{"as_of":"2026-08-11T15:02:00Z","caps":{"database_statements":6,"inbound":100,"outbound":100},"context_digest":"sha256:0722779ce0b257d8b5bc73736fca5a42b5ff7252db574f17b7316088095244ac","coverage":[{"denominator":61,"lane":"reference_resolution","note":"Typed states for the displayed outbound observations.","records_observed":61,"source":"paper_references, paper_reference_links","source_observed_at":"2026-08-10T04:29:49.489820Z","state":"measured"},{"denominator":61,"lane":"standing_notices","note":"One-hop event checks from named stored sources.","records_observed":61,"source":"scholarly_work_events, retraction_status_cache","source_observed_at":"2026-08-11T06:34:44.6726+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/2501.17977/citation-record","integrity":"/paper/2501.17977/integrity","json":"/paper/2501.17977/citation-record.json","paper":"/paper/2501.17977"},"outbound":[{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-10T04:29:50.168262Z","title":"3d radar and camera co-calibration: A flexible and accurate method for target-based extrinsic calibration,","venue":null,"work_id":"565b875e-be45-40bf-84ab-69caff62d47a","year":2023},"citing_paper":{"arxiv_id":"2501.17977","last_updated":"2025-01-29T20:21:41Z","snapshot_observed_at":"2026-08-10T04:23:56.826114Z","submitted_at":"2025-01-29T20:21:41Z","title":"TransRAD: Retentive Vision Transformer for Enhanced Radar Object Detection","version":1},"reference_index":1,"source":"pdf_text","source_observed_at":"2026-08-10T04:29:49.260331Z"},"links":{"citing_paper":"/paper/2501.17977"},"observation_digest":"sha256:1820e627d85d2df7926aa353933889a68459c11c2b5222a42b2d1626c8044d0f","observation_id":"791294bc-c93b-460c-9f01-071cd604e1aa","resolution":{"observed_at":"2026-08-10T04:29:50.172584Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-11T06:34:44.6726+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-11T06:34:44.6726+00:00","source":"crossref"},{"observed_at":"2026-08-11T06:34:36.301508+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":"2026-08-10T04:29:50.156557Z","title":"A comprehensive review on limitations of autonomous driving and its impact on accidents and collisions,","venue":null,"work_id":"c5ad93aa-988d-454a-b6a8-73f0498eecd5","year":2023},"citing_paper":{"arxiv_id":"2501.17977","last_updated":"2025-01-29T20:21:41Z","snapshot_observed_at":"2026-08-10T04:23:56.826114Z","submitted_at":"2025-01-29T20:21:41Z","title":"TransRAD: Retentive Vision Transformer for Enhanced Radar Object Detection","version":1},"reference_index":2,"source":"pdf_text","source_observed_at":"2026-08-10T04:29:49.264742Z"},"links":{"citing_paper":"/paper/2501.17977"},"observation_digest":"sha256:ff1a4fd81d6b1595f0b86794713fee55da4f908c2fa24203c5294ac25eee4791","observation_id":"f568f5a4-be59-43b1-9f92-3a4cd6cea2a7","resolution":{"observed_at":"2026-08-10T04:29:50.160537Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-11T06:34:44.6726+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-11T06:34:44.6726+00:00","source":"crossref"},{"observed_at":"2026-08-11T06:34:36.301508+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":"2026-08-10T04:29:50.144247Z","title":"Deep learning-based robust multi- object tracking via fusion of mmwave radar and camera sensors,","venue":null,"work_id":"d7699278-880b-4324-902b-2cf64b5ab9ba","year":2024},"citing_paper":{"arxiv_id":"2501.17977","last_updated":"2025-01-29T20:21:41Z","snapshot_observed_at":"2026-08-10T04:23:56.826114Z","submitted_at":"2025-01-29T20:21:41Z","title":"TransRAD: Retentive Vision Transformer for Enhanced Radar Object Detection","version":1},"reference_index":3,"source":"pdf_text","source_observed_at":"2026-08-10T04:29:49.268828Z"},"links":{"citing_paper":"/paper/2501.17977"},"observation_digest":"sha256:3c6edd4181c0eb12728a249c6444a3893d26bb08ea487df8848c27d856f1d20c","observation_id":"1ebdb2cc-bd60-479f-9edc-8dbd61da9758","resolution":{"observed_at":"2026-08-10T04:29:50.148495Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-11T06:34:44.6726+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-11T06:34:44.6726+00:00","source":"crossref"},{"observed_at":"2026-08-11T06:34:36.301508+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":"2026-08-10T04:29:50.131616Z","title":"Robust multiobject tracking using mmwave radar-camera sensor fusion,","venue":null,"work_id":"0a0e0b25-a420-4452-b4ea-ba301c8704a8","year":2022},"citing_paper":{"arxiv_id":"2501.17977","last_updated":"2025-01-29T20:21:41Z","snapshot_observed_at":"2026-08-10T04:23:56.826114Z","submitted_at":"2025-01-29T20:21:41Z","title":"TransRAD: Retentive Vision Transformer for Enhanced Radar Object Detection","version":1},"reference_index":4,"source":"pdf_text","source_observed_at":"2026-08-10T04:29:49.272689Z"},"links":{"citing_paper":"/paper/2501.17977"},"observation_digest":"sha256:1f8d876f13c85ed8ac3398be8b3452632721f7978a824880697886f61018f3f4","observation_id":"387f4145-6867-41d2-b9fc-052f1091ba08","resolution":{"observed_at":"2026-08-10T04:29:50.136021Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-11T06:34:44.6726+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-11T06:34:44.6726+00:00","source":"crossref"},{"observed_at":"2026-08-11T06:34:36.301508+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":"2026-08-10T04:29:49.276707Z","title":"Ramp-cnn: A novel neural net- work for enhanced automotive radar object recognition,","venue":null,"work_id":null,"year":2020},"citing_paper":{"arxiv_id":"2501.17977","last_updated":"2025-01-29T20:21:41Z","snapshot_observed_at":"2026-08-10T04:23:56.826114Z","submitted_at":"2025-01-29T20:21:41Z","title":"TransRAD: Retentive Vision Transformer for Enhanced Radar Object Detection","version":1},"reference_index":5,"source":"pdf_text","source_observed_at":"2026-08-10T04:29:49.276707Z"},"links":{"citing_paper":"/paper/2501.17977"},"observation_digest":"sha256:f51bf5a1f078d71a87ec803a61213cf5c011b63f9a11c8961c5c8b41188d3b7b","observation_id":"92f3b5b8-682b-4f2c-bf3f-9c3f26085d50","resolution":{"observed_at":"2026-08-10T04:29:49.276707Z","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":"2026-08-10T04:29:49.280654Z","title":"K-radar: 4d radar object detection for autonomous driving in various weather conditions,","venue":null,"work_id":null,"year":2022},"citing_paper":{"arxiv_id":"2501.17977","last_updated":"2025-01-29T20:21:41Z","snapshot_observed_at":"2026-08-10T04:23:56.826114Z","submitted_at":"2025-01-29T20:21:41Z","title":"TransRAD: Retentive Vision Transformer for Enhanced Radar Object Detection","version":1},"reference_index":6,"source":"pdf_text","source_observed_at":"2026-08-10T04:29:49.280654Z"},"links":{"citing_paper":"/paper/2501.17977"},"observation_digest":"sha256:05ca816c643505be7ae5fd133650efee3c8cad0d456a56dda44b3af6dc260f9c","observation_id":"808e9242-df59-4856-9fcc-66aef347de9f","resolution":{"observed_at":"2026-08-10T04:29:49.280654Z","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":"2026-08-10T04:29:50.105233Z","title":"Online