08258","last_updated":"2025-01-16T10:55:41Z","snapshot_observed_at":"2026-08-14T11:47:29.738378Z","submitted_at":"2025-01-14T17:10:02Z","title":"Towards an End-to-End (E2E) Adversarial Learning and Application in the Physical World","version":2},"reference_index":9,"source":"pdf_text","source_observed_at":"2026-08-10T20:33:10.739102Z"},"links":{"citing_paper":"/paper/2501.08258"},"observation_digest":"sha256:66dd3adfe769c1499182831dca8a7e887dd262ad0deb5775f0878b98d1fb31ee","observation_id":"eb3e3aea-0c4a-41eb-a9e1-0d202ec7be3c","resolution":{"observed_at":"2026-08-10T20:33:11.940180Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-14T06:32:32.682623+00:00","source":"crossref"},{"observed_at":"2026-08-14T06:32:18.44784+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"1906.11897","last_updated":"2019-06-20T11:04:57Z","snapshot_observed_at":"2026-08-13T18:17:41.806260Z","submitted_at":"2019-06-20T11:04:57Z","title":"On Physical Adversarial Patches for Object Detection","version":1},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"1906.11897","snapshot_observed_at":"2026-08-10T20:33:10.744310Z","title":"On physical adversarial patches for object detection,","venue":null,"work_id":null,"year":1906},"citing_paper":{"arxiv_id":"2501.08258","last_updated":"2025-01-16T10:55:41Z","snapshot_observed_at":"2026-08-14T11:47:29.738378Z","submitted_at":"2025-01-14T17:10:02Z","title":"Towards an End-to-End (E2E) Adversarial Learning and Application in the Physical World","version":2},"reference_index":10,"source":"pdf_text","source_observed_at":"2026-08-10T20:33:10.744310Z"},"links":{"cited_paper":"/paper/1906.11897","citing_paper":"/paper/2501.08258"},"observation_digest":"sha256:4254e9e7c1181fb79cad2509fd67064e78d87c00c2df041e17718db44a36363b","observation_id":"eb659320-9df5-4893-9bf9-f7b698aa5928","resolution":{"observed_at":"2026-08-10T20:33:10.744310Z","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":"2026-08-10T20:33:11.919549Z","title":"Robust physical-world attacks on deep learning visual classification,","venue":null,"work_id":"e3b7bd75-d13c-4154-8715-d2499ea8968d","year":2018},"citing_paper":{"arxiv_id":"2501.08258","last_updated":"2025-01-16T10:55:41Z","snapshot_observed_at":"2026-08-14T11:47:29.738378Z","submitted_at":"2025-01-14T17:10:02Z","title":"Towards an End-to-End (E2E) Adversarial Learning and Application in the Physical World","version":2},"reference_index":11,"source":"pdf_text","source_observed_at":"2026-08-10T20:33:10.750034Z"},"links":{"citing_paper":"/paper/2501.08258"},"observation_digest":"sha256:db5a79e56356e82ce67a8bc0a934e6b3dbf3a50d988d3f02fe3aa16d0f4b5cd1","observation_id":"40a44acc-7346-4e31-bd95-721a274baa85","resolution":{"observed_at":"2026-08-10T20:33:11.924585Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-14T06:32:32.682623+00:00","source":"crossref"},{"observed_at":"2026-08-14T06:32:18.44784+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":"2026-08-10T20:33:11.903052Z","title":"Adversarialeak: External information leak- age attack using adversarial samples on face recognition systems,","venue":null,"work_id":"f8c7924f-c1f0-4e00-ac01-72a3b841094f","year":2025},"citing_paper":{"arxiv_id":"2501.08258","last_updated":"2025-01-16T10:55:41Z","snapshot_observed_at":"2026-08-14T11:47:29.738378Z","submitted_at":"2025-01-14T17:10:02Z","title":"Towards an End-to-End (E2E) Adversarial Learning and Application in the Physical World","version":2},"reference_index":12,"source":"pdf_text","source_observed_at":"2026-08-10T20:33:10.755036Z"},"links":{"citing_paper":"/paper/2501.08258"},"observation_digest":"sha256:d76c9c80a21fc1e5b4b81050a29a35d002ebe10e4fc349c7c93128fdd1f5f5de","observation_id":"7114ed83-f7df-48fa-b4f2-31becccb9ef9","resolution":{"observed_at":"2026-08-10T20:33:11.908486Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-14T06:32:32.682623+00:00","source":"crossref"},{"observed_at":"2026-08-14T06:32:18.44784+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":"2026-08-10T20:33:11.886542Z","title":"Shapeshifter: Robust physical adversarial attack on faster r-cnn object detector,","venue":null,"work_id":"855a26ea-f5ca-4dc3-9774-cf9ed96245f3","year":2018},"citing_paper":{"arxiv_id":"2501.08258","last_updated":"2025-01-16T10:55:41Z","snapshot_observed_at":"2026-08-14T11:47:29.738378Z","submitted_at":"2025-01-14T17:10:02Z","title":"Towards an End-to-End (E2E) Adversarial Learning and Application in the Physical World","version":2},"reference_index":13,"source":"pdf_text","source_observed_at":"2026-08-10T20:33:10.760023Z"},"links":{"citing_paper":"/paper/2501.08258"},"observation_digest":"sha256:99be919cda84864c7d897c301fdc72f8aa098287906732b2c80cf08b337a9a42","observation_id":"36275dc0-0a3a-43e1-aa24-f7d56d94de0b","resolution":{"observed_at":"2026-08-10T20:33:11.892001Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-14T06:32:32.682623+00:00","source":"crossref"},{"observed_at":"2026-08-14T06:32:18.44784+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"1806.02299","last_updated":"2019-04-23T16:44:32Z","snapshot_observed_at":"2026-08-14T19:07:14.084742Z","submitted_at":"2018-06-05T17:04:37Z","title":"DPatch: An Adversarial Patch Attack on Object Detectors","version":4},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"1806.02299","snapshot_observed_at":"2026-08-10T20:33:10.765118Z","title":"Dpatch: An adversarial patch attack on object detec- tors,","venue":null,"work_id":null,"year":2018},"citing_paper":{"arxiv_id":"2501.08258","last_updated":"2025-01-16T10:55:41Z","snapshot_observed_at":"2026-08-14T11:47:29.738378Z","submitted_at":"2025-01-14T17:10:02Z","title":"Towards an End-to-End (E2E) Adversarial Learning and Application in the Physical World","version":2},"reference_index":14,"source":"pdf_text","source_observed_at":"2026-08-10T20:33:10.765118Z"},"links":{"cited_paper":"/paper/1806.02299","citing_paper":"/paper/2501.08258"},"observation_digest":"sha256:dae3089a54579f5ffcea298eaf95f2474ec6ae8920165c039957d562fe9b44eb","observation_id":"ef45cd5e-8c31-4b55-ab7e-46bdf8e7d8ee","resolution":{"observed_at":"2026-08-10T20:33:10.765118Z","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":"2026-08-10T20:33:11.870339Z","title":"Camou: Learning physical vehicle camouflages to adversarially attack detectors in the wild,","venue":null,"work_id":"95aeb9cb-c5bb-4b2e-be79-43beae26c94c","year":2018},"citing_paper":{"arxiv_id":"2501.08258","last_updated":"2025-01-16T10:55:41Z","snapshot_observed_at":"2026-08-14T11:47:29.738378Z","submitted_at":"2025-01-14T17:10:02Z","title":"Towards an End-to-End (E2E) Adversarial Learning and Application in the Physical