{"as_of":"2026-08-20T09:04:00Z","caps":{"database_statements":6,"inbound":100,"outbound":100},"context_digest":"sha256:79b5cabb15d29d94500c42be0832b4232b7c3a4ccdc6e4a69c3181568923b2e4","coverage":[{"denominator":35,"lane":"reference_resolution","note":"Typed states for the displayed outbound observations.","records_observed":35,"source":"paper_references, paper_reference_links","source_observed_at":"2026-08-09T22:24:13.437630Z","state":"measured"},{"denominator":35,"lane":"standing_notices","note":"One-hop event checks from named stored sources.","records_observed":35,"source":"scholarly_work_events, retraction_status_cache","source_observed_at":"2026-08-20T06:33:59.587034+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/2501.18821/citation-record","integrity":"/paper/2501.18821/integrity","json":"/paper/2501.18821/citation-record.json","paper":"/paper/2501.18821"},"outbound":[{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"arxiv_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-09T22:24:16.838562Z","title":"Federated learning-based misbehavior detection for the 5G-enabled internet of vehicles,","venue":null,"work_id":"01b3fc18-a458-44c1-b0cb-1ef287edc72d","year":2024},"citing_paper":{"arxiv_id":"2501.18821","last_updated":"2025-06-05T21:37:44Z","snapshot_observed_at":"2026-08-20T04:34:32.022188Z","submitted_at":"2025-01-31T00:36:08Z","title":"An Optimal Cascade Feature-Level Spatiotemporal Fusion Strategy for Anomaly Detection in CAN Bus","version":3},"reference_index":1,"source":"pdf_text","source_observed_at":"2026-08-09T22:24:13.343020Z"},"links":{"citing_paper":"/paper/2501.18821"},"observation_digest":"sha256:75bd5e7e63923163f6eafa1b24eaf96bd565a278d5003d7985badc3abb622620","observation_id":"aa60fb5d-1c1b-405f-91cb-6c085749d274","resolution":{"observed_at":"2026-08-09T22:24:16.842843Z","resolver_source":"arxiv_id_nonexistent","status":"verified_exact"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-20T06:33:59.587034+00:00","source":"crossref"},{"observed_at":"2026-08-20T06:33:54.927442+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"arxiv_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-09T22:24:16.654456Z","title":"CANival: A multimodal approach to intrusion detection on the vehicle CAN bus,","venue":null,"work_id":"f04545a8-d2c2-4efb-abf1-525c57dd72eb","year":2024},"citing_paper":{"arxiv_id":"2501.18821","last_updated":"2025-06-05T21:37:44Z","snapshot_observed_at":"2026-08-20T04:34:32.022188Z","submitted_at":"2025-01-31T00:36:08Z","title":"An Optimal Cascade Feature-Level Spatiotemporal Fusion Strategy for Anomaly Detection in CAN Bus","version":3},"reference_index":2,"source":"pdf_text","source_observed_at":"2026-08-09T22:24:13.346307Z"},"links":{"citing_paper":"/paper/2501.18821"},"observation_digest":"sha256:04c6fc900466dc773f3974f20ddaaed60f7d23ce2c77a497879571725b48b259","observation_id":"43a3098e-f813-426b-949f-ba6b7ca43948","resolution":{"observed_at":"2026-08-09T22:24:16.659858Z","resolver_source":"arxiv_id_nonexistent","status":"verified_exact"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-20T06:33:59.587034+00:00","source":"crossref"},{"observed_at":"2026-08-20T06:33:54.927442+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"arxiv_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-09T22:24:16.485357Z","title":"NovelADS: A novel anomaly detection system for intra-vehicular networks,","venue":null,"work_id":"c0d35ac7-8321-4cbd-8cb8-bf8b4bcaaee2","year":2022},"citing_paper":{"arxiv_id":"2501.18821","last_updated":"2025-06-05T21:37:44Z","snapshot_observed_at":"2026-08-20T04:34:32.022188Z","submitted_at":"2025-01-31T00:36:08Z","title":"An Optimal Cascade Feature-Level Spatiotemporal Fusion Strategy for Anomaly Detection in CAN Bus","version":3},"reference_index":3,"source":"pdf_text","source_observed_at":"2026-08-09T22:24:13.349239Z"},"links":{"citing_paper":"/paper/2501.18821"},"observation_digest":"sha256:b5474716d7f022b1640b9e5d0f83c7959b79083dafe8c974e68223b98c904555","observation_id":"cd94302c-1107-445b-8b02-efcfb95241a3","resolution":{"observed_at":"2026-08-09T22:24:16.490455Z","resolver_source":"arxiv_id_nonexistent","status":"verified_exact"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-20T06:33:59.587034+00:00","source":"crossref"},{"observed_at":"2026-08-20T06:33:54.927442+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"arxiv_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-09T22:24:16.317562Z","title":"Car hacking and defense competition on in-vehicle network,","venue":null,"work_id":"2f46dd42-b38e-4523-b040-bce4e57f10a6","year":2021},"citing_paper":{"arxiv_id":"2501.18821","last_updated":"2025-06-05T21:37:44Z","snapshot_observed_at":"2026-08-20T04:34:32.022188Z","submitted_at":"2025-01-31T00:36:08Z","title":"An Optimal Cascade Feature-Level Spatiotemporal Fusion Strategy for Anomaly Detection in CAN