{"as_of":"2026-08-07T08:19:00Z","caps":{"database_statements":6,"inbound":100,"outbound":100},"context_digest":"sha256:d2e3ac04a558f3f3a8a076197167cd95eb9b41455e7d4b4674facc09c05c093b","coverage":[{"denominator":33,"lane":"reference_resolution","note":"Typed states for the displayed outbound observations.","records_observed":33,"source":"paper_references, paper_reference_links","source_observed_at":"2026-08-06T17:42:51.851375Z","state":"measured"},{"denominator":33,"lane":"standing_notices","note":"One-hop event checks from named stored sources.","records_observed":33,"source":"scholarly_work_events, retraction_status_cache","source_observed_at":"2026-08-07T06:34:17.273281+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/2507.10162/citation-record","integrity":"/paper/2507.10162/integrity","json":"/paper/2507.10162/citation-record.json","paper":"/paper/2507.10162"},"outbound":[{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-06T17:42:55.097748Z","title":"1–88, May 2016","venue":null,"work_id":"33dccc64-b8e4-482e-85f7-c1e1f7ee45e3","year":2016},"citing_paper":{"arxiv_id":"2507.10162","last_updated":"2025-07-14T11:22:50Z","snapshot_observed_at":"2026-08-06T17:35:40.525066Z","submitted_at":"2025-07-14T11:22:50Z","title":"HASSLE: A Self-Supervised Learning Enhanced Hijacking Attack on Vertical Federated Learning","version":1},"reference_index":1,"source":"pdf_text","source_observed_at":"2026-08-06T17:42:48.455432Z"},"links":{"citing_paper":"/paper/2507.10162"},"observation_digest":"sha256:3fab315160c0d7ceab217382fe14ea65cac449cd4063badfcbbc38e951fa11fc","observation_id":"d3e9bdc4-486a-4910-ad9c-587e826565d6","resolution":{"observed_at":"2026-08-06T17:42:55.147411Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-07T06:34:17.273281+00:00","source":"crossref"},{"observed_at":"2026-08-07T06:34:11.927384+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":"2026-08-06T17:42:54.980958Z","title":"California Consumer Privacy Act of 2018,","venue":null,"work_id":"db7337ea-883f-46df-a4aa-24619d3b3d8a","year":2018},"citing_paper":{"arxiv_id":"2507.10162","last_updated":"2025-07-14T11:22:50Z","snapshot_observed_at":"2026-08-06T17:35:40.525066Z","submitted_at":"2025-07-14T11:22:50Z","title":"HASSLE: A Self-Supervised Learning Enhanced Hijacking Attack on Vertical Federated Learning","version":1},"reference_index":2,"source":"pdf_text","source_observed_at":"2026-08-06T17:42:48.538211Z"},"links":{"citing_paper":"/paper/2507.10162"},"observation_digest":"sha256:e75b5a8a385c2463ef2023eb431226361ff7247dcb90fa989a332db3166cba7b","observation_id":"671d0328-335a-45f5-9722-b9d57c8e9d49","resolution":{"observed_at":"2026-08-06T17:42:55.038425Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-07T06:34:17.273281+00:00","source":"crossref"},{"observed_at":"2026-08-07T06:34:11.927384+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":"2026-08-06T17:42:54.862120Z","title":"Federated learning for open banking,","venue":null,"work_id":"9a968a3d-1f09-4b21-84a6-6d2dbb11b261","year":2020},"citing_paper":{"arxiv_id":"2507.10162","last_updated":"2025-07-14T11:22:50Z","snapshot_observed_at":"2026-08-06T17:35:40.525066Z","submitted_at":"2025-07-14T11:22:50Z","title":"HASSLE: A Self-Supervised Learning Enhanced Hijacking Attack on Vertical Federated Learning","version":1},"reference_index":3,"source":"pdf_text","source_observed_at":"2026-08-06T17:42:48.688706Z"},"links":{"citing_paper":"/paper/2507.10162"},"observation_digest":"sha256:df667241a51b9a9a943da9d2ed586c1cdcfcfbe6c9c96556f865ad62b5a8e2e9","observation_id":"fcf2b614-9c65-4714-9eb7-960a3574a8d0","resolution":{"observed_at":"2026-08-06T17:42:54.904964Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-07T06:34:17.273281+00:00","source":"crossref"},{"observed_at":"2026-08-07T06:34:11.927384+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":"2026-08-06T17:42:54.725106Z","title":"Implementing vertical federated learning using autoen- coders: Practical application, generalizability, and utility study,","venue":null,"work_id":"603406f5-be1c-444c-bc55-8f2c15af627d","year":2021},"citing_paper":{"arxiv_id":"2507.10162","last_updated":"2025-07-14T11:22:50Z","snapshot_observed_at":"2026-08-06T17:35:40.525066Z","submitted_at":"2025-07-14T11:22:50Z","title":"HASSLE: A Self-Supervised Learning Enhanced Hijacking Attack on Vertical