World","version":2},"reference_index":15,"source":"pdf_text","source_observed_at":"2026-08-10T20:33:10.770268Z"},"links":{"citing_paper":"/paper/2501.08258"},"observation_digest":"sha256:bd16162a2c7e65ec5e63fb28bab1534a38fb52680fae843a2dbaee03a746221f","observation_id":"611762b1-a5a7-4d86-ba9a-56fe15e46392","resolution":{"observed_at":"2026-08-10T20:33:11.875710Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-14T06:32:32.682623+00:00","source":"crossref"},{"observed_at":"2026-08-14T06:32:18.44784+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":"2026-08-10T20:33:11.854470Z","title":"Fooling automated surveillance cameras: adversarial patches to attack person detection,","venue":null,"work_id":"13ad5c25-58c2-4fc9-ac7f-11b1676767fb","year":2019},"citing_paper":{"arxiv_id":"2501.08258","last_updated":"2025-01-16T10:55:41Z","snapshot_observed_at":"2026-08-14T11:47:29.738378Z","submitted_at":"2025-01-14T17:10:02Z","title":"Towards an End-to-End (E2E) Adversarial Learning and Application in the Physical World","version":2},"reference_index":16,"source":"pdf_text","source_observed_at":"2026-08-10T20:33:10.775066Z"},"links":{"citing_paper":"/paper/2501.08258"},"observation_digest":"sha256:7050df74980ea7221a32f5cafbe47507f51f8fd491e01ed2309655a4bb80742b","observation_id":"31e541cb-e035-42aa-b316-23d425778658","resolution":{"observed_at":"2026-08-10T20:33:11.859672Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-14T06:32:32.682623+00:00","source":"crossref"},{"observed_at":"2026-08-14T06:32:18.44784+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":"2026-08-10T20:33:11.838570Z","title":"Adversarial t-shirt! evading person detectors in a physical world,","venue":null,"work_id":"b90c844e-2225-443e-b4a8-ef974eaafa47","year":2020},"citing_paper":{"arxiv_id":"2501.08258","last_updated":"2025-01-16T10:55:41Z","snapshot_observed_at":"2026-08-14T11:47:29.738378Z","submitted_at":"2025-01-14T17:10:02Z","title":"Towards an End-to-End (E2E) Adversarial Learning and Application in the Physical World","version":2},"reference_index":17,"source":"pdf_text","source_observed_at":"2026-08-10T20:33:10.779564Z"},"links":{"citing_paper":"/paper/2501.08258"},"observation_digest":"sha256:d7416a1b4dcdcc913d43cd33b9cf196ca67f5e761d42d3378fc39d3a0a3bb2b5","observation_id":"208055f8-d4bf-4e7b-9633-9c0a2681230e","resolution":{"observed_at":"2026-08-10T20:33:11.844005Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-14T06:32:32.682623+00:00","source":"crossref"},{"observed_at":"2026-08-14T06:32:18.44784+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":"2026-08-10T20:33:11.823924Z","title":null,"venue":null,"work_id":"0992f3ad-aecc-413c-b11e-79505d4ffdf5","year":2020},"citing_paper":{"arxiv_id":"2501.08258","last_updated":"2025-01-16T10:55:41Z","snapshot_observed_at":"2026-08-14T11:47:29.738378Z","submitted_at":"2025-01-14T17:10:02Z","title":"Towards an End-to-End (E2E) Adversarial Learning and Application in the Physical World","version":2},"reference_index":18,"source":"pdf_text","source_observed_at":"2026-08-10T20:33:10.784445Z"},"links":{"citing_paper":"/paper/2501.08258"},"observation_digest":"sha256:4a3a09ef875591e048ccb74c356445a5d45220625d0239fe0d09261917e67e76","observation_id":"94019f5d-315e-454e-9ad8-46c567313c29","resolution":{"observed_at":"2026-08-10T20:33:11.828560Z","resolver_source":"raw_fallback","status":"unresolved"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-14T06:32:32.682623+00:00","source":"crossref"},{"observed_at":"2026-08-14T06:32:18.44784+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":"2026-08-10T20:33:11.809257Z","title":"Universal physical camouflage attacks on object detectors,","venue":null,"work_id":"20fb38ba-51c8-4e8f-a407-1bcab5c5b5d9","year":2020},"citing_paper":{"arxiv_id":"2501.08258","last_updated":"2025-01-16T10:55:41Z","snapshot_observed_at":"2026-08-14T11:47:29.738378Z","submitted_at":"2025-01-14T17:10:02Z","title":"Towards an End-to-End (E2E) Adversarial Learning and Application in the Physical World","version":2},"reference_index":19,"source":"pdf_text","source_observed_at":"2026-08-10T20:33:10.789213Z"},"links":{"citing_paper":"/paper/2501.08258"},"observation_digest":"sha256:ddad745fc6067e731bcf8e556b9c75a6c5ba295988e3c9a87ee15e5842a9b592","observation_id":"96e0d0c6-91b5-46f3-8667-53d4b96de067","resolution":{"observed_at":"2026-08-10T20:33:11.813869Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-14T06:32:32.682623+00:00","source":"crossref"},{"observed_at":"2026-08-14T06:32:18.44784+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":"2026-08-10T20:33:11.793215Z","title":"Mak- ing an invisibility cloak: Real world adversarial attacks on object detectors,","venue":null,"work_id":"08b11ee5-005a-41d6-b3c1-215da0e13ffe","year":2020},"citing_paper":{"arxiv_id":"2501.08258","last_updated":"2025-01-16T10:55:41Z","snapshot_observed_at":"2026-08-14T11:47:29.738378Z","submitted_at":"2025-01-14T17:10:02Z","title":"Towards an End-to-End (E2E) Adversarial Learning and Application in the Physical World","version":2},"reference_index":20,"source":"pdf_text","source_observed_at":"2026-08-10T20:33:10.794294Z"},"links":{"citing_paper":"/paper/2501.08258"},"observation_digest":"sha256:ec970b8c604749736f16b3f079b46a5ce1b572533db8f6b654de1b75f90a6898","observation_id":"6b450b26-a312-4216-8a0f-f51cee4db456","resolution":{"observed_at":"2026-08-10T20:33:11.798560Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-14T06:32:32.682623+00:00","source":"crossref"},{"observed_at":"2026-08-14T06:32:18.44784+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":"2026-08-10T20:33:11.775858Z","title":"The translucent patch: A physical and universal attack on object detectors,","venue":null,"work_id":"61fce233-6d75-4ee1-94f5-93c10cf48f2b","year":2021},"citing_paper":{"arxiv_id":"2501.08258","last_updated":"2025-01-16T10:55:41Z","snapshot_observed_at":"2026-08-14T11:47:29.738378Z","submitted_at":"2025-01-14T17:10:02Z","title":"Towards an End-to-End (E2E) Adversarial Learning and Application in the Physical World","version":2},"reference_index":21,"source":"pdf_text","source_observed_at":"2026-08-10T20:33:10.799071Z"},"links":{"citing_paper":"/paper/2501.08258"},"observation_digest":"sha256:32c0581edcff5c58686b8ba067ecb712d28c85d8b84e59c0d5144cc714b6ed41","observation_id":"2277cac1-7c05-4cad-8bc5-6367a8a8050b","resolution":{"observed_at":"2026-08-10T20:33:11.781539Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-14T06:32:32.682623+00:00","source":"crossref"},{"observed_at":"2026-08-14T06:32:18.44784+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":"2026-08-10T20:33:11.757920Z","title":"Too good to be safe: Tricking lane detection in autonomous driving with crafted perturbations,","venue":null,"work_id":"ebc3f01d-38c9-40aa-bee1-b77c529bf856","year":2021},"citing_paper":{"arxiv_id":"2501.08258","last_updated":"2025-01-16T10:55:41Z","snapshot_observed_at":"2026-08-14T11:47:29.738378Z","submitted_at":"2025-01-14T17:10:02Z","title":"Towards an End-to-End (E2E) Adversarial Learning and Application in the Physical