Bus","version":3},"reference_index":4,"source":"pdf_text","source_observed_at":"2026-08-09T22:24:13.352086Z"},"links":{"citing_paper":"/paper/2501.18821"},"observation_digest":"sha256:17765b34b419ad441185b467f46a6b852316d594c90bf25a7de94b84af9e249a","observation_id":"4c723819-e5e4-4fa1-a926-ccebe119a7a2","resolution":{"observed_at":"2026-08-09T22:24:16.320396Z","resolver_source":"arxiv_id_nonexistent","status":"verified_exact"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-20T06:33:59.587034+00:00","source":"crossref"},{"observed_at":"2026-08-20T06:33:54.927442+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"arxiv_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-09T22:24:16.133951Z","title":"In-vehicle network intrusion detection using deep convolutional neural network,","venue":null,"work_id":"a2397a02-fca7-4c30-83eb-8420a3e9d57f","year":2020},"citing_paper":{"arxiv_id":"2501.18821","last_updated":"2025-06-05T21:37:44Z","snapshot_observed_at":"2026-08-20T04:34:32.022188Z","submitted_at":"2025-01-31T00:36:08Z","title":"An Optimal Cascade Feature-Level Spatiotemporal Fusion Strategy for Anomaly Detection in CAN Bus","version":3},"reference_index":5,"source":"pdf_text","source_observed_at":"2026-08-09T22:24:13.354983Z"},"links":{"citing_paper":"/paper/2501.18821"},"observation_digest":"sha256:3575c35bf4cfc5a877d3b5f2f5fc918411b38e2b44dce74d02540a4baafbe8c9","observation_id":"2eb48dd7-2199-47d9-8427-b0039a172458","resolution":{"observed_at":"2026-08-09T22:24:16.138901Z","resolver_source":"arxiv_id_nonexistent","status":"verified_exact"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-20T06:33:59.587034+00:00","source":"crossref"},{"observed_at":"2026-08-20T06:33:54.927442+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":"10.3390/s22239195","metadata_source":"openalex","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-10T05:30:23.456663Z","title":"Classification of normal and malicious traffic based on an ensemble of machine learning for a vehicle CAN-network,","venue":"Sensors","work_id":"1ef35f0b-80d2-43bf-a46b-febb997aec5c","year":2022},"citing_paper":{"arxiv_id":"2501.18821","last_updated":"2025-06-05T21:37:44Z","snapshot_observed_at":"2026-08-20T04:34:32.022188Z","submitted_at":"2025-01-31T00:36:08Z","title":"An Optimal Cascade Feature-Level Spatiotemporal Fusion Strategy for Anomaly Detection in CAN Bus","version":3},"reference_index":6,"source":"pdf_text","source_observed_at":"2026-08-09T22:24:13.357851Z"},"links":{"citing_paper":"/paper/2501.18821"},"observation_digest":"sha256:e60597f6f7b548c6a86b9ee91fe81a827fb67bcbeed96de5f0dc6b8cc781fce3","observation_id":"dfcf0af7-7d12-4bf9-9b67-49002327d136","resolution":{"observed_at":"2026-08-09T22:24:13.516667Z","resolver_source":"doi","status":"verified_exact"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-20T06:33:59.587034+00:00","source":"crossref"},{"observed_at":"2026-08-20T06:33:54.927442+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"arxiv_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-09T22:24:15.961848Z","title":"V ANET network traffic anomaly detection using GRU-based deep learning model,","venue":null,"work_id":"0dd51c2a-d49e-44c4-8840-538e09d03c72","year":2024},"citing_paper":{"arxiv_id":"2501.18821","last_updated":"2025-06-05T21:37:44Z","snapshot_observed_at":"2026-08-20T04:34:32.022188Z","submitted_at":"2025-01-31T00:36:08Z","title":"An Optimal Cascade Feature-Level Spatiotemporal Fusion Strategy for Anomaly Detection in CAN Bus","version":3},"reference_index":7,"source":"pdf_text","source_observed_at":"2026-08-09T22:24:13.360916Z"},"links":{"citing_paper":"/paper/2501.18821"},"observation_digest":"sha256:3966b40d896877530d5bedd4e4ca73d54a81d80cb20331cfd2dc456c552affbe","observation_id":"4809aa88-2e7c-4cf1-ad4d-586c6401925e","resolution":{"observed_at":"2026-08-09T22:24:15.965059Z","resolver_source":"arxiv_id_nonexistent","status":"verified_exact"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-20T06:33:59.587034+00:00","source":"crossref"},{"observed_at":"2026-08-20T06:33:54.927442+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":"10.1007/s12083-023-01508-7","metadata_source":"openalex","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-10T05:30:23.456663Z","title":"Machine learning based intrusion detection systems for connected autonomous vehicles: A survey,","venue":"Peer-to-Peer Networking and Applications","work_id":"e22e9955-e940-4a6d-9b9f-c980253eccd9","year":2023},"citing_paper":{"arxiv_id":"2501.18821","last_updated":"2025-06-05T21:37:44Z","snapshot_observed_at":"2026-08-20T04:34:32.022188Z","submitted_at":"2025-01-31T00:36:08Z","title":"An Optimal Cascade Feature-Level Spatiotemporal Fusion Strategy for Anomaly Detection in CAN Bus","version":3},"reference_index":8,"source":"pdf_text","source_observed_at":"2026-08-09T22:24:13.363535Z"},"links":{"citing_paper":"/paper/2501.18821"},"observation_digest":"sha256:09298f5a358ff1138abef06f7c60bedb7740fefcf629af8ee911c7a08edceaec","observation_id":"ffa0ac7f-8ca5-4ddc-8a05-4a5485238e8e","resolution":{"observed_at":"2026-08-09T22:24:13.508183Z","resolver_source":"doi","status":"verified_exact"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-20T06:33:59.587034+00:00","source":"crossref"},{"observed_at":"2026-08-20T06:33:54.927442+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"arxiv_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-09T22:24:15.761163Z","title":"Entropy- based