Federated Learning","version":1},"reference_index":4,"source":"pdf_text","source_observed_at":"2026-08-06T17:42:48.775421Z"},"links":{"citing_paper":"/paper/2507.10162"},"observation_digest":"sha256:0c9a7295acb0a0b04a7569fcc6ab91f74c14d1e75b776e0ca3f580ac4b633f27","observation_id":"cc6ccea4-9e0e-4c68-97d1-b8acac814646","resolution":{"observed_at":"2026-08-06T17:42:54.776660Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-07T06:34:17.273281+00:00","source":"crossref"},{"observed_at":"2026-08-07T06:34:11.927384+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":"2026-08-06T17:42:54.582824Z","title":"Federated learning application on telecommunication- joint healthcare recommendation,","venue":null,"work_id":"3752aa9c-97fb-4690-8ffd-dfc8dea626ad","year":2021},"citing_paper":{"arxiv_id":"2507.10162","last_updated":"2025-07-14T11:22:50Z","snapshot_observed_at":"2026-08-06T17:35:40.525066Z","submitted_at":"2025-07-14T11:22:50Z","title":"HASSLE: A Self-Supervised Learning Enhanced Hijacking Attack on Vertical Federated Learning","version":1},"reference_index":5,"source":"pdf_text","source_observed_at":"2026-08-06T17:42:48.863043Z"},"links":{"citing_paper":"/paper/2507.10162"},"observation_digest":"sha256:edece4e878d535c5a8c17c06aa2ca8a9f333cd60d4b8668325344864b5573508","observation_id":"6c38f0af-4247-4d58-90d9-b19768a26432","resolution":{"observed_at":"2026-08-06T17:42:54.650800Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-07T06:34:17.273281+00:00","source":"crossref"},{"observed_at":"2026-08-07T06:34:11.927384+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":"2026-08-06T17:42:54.468979Z","title":"Survey on federated learning threats: Concepts, taxonomy on attacks and defences, experimental study and challenges,","venue":null,"work_id":"0a97f619-a625-4944-87a6-bc4916fae775","year":2023},"citing_paper":{"arxiv_id":"2507.10162","last_updated":"2025-07-14T11:22:50Z","snapshot_observed_at":"2026-08-06T17:35:40.525066Z","submitted_at":"2025-07-14T11:22:50Z","title":"HASSLE: A Self-Supervised Learning Enhanced Hijacking Attack on Vertical Federated Learning","version":1},"reference_index":6,"source":"pdf_text","source_observed_at":"2026-08-06T17:42:48.960104Z"},"links":{"citing_paper":"/paper/2507.10162"},"observation_digest":"sha256:696995a51c5c849a3117e97e0f4e904add3a0da0d41c39b083f1cd3f100c73de","observation_id":"983d69fc-b7ab-43cf-90b5-8d58dfa4af6e","resolution":{"observed_at":"2026-08-06T17:42:54.518078Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-07T06:34:17.273281+00:00","source":"crossref"},{"observed_at":"2026-08-07T06:34:11.927384+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":"2026-08-06T17:42:49.078329Z","title":"Label inference attacks against vertical federated learning,","venue":null,"work_id":null,"year":2022},"citing_paper":{"arxiv_id":"2507.10162","last_updated":"2025-07-14T11:22:50Z","snapshot_observed_at":"2026-08-06T17:35:40.525066Z","submitted_at":"2025-07-14T11:22:50Z","title":"HASSLE: A Self-Supervised Learning Enhanced Hijacking Attack on Vertical Federated Learning","version":1},"reference_index":7,"source":"pdf_text","source_observed_at":"2026-08-06T17:42:49.078329Z"},"links":{"citing_paper":"/paper/2507.10162"},"observation_digest":"sha256:f2a510388b16e7bae4cee7cc8aec675c0bd33096709b62578de8da107743b324","observation_id":"34ab362d-1758-4cbc-994c-542ce97b4549","resolution":{"observed_at":"2026-08-06T17:42:49.078329Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2201.02775","last_updated":"2024-11-13T06:57:35Z","snapshot_observed_at":"2026-07-06T12:25:41.166977Z","submitted_at":"2022-01-08T06:18:17Z","title":"ADI: Adversarial Dominating Inputs in Vertical Federated Learning Systems","version":4},"cited_work":{"arxiv_id":"2201.02775","doi":null,"metadata_source":"pith","pith_arxiv_id":"2201.02775","snapshot_observed_at":"2026-08-06T17:42:52.064164Z","title":"ADI: Adversarial Dominating Inputs in Vertical Federated Learning Systems","venue":"cs.CR","work_id":"48266e81-242a-48cd-b18e-86a7beaea338","year":2022},"citing_paper":{"arxiv_id":"2507.10162","last_updated":"2025-07-14T11:22:50Z","snapshot_observed_at":"2026-08-06T17:35:40.525066Z","submitted_at":"2025-07-14T11:22:50Z","title":"HASSLE: A Self-Supervised Learning Enhanced Hijacking Attack on Vertical Federated