World","version":2},"reference_index":22,"source":"pdf_text","source_observed_at":"2026-08-10T20:33:10.803716Z"},"links":{"citing_paper":"/paper/2501.08258"},"observation_digest":"sha256:e1071277322745c3f21218c8d9743e7caf53cbad56bfcee0dcb225e9d9e62d51","observation_id":"023a0262-444d-4c3f-b2f3-8f810bd87bed","resolution":{"observed_at":"2026-08-10T20:33:11.764006Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-14T06:32:32.682623+00:00","source":"crossref"},{"observed_at":"2026-08-14T06:32:18.44784+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":"2026-08-10T20:33:11.740696Z","title":"Legitimate adver- sarial patches: Evading human eyes and detection models in the physical world,","venue":null,"work_id":"c6720aa6-0bd6-4a2d-8718-950e35bb31b0","year":2021},"citing_paper":{"arxiv_id":"2501.08258","last_updated":"2025-01-16T10:55:41Z","snapshot_observed_at":"2026-08-14T11:47:29.738378Z","submitted_at":"2025-01-14T17:10:02Z","title":"Towards an End-to-End (E2E) Adversarial Learning and Application in the Physical World","version":2},"reference_index":23,"source":"pdf_text","source_observed_at":"2026-08-10T20:33:10.808495Z"},"links":{"citing_paper":"/paper/2501.08258"},"observation_digest":"sha256:21b85594b6ebbdcccd453330dbac394e960de57914213d355d3c345c6d223ee8","observation_id":"9cccfd70-e988-44eb-8568-1dfb57b1c851","resolution":{"observed_at":"2026-08-10T20:33:11.746120Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-14T06:32:32.682623+00:00","source":"crossref"},{"observed_at":"2026-08-14T06:32:18.44784+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":"2026-08-10T20:33:11.722661Z","title":"Dta: Physical camouflage attacks using differentiable transformation network,","venue":null,"work_id":"bbb00c01-ac89-4681-9832-e1a19c4b284b","year":2022},"citing_paper":{"arxiv_id":"2501.08258","last_updated":"2025-01-16T10:55:41Z","snapshot_observed_at":"2026-08-14T11:47:29.738378Z","submitted_at":"2025-01-14T17:10:02Z","title":"Towards an End-to-End (E2E) Adversarial Learning and Application in the Physical World","version":2},"reference_index":24,"source":"pdf_text","source_observed_at":"2026-08-10T20:33:10.813359Z"},"links":{"citing_paper":"/paper/2501.08258"},"observation_digest":"sha256:b85693e540098d49ddae151f9166c9cdf17b3e9a61623a4da2f80494c554838d","observation_id":"cd791041-49cd-4023-bee2-b103d26c3dd6","resolution":{"observed_at":"2026-08-10T20:33:11.728508Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-14T06:32:32.682623+00:00","source":"crossref"},{"observed_at":"2026-08-14T06:32:18.44784+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":"2026-08-10T20:33:11.705057Z","title":"Adversarial texture for fooling person detectors in the physical world,","venue":null,"work_id":"eff40b60-7e72-4d89-978a-f78408edf188","year":2022},"citing_paper":{"arxiv_id":"2501.08258","last_updated":"2025-01-16T10:55:41Z","snapshot_observed_at":"2026-08-14T11:47:29.738378Z","submitted_at":"2025-01-14T17:10:02Z","title":"Towards an End-to-End (E2E) Adversarial Learning and Application in the Physical World","version":2},"reference_index":25,"source":"pdf_text","source_observed_at":"2026-08-10T20:33:10.817922Z"},"links":{"citing_paper":"/paper/2501.08258"},"observation_digest":"sha256:c9b4cd7c269db77c0fb675b2ae1d4744422a53a6d2b6d729cfcb617e7857d4c9","observation_id":"ad820433-b15b-4fae-b19c-f47c495b7821","resolution":{"observed_at":"2026-08-10T20:33:11.710577Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-14T06:32:32.682623+00:00","source":"crossref"},{"observed_at":"2026-08-14T06:32:18.44784+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":"2026-08-10T20:33:11.687923Z","title":"The adversarial implications of variable-time inference,","venue":null,"work_id":"8164dd8d-f592-422f-9180-d855860ed284","year":2023},"citing_paper":{"arxiv_id":"2501.08258","last_updated":"2025-01-16T10:55:41Z","snapshot_observed_at":"2026-08-14T11:47:29.738378Z","submitted_at":"2025-01-14T17:10:02Z","title":"Towards an End-to-End (E2E) Adversarial Learning and Application in the Physical World","version":2},"reference_index":26,"source":"pdf_text","source_observed_at":"2026-08-10T20:33:10.822819Z"},"links":{"citing_paper":"/paper/2501.08258"},"observation_digest":"sha256:6c8495e84c78885ab1435a0c51619f172fc91af70b42e3e777a3afffa2736f1d","observation_id":"68d55338-b4b0-462d-b4fd-be4a240ce413","resolution":{"observed_at":"2026-08-10T20:33:11.693738Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-14T06:32:32.682623+00:00","source":"crossref"},{"observed_at":"2026-08-14T06:32:18.44784+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"2201.06192","last_updated":"2022-01-17T03:24:31Z","snapshot_observed_at":"2026-08-14T15:10:52.153867Z","submitted_at":"2022-01-17T03:24:31Z","title":"Fooling the Eyes of Autonomous Vehicles: Robust Physical Adversarial Examples Against Traffic Sign Recognition Systems","version":1},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2201.06192","snapshot_observed_at":"2026-08-10T20:33:10.827518Z","title":"Fooling the eyes of autonomous vehicles: Robust phys- ical adversarial examples against traffic sign recognition systems,","venue":null,"work_id":null,"year":2022},"citing_paper":{"arxiv_id":"2501.08258","last_updated":"2025-01-16T10:55:41Z","snapshot_observed_at":"2026-08-14T11:47:29.738378Z","submitted_at":"2025-01-14T17:10:02Z","title":"Towards an End-to-End (E2E) Adversarial Learning and Application in the Physical World","version":2},"reference_index":27,"source":"pdf_text","source_observed_at":"2026-08-10T20:33:10.827518Z"},"links":{"cited_paper":"/paper/2201.06192","citing_paper":"/paper/2501.08258"},"observation_digest":"sha256:70aa81089883a911d05acbb40d3f8bf3a427c5f350f639a75b54f483c804ed00","observation_id":"5fab0a44-1617-4e9c-ad78-0a191fb7c375","resolution":{"observed_at":"2026-08-10T20:33:10.827518Z","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":"2026-08-10T20:33:11.667313Z","title":"T-sea: Transfer-based self-ensemble attack on object detection,","venue":null,"work_id":"a4badbab-bae8-4a93-b7fe-7cd0d0b16edf","year":2023},"citing_paper":{"arxiv_id":"2501.08258","last_updated":"2025-01-16T10:55:41Z","snapshot_observed_at":"2026-08-14T11:47:29.738378Z","submitted_at":"2025-01-14T17:10:02Z","title":"Towards an End-to-End (E2E) Adversarial Learning and Application in the Physical World","version":2},"reference_index":28,"source":"pdf_text","source_observed_at":"2026-08-10T20:33:10.832823Z"},"links":{"citing_paper":"/paper/2501.08258"},"observation_digest":"sha256:5b429aa73fc9d1f946c21748a267f2269a7fb799d86ae294736d9a655cfd7227","observation_id":"fe3dde72-8c25-4d3c-915e-1733b248f076","resolution":{"observed_at":"2026-08-10T20:33:11.673094Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-14T06:32:32.682623+00:00","source":"crossref"},{"observed_at":"2026-08-14T06:32:18.44784+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":"2026-08-10T20:33:11.649802Z","title":"{TPatch}: A triggered physical adversarial patch,","venue":null,"work_id":"759f0686-1614-426e-9dca-e1d2d7ef4a08","year":2023},"citing_paper":{"arxiv_id":"2501.08258","last_updated":"2025-01-16T10:55:41Z","snapshot_observed_at":"2026-08-14T11:47:29.738378Z","submitted_at":"2025-01-14T17:10:02Z","title":"Towards an End-to-End (E2E) Adversarial Learning and Application in the Physical World","version":2},"reference_index":29,"source":"pdf_text","source_observed_at":"2026-08-10T20:33:10.837646Z"},"links":{"citing_paper":"/paper/2501.08258"},"observation_digest":"sha256:4f3a8d89b58e55674cc3159a57fdcf92e141abe7d3bc7c950ff1efb342021a18","observation_id":"6ad172a0-fc2e-45c2-8c3f-9bb7a35864b9","resolution":{"observed_at":"2026-08-10T20:33:11.654972Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-14T06:32:32.682623+00:00","source":"crossref"},{"observed_at":"2026-08-14T06:32:18.44784+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":"2026-08-10T20:33:11.633148Z","title":"Physically realizable natural-looking clothing textures evade person detectors via 3d modeling,","venue":null,"work_id":"b5fc7137-e40f-4d22-a606-fa8b526720cd","year":2023},"citing_paper":{"arxiv_id":"2501.08258","last_updated":"2025-01-16T10:55:41Z","snapshot_observed_at":"2026-08-14T11:47:29.738378Z","submitted_at":"2025-01-14T17:10:02Z","title":"Towards an End-to-End (E2E) Adversarial Learning and Application in the Physical World","version":2},"reference_index":30,"source":"pdf_text","source_observed_at":"2026-08-10T20:33:10.842602Z"},"links":{"citing_paper":"/paper/2501.08258"},"observation_digest":"sha256:fd8bba495c0a3e9aaaadc9fd2cab71bd1be540705a7081dcaf0255e0fa06eb47","observation_id":"874d77ce-2723-4da6-b473-080a2adb6568","resolution":{"observed_at":"2026-08-10T20:33:11.638108Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-14T06:32:32.682623+00:00","source":"crossref"},{"observed_at":"2026-08-14T06:32:18.44784+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":"2026-08-10T20:33:10.847640Z","title":"Dap: A dynamic adversarial patch for evading person detectors,","venue":null,"work_id":null,"year":2024},"citing_paper":{"arxiv_id":"2501.08258","last_updated":"2025-01-16T10:55:41Z","snapshot_observed_at":"2026-08-14T11:47:29.738378Z","submitted_at":"2025-01-14T17:10:02Z","title":"Towards an End-to-End (E2E) Adversarial Learning and Application in the Physical World","version":2},"reference_index":31,"source":"pdf_text","source_observed_at":"2026-08-10T20:33:10.847640Z"},"links":{"citing_paper":"/paper/2501.08258"},"observation_digest":"sha256:7290a7aaf008b5b4ac420a437c714f2b9efc5615875258eb9e53eb0ba3770383","observation_id":"238c20cf-75cf-46d8-8d3a-d6d52f30dc1d","resolution":{"observed_at":"2026-08-10T20:33:10.847640Z","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":"2026-08-10T20:33:11.607994Z","title":"Revisiting adversarial patches for designing camera-agnostic attacks against person detection,","venue":null,"work_id":"e4538a35-6bb9-487c-a231-fcfc218cfc34","year":null},"citing_paper":{"arxiv_id":"2501.08258","last_updated":"2025-01-16T10:55:41Z","snapshot_observed_at":"2026-08-14T11:47:29.738378Z","submitted_at":"2025-01-14T17:10:02Z","title":"Towards an End-to-End (E2E) Adversarial Learning and Application in the Physical World","version":2},"reference_index":32,"source":"pdf_text","source_observed_at":"2026-08-10T20:33:10.852850Z"},"links":{"citing_paper":"/paper/2501.08258"},"observation_digest":"sha256:f474b8ef993d2240a93b653d4965efefd2d10ed4c67754e1681e3371d5cc0757","observation_id":"fbf8a7b9-23c2-40d7-811c-1621a9eee7ab","resolution":{"observed_at":"2026-08-10T20:33:11.612812Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-14T06:32:32.682623+00:00","source":"crossref"},{"observed_at":"2026-08-14T06:32:18.44784+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":"2026-08-10T20:33:11.591315Z","title":"Full-distance evasion of pedestrian detectors in the physical world,","venue":null,"work_id":"f6d53ef6-fd7e-40c8-bf7a-3e868dcb3ac5","year":null},"citing_paper":{"arxiv_id":"2501.08258","last_updated":"2025-01-16T10:55:41Z","snapshot_observed_at":"2026-08-14T11:47:29.738378Z","submitted_at":"2025-01-14T17:10:02Z","title":"Towards an End-to-End (E2E) Adversarial Learning and Application in the Physical World","version":2},"reference_index":33,"source":"pdf_text","source_observed_at":"2026-08-10T20:33:10.857908Z"},"links":{"citing_paper":"/paper/2501.08258"},"observation_digest":"sha256:b4fb2067544a9c7030a355eae65aa3baae2781f099454f34ff3e0d888068f40a","observation_id":"ea9041d1-64f1-44b8-b1ca-a88e351acf70","resolution":{"observed_at":"2026-08-10T20:33:11.596853Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-14T06:32:32.682623+00:00","source":"crossref"},{"observed_at":"2026-08-14T06:32:18.44784+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":"2026-08-10T20:33:11.574136Z","title":"Infrared invisible clothing: Hiding from infrared detectors at multiple angles in real world,","venue":null,"work_id":"d17e50bd-8358-48df-8db3-f0c77a3112c2","year":2022},"citing_paper":{"arxiv_id":"2501.08258","last_updated":"2025-01-16T10:55:41Z","snapshot_observed_at":"2026-08-14T11:47:29.738378Z","submitted_at":"2025-01-14T17:10:02Z","title":"Towards an End-to-End (E2E) Adversarial Learning and Application in the Physical World","version":2},"reference_index":34,"source":"pdf_text","source_observed_at":"2026-08-10T20:33:10.863350Z"},"links":{"citing_paper":"/paper/2501.08258"},"observation_digest":"sha256:37e0b9ea19d23a46c8e6066feadac1cded22613ec7dfed68ca35683ddd1d7490","observation_id":"c6f02dad-2280-407c-9143-55c6dcc185de","resolution":{"observed_at":"2026-08-10T20:33:11.579906Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-14T06:32:32.682623+00:00","source":"crossref"},{"observed_at":"2026-08-14T06:32:18.44784+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":"2026-08-10T20:33:11.556538Z","title":"Hotcold block: Fooling thermal infrared detectors with a novel wearable design,","venue":null,"work_id":"abbb49bf-7eff-4359-8cb3-53210834ac9a","year":2023},"citing_paper":{"arxiv_id":"2501.08258","last_updated":"2025-01-16T10:55:41Z","snapshot_observed_at":"2026-08-14T11:47:29.738378Z","submitted_at":"2025-01-14T17:10:02Z","title":"Towards an End-to-End (E2E) Adversarial Learning and Application in the Physical World","version":2},"reference_index":35,"source":"pdf_text","source_observed_at":"2026-08-10T20:33:10.868203Z"},"links":{"citing_paper":"/paper/2501.08258"},"observation_digest":"sha256:8208bb61249bcec1c4c6d214706baae5f81bbf826eba26271436d9d884173760","observation_id":"9da5d09d-5f6e-4b8d-9b8e-fde1278f3e3e","resolution":{"observed_at":"2026-08-10T20:33:11.562894Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-14T06:32:32.682623+00:00","source":"crossref"},{"observed_at":"2026-08-14T06:32:18.44784+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":"2026-08-10T20:33:11.537665Z","title":"Infrared