genetic feature engineering and multi-classifier fusion for anomaly detection in vehicle controller area networks,","venue":null,"work_id":"78cbf4e5-488a-439e-abed-20b09cad7ed4","year":2025},"citing_paper":{"arxiv_id":"2501.18821","last_updated":"2025-06-05T21:37:44Z","snapshot_observed_at":"2026-08-20T04:34:32.022188Z","submitted_at":"2025-01-31T00:36:08Z","title":"An Optimal Cascade Feature-Level Spatiotemporal Fusion Strategy for Anomaly Detection in CAN Bus","version":3},"reference_index":9,"source":"pdf_text","source_observed_at":"2026-08-09T22:24:13.366199Z"},"links":{"citing_paper":"/paper/2501.18821"},"observation_digest":"sha256:3de46768215b6a6a5442401344423e761054201874d799d7ab0ed3d08fbf4a17","observation_id":"f0a50c28-714b-48bf-8d67-283bdd2b7edd","resolution":{"observed_at":"2026-08-09T22:24:15.766053Z","resolver_source":"arxiv_id_nonexistent","status":"verified_exact"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-20T06:33:59.587034+00:00","source":"crossref"},{"observed_at":"2026-08-20T06:33:54.927442+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"arxiv_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-09T22:24:15.618426Z","title":"Novel deep learning-enabled LSTM autoencoder architecture for discovering anomalous events from intelligent transportation systems,","venue":null,"work_id":"add55318-ee76-4eec-bda9-4745c08b11f4","year":2021},"citing_paper":{"arxiv_id":"2501.18821","last_updated":"2025-06-05T21:37:44Z","snapshot_observed_at":"2026-08-20T04:34:32.022188Z","submitted_at":"2025-01-31T00:36:08Z","title":"An Optimal Cascade Feature-Level Spatiotemporal Fusion Strategy for Anomaly Detection in CAN Bus","version":3},"reference_index":10,"source":"pdf_text","source_observed_at":"2026-08-09T22:24:13.368700Z"},"links":{"citing_paper":"/paper/2501.18821"},"observation_digest":"sha256:2b1488c3fc319a659e10f6794f14bdd72cdb9384171a23f062f503b43c8c5976","observation_id":"289b7005-3b8e-45c7-8cdc-8d0d06eb531c","resolution":{"observed_at":"2026-08-09T22:24:15.621361Z","resolver_source":"arxiv_id_nonexistent","status":"verified_exact"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-20T06:33:59.587034+00:00","source":"crossref"},{"observed_at":"2026-08-20T06:33:54.927442+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":"2026-08-09T22:24:16.871969Z","title":"Self-supervised anomaly detection for in- vehicle network using noised pseudo normal data,","venue":null,"work_id":"bc950cfa-369f-4dda-967b-fa64e53df7f4","year":null},"citing_paper":{"arxiv_id":"2501.18821","last_updated":"2025-06-05T21:37:44Z","snapshot_observed_at":"2026-08-20T04:34:32.022188Z","submitted_at":"2025-01-31T00:36:08Z","title":"An Optimal Cascade Feature-Level Spatiotemporal Fusion Strategy for Anomaly Detection in CAN Bus","version":3},"reference_index":11,"source":"pdf_text","source_observed_at":"2026-08-09T22:24:13.371259Z"},"links":{"citing_paper":"/paper/2501.18821"},"observation_digest":"sha256:c8d7a27b6fca9274ae4bba54240b67f3347cd29e87294cb98935760f03f5b315","observation_id":"135f1c1e-2ca3-4cd1-81f3-0f61255c31ad","resolution":{"observed_at":"2026-08-09T22:24:16.875319Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-20T06:33:59.587034+00:00","source":"crossref"},{"observed_at":"2026-08-20T06:33:54.927442+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":"2026-08-09T22:24:16.862842Z","title":"A federated learning framework for cyberattack detection in vehicular sensor networks,","venue":null,"work_id":"c4ae2484-dfd6-4d49-aef3-e3d18b22dd8a","year":null},"citing_paper":{"arxiv_id":"2501.18821","last_updated":"2025-06-05T21:37:44Z","snapshot_observed_at":"2026-08-20T04:34:32.022188Z","submitted_at":"2025-01-31T00:36:08Z","title":"An Optimal Cascade Feature-Level Spatiotemporal Fusion Strategy for Anomaly Detection in CAN Bus","version":3},"reference_index":12,"source":"pdf_text","source_observed_at":"2026-08-09T22:24:13.376996Z"},"links":{"citing_paper":"/paper/2501.18821"},"observation_digest":"sha256:f4a1d1f10143c6f3ab9481f54a0232b98c2040016b69c8c8ba7291d4733ad6ce","observation_id":"5e56badb-8d77-4744-8858-51154bbba6fa","resolution":{"observed_at":"2026-08-09T22:24:16.867674Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-20T06:33:59.587034+00:00","source":"crossref"},{"observed_at":"2026-08-20T06:33:54.927442+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"arxiv_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-09T22:24:15.292513Z","title":"MGA-IDS: Optimal feature subset selection for anomaly detection framework on in-vehicle networks- CAN bus based on genetic algorithm and intrusion detection approach,","venue":null,"work_id":"76127deb-36a8-41b8-92fe-6c2399e87f51","year":2022},"citing_paper":{"arxiv_id":"2501.18821","last_updated":"2025-06-05T21:37:44Z","snapshot_observed_at":"2026-08-20T04:34:32.022188Z","submitted_at":"2025-01-31T00:36:08Z","title":"An Optimal Cascade Feature-Level Spatiotemporal Fusion Strategy for Anomaly Detection in CAN