Learning","version":1},"reference_index":8,"source":"pdf_text","source_observed_at":"2026-08-06T17:42:49.247247Z"},"links":{"cited_paper":"/paper/2201.02775","citing_paper":"/paper/2507.10162"},"observation_digest":"sha256:e5569e8397ac004588f8574991f11a36c6aee11dd02a8d1917c1029e416a1214","observation_id":"011e9763-b667-4b8d-ac6b-424a74556417","resolution":{"observed_at":"2026-08-06T17:42:52.133434Z","resolver_source":"local_arxiv","status":"verified_exact"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-07T06:34:17.273281+00:00","source":"crossref"},{"observed_at":"2026-08-07T06:34:11.927384+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":"2026-08-06T17:42:54.304537Z","title":"Badvfl: Backdoor attacks in vertical federated learning,","venue":null,"work_id":"f3b90a48-8db3-4330-96bd-6affd622f001","year":2024},"citing_paper":{"arxiv_id":"2507.10162","last_updated":"2025-07-14T11:22:50Z","snapshot_observed_at":"2026-08-06T17:35:40.525066Z","submitted_at":"2025-07-14T11:22:50Z","title":"HASSLE: A Self-Supervised Learning Enhanced Hijacking Attack on Vertical Federated Learning","version":1},"reference_index":9,"source":"pdf_text","source_observed_at":"2026-08-06T17:42:49.333312Z"},"links":{"citing_paper":"/paper/2507.10162"},"observation_digest":"sha256:29b71ea3fc39ffc9f02701999f09bdaf5bb317a1fdbd9df2af8f3636b514cde2","observation_id":"cfbd212b-b85c-4e5b-8a70-ac8bc0e59ded","resolution":{"observed_at":"2026-08-06T17:42:54.369921Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-07T06:34:17.273281+00:00","source":"crossref"},{"observed_at":"2026-08-07T06:34:11.927384+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":"2026-08-06T17:42:54.146584Z","title":"Vertical federated learning: Concepts, advances, and challenges,","venue":null,"work_id":"83889828-9451-4062-bd3e-5b7dce8de06c","year":2024},"citing_paper":{"arxiv_id":"2507.10162","last_updated":"2025-07-14T11:22:50Z","snapshot_observed_at":"2026-08-06T17:35:40.525066Z","submitted_at":"2025-07-14T11:22:50Z","title":"HASSLE: A Self-Supervised Learning Enhanced Hijacking Attack on Vertical Federated Learning","version":1},"reference_index":10,"source":"pdf_text","source_observed_at":"2026-08-06T17:42:49.417837Z"},"links":{"citing_paper":"/paper/2507.10162"},"observation_digest":"sha256:3536b1a793bf8efa4869ffbc181b6b94edd03007b21a106935221d8aeb4f97b5","observation_id":"03cf1433-454c-4054-a877-03427bf02807","resolution":{"observed_at":"2026-08-06T17:42:54.204767Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-07T06:34:17.273281+00:00","source":"crossref"},{"observed_at":"2026-08-07T06:34:11.927384+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":"2026-08-06T17:42:53.968215Z","title":"Defending batch-level label inference and replacement attacks in vertical federated learning,","venue":null,"work_id":"4501f942-771f-4ee3-bd7c-7881d1c38b75","year":2022},"citing_paper":{"arxiv_id":"2507.10162","last_updated":"2025-07-14T11:22:50Z","snapshot_observed_at":"2026-08-06T17:35:40.525066Z","submitted_at":"2025-07-14T11:22:50Z","title":"HASSLE: A Self-Supervised Learning Enhanced Hijacking Attack on Vertical Federated Learning","version":1},"reference_index":11,"source":"pdf_text","source_observed_at":"2026-08-06T17:42:49.510382Z"},"links":{"citing_paper":"/paper/2507.10162"},"observation_digest":"sha256:a1ef081f4bf08933e0ac88975889a27bf10cfcd8a95de62a811e4e9b02748a61","observation_id":"642fc1bd-3e5c-4213-9170-1d3c6f3ee171","resolution":{"observed_at":"2026-08-06T17:42:54.070733Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-07T06:34:17.273281+00:00","source":"crossref"},{"observed_at":"2026-08-07T06:34:11.927384+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":"2026-08-06T17:42:53.827257Z","title":"Label leakage and protection in two-party split learning,","venue":null,"work_id":"0e7eb7a7-0706-4eda-98db-6ee6be85b554","year":2022},"citing_paper":{"arxiv_id":"2507.10162","last_updated":"2025-07-14T11:22:50Z","snapshot_observed_at":"2026-08-06T17:35:40.525066Z","submitted_at":"2025-07-14T11:22:50Z","title":"HASSLE: A Self-Supervised Learning Enhanced Hijacking Attack on Vertical Federated