targetless radar-camera extrinsic calibra- tion based on the common features of radar and camera,","venue":null,"work_id":"94b07e20-060d-4cf3-a08d-81bfd719f2ec","year":2023},"citing_paper":{"arxiv_id":"2501.17977","last_updated":"2025-01-29T20:21:41Z","snapshot_observed_at":"2026-08-10T04:23:56.826114Z","submitted_at":"2025-01-29T20:21:41Z","title":"TransRAD: Retentive Vision Transformer for Enhanced Radar Object Detection","version":1},"reference_index":7,"source":"pdf_text","source_observed_at":"2026-08-10T04:29:49.285210Z"},"links":{"citing_paper":"/paper/2501.17977"},"observation_digest":"sha256:dc3a5147398119312eb1a4eeb86011f7dbbdb78f71594586beca90689e02591d","observation_id":"179628b8-b5f1-4594-bea6-a3518f13f8c6","resolution":{"observed_at":"2026-08-10T04:29:50.109140Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-11T06:34:44.6726+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-11T06:34:44.6726+00:00","source":"crossref"},{"observed_at":"2026-08-11T06:34:36.301508+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":"2026-08-10T04:29:50.093125Z","title":"Robust target recognition and tracking of self-driving cars with radar and camera information fusion under severe weather conditions,","venue":null,"work_id":"c3b5f9c2-6dec-4f11-abe1-ed1d6774e4c0","year":2021},"citing_paper":{"arxiv_id":"2501.17977","last_updated":"2025-01-29T20:21:41Z","snapshot_observed_at":"2026-08-10T04:23:56.826114Z","submitted_at":"2025-01-29T20:21:41Z","title":"TransRAD: Retentive Vision Transformer for Enhanced Radar Object Detection","version":1},"reference_index":8,"source":"pdf_text","source_observed_at":"2026-08-10T04:29:49.288933Z"},"links":{"citing_paper":"/paper/2501.17977"},"observation_digest":"sha256:7f1c92bce10b4d130f9dcffbada3e6b54dab75526683e1218f3ed3c458a73b65","observation_id":"82c5cc8e-63b1-4568-9c53-5e2f6a498454","resolution":{"observed_at":"2026-08-10T04:29:50.097492Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-11T06:34:44.6726+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-11T06:34:44.6726+00:00","source":"crossref"},{"observed_at":"2026-08-11T06:34:36.301508+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":"2026-08-10T04:29:50.080879Z","title":"Robust detection and tracking method for moving object based on radar and camera data fusion,","venue":null,"work_id":"a7b4e663-54ee-4947-b818-b156c3f36961","year":2021},"citing_paper":{"arxiv_id":"2501.17977","last_updated":"2025-01-29T20:21:41Z","snapshot_observed_at":"2026-08-10T04:23:56.826114Z","submitted_at":"2025-01-29T20:21:41Z","title":"TransRAD: Retentive Vision Transformer for Enhanced Radar Object Detection","version":1},"reference_index":9,"source":"pdf_text","source_observed_at":"2026-08-10T04:29:49.293072Z"},"links":{"citing_paper":"/paper/2501.17977"},"observation_digest":"sha256:fc95485730f9939dee4e882be237cf2d3960dedf6a18529765eba0682f1028b2","observation_id":"f961a4cb-ff0b-4ca8-b706-3212184f7b9e","resolution":{"observed_at":"2026-08-10T04:29:50.085147Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-11T06:34:44.6726+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-11T06:34:44.6726+00:00","source":"crossref"},{"observed_at":"2026-08-11T06:34:36.301508+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":"2026-08-10T04:29:50.068958Z","title":"Multi- view radar semantic