Bus","version":3},"reference_index":13,"source":"pdf_text","source_observed_at":"2026-08-09T22:24:13.382517Z"},"links":{"citing_paper":"/paper/2501.18821"},"observation_digest":"sha256:cd0a66a069e1e5e0a52808879c0f4515a1b0ab7ccf3ca9a871bae81e0dd7a29f","observation_id":"0acce5f2-6ad2-4161-a80a-c0579fc46989","resolution":{"observed_at":"2026-08-09T22:24:15.295762Z","resolver_source":"arxiv_id_nonexistent","status":"verified_exact"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-20T06:33:59.587034+00:00","source":"crossref"},{"observed_at":"2026-08-20T06:33:54.927442+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":"10.1016/j.dcan.2022.04.021","metadata_source":"openalex","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-10T05:30:23.456663Z","title":"A novel intrusion detection model for the can bus packet of in-vehicle network based on attention mechanism and autoencoder,","venue":"Digital Communications and Networks","work_id":"120b060e-3052-4ddb-ba0e-e1f423ce5f55","year":2023},"citing_paper":{"arxiv_id":"2501.18821","last_updated":"2025-06-05T21:37:44Z","snapshot_observed_at":"2026-08-20T04:34:32.022188Z","submitted_at":"2025-01-31T00:36:08Z","title":"An Optimal Cascade Feature-Level Spatiotemporal Fusion Strategy for Anomaly Detection in CAN Bus","version":3},"reference_index":14,"source":"pdf_text","source_observed_at":"2026-08-09T22:24:13.384876Z"},"links":{"citing_paper":"/paper/2501.18821"},"observation_digest":"sha256:5f133151f182ba2d91a11393c92ba5500f31de4fc0e7ad69db6a506db4d7ec6a","observation_id":"741f6e3b-df56-4656-961e-b8cfbde11e71","resolution":{"observed_at":"2026-08-09T22:24:13.491529Z","resolver_source":"doi","status":"verified_exact"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-20T06:33:59.587034+00:00","source":"crossref"},{"observed_at":"2026-08-20T06:33:54.927442+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"arxiv_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-09T22:24:15.150370Z","title":"OTIDS: A novel intrusion detection system for in-vehicle network by using remote frame,","venue":null,"work_id":"8a53b49a-d4c2-48fe-9c8d-af34b0f29082","year":2017},"citing_paper":{"arxiv_id":"2501.18821","last_updated":"2025-06-05T21:37:44Z","snapshot_observed_at":"2026-08-20T04:34:32.022188Z","submitted_at":"2025-01-31T00:36:08Z","title":"An Optimal Cascade Feature-Level Spatiotemporal Fusion Strategy for Anomaly Detection in CAN Bus","version":3},"reference_index":15,"source":"pdf_text","source_observed_at":"2026-08-09T22:24:13.387560Z"},"links":{"citing_paper":"/paper/2501.18821"},"observation_digest":"sha256:93c285ceaffa08c511fbd9561ee62529e66a6e7f8a2c807bb72038fd5b803697","observation_id":"452f1a16-a9f9-4930-833e-47e9b49d1ace","resolution":{"observed_at":"2026-08-09T22:24:15.153591Z","resolver_source":"arxiv_id_nonexistent","status":"verified_exact"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-20T06:33:59.587034+00:00","source":"crossref"},{"observed_at":"2026-08-20T06:33:54.927442+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":"2026-08-09T22:24:16.855635Z","title":"Deep learning-based anomaly detection for connected autonomous vehicles using spatiotemporal information,","venue":null,"work_id":"1d7f4ec9-1ff7-49ba-8964-2d9626b40970","year":null},"citing_paper":{"arxiv_id":"2501.18821","last_updated":"2025-06-05T21:37:44Z","snapshot_observed_at":"2026-08-20T04:34:32.022188Z","submitted_at":"2025-01-31T00:36:08Z","title":"An Optimal Cascade Feature-Level Spatiotemporal Fusion Strategy for Anomaly Detection in CAN Bus","version":3},"reference_index":16,"source":"pdf_text","source_observed_at":"2026-08-09T22:24:13.390359Z"},"links":{"citing_paper":"/paper/2501.18821"},"observation_digest":"sha256:498a81843c64d837d2d432ef1f5ecb47c374f099ee573b4a69ca71d9c592bf28","observation_id":"e2df25f5-ec5c-431d-b27b-1215c1517dd8","resolution":{"observed_at":"2026-08-09T22:24:16.858119Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-20T06:33:59.587034+00:00","source":"crossref"},{"observed_at":"2026-08-20T06:33:54.927442+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":"10.1007/978-981-19-7874-6","metadata_source":"openalex","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-10T05:30:23.456663Z","title":"A lightweight intrusion detection model for in-vehicular CAN networks,","venue":"Lecture notes in networks and systems","work_id":"1defc6eb-7a9e-44be-a7f9-abaaa9c4de37","year":2023},"citing_paper":{"arxiv_id":"2501.18821","last_updated":"2025-06-05T21:37:44Z","snapshot_observed_at":"2026-08-20T04:34:32.022188Z","submitted_at":"2025-01-31T00:36:08Z","title":"An Optimal Cascade Feature-Level Spatiotemporal Fusion Strategy for Anomaly Detection in CAN Bus","version":3},"reference_index":17,"source":"pdf_text","source_observed_at":"2026-08-09T22:24:13.395763Z"},"links":{"citing_paper":"/paper/2501.18821"},"observation_digest":"sha256:13694e9cb92a2a8649efe0179a41907fd5fc03d799acd0a7f7d80a244b6fb751","observation_id":"6a6d4146-3b2b-445f-b840-56aa631b150c","resolution":{"observed_at":"2026-08-09T22:24:13.482900Z","resolver_source":"doi","status":"verified_exact"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-20T06:33:59.587034+00:00","source":"crossref"},{"observed_at":"2026-08-20T06:33:54.927442+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"arxiv_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-09T22:24:14.838083Z","title":"Multi-order