Learning","version":1},"reference_index":12,"source":"pdf_text","source_observed_at":"2026-08-06T17:42:49.586500Z"},"links":{"citing_paper":"/paper/2507.10162"},"observation_digest":"sha256:b9a3e6788f239d6e970fbfb83a5e44d2db713805e218f217f4d1a3320da7a124","observation_id":"2a72e3ef-6529-4943-8925-12f15fd85aa8","resolution":{"observed_at":"2026-08-06T17:42:53.883461Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-07T06:34:17.273281+00:00","source":"crossref"},{"observed_at":"2026-08-07T06:34:11.927384+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":"2026-08-06T17:42:53.729769Z","title":"Practical and general backdoor attacks against vertical federated learning,","venue":null,"work_id":"afe031ea-052d-4e64-9a92-c0d2a0b08437","year":2023},"citing_paper":{"arxiv_id":"2507.10162","last_updated":"2025-07-14T11:22:50Z","snapshot_observed_at":"2026-08-06T17:35:40.525066Z","submitted_at":"2025-07-14T11:22:50Z","title":"HASSLE: A Self-Supervised Learning Enhanced Hijacking Attack on Vertical Federated Learning","version":1},"reference_index":13,"source":"pdf_text","source_observed_at":"2026-08-06T17:42:49.685357Z"},"links":{"citing_paper":"/paper/2507.10162"},"observation_digest":"sha256:9876f9b66739edbc17dd71a67c6359d388acb822eead12b146fc6748cd301c61","observation_id":"5ed0fc35-8808-459a-9e8c-1a73cab71b6f","resolution":{"observed_at":"2026-08-06T17:42:53.779318Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-07T06:34:17.273281+00:00","source":"crossref"},{"observed_at":"2026-08-07T06:34:11.927384+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":"2026-08-06T17:42:53.571982Z","title":"{VILLAIN}: Backdoor attacks against vertical split learning,","venue":null,"work_id":"5b4da8f0-b6af-4ccf-88e1-f18c63b8277f","year":2023},"citing_paper":{"arxiv_id":"2507.10162","last_updated":"2025-07-14T11:22:50Z","snapshot_observed_at":"2026-08-06T17:35:40.525066Z","submitted_at":"2025-07-14T11:22:50Z","title":"HASSLE: A Self-Supervised Learning Enhanced Hijacking Attack on Vertical Federated Learning","version":1},"reference_index":14,"source":"pdf_text","source_observed_at":"2026-08-06T17:42:49.800390Z"},"links":{"citing_paper":"/paper/2507.10162"},"observation_digest":"sha256:0da1381b84dce6a11e666b0f0c41742eac3b30eec053898bacb934672735732b","observation_id":"aa456202-edd4-41d1-a2b2-c6f33b6d7675","resolution":{"observed_at":"2026-08-06T17:42:53.626478Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-07T06:34:17.273281+00:00","source":"crossref"},{"observed_at":"2026-08-07T06:34:11.927384+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"2203.01451","last_updated":"2022-05-25T00:33:07Z","snapshot_observed_at":"2026-08-01T00:49:27.970628Z","submitted_at":"2022-03-02T22:54:54Z","title":"Label Leakage and Protection from Forward Embedding in Vertical Federated Learning","version":3},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2203.01451","snapshot_observed_at":"2026-08-06T17:42:49.925227Z","title":"Label leakage and protection from forward embedding in vertical federated learning,","venue":null,"work_id":null,"year":2022},"citing_paper":{"arxiv_id":"2507.10162","last_updated":"2025-07-14T11:22:50Z","snapshot_observed_at":"2026-08-06T17:35:40.525066Z","submitted_at":"2025-07-14T11:22:50Z","title":"HASSLE: A Self-Supervised Learning Enhanced Hijacking Attack on Vertical Federated Learning","version":1},"reference_index":15,"source":"pdf_text","source_observed_at":"2026-08-06T17:42:49.925227Z"},"links":{"cited_paper":"/paper/2203.01451","citing_paper":"/paper/2507.10162"},"observation_digest":"sha256:90bdfa39fe694e47ec99c6bbe3d0174147c361c2711a97b4b728e51e03598985","observation_id":"b360fd1f-5173-4a5c-8693-efdd22586ade","resolution":{"observed_at":"2026-08-06T17:42:49.925227Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"1412.6572","last_updated":"2015-03-20T20:19:16Z","snapshot_observed_at":"2026-07-06T04:04:16.777653Z","submitted_at":"2014-12-20T01:17:12Z","title":"Explaining and Harnessing Adversarial Examples","version":3},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"1412.6572","snapshot_observed_at":"2026-08-06T17:42:50.045362Z","title":"Explaining and harnessing adversarial examples,","venue":null,"work_id":null,"year":2014},"citing_paper":{"arxiv_id":"2507.10162","last_updated":"2025-07-14T11:22:50Z","snapshot_observed_at":"2026-08-06T17:35:40.525066Z","submitted_at":"2025-07-14T11:22:50Z","title":"HASSLE: A Self-Supervised Learning Enhanced Hijacking Attack on Vertical Federated