segmentation,","venue":null,"work_id":"9f6f888e-96f8-4a5d-a090-434776264e68","year":2021},"citing_paper":{"arxiv_id":"2501.17977","last_updated":"2025-01-29T20:21:41Z","snapshot_observed_at":"2026-08-10T04:23:56.826114Z","submitted_at":"2025-01-29T20:21:41Z","title":"TransRAD: Retentive Vision Transformer for Enhanced Radar Object Detection","version":1},"reference_index":10,"source":"pdf_text","source_observed_at":"2026-08-10T04:29:49.297333Z"},"links":{"citing_paper":"/paper/2501.17977"},"observation_digest":"sha256:8463d2d390788221debb0cf02f1a3d65e5b5a6db6fcfa366811d756a48daf82f","observation_id":"8638a51a-1058-462d-9718-15a12e737ee5","resolution":{"observed_at":"2026-08-10T04:29:50.073031Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-11T06:34:44.6726+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-11T06:34:44.6726+00:00","source":"crossref"},{"observed_at":"2026-08-11T06:34:36.301508+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":"2026-08-10T04:29:50.057230Z","title":"Darod: A deep automotive radar object detector on range-doppler maps,","venue":null,"work_id":"b50a6c5d-367e-4a15-9d00-d452bb2cb152","year":2022},"citing_paper":{"arxiv_id":"2501.17977","last_updated":"2025-01-29T20:21:41Z","snapshot_observed_at":"2026-08-10T04:23:56.826114Z","submitted_at":"2025-01-29T20:21:41Z","title":"TransRAD: Retentive Vision Transformer for Enhanced Radar Object Detection","version":1},"reference_index":11,"source":"pdf_text","source_observed_at":"2026-08-10T04:29:49.301178Z"},"links":{"citing_paper":"/paper/2501.17977"},"observation_digest":"sha256:c49a67eb3493ef20526a5fdcb6bd9fd9670fbc2d2af2e6d3d8e06ab06c267788","observation_id":"88b0dba8-37ba-4d31-9deb-a39f8db2a1b9","resolution":{"observed_at":"2026-08-10T04:29:50.061208Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-11T06:34:44.6726+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-11T06:34:44.6726+00:00","source":"crossref"},{"observed_at":"2026-08-11T06:34:36.301508+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":"2026-08-10T04:29:50.044822Z","title":"Raddet: Range-azimuth- doppler based radar object detection for dynamic road users,","venue":null,"work_id":"f438d1f0-33a5-4b28-a157-29fe42ec312f","year":2021},"citing_paper":{"arxiv_id":"2501.17977","last_updated":"2025-01-29T20:21:41Z","snapshot_observed_at":"2026-08-10T04:23:56.826114Z","submitted_at":"2025-01-29T20:21:41Z","title":"TransRAD: Retentive Vision Transformer for Enhanced Radar Object Detection","version":1},"reference_index":12,"source":"pdf_text","source_observed_at":"2026-08-10T04:29:49.304922Z"},"links":{"citing_paper":"/paper/2501.17977"},"observation_digest":"sha256:f4c37928f287491f1705c1a47bc9037441871fa823f6eb9d0ebcb6e0f98bb8ee","observation_id":"142b2804-08eb-44fd-b615-6f99bb2b2d3d","resolution":{"observed_at":"2026-08-10T04:29:50.049066Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-11T06:34:44.6726+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-11T06:34:44.6726+00:00","source":"crossref"},{"observed_at":"2026-08-11T06:34:36.301508+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":"2026-08-10T04:29:50.032412Z","title":"Radarformer: Lightweight and accurate real-time radar object detection model,","venue":null,"work_id":"75eda684-9823-4724-9a55-fd1b7da03e69","year":2023},"citing_paper":{"arxiv_id":"2501.17977","last_updated":"2025-01-29T20:21:41Z","snapshot_observed_at":"2026-08-10T04:23:56.826114Z","submitted_at":"2025-01-29T20:21:41Z","title":"TransRAD: Retentive Vision Transformer for Enhanced Radar Object Detection","version":1},"reference_