feature interaction-aware intrusion detection scheme for ensuring cyber security of intelligent connected vehicles,","venue":null,"work_id":"888ff996-5b95-41b9-b060-2d2904490f41","year":2024},"citing_paper":{"arxiv_id":"2501.18821","last_updated":"2025-06-05T21:37:44Z","snapshot_observed_at":"2026-08-20T04:34:32.022188Z","submitted_at":"2025-01-31T00:36:08Z","title":"An Optimal Cascade Feature-Level Spatiotemporal Fusion Strategy for Anomaly Detection in CAN Bus","version":3},"reference_index":18,"source":"pdf_text","source_observed_at":"2026-08-09T22:24:13.398432Z"},"links":{"citing_paper":"/paper/2501.18821"},"observation_digest":"sha256:7caa3b3bcd162b5fbd9b48d557b31956306f222626e182be754b06bf25f2ac25","observation_id":"a7e4b20f-17e4-4e2e-988f-66bebfdb0b05","resolution":{"observed_at":"2026-08-09T22:24:14.841272Z","resolver_source":"arxiv_id_nonexistent","status":"malformed_identifier"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-20T06:33:59.587034+00:00","source":"crossref"},{"observed_at":"2026-08-20T06:33:54.927442+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"arxiv_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-09T22:24:14.684007Z","title":"Sustainable and lightweight domain-based intrusion detection system for in-vehicle network,","venue":null,"work_id":"d4041eb6-fae8-4244-9b97-0f9e45506134","year":2024},"citing_paper":{"arxiv_id":"2501.18821","last_updated":"2025-06-05T21:37:44Z","snapshot_observed_at":"2026-08-20T04:34:32.022188Z","submitted_at":"2025-01-31T00:36:08Z","title":"An Optimal Cascade Feature-Level Spatiotemporal Fusion Strategy for Anomaly Detection in CAN Bus","version":3},"reference_index":19,"source":"pdf_text","source_observed_at":"2026-08-09T22:24:13.401101Z"},"links":{"citing_paper":"/paper/2501.18821"},"observation_digest":"sha256:8a44e71154964f4f9c98cae1f76db0e416ab7ec68a47d44034c365b59a48ad6d","observation_id":"8a685f8c-44f7-4cd4-973d-45b78c54955d","resolution":{"observed_at":"2026-08-09T22:24:14.686762Z","resolver_source":"arxiv_id_nonexistent","status":"malformed_identifier"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-20T06:33:59.587034+00:00","source":"crossref"},{"observed_at":"2026-08-20T06:33:54.927442+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":"2026-08-09T22:24:13.403840Z","title":"SMOTE: Synthetic minority over-sampling technique,","venue":null,"work_id":null,"year":2002},"citing_paper":{"arxiv_id":"2501.18821","last_updated":"2025-06-05T21:37:44Z","snapshot_observed_at":"2026-08-20T04:34:32.022188Z","submitted_at":"2025-01-31T00:36:08Z","title":"An Optimal Cascade Feature-Level Spatiotemporal Fusion Strategy for Anomaly Detection in CAN Bus","version":3},"reference_index":20,"source":"pdf_text","source_observed_at":"2026-08-09T22:24:13.403840Z"},"links":{"citing_paper":"/paper/2501.18821"},"observation_digest":"sha256:9dbaf9db381965b684da9d06481132ed2d7cb909d172a1e4408a765e3caaef4d","observation_id":"063860c3-5c29-4950-93e1-0141561378e0","resolution":{"observed_at":"2026-08-09T22:24:13.403840Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"1512.03385","last_updated":"2015-12-10T19:51:55Z","snapshot_observed_at":"2026-07-06T04:39:28.429064Z","submitted_at":"2015-12-10T19:51:55Z","title":"Deep Residual Learning for Image Recognition","version":1},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"1512.03385","snapshot_observed_at":"2026-08-09T22:24:13.406664Z","title":"Deep residual learning for image recognition,","venue":null,"work_id":null,"year":2015},"citing_paper":{"arxiv_id":"2501.18821","last_updated":"2025-06-05T21:37:44Z","snapshot_observed_at":"2026-08-20T04:34:32.022188Z","submitted_at":"2025-01-31T00:36:08Z","title":"An Optimal Cascade Feature-Level Spatiotemporal Fusion Strategy for Anomaly Detection in CAN Bus","version":3},"reference_index":21,"source":"pdf_text","source_observed_at":"2026-08-09T22:24:13.406664Z"},"links":{"cited_paper":"/paper/1512.03385","citing_paper":"/paper/2501.18821"},"observation_digest":"sha256:0f31de0700cf47c6304db282b192fb6fe620170e109282f33dac2b326bdf75a7","observation_id":"c390dae9-a79d-4242-99ee-3e0a09c7d835","resolution":{"observed_at":"2026-08-09T22:24:13.406664Z","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":"arxiv_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-09T22:24:14.520863Z","title":"Forecasting vegetation behavior based on PlanetScope time series data using RNN-based models,","venue":null,"work_id":"0343b8c4-0019-407d-b1db-a0c7edca9a38","year":2024},"citing_paper":{"arxiv_id":"2501.18821","last_updated":"2025-06-05T21:37:44Z","snapshot_observed_at":"2026-08-20T04:34:32.022188Z","submitted_at":"2025-01-31T00:36:08Z","title":"An Optimal Cascade Feature-Level Spatiotemporal Fusion Strategy for Anomaly Detection in CAN