Learning","version":1},"reference_index":16,"source":"pdf_text","source_observed_at":"2026-08-06T17:42:50.045362Z"},"links":{"cited_paper":"/paper/1412.6572","citing_paper":"/paper/2507.10162"},"observation_digest":"sha256:136ee0382822a149f38671b00ef0563699532fd51c68c633e4bc7f76bba22549","observation_id":"a3a3048b-9e65-4953-8aa6-86b4967b6222","resolution":{"observed_at":"2026-08-06T17:42:50.045362Z","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":"2026-08-06T17:42:53.424511Z","title":"Backdoor attack against split neural network-based vertical federated learning,","venue":null,"work_id":"d9947e6c-3cf3-4c00-9a1b-a0967f0fb65c","year":2023},"citing_paper":{"arxiv_id":"2507.10162","last_updated":"2025-07-14T11:22:50Z","snapshot_observed_at":"2026-08-06T17:35:40.525066Z","submitted_at":"2025-07-14T11:22:50Z","title":"HASSLE: A Self-Supervised Learning Enhanced Hijacking Attack on Vertical Federated Learning","version":1},"reference_index":17,"source":"pdf_text","source_observed_at":"2026-08-06T17:42:50.160298Z"},"links":{"citing_paper":"/paper/2507.10162"},"observation_digest":"sha256:6868c077f03db1487d9a46c42943d4714426c0eedcecb131df27e83a290432b4","observation_id":"038d50b1-d100-47a5-90ef-aafa8ef0c55e","resolution":{"observed_at":"2026-08-06T17:42:53.494242Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-07T06:34:17.273281+00:00","source":"crossref"},{"observed_at":"2026-08-07T06:34:11.927384+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":"2026-08-06T17:42:53.256429Z","title":"Lr-ba: Backdoor attack against vertical federated learning using local latent representations,","venue":null,"work_id":"d45a0b5c-2616-46a0-898c-6b564a1266f9","year":2023},"citing_paper":{"arxiv_id":"2507.10162","last_updated":"2025-07-14T11:22:50Z","snapshot_observed_at":"2026-08-06T17:35:40.525066Z","submitted_at":"2025-07-14T11:22:50Z","title":"HASSLE: A Self-Supervised Learning Enhanced Hijacking Attack on Vertical Federated Learning","version":1},"reference_index":18,"source":"pdf_text","source_observed_at":"2026-08-06T17:42:50.258579Z"},"links":{"citing_paper":"/paper/2507.10162"},"observation_digest":"sha256:98d3b2e5a25c11655eca0ca56198bacd5968e10970a223054829a8576522d4c9","observation_id":"3d5bdea0-07c4-49eb-9928-162346bb79be","resolution":{"observed_at":"2026-08-06T17:42:53.310017Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-07T06:34:17.273281+00:00","source":"crossref"},{"observed_at":"2026-08-07T06:34:11.927384+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":"2026-08-06T17:42:53.133478Z","title":"Hijack vertical federated learning models as one party,","venue":null,"work_id":"8184d134-d500-49da-a7a2-022d278f9e59","year":2024},"citing_paper":{"arxiv_id":"2507.10162","last_updated":"2025-07-14T11:22:50Z","snapshot_observed_at":"2026-08-06T17:35:40.525066Z","submitted_at":"2025-07-14T11:22:50Z","title":"HASSLE: A Self-Supervised Learning Enhanced Hijacking Attack on Vertical Federated Learning","version":1},"reference_index":19,"source":"pdf_text","source_observed_at":"2026-08-06T17:42:50.385899Z"},"links":{"citing_paper":"/paper/2507.10162"},"observation_digest":"sha256:5faa8133462d5ba2448ebe156a950b4f8667e8cf68a0600ee0fa14331a987c0e","observation_id":"88b7fd3c-cc2b-40f7-b690-722aad61377e","resolution":{"observed_at":"2026-08-06T17:42:53.186208Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-07T06:34:17.273281+00:00","source":"crossref"},{"observed_at":"2026-08-07T06:34:11.927384+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":"2026-08-06T17:42:50.467398Z","title":"Learning multiple layers of features from tiny images,","venue":null,"work_id":null,"year":2009},"citing_paper":{"arxiv_id":"2507.10162","last_updated":"2025-07-14T11:22:50Z","snapshot_observed_at":"2026-08-06T17:35:40.525066Z","submitted_at":"2025-07-14T11:22:50Z","title":"HASSLE: A Self-Supervised Learning Enhanced Hijacking Attack on Vertical Federated Learning","version":1},"reference_index":20,"source":"pdf_text","source_observed_at":"2026-08-06T17:42:50.467398Z"},"links":{"citing_paper":"/paper/2507.10162"},"observation_digest":"sha256:f8fc2b9a7de5438b3dbab82db461d5bb68e857a5da5f7b7c0a59cba2069d8583","observation_id":"a7166ebe-c30d-4371-9bf3-cd1e70ddfd50","resolution":{"observed_at":"2026-08-06T17:42:50.467398Z","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":"2026-08-06T17:42:53.012077Z","title":"Imagenette