adversarial patches with learnable shapes and locations in the phys- ical world,","venue":null,"work_id":"84963e53-9d97-4816-9323-f37391df8065","year":1928},"citing_paper":{"arxiv_id":"2501.08258","last_updated":"2025-01-16T10:55:41Z","snapshot_observed_at":"2026-08-14T11:47:29.738378Z","submitted_at":"2025-01-14T17:10:02Z","title":"Towards an End-to-End (E2E) Adversarial Learning and Application in the Physical World","version":2},"reference_index":36,"source":"pdf_text","source_observed_at":"2026-08-10T20:33:10.874003Z"},"links":{"citing_paper":"/paper/2501.08258"},"observation_digest":"sha256:a7699cf29ae03655e22ce65b80d4073e551570fa5992dab0b71fef82f2c41d1b","observation_id":"fcece39a-9de4-43a1-b70e-6c5720a0880d","resolution":{"observed_at":"2026-08-10T20:33:11.543868Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-14T06:32:32.682623+00:00","source":"crossref"},{"observed_at":"2026-08-14T06:32:18.44784+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":"2026-08-10T20:33:11.520679Z","title":"Infrared adversarial car stickers,","venue":null,"work_id":"1bd04285-b110-470d-951d-d43277801451","year":2024},"citing_paper":{"arxiv_id":"2501.08258","last_updated":"2025-01-16T10:55:41Z","snapshot_observed_at":"2026-08-14T11:47:29.738378Z","submitted_at":"2025-01-14T17:10:02Z","title":"Towards an End-to-End (E2E) Adversarial Learning and Application in the Physical World","version":2},"reference_index":37,"source":"pdf_text","source_observed_at":"2026-08-10T20:33:10.878870Z"},"links":{"citing_paper":"/paper/2501.08258"},"observation_digest":"sha256:951968ee3b91bb1c912d0fb114a9e73a6f99965cfb680588bbce8b2caa4f1a53","observation_id":"ebe138b8-00da-4066-98fd-4bd5e065c98e","resolution":{"observed_at":"2026-08-10T20:33:11.526148Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-14T06:32:32.682623+00:00","source":"crossref"},{"observed_at":"2026-08-14T06:32:18.44784+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":"2026-08-10T20:33:11.502794Z","title":"{SLAP}: Improving physical adver- sarial examples with {Short-Lived} adversarial perturba- tions,","venue":null,"work_id":"6f579d38-7121-48ef-8365-4dcb83a811ad","year":2021},"citing_paper":{"arxiv_id":"2501.08258","last_updated":"2025-01-16T10:55:41Z","snapshot_observed_at":"2026-08-14T11:47:29.738378Z","submitted_at":"2025-01-14T17:10:02Z","title":"Towards an End-to-End (E2E) Adversarial Learning and Application in the Physical World","version":2},"reference_index":38,"source":"pdf_text","source_observed_at":"2026-08-10T20:33:10.883819Z"},"links":{"citing_paper":"/paper/2501.08258"},"observation_digest":"sha256:7bba0805144438e02ba57a037f7606030a5c2915c6e3b6d363092f4b420fe9bc","observation_id":"012052f2-f188-4206-97ac-d0ff8fbf4df2","resolution":{"observed_at":"2026-08-10T20:33:11.508389Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-14T06:32:32.682623+00:00","source":"crossref"},{"observed_at":"2026-08-14T06:32:18.44784+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":"2026-08-10T20:33:11.485367Z","title":"Opticloak: Blinding vision-based autonomous driving systems through adversarial optical projection,","venue":null,"work_id":"5b7bbed7-3396-462e-96bc-aa9c925e873b","year":2024},"citing_paper":{"arxiv_id":"2501.08258","last_updated":"2025-01-16T10:55:41Z","snapshot_observed_at":"2026-08-14T11:47:29.738378Z","submitted_at":"2025-01-14T17:10:02Z","title":"Towards an End-to-End (E2E) Adversarial Learning and Application in the Physical World","version":2},"reference_index":39,"source":"pdf_text","source_observed_at":"2026-08-10T20:33:10.888845Z"},"links":{"citing_paper":"/paper/2501.08258"},"observation_digest":"sha256:b8c5144c8a00cafe765be00857e83c89700277b3679f567552ff97da4675a766","observation_id":"4f047b19-2e7c-47d5-a338-320dff0f859f","resolution":{"observed_at":"2026-08-10T20:33:11.490963Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-14T06:32:32.682623+00:00","source":"crossref"},{"observed_at":"2026-08-14T06:32:18.44784+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":"2026-08-10T20:33:11.467311Z","title":"Adversarial color projection: A projector-based physical-world attack to dnns,","venue":null,"work_id":"91e64e27-3333-4d2a-bae2-c0d0381c7a90","year":2023},"citing_paper":{"arxiv_id":"2501.08258","last_updated":"2025-01-16T10:55:41Z","snapshot_observed_at":"2026-08-14T11:47:29.738378Z","submitted_at":"2025-01-14T17:10:02Z","title":"Towards an End-to-End (E2E) Adversarial Learning and Application in the Physical World","version":2},"reference_index":40,"source":"pdf_text","source_observed_at":"2026-08-10T20:33:10.893670Z"},"links":{"citing_paper":"/paper/2501.08258"},"observation_digest":"sha256:27f15e5b1fd7b3362ed82585462fed7dce3450e018c4068dbb69d859ba389679","observation_id":"c092da90-9962-460f-b0b4-d2d89040b80b","resolution":{"observed_at":"2026-08-10T20:33:11.473488Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-14T06:32:32.682623+00:00","source":"crossref"},{"observed_at":"2026-08-14T06:32:18.44784+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":"2026-08-10T20:33:11.448778Z","title":"Adversarial patch attacks on deep-learning-based face recognition systems using generative adversarial networks,","venue":null,"work_id":"5ee01b9b-866b-407e-996a-5911e93e6b04","year":2023},"citing_paper":{"arxiv_id":"2501.08258","last_updated":"2025-01-16T10:55:41Z","snapshot_observed_at":"2026-08-14T11:47:29.738378Z","submitted_at":"2025-01-14T17:10:02Z","title":"Towards an End-to-End (E2E) Adversarial Learning and Application in the Physical World","version":2},"reference_index":41,"source":"pdf_text","source_observed_at":"2026-08-10T20:33:10.898527Z"},"links":{"citing_paper":"/paper/2501.08258"},"observation_digest":"sha256:58a76cb3c452e39bc94d9ca6327289fee4a13361490a4c528ae5d9d8c3bd27f3","observation_id":"b33c4651-68b8-4c20-aea3-82a5f8aef5b7","resolution":{"observed_at":"2026-08-10T20:33:11.454200Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-14T06:32:32.682623+00:00","source":"crossref"},{"observed_at":"2026-08-14T06:32:18.44784+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":"2026-08-10T20:33:11.430067Z","title":"Advhat: Real-world ad- versarial attack on arcface face id system,","venue":null,"work_id":"157fda23-5f0d-4b8d-96a9-272358fe1f42","year":2020},"citing_paper":{"arxiv_id":"2501.08258","last_updated":"2025-01-16T10:55:41Z","snapshot_observed_at":"2026-08-14T11:47:29.738378Z","submitted_at":"2025-01-14T17:10:02Z","title":"Towards an End-to-End (E2E) Adversarial Learning and Application in the Physical