Bus","version":3},"reference_index":22,"source":"pdf_text","source_observed_at":"2026-08-09T22:24:13.409780Z"},"links":{"citing_paper":"/paper/2501.18821"},"observation_digest":"sha256:afff3a9980f27aaf5b0d28ada9fb22e6533f7ff5c3f156e6dd2a39051f9b6088","observation_id":"2436cb06-6d7c-46ff-919a-5b92509fb592","resolution":{"observed_at":"2026-08-09T22:24:14.523942Z","resolver_source":"arxiv_id_nonexistent","status":"verified_exact"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-20T06:33:59.587034+00:00","source":"crossref"},{"observed_at":"2026-08-20T06:33:54.927442+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":"2026-08-09T22:24:13.412520Z","title":"Long short-term memory,","venue":null,"work_id":null,"year":1997},"citing_paper":{"arxiv_id":"2501.18821","last_updated":"2025-06-05T21:37:44Z","snapshot_observed_at":"2026-08-20T04:34:32.022188Z","submitted_at":"2025-01-31T00:36:08Z","title":"An Optimal Cascade Feature-Level Spatiotemporal Fusion Strategy for Anomaly Detection in CAN Bus","version":3},"reference_index":23,"source":"pdf_text","source_observed_at":"2026-08-09T22:24:13.412520Z"},"links":{"citing_paper":"/paper/2501.18821"},"observation_digest":"sha256:0f3c0eee3a124aa549586ae0b0cf0c00a013f68890135d21059629ad570c071e","observation_id":"13a8015e-f963-4daf-a52f-d5b8fb2400eb","resolution":{"observed_at":"2026-08-09T22:24:13.412520Z","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":"arxiv_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-09T22:24:14.341902Z","title":"Gate-variants of gated recurrent unit (GRU) neural networks,","venue":null,"work_id":"e4b281bf-6d39-4fa5-a6f1-306e0ca52311","year":2017},"citing_paper":{"arxiv_id":"2501.18821","last_updated":"2025-06-05T21:37:44Z","snapshot_observed_at":"2026-08-20T04:34:32.022188Z","submitted_at":"2025-01-31T00:36:08Z","title":"An Optimal Cascade Feature-Level Spatiotemporal Fusion Strategy for Anomaly Detection in CAN Bus","version":3},"reference_index":24,"source":"pdf_text","source_observed_at":"2026-08-09T22:24:13.415355Z"},"links":{"citing_paper":"/paper/2501.18821"},"observation_digest":"sha256:cf553baba82265adc95333048ab20419049138012d8ee9f01247f1806b0e6dde","observation_id":"5672ab52-20a5-4547-aac3-1d5b9e4ff4da","resolution":{"observed_at":"2026-08-09T22:24:14.344779Z","resolver_source":"arxiv_id_nonexistent","status":"verified_exact"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-20T06:33:59.587034+00:00","source":"crossref"},{"observed_at":"2026-08-20T06:33:54.927442+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"2405.04517","last_updated":"2024-12-06T15:42:07Z","snapshot_observed_at":"2026-08-16T13:54:34.627474Z","submitted_at":"2024-05-07T17:50:21Z","title":"xLSTM: Extended Long Short-Term Memory","version":2},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2405.04517","snapshot_observed_at":"2026-08-09T22:24:13.418019Z","title":"xLSTM: Extended long short-term memory,","venue":null,"work_id":null,"year":2024},"citing_paper":{"arxiv_id":"2501.18821","last_updated":"2025-06-05T21:37:44Z","snapshot_observed_at":"2026-08-20T04:34:32.022188Z","submitted_at":"2025-01-31T00:36:08Z","title":"An Optimal Cascade Feature-Level Spatiotemporal Fusion Strategy for Anomaly Detection in CAN Bus","version":3},"reference_index":25,"source":"pdf_text","source_observed_at":"2026-08-09T22:24:13.418019Z"},"links":{"cited_paper":"/paper/2405.04517","citing_paper":"/paper/2501.18821"},"observation_digest":"sha256:0cd66a92b74aa404d8724ab99e981b158193d19d451bd11f6b64682ff00b6fe4","observation_id":"1d1c578c-1d5b-4731-9fe2-0bb52b6d3294","resolution":{"observed_at":"2026-08-09T22:24:13.418019Z","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":"arxiv_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-09T22:24:14.157791Z","title":"A novel model for student’s mental health monitoring based on hard and soft data fusion,","venue":null,"work_id":"fde3f0fb-55e1-4727-bffb-1b36e1a354e5","year":2023},"citing_paper":{"arxiv_id":"2501.18821","last_updated":"2025-06-05T21:37:44Z","snapshot_observed_at":"2026-08-20T04:34:32.022188Z","submitted_at":"2025-01-31T00:36:08Z","title":"An Optimal Cascade Feature-Level Spatiotemporal Fusion Strategy for Anomaly Detection in CAN Bus","version":3},"reference_index":26,"source":"pdf_text","source_observed_at":"2026-08-09T22:24:13.421647Z"},"links":{"citing_paper":"/paper/2501.18821"},"observation_digest":"sha256:6c6e127681197bd5b3af65b9b9eb86b20e13b16f97ce44b3c971a7b8363e3ed4","observation_id":"3a22da98-ff1e-4c7d-bca1-8a8d4837bd02","resolution":{"observed_at":"2026-08-09T22:24:14.160611Z","resolver_source":"arxiv_id_nonexistent","status":"verified_exact"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-20T06:33:59.587034+00:00","source":"crossref"},{"observed_at":"2026-08-20T06:33:54.927442+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"arxiv_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-09T22:24:13.998121Z","title":"1D-CNN-IDS: 1D CNN-based intrusion detection system for IIoT,","venue":null,"work_id":"a5760231-7861-48ee-b0f3-6dfeca918a8d","year":2024},"citing_paper":{"arxiv_id":"2501.18821","last_updated":"2025-06-05T21:37:44Z","snapshot_observed_at":"2026-08-20T04:34:32.022188Z","submitted_at":"2025-01-31T00:36:08Z","title":"An