dataset,","venue":null,"work_id":"fc179bf1-8224-4256-b553-471d0d5cdea0","year":2019},"citing_paper":{"arxiv_id":"2507.10162","last_updated":"2025-07-14T11:22:50Z","snapshot_observed_at":"2026-08-06T17:35:40.525066Z","submitted_at":"2025-07-14T11:22:50Z","title":"HASSLE: A Self-Supervised Learning Enhanced Hijacking Attack on Vertical Federated Learning","version":1},"reference_index":21,"source":"pdf_text","source_observed_at":"2026-08-06T17:42:50.564937Z"},"links":{"citing_paper":"/paper/2507.10162"},"observation_digest":"sha256:c070920fce27d93f343704dedecfaa8ad4c076b00a1ef809875374ffd9774356","observation_id":"a056b842-47e5-45da-96f5-50a38b82fdc4","resolution":{"observed_at":"2026-08-06T17:42:53.064064Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-07T06:34:17.273281+00:00","source":"crossref"},{"observed_at":"2026-08-07T06:34:11.927384+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":"2026-08-06T17:42:50.637996Z","title":"Nus-wide: a real-world web image database from national university of singapore,","venue":null,"work_id":null,"year":2009},"citing_paper":{"arxiv_id":"2507.10162","last_updated":"2025-07-14T11:22:50Z","snapshot_observed_at":"2026-08-06T17:35:40.525066Z","submitted_at":"2025-07-14T11:22:50Z","title":"HASSLE: A Self-Supervised Learning Enhanced Hijacking Attack on Vertical Federated Learning","version":1},"reference_index":22,"source":"pdf_text","source_observed_at":"2026-08-06T17:42:50.637996Z"},"links":{"citing_paper":"/paper/2507.10162"},"observation_digest":"sha256:4f2d072927746bf2f0a49fd93e0d9eb367a4697a098ebc112043d3dcfd5ca245","observation_id":"c82a3bdf-e42e-4d6f-9665-0f59080aa4c7","resolution":{"observed_at":"2026-08-06T17:42:50.637996Z","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":"2026-08-06T17:42:50.703383Z","title":"Becker and R","venue":null,"work_id":null,"year":1996},"citing_paper":{"arxiv_id":"2507.10162","last_updated":"2025-07-14T11:22:50Z","snapshot_observed_at":"2026-08-06T17:35:40.525066Z","submitted_at":"2025-07-14T11:22:50Z","title":"HASSLE: A Self-Supervised Learning Enhanced Hijacking Attack on Vertical Federated Learning","version":1},"reference_index":23,"source":"pdf_text","source_observed_at":"2026-08-06T17:42:50.703383Z"},"links":{"citing_paper":"/paper/2507.10162"},"observation_digest":"sha256:4eb0516b2654a9e411f31e2093ccac026c3b2e4b2ccc17854a387370ca739eac","observation_id":"5e40bcc0-b296-4df5-b16a-b3714884cf90","resolution":{"observed_at":"2026-08-06T17:42:50.703383Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2003.04297","last_updated":"2020-03-09T17:56:49Z","snapshot_observed_at":"2026-07-06T09:03:25.467987Z","submitted_at":"2020-03-09T17:56:49Z","title":"Improved Baselines with Momentum Contrastive Learning","version":1},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2003.04297","snapshot_observed_at":"2026-08-06T17:42:50.821003Z","title":"Improved baselines with mo- mentum contrastive learning,","venue":null,"work_id":null,"year":2003},"citing_paper":{"arxiv_id":"2507.10162","last_updated":"2025-07-14T11:22:50Z","snapshot_observed_at":"2026-08-06T17:35:40.525066Z","submitted_at":"2025-07-14T11:22:50Z","title":"HASSLE: A Self-Supervised Learning Enhanced Hijacking Attack on Vertical Federated Learning","version":1},"reference_index":24,"source":"pdf_text","source_observed_at":"2026-08-06T17:42:50.821003Z"},"links":{"cited_paper":"/paper/2003.04297","citing_paper":"/paper/2507.10162"},"observation_digest":"sha256:975af4ffb6571cb8aa1dc560a76282e79fbf366be363124fee9fdb9771e2fe9d","observation_id":"7c74a476-0443-4bd3-8b20-1c705cf60d81","resolution":{"observed_at":"2026-08-06T17:42:50.821003Z","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":"2026-08-06T17:42:52.882261Z","title":"Scarf: Self-supervised contrastive learning using random feature corruption,","venue":null,"work_id":"0db1bb3d-b018-4bed-b648-615619ce59e3","year":2022},"citing_paper":{"arxiv_id":"2507.10162","last_updated":"2025-07-14T11:22:50Z","snapshot_observed_at":"2026-08-06T17:35:40.525066Z","submitted_at":"2025-07-14T11:22:50Z","title":"HASSLE: A Self-Supervised Learning Enhanced Hijacking Attack on Vertical Federated