World","version":2},"reference_index":42,"source":"pdf_text","source_observed_at":"2026-08-10T20:33:10.902783Z"},"links":{"citing_paper":"/paper/2501.08258"},"observation_digest":"sha256:13e52e88bb2f6db8b5009e4b2d76cfcbb14d30fbf8fa1d91e9c3e1b80014c0f7","observation_id":"ba11b16d-babf-4436-a10e-5aedddf7a9d1","resolution":{"observed_at":"2026-08-10T20:33:11.435948Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-14T06:32:32.682623+00:00","source":"crossref"},{"observed_at":"2026-08-14T06:32:18.44784+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":"2026-08-10T20:33:11.411808Z","title":"Real- world adversarial examples via makeup,","venue":null,"work_id":"9417c06f-2d26-4d97-8a76-e9485eb37947","year":2022},"citing_paper":{"arxiv_id":"2501.08258","last_updated":"2025-01-16T10:55:41Z","snapshot_observed_at":"2026-08-14T11:47:29.738378Z","submitted_at":"2025-01-14T17:10:02Z","title":"Towards an End-to-End (E2E) Adversarial Learning and Application in the Physical World","version":2},"reference_index":43,"source":"pdf_text","source_observed_at":"2026-08-10T20:33:10.907087Z"},"links":{"citing_paper":"/paper/2501.08258"},"observation_digest":"sha256:aeb8677a360234b4c0ffb922b01a749ee3345085d391bffd1e4a43f30c088474","observation_id":"5ac6d640-0460-4c71-98d0-c2d985dfd028","resolution":{"observed_at":"2026-08-10T20:33:11.417785Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-14T06:32:32.682623+00:00","source":"crossref"},{"observed_at":"2026-08-14T06:32:18.44784+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":"2026-08-10T20:33:11.393403Z","title":"Unified adversarial patch for cross-modal attacks in the physical world,","venue":null,"work_id":"c013c11b-a5db-4dfc-88cb-88280db0e213","year":2023},"citing_paper":{"arxiv_id":"2501.08258","last_updated":"2025-01-16T10:55:41Z","snapshot_observed_at":"2026-08-14T11:47:29.738378Z","submitted_at":"2025-01-14T17:10:02Z","title":"Towards an End-to-End (E2E) Adversarial Learning and Application in the Physical World","version":2},"reference_index":44,"source":"pdf_text","source_observed_at":"2026-08-10T20:33:10.911730Z"},"links":{"citing_paper":"/paper/2501.08258"},"observation_digest":"sha256:779f25e23fdcb106f46511f3490b08ae4e4ecb6662ca3b6120c0dd4b5e018eb5","observation_id":"c24d9dad-b4c5-46b7-b109-5c9960908628","resolution":{"observed_at":"2026-08-10T20:33:11.398566Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-14T06:32:32.682623+00:00","source":"crossref"},{"observed_at":"2026-08-14T06:32:18.44784+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":"2026-08-10T20:33:11.376133Z","title":"Phantom of the adas: Secur- ing advanced driver-assistance systems from split-second phantom attacks,","venue":null,"work_id":"6b380992-b84d-4145-a711-36d1a2f65f22","year":2020},"citing_paper":{"arxiv_id":"2501.08258","last_updated":"2025-01-16T10:55:41Z","snapshot_observed_at":"2026-08-14T11:47:29.738378Z","submitted_at":"2025-01-14T17:10:02Z","title":"Towards an End-to-End (E2E) Adversarial Learning and Application in the Physical World","version":2},"reference_index":45,"source":"pdf_text","source_observed_at":"2026-08-10T20:33:10.915830Z"},"links":{"citing_paper":"/paper/2501.08258"},"observation_digest":"sha256:81b0eb9dc8b3156ae44cedb07b6a0de1203036f6696e74e7a510ac4369809888","observation_id":"d2d7206b-4869-40e7-a63d-8fb912351cee","resolution":{"observed_at":"2026-08-10T20:33:11.381644Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-14T06:32:32.682623+00:00","source":"crossref"},{"observed_at":"2026-08-14T06:32:18.44784+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"1807.01069","last_updated":"2019-11-15T15:05:57Z","snapshot_observed_at":"2026-08-14T18:56:17.124955Z","submitted_at":"2018-07-03T10:25:26Z","title":"Adversarial Robustness Toolbox v1.0.0","version":4},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"1807.01069","snapshot_observed_at":"2026-08-10T20:33:10.920054Z","title":"Adversarial robustness toolbox v1. 0.0,","venue":null,"work_id":null,"year":2018},"citing_paper":{"arxiv_id":"2501.08258","last_updated":"2025-01-16T10:55:41Z","snapshot_observed_at":"2026-08-14T11:47:29.738378Z","submitted_at":"2025-01-14T17:10:02Z","title":"Towards an End-to-End (E2E) Adversarial Learning and Application in the Physical World","version":2},"reference_index":46,"source":"pdf_text","source_observed_at":"2026-08-10T20:33:10.920054Z"},"links":{"cited_paper":"/paper/1807.01069","citing_paper":"/paper/2501.08258"},"observation_digest":"sha256:9cfdbe155dae3b2beb2cd87817287cb1f5fb03e6f51a67b31244e0d31bb6c848","observation_id":"39a037c1-e40c-4622-8823-ab62b72bed09","resolution":{"observed_at":"2026-08-10T20:33:10.920054Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"1804.02767","last_updated":"2018-04-08T22:27:57Z","snapshot_observed_at":"2026-08-06T11:09:16.409556Z","submitted_at":"2018-04-08T22:27:57Z","title":"YOLOv3: An Incremental Improvement","version":1},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"1804.02767","snapshot_observed_at":"2026-08-10T20:33:10.925474Z","title":"Yolov3: An incremental improvement,","venue":null,"work_id":null,"year":2018},"citing_paper":{"arxiv_id":"2501.08258","last_updated":"2025-01-16T10:55:41Z","snapshot_observed_at":"2026-08-14T11:47:29.738378Z","submitted_at":"2025-01-14T17:10:02Z","title":"Towards an End-to-End (E2E) Adversarial Learning and Application in the Physical World","version":2},"reference_index":47,"source":"pdf_text","source_observed_at":"2026-08-10T20:33:10.925474Z"},"links":{"cited_paper":"/paper/1804.02767","citing_paper":"/paper/2501.08258"},"observation_digest":"sha256:2900d3fe97375c32d7cff44589b12768da96e48c9a6947586ee332723b35d779","observation_id":"c5020f19-a7bc-4dba-8a4c-2f15861289b0","resolution":{"observed_at":"2026-08-10T20:33:10.925474Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":null,"snapshot_observed_at":"2026-08-10T20:33:10.930586Z","title":"Faster r-cnn: Towards real-time object detection with region proposal networks,","venue":null,"work_id":null,"year":2016},"citing_paper":{"arxiv_id":"2501.08258","last_updated":"2025-01-16T10:55:41Z","snapshot_observed_at":"2026-08-14T11:47:29.738378Z","submitted_at":"2025-01-14T17:10:02Z","title":"Towards an End-to-End (E2E) Adversarial Learning and Application in the Physical World","version":2},"reference_index":48,"source":"pdf_text","source_observed_at":"2026-08-10T20:33:10.930586Z"},"links":{"citing_paper":"/paper/2501.08258"},"observation_digest":"sha256:3caec4c7574264431924afc17523a3e5f335d48c4a5364c6df98d213b62c1daa","observation_id":"1f3c2d1c-5997-4b73-8d7e-10539f534b77","resolution":{"observed_at":"2026-08-10T20:33:10.930586Z","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":"2026-08-10T20:33:11.346843Z","title":"Focal loss for dense object detection,","venue":null,"work_id":"d91859c0-13f4-46c5-9cff-826040b7a704","year":2017},"citing_paper":{"arxiv_id":"2501.08258","last_updated":"2025-01-16T10:55:41Z","snapshot_observed_at":"2026-08-14T11:47:29.738378Z","submitted_at":"2025-01-14T17:10:02Z","title":"Towards an End-to-End (E2E) Adversarial Learning and Application in the Physical