Optimal Cascade Feature-Level Spatiotemporal Fusion Strategy for Anomaly Detection in CAN Bus","version":3},"reference_index":27,"source":"pdf_text","source_observed_at":"2026-08-09T22:24:13.424210Z"},"links":{"citing_paper":"/paper/2501.18821"},"observation_digest":"sha256:dd3b0e508f53fa4bc9c6b4d501303a1d4241ce413856357f30db4431a8a755d0","observation_id":"b94aca37-589f-4702-9b53-ce2b949c044c","resolution":{"observed_at":"2026-08-09T22:24:14.001062Z","resolver_source":"arxiv_id_nonexistent","status":"verified_exact"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-20T06:33:59.587034+00:00","source":"crossref"},{"observed_at":"2026-08-20T06:33:54.927442+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":"10.1201/9781420053098","metadata_source":"openalex","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-10T05:30:23.456663Z","title":"Liggins II, D","venue":null,"work_id":"5bc3e569-5c10-4bb1-9032-d983c8877e43","year":2009},"citing_paper":{"arxiv_id":"2501.18821","last_updated":"2025-06-05T21:37:44Z","snapshot_observed_at":"2026-08-20T04:34:32.022188Z","submitted_at":"2025-01-31T00:36:08Z","title":"An Optimal Cascade Feature-Level Spatiotemporal Fusion Strategy for Anomaly Detection in CAN Bus","version":3},"reference_index":28,"source":"pdf_text","source_observed_at":"2026-08-09T22:24:13.426744Z"},"links":{"citing_paper":"/paper/2501.18821"},"observation_digest":"sha256:a9f26ca3c64a12fb16f6435428a982c4281ddd4e490576c7b9b3366e1eaf9e6f","observation_id":"ab208047-4c42-4e49-a751-55ee626d1a45","resolution":{"observed_at":"2026-08-09T22:24:13.465292Z","resolver_source":"doi","status":"verified_exact"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-20T06:33:59.587034+00:00","source":"crossref"},{"observed_at":"2026-08-20T06:33:54.927442+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"arxiv_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-09T22:24:13.701923Z","title":"Cascaded feature fusion with multi-level self-attention mechanism for object detection,","venue":null,"work_id":"a4ee1e4f-1aa8-4460-9045-6d00ad7d8f31","year":2023},"citing_paper":{"arxiv_id":"2501.18821","last_updated":"2025-06-05T21:37:44Z","snapshot_observed_at":"2026-08-20T04:34:32.022188Z","submitted_at":"2025-01-31T00:36:08Z","title":"An Optimal Cascade Feature-Level Spatiotemporal Fusion Strategy for Anomaly Detection in CAN Bus","version":3},"reference_index":29,"source":"pdf_text","source_observed_at":"2026-08-09T22:24:13.429439Z"},"links":{"citing_paper":"/paper/2501.18821"},"observation_digest":"sha256:52d16010f5f7cbdada886039e48bb8fd4cd6a8104b25395777e3cc4f9258a57e","observation_id":"ed83aadc-ed91-4e15-9c42-2df668eb72b6","resolution":{"observed_at":"2026-08-09T22:24:13.705022Z","resolver_source":"arxiv_id_nonexistent","status":"verified_exact"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-20T06:33:59.587034+00:00","source":"crossref"},{"observed_at":"2026-08-20T06:33:54.927442+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":"2026-08-09T22:24:16.847866Z","title":"HCRL website,","venue":null,"work_id":"7f86177a-e642-4512-8265-634f5c90b26b","year":2024},"citing_paper":{"arxiv_id":"2501.18821","last_updated":"2025-06-05T21:37:44Z","snapshot_observed_at":"2026-08-20T04:34:32.022188Z","submitted_at":"2025-01-31T00:36:08Z","title":"An Optimal Cascade Feature-Level Spatiotemporal Fusion Strategy for Anomaly Detection in CAN Bus","version":3},"reference_index":30,"source":"pdf_text","source_observed_at":"2026-08-09T22:24:13.432113Z"},"links":{"citing_paper":"/paper/2501.18821"},"observation_digest":"sha256:c1135ede1daca3e63f1e7093b3d29fb57983fba0a7889dd070458318123d383d","observation_id":"4c98b92b-3f96-4770-885b-b1169d564abe","resolution":{"observed_at":"2026-08-09T22:24:16.850588Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-20T06:33:59.587034+00:00","source":"crossref"},{"observed_at":"2026-08-20T06:33:54.927442+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":"2026-08-09T22:24:13.434745Z","title":"Approximate statistical tests for comparing supervised classification learning algorithms,","venue":null,"work_id":null,"year":1923},"citing_paper":{"arxiv_id":"2501.18821","last_updated":"2025-06-05T21:37:44Z","snapshot_observed_at":"2026-08-20T04:34:32.022188Z","submitted_at":"2025-01-31T00:36:08Z","title":"An Optimal Cascade Feature-Level Spatiotemporal Fusion Strategy for Anomaly Detection in CAN Bus","version":3},"reference_index":31,"source":"pdf_text","source_observed_at":"2026-08-09T22:24:13.434745Z"},"links":{"citing_paper":"/paper/2501.18821"},"observation_digest":"sha256:c04d7729d5e38a8dc58f7164bea5db10a7b8dd634edc2f3c45612f28344c6bd3","observation_id":"f33a8bab-bd26-4a5e-a8a4-e27359bb2547","resolution":{"observed_at":"2026-08-09T22:24:13.434745Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2404.19756","last_updated":"2025-02-09T21:09:09Z","snapshot_observed_at":"2026-08-15T02:33:31.807561Z","submitted_at":"2024-04-30T17:58:29Z","title":"KAN: Kolmogorov-Arnold Networks","version":5},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2404.19756","snapshot_observed_at":"2026-08-09T22:24:13.437630Z","title":"KAN: Kolmogorov-Arnold Networks,","venue":null,"work_id":null,"year":2024},"citing_paper":{"arxiv_id":"2501.18821","last_updated":"2025-06-05T21:37:44Z","snapshot_observed_at":"2026-08-20T04:34:32.022188Z","submitted_at":"2025-01-31T00:36:08Z","title":"An Optimal Cascade Feature-Level Spatiotemporal Fusion Strategy for Anomaly Detection in CAN Bus","version":3},"reference_index":32,"source":"pdf_text","source_observed_at":"2026-08-09T22:24:13.437630Z"},"links":{"cited_paper":"/paper/2404.19756","citing_paper":"/paper/2501.18821"},"observation_digest":"sha256:098df87016a240653d4595b85719ad799fc33515ef84a214604551ef425da11c","observation_id":"b81dc706-4de6-49a7-a5e8-5ade71758127","resolution":{"observed_at":"2026-08-09T22:24:13.437630Z","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":"arxiv_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-09T22:24:15.465846Z","title":"Available: https://doi.org/10.1109/TVT.2021.3051026","venue":null,"work_id":"3b906d11-8560-4710-9eea-3a9f6627ec78","year":2021},"citing_paper":{"arxiv_id":"2501.18821","last_updated":"2025-06-05T21:37:44Z","snapshot_observed_at":"2026-08-20T04:34:32.022188Z","submitted_at":"2025-01-31T00:36:08Z","title":"An Optimal Cascade Feature-Level Spatiotemporal Fusion Strategy for Anomaly Detection in CAN Bus","version":3},"reference_index":2021,"source":"pdf_text","source_observed_at":"2026-08-09T22:24:13.374230Z"},"links":{"citing_paper":"/paper/2501.18821"},"observation_digest":"sha256:28b5d5f40b751ed430341ca111a8edc7266d6b079dfa906f2d20dadeace87920","observation_id":"a4c528a1-b757-4146-981d-5610100958d8","resolution":{"observed_at":"2026-08-09T22:24:15.470626Z","resolver_source":"arxiv_id_nonexistent","status":"verified_exact"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-20T06:33:59.587034+00:00","source":"crossref"},{"observed_at":"2026-08-20T06:33:54.927442+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":"10.1007/s40747-022-00705-w","metadata_source":"openalex","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-10T05:30:23.456663Z","title":"Available: https://doi.org/10.1007/s40747-022-00705-w","venue":"Complex & Intelligent Systems","work_id":"60b03e0d-4f66-4e0e-a4cc-68ff7243ac58","year":null},"citing_paper":{"arxiv_id":"2501.18821","last_updated":"2025-06-05T21:37:44Z","snapshot_observed_at":"2026-08-20T04:34:32.022188Z","submitted_at":"2025-01-31T00:36:08Z","title":"An Optimal Cascade Feature-Level Spatiotemporal Fusion Strategy for Anomaly Detection in CAN Bus","version":3},"reference_index":2022,"source":"pdf_text","source_observed_at":"2026-08-09T22:24:13.379607Z"},"links":{"citing_paper":"/paper/2501.18821"},"observation_digest":"sha256:967555d57928ee8ed6ddf88af80358c94cc179037369de648f1cd28b154a67a7","observation_id":"f64d5924-933d-4c1a-a827-1263f1155a8d","resolution":{"observed_at":"2026-08-09T22:24:13.499745Z","resolver_source":"doi","status":"verified_exact"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-20T06:33:59.587034+00:00","source":"crossref"},{"observed_at":"2026-08-20T06:33:54.927442+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"arxiv_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-09T22:24:15.000411Z","title":"Available: https://doi.org/10.1109/TITS.2023.3286611","venue":null,"work_id":"f198c044-65a5-4306-aa11-ca563e3826b0","year":2023},"citing_paper":{"arxiv_id":"2501.18821","last_updated":"2025-06-05T21:37:44Z","snapshot_observed_at":"2026-08-20T04:34:32.022188Z","submitted_at":"2025-01-31T00:36:08Z","title":"An Optimal Cascade Feature-Level Spatiotemporal Fusion Strategy for Anomaly Detection in CAN Bus","version":3},"reference_index":2023,"source":"pdf_text","source_observed_at":"2026-08-09T22:24:13.393078Z"},"links":{"citing_paper":"/paper/2501.18821"},"observation_digest":"sha256:17ef82513217b99b1d88c258c00559fbe9cb24e5b6e0ee351be5f53a95d312e8","observation_id":"c1afde49-dfc9-4a99-8280-be976142acfe","resolution":{"observed_at":"2026-08-09T22:24:15.003384Z","resolver_source":"arxiv_id_nonexistent","status":"verified_exact"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-20T06:33:59.587034+00:00","source":"crossref"},{"observed_at":"2026-08-20T06:33:54.927442+00:00","source":"retraction_watch"}],"state":"measured"}}],"paper":{"arxiv_id":"2501.18821","last_updated":"2025-06-05T21:37:44Z","latest_version":3,"primary_category":"cs.LG","snapshot_observed_at":"2026-08-20T04:34:32.022188Z","submitted_at":"2025-01-31T00:36:08Z","title":"An Optimal Cascade Feature-Level Spatiotemporal Fusion Strategy for Anomaly Detection in CAN Bus"},"reference_resolution":{"displayed":35,"state_counts":{"malformed_identifier":2,"metadata_mismatch":0,"parse_uncertain":0,"unresolved":6,"verified_exact":23,"verified_fuzzy":4},"total_outbound_references":35},"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":"2026-08-20T06:33:59.587034+00:00","source":"crossref"},{"observed_at":"2026-08-20T06:33:54.927442+00:00","source":"retraction_watch"}],"thesis":"As of 20 August 2026, this Paper Citation Record lists 35 of 35 outbound references and 0 inbound Pith citation observations for arXiv:2501.18821."}