Learning","version":1},"reference_index":25,"source":"pdf_text","source_observed_at":"2026-08-06T17:42:50.869003Z"},"links":{"citing_paper":"/paper/2507.10162"},"observation_digest":"sha256:d45ac3f447c2d427be7fc1c1c32a766449d3fbb52b04edf6a098acf9fc2ddb52","observation_id":"418a2203-9868-4844-85fa-a680d45fbbfd","resolution":{"observed_at":"2026-08-06T17:42:52.957455Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-07T06:34:17.273281+00:00","source":"crossref"},{"observed_at":"2026-08-07T06:34:11.927384+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":"2026-08-06T17:42:50.910570Z","title":"Scikit-learn: Machine learning in Python,","venue":null,"work_id":null,"year":2011},"citing_paper":{"arxiv_id":"2507.10162","last_updated":"2025-07-14T11:22:50Z","snapshot_observed_at":"2026-08-06T17:35:40.525066Z","submitted_at":"2025-07-14T11:22:50Z","title":"HASSLE: A Self-Supervised Learning Enhanced Hijacking Attack on Vertical Federated Learning","version":1},"reference_index":26,"source":"pdf_text","source_observed_at":"2026-08-06T17:42:50.910570Z"},"links":{"citing_paper":"/paper/2507.10162"},"observation_digest":"sha256:7f86480f962d97174b6c6b38f87dcaafd7601c3ed6367a16e60c90e8e95b85d6","observation_id":"0700211e-4077-4f32-addc-b501e04159f4","resolution":{"observed_at":"2026-08-06T17:42:50.910570Z","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":"2026-08-06T17:42:52.740125Z","title":"Grad-cam: Visual explanations from deep networks via gradient-based localization,","venue":null,"work_id":"e3e64ee0-8796-4f8e-babb-68486d93529d","year":2017},"citing_paper":{"arxiv_id":"2507.10162","last_updated":"2025-07-14T11:22:50Z","snapshot_observed_at":"2026-08-06T17:35:40.525066Z","submitted_at":"2025-07-14T11:22:50Z","title":"HASSLE: A Self-Supervised Learning Enhanced Hijacking Attack on Vertical Federated Learning","version":1},"reference_index":27,"source":"pdf_text","source_observed_at":"2026-08-06T17:42:51.072194Z"},"links":{"citing_paper":"/paper/2507.10162"},"observation_digest":"sha256:7592ee0c317eb01581210ea6a63d81611a4190ccf5c42040d07618a3726815ca","observation_id":"2bf787f1-4017-45ec-96f9-1b2a07ef54a3","resolution":{"observed_at":"2026-08-06T17:42:52.787319Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-07T06:34:17.273281+00:00","source":"crossref"},{"observed_at":"2026-08-07T06:34:11.927384+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":"2026-08-06T17:42:51.164323Z","title":"Deep learning with differential privacy,","venue":null,"work_id":null,"year":2016},"citing_paper":{"arxiv_id":"2507.10162","last_updated":"2025-07-14T11:22:50Z","snapshot_observed_at":"2026-08-06T17:35:40.525066Z","submitted_at":"2025-07-14T11:22:50Z","title":"HASSLE: A Self-Supervised Learning Enhanced Hijacking Attack on Vertical Federated Learning","version":1},"reference_index":28,"source":"pdf_text","source_observed_at":"2026-08-06T17:42:51.164323Z"},"links":{"citing_paper":"/paper/2507.10162"},"observation_digest":"sha256:ea9fd410c9184d667adab78cbfe3f4aff955e4a5f11e62503bd771f4f0886d1c","observation_id":"97c3ecdc-1af1-41cc-85a5-c9a2381159d6","resolution":{"observed_at":"2026-08-06T17:42:51.164323Z","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":"2026-08-06T17:42:52.551983Z","title":"Scalable distributed dnn training using commodity gpu cloud computing,","venue":null,"work_id":"b274f3a9-d01f-4be5-9104-77b7bea22d32","year":2015},"citing_paper":{"arxiv_id":"2507.10162","last_updated":"2025-07-14T11:22:50Z","snapshot_observed_at":"2026-08-06T17:35:40.525066Z","submitted_at":"2025-07-14T11:22:50Z","title":"HASSLE: A Self-Supervised Learning Enhanced Hijacking Attack on Vertical Federated Learning","version":1},"reference_index":29,"source":"pdf_text","source_observed_at":"2026-08-06T17:42:51.340256Z"},"links":{"citing_paper":"/paper/2507.10162"},"observation_digest":"sha256:8dde0eb7f857d62b5b59d95be8f5e917a377b77fd75318583a44a452ac70d576","observation_id":"bb8f1bf6-7ab2-4670-bf24-3e19b62c6415","resolution":{"observed_at":"2026-08-06T17:42:52.629906Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-07T06:34:17.273281+00:00","source":"crossref"},{"observed_at":"2026-08-07T06:34:11.927384+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":"2026-08-06T17:42:52.389535Z","title":"Anti-backdoor learning: Training clean models on poisoned data,","venue":null,"work_id":"b11f757d-2fe4-48f3-8f49-328acba51d8b","year":2021},"citing_paper":{"arxiv_id":"2507.10162","last_updated":"2025-07-14T11:22:50Z","snapshot_observed_at":"2026-08-06T17:35:40.525066Z","submitted_at":"2025-07-14T11:22:50Z","title":"HASSLE: A Self-Supervised Learning