World","version":2},"reference_index":49,"source":"pdf_text","source_observed_at":"2026-08-10T20:33:10.935450Z"},"links":{"citing_paper":"/paper/2501.08258"},"observation_digest":"sha256:18840d7dba9856c8539bb4852f0096bc7717464616e8998bca8a542eadf0d68e","observation_id":"bb7620b0-5848-42fb-8766-4f810c96ad5d","resolution":{"observed_at":"2026-08-10T20:33:11.352164Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-14T06:32:32.682623+00:00","source":"crossref"},{"observed_at":"2026-08-14T06:32:18.44784+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":"2026-08-10T20:33:11.330117Z","title":"Ssd: Single shot multibox detector,","venue":null,"work_id":"b663f1cd-38a2-4d6e-8ee6-745a27f6f49d","year":2016},"citing_paper":{"arxiv_id":"2501.08258","last_updated":"2025-01-16T10:55:41Z","snapshot_observed_at":"2026-08-14T11:47:29.738378Z","submitted_at":"2025-01-14T17:10:02Z","title":"Towards an End-to-End (E2E) Adversarial Learning and Application in the Physical World","version":2},"reference_index":50,"source":"pdf_text","source_observed_at":"2026-08-10T20:33:10.940404Z"},"links":{"citing_paper":"/paper/2501.08258"},"observation_digest":"sha256:4ca52e44cdf84f23dd7fc3de504c394d30cafd85558847e0fb47271d4b241e30","observation_id":"f48696d4-5100-4601-9188-80153ab00113","resolution":{"observed_at":"2026-08-10T20:33:11.335718Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-14T06:32:32.682623+00:00","source":"crossref"},{"observed_at":"2026-08-14T06:32:18.44784+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"2401.03582","last_updated":"2024-01-07T21:22:42Z","snapshot_observed_at":"2026-08-13T04:47:41.488373Z","submitted_at":"2024-01-07T21:22:42Z","title":"Invisible Reflections: Leveraging Infrared Laser Reflections to Target Traffic Sign Perception","version":1},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2401.03582","snapshot_observed_at":"2026-08-10T20:33:10.946325Z","title":"Invisible reflections: Leveraging infrared laser reflections to target traffic sign perception,","venue":null,"work_id":null,"year":2024},"citing_paper":{"arxiv_id":"2501.08258","last_updated":"2025-01-16T10:55:41Z","snapshot_observed_at":"2026-08-14T11:47:29.738378Z","submitted_at":"2025-01-14T17:10:02Z","title":"Towards an End-to-End (E2E) Adversarial Learning and Application in the Physical World","version":2},"reference_index":51,"source":"pdf_text","source_observed_at":"2026-08-10T20:33:10.946325Z"},"links":{"cited_paper":"/paper/2401.03582","citing_paper":"/paper/2501.08258"},"observation_digest":"sha256:5fa8f02c1122495777152319cbbfc2df4fab3f2b36415d85a61718895246ab5f","observation_id":"2265c3c6-0c59-45bf-b885-15fafbdbc54e","resolution":{"observed_at":"2026-08-10T20:33:10.946325Z","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":"2026-08-10T20:33:11.314126Z","title":"Light can be dangerous: Stealthy and effective physical-world adversarial attack by spot light,","venue":null,"work_id":"7aa44d36-67e8-47c6-affc-e34a12663891","year":2023},"citing_paper":{"arxiv_id":"2501.08258","last_updated":"2025-01-16T10:55:41Z","snapshot_observed_at":"2026-08-14T11:47:29.738378Z","submitted_at":"2025-01-14T17:10:02Z","title":"Towards an End-to-End (E2E) Adversarial Learning and Application in the Physical World","version":2},"reference_index":52,"source":"pdf_text","source_observed_at":"2026-08-10T20:33:10.952495Z"},"links":{"citing_paper":"/paper/2501.08258"},"observation_digest":"sha256:c5212f59ad2ca2b674c77feac135b8759647eedaed57d2beb0b2dea548ce937f","observation_id":"a13d09ba-2a3c-4ed3-a657-a7e4ad00ef8d","resolution":{"observed_at":"2026-08-10T20:33:11.319270Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-14T06:32:32.682623+00:00","source":"crossref"},{"observed_at":"2026-08-14T06:32:18.44784+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":"2026-08-10T20:33:11.298641Z","title":"On adversarial patches: real-world attack on arcface-100 face recognition system,","venue":null,"work_id":"972e988c-c024-421b-bd48-edd6c713a1d1","year":2019},"citing_paper":{"arxiv_id":"2501.08258","last_updated":"2025-01-16T10:55:41Z","snapshot_observed_at":"2026-08-14T11:47:29.738378Z","submitted_at":"2025-01-14T17:10:02Z","title":"Towards an End-to-End (E2E) Adversarial Learning and Application in the Physical World","version":2},"reference_index":53,"source":"pdf_text","source_observed_at":"2026-08-10T20:33:10.958656Z"},"links":{"citing_paper":"/paper/2501.08258"},"observation_digest":"sha256:a8f89bab5dfd8f633f1d98ee3642f9b50fbf022590a89c58b43619c94e4722d3","observation_id":"79a8ec7a-62a4-4d47-b0a3-ed5b4da86f27","resolution":{"observed_at":"2026-08-10T20:33:11.303262Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-14T06:32:32.682623+00:00","source":"crossref"},{"observed_at":"2026-08-14T06:32:18.44784+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":"2026-08-10T20:33:10.963747Z","title":"Accessorize to a crime: Real and stealthy attacks on state-of-the-art face recognition,","venue":null,"work_id":null,"year":2016},"citing_paper":{"arxiv_id":"2501.08258","last_updated":"2025-01-16T10:55:41Z","snapshot_observed_at":"2026-08-14T11:47:29.738378Z","submitted_at":"2025-01-14T17:10:02Z","title":"Towards an End-to-End (E2E) Adversarial Learning and Application in the Physical World","version":2},"reference_index":54,"source":"pdf_text","source_observed_at":"2026-08-10T20:33:10.963747Z"},"links":{"citing_paper":"/paper/2501.08258"},"observation_digest":"sha256:98fa55e06548a9af99aeb40d1d8e3d7a2c3e4ef31de64da8cc86b361ddf4d9de","observation_id":"4fa29615-c476-4468-8379-81c69a429878","resolution":{"observed_at":"2026-08-10T20:33:10.963747Z","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":"2026-08-10T20:33:11.269904Z","title":"Generating adversarial examples by makeup attacks on face recogni- tion,","venue":null,"work_id":"6ad652e4-4108-4310-9d61-38afb9e19bca","year":2019},"citing_paper":{"arxiv_id":"2501.08258","last_updated":"2025-01-16T10:55:41Z","snapshot_observed_at":"2026-08-14T11:47:29.738378Z","submitted_at":"2025-01-14T17:10:02Z","title":"Towards an End-to-End (E2E) Adversarial Learning and Application in the Physical World","version":2},"reference_index":55,"source":"pdf_text","source_observed_at":"2026-08-10T20:33:10.968948Z"},"links":{"citing_paper":"/paper/2501.08258"},"observation_digest":"sha256:992800208315cc76d0ac9c5d524ee27ee5d5e36cd0960ac1e4663314fafe76dc","observation_id":"bfd04f41-71e5-4b31-a315-23558838f3cc","resolution":{"observed_at":"2026-08-10T20:33:11.275177Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-14T06:32:32.682623+00:00","source":"crossref"},{"observed_at":"2026-08-14T06:32:18.44784+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"2105.03162","last_updated":"2021-05-07T11:00:35Z","snapshot_observed_at":"2026-08-13T19:27:15.419384Z","submitted_at":"2021-05-07T11:00:35Z","title":"Adv-Makeup: A New Imperceptible and Transferable Attack on Face Recognition","version":1},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2105.03162","snapshot_observed_at":"2026-08-10T20:33:10.974022Z","title":"Adv-makeup: A new imperceptible and transferable attack on face recognition,","venue":null,"work_id":null,"year":2021},"citing_paper":{"arxiv_id":"2501.08258","last_updated":"2025-01-16T10:55:41Z","snapshot_observed_at":"2026-08-14T11:47:29.738378Z","submitted_at":"2025-01-14T17:10:02Z","title":"Towards an End-to-End (E2E) Adversarial Learning and Application in the Physical World","version":2},"reference_index":56,"source":"pdf_text","source_observed_at":"2026-08-10T20:33:10.974022Z"},"links":{"cited_paper":"/paper/2105.03162","citing_paper":"/paper/2501.08258"},"observation_digest":"sha256:d14ede63535b887ae292d1b296c78923b91c48442b5af647a500891ca92083b9","observation_id":"aff0e862-623e-4e1d-8f1c-21d2324a199a","resolution":{"observed_at":"2026-08-10T20:33:10.974022Z","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":"2026-08-10T20:33:11.252248Z","title":"Adversarial laser beam: Effective physical- world attack to dnns in a blink,","venue":null,"work_id":"b69668b7-aa44-4cfd-840c-c74ae72cabab","year":2021},"citing_paper":{"arxiv_id":"2501.08258","last_updated":"2025-01-16T10:55:41Z","snapshot_observed_at":"2026-08-14T11:47:29.738378Z","submitted_at":"2025-01-14T17:10:02Z","title":"Towards an End-to-End (E2E) Adversarial Learning and Application in the Physical World","version":2},"reference_index":57,"source":"pdf_text","source_observed_at":"2026-08-10T20:33:10.979423Z"},"links":{"citing_paper":"/paper/2501.08258"},"observation_digest":"sha256:032b7a97ffcdcfdb9ec6deef0e65f6879288ca089169ab29085183afccab6a65","observation_id":"f87d31d4-c69c-4ee8-9109-44baf21c17f1","resolution":{"observed_at":"2026-08-10T20:33:11.257502Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-14T06:32:32.682623+00:00","source":"crossref"},{"observed_at":"2026-08-14T06:32:18.44784+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"1803.04683","last_updated":"2018-03-13T08:51:01Z","snapshot_observed_at":"2026-08-14T19:36:48.181786Z","submitted_at":"2018-03-13T08:51:01Z","title":"Invisible Mask: Practical Attacks on Face Recognition with Infrared","version":1},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"1803.04683","snapshot_observed_at":"2026-08-10T20:33:10.984443Z","title":"Invisible mask: Practical attacks on face recognition with infrared,","venue":null,"work_id":null,"year":2018},"citing_paper":{"arxiv_id":"2501.08258","last_updated":"2025-01-16T10:55:41Z","snapshot_observed_at":"2026-08-14T11:47:29.738378Z","submitted_at":"2025-01-14T17:10:02Z","title":"Towards an End-to-End (E2E) Adversarial Learning and Application in the Physical World","version":2},"reference_index":58,"source":"pdf_text","source_observed_at":"2026-08-10T20:33:10.984443Z"},"links":{"cited_paper":"/paper/1803.04683","citing_paper":"/paper/2501.08258"},"observation_digest":"sha256:a58469cf980ca40ecf2f8141185b9954d948cdf1c58a132ae9ff8dae0173b775","observation_id":"72aa6f2c-2c03-4c82-bd38-fa8239d759cc","resolution":{"observed_at":"2026-08-10T20:33:10.984443Z","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":"2026-08-10T20:33:11.235638Z","title":"Vla: A practical visible light-based attack on face recognition systems in physical world,","venue":null,"work_id":"2058a26a-891c-47d7-9fa5-1048e92fbffe","year":2019},"citing_paper":{"arxiv_id":"2501.08258","last_updated":"2025-01-16T10:55:41Z","snapshot_observed_at":"2026-08-14T11:47:29.738378Z","submitted_at":"2025-01-14T17:10:02Z","title":"Towards an End-to-End (E2E) Adversarial Learning and Application in the Physical World","version":2},"reference_index":59,"source":"pdf_text","source_observed_at":"2026-08-10T20:33:10.990117Z"},"links":{"citing_paper":"/paper/2501.08258"},"observation_digest":"sha256:24d9d51efe430fb340044afd452d93bb09d0ad2ebda1f80ba3e8f1417dc1d523","observation_id":"307955e9-89b2-4ba9-98c0-822a111ba40c","resolution":{"observed_at":"2026-08-10T20:33:11.240713Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-14T06:32:32.682623+00:00","source":"crossref"},{"observed_at":"2026-08-14T06:32:18.44784+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":"2026-08-10T20:33:11.216632Z","title":"Fooling thermal infrared pedestrian detectors in real world using small bulbs,","venue":null,"work_id":"6d3319d6-df3a-4a08-bca4-1c4bd5b0acab","year":2021},"citing_paper":{"arxiv_id":"2501.08258","last_updated":"2025-01-16T10:55:41Z","snapshot_observed_at":"2026-08-14T11:47:29.738378Z","submitted_at":"2025-01-14T17:10:02Z","title":"Towards an End-to-End (E2E) Adversarial Learning and Application in the Physical World","version":2},"reference_index":60,"source":"pdf_text","source_observed_at":"2026-08-10T20:33:10.995711Z"},"links":{"citing_paper":"/paper/2501.08258"},"observation_digest":"sha256:4617c0055bba61d43672ecad76bdf946c45d3fd2bc580034b4396cbd1d504952","observation_id":"2b4aa974-2134-4c4e-a32c-39f68406e7f0","resolution":{"observed_at":"2026-08-10T20:33:11.223618Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-14T06:32:32.682623+00:00","source":"crossref"},{"observed_at":"2026-08-14T06:32:18.44784+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":"2026-08-10T20:33:11.000621Z","title":"I can see the light: Attacks on autonomous vehicles using invisible lights,","venue":null,"work_id":null,"year":2021},"citing_paper":{"arxiv_id":"2501.08258","last_updated":"2025-01-16T10:55:41Z","snapshot_observed_at":"2026-08-14T11:47:29.738378Z","submitted_at":"2025-01-14T17:10:02Z","title":"Towards an End-to-End (E2E) Adversarial Learning and Application in the Physical World","version":2},"reference_index":61,"source":"pdf_text","source_observed_at":"2026-08-10T20:33:11.000621Z"},"links":{"citing_paper":"/paper/2501.08258"},"observation_digest":"sha256:6971bbf26bde809a47e64a4c6caa8e5018f3622dfc7150583ebb84288a3889f3","observation_id":"8ab8a053-3df5-4ebf-92ab-22d3c84db0a5","resolution":{"observed_at":"2026-08-10T20:33:11.000621Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}}],"paper":{"arxiv_id":"2501.08258","last_updated":"2025-01-16T10:55:41Z","latest_version":2,"primary_category":"cs.CV","snapshot_observed_at":"2026-08-14T11:47:29.738378Z","submitted_at":"2025-01-14T17:10:02Z","title":"Towards an End-to-End (E2E) Adversarial Learning and Application in the Physical World"},"reference_resolution":{"displayed":61,"state_counts":{"malformed_identifier":0,"metadata_mismatch":0,"parse_uncertain":0,"unresolved":15,"verified_exact":0,"verified_fuzzy":46},"total_outbound_references":61},"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":"2026-08-14T06:32:32.682623+00:00","source":"crossref"},{"observed_at":"2026-08-14T06:32:18.44784+00:00","source":"retraction_watch"}],"thesis":"As of 14 August 2026, this Paper Citation Record lists 61 of 61 outbound references and 0 inbound Pith citation observations for arXiv:2501.08258."}