Enhanced Hijacking Attack on Vertical Federated Learning","version":1},"reference_index":30,"source":"pdf_text","source_observed_at":"2026-08-06T17:42:51.469338Z"},"links":{"citing_paper":"/paper/2507.10162"},"observation_digest":"sha256:ccb5a43f6dc946d741298defdeeba9fcb174a95021d35353c33352d84a61da6e","observation_id":"861bc8aa-9ad2-4f1e-a46b-3c9e485d7840","resolution":{"observed_at":"2026-08-06T17:42:52.464814Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-07T06:34:17.273281+00:00","source":"crossref"},{"observed_at":"2026-08-07T06:34:11.927384+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":"2026-08-06T17:42:52.285881Z","title":"Adversarial neuron pruning purifies backdoored deep models,","venue":null,"work_id":"2d91070b-ceeb-443c-82e9-df446c1fdb43","year":2021},"citing_paper":{"arxiv_id":"2507.10162","last_updated":"2025-07-14T11:22:50Z","snapshot_observed_at":"2026-08-06T17:35:40.525066Z","submitted_at":"2025-07-14T11:22:50Z","title":"HASSLE: A Self-Supervised Learning Enhanced Hijacking Attack on Vertical Federated Learning","version":1},"reference_index":31,"source":"pdf_text","source_observed_at":"2026-08-06T17:42:51.573317Z"},"links":{"citing_paper":"/paper/2507.10162"},"observation_digest":"sha256:7b9f44f2e3b997a3c7fcd53d15b4ad3695df85551b994346107f545dfb1f15e5","observation_id":"985161ce-1db4-497f-9326-c662acbb5c88","resolution":{"observed_at":"2026-08-06T17:42:52.350437Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-07T06:34:17.273281+00:00","source":"crossref"},{"observed_at":"2026-08-07T06:34:11.927384+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":"2026-08-06T17:42:52.204486Z","title":"Vflip: A backdoor defense for vertical federated learning via identification and purification,","venue":null,"work_id":"eeae75cc-17a4-4214-aeb2-ee3c42ce1dc3","year":2024},"citing_paper":{"arxiv_id":"2507.10162","last_updated":"2025-07-14T11:22:50Z","snapshot_observed_at":"2026-08-06T17:35:40.525066Z","submitted_at":"2025-07-14T11:22:50Z","title":"HASSLE: A Self-Supervised Learning Enhanced Hijacking Attack on Vertical Federated Learning","version":1},"reference_index":32,"source":"pdf_text","source_observed_at":"2026-08-06T17:42:51.682679Z"},"links":{"citing_paper":"/paper/2507.10162"},"observation_digest":"sha256:483e137098a9bad9d5ab054683e72835c8c52876b1e827a25a728a7224d69f7d","observation_id":"e102e7c0-cb1a-4991-950a-e43da185e53c","resolution":{"observed_at":"2026-08-06T17:42:52.231039Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-07T06:34:17.273281+00:00","source":"crossref"},{"observed_at":"2026-08-07T06:34:11.927384+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":"2026-08-06T17:42:51.851375Z","title":"Certified adversarial robustness via randomized smoothing,","venue":null,"work_id":null,"year":2019},"citing_paper":{"arxiv_id":"2507.10162","last_updated":"2025-07-14T11:22:50Z","snapshot_observed_at":"2026-08-06T17:35:40.525066Z","submitted_at":"2025-07-14T11:22:50Z","title":"HASSLE: A Self-Supervised Learning Enhanced Hijacking Attack on Vertical Federated Learning","version":1},"reference_index":33,"source":"pdf_text","source_observed_at":"2026-08-06T17:42:51.851375Z"},"links":{"citing_paper":"/paper/2507.10162"},"observation_digest":"sha256:3bc0d513c753c041c120bc085f34adef03e4a771f3f9651afb21c16df78dca64","observation_id":"c37e447c-b701-40f8-81d5-c99c0e7394b9","resolution":{"observed_at":"2026-08-06T17:42:51.851375Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}}],"paper":{"arxiv_id":"2507.10162","last_updated":"2025-07-14T11:22:50Z","latest_version":1,"primary_category":"cs.CR","snapshot_observed_at":"2026-08-06T17:35:40.525066Z","submitted_at":"2025-07-14T11:22:50Z","title":"HASSLE: A Self-Supervised Learning Enhanced Hijacking Attack on Vertical Federated Learning"},"reference_resolution":{"displayed":33,"state_counts":{"malformed_identifier":0,"metadata_mismatch":0,"parse_uncertain":0,"unresolved":10,"verified_exact":1,"verified_fuzzy":22},"total_outbound_references":33},"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":"2026-08-07T06:34:17.273281+00:00","source":"crossref"},{"observed_at":"2026-08-07T06:34:11.927384+00:00","source":"retraction_watch"}],"thesis":"As of 7 August 2026, this Paper Citation Record lists 33 of 33 outbound references and 0 inbound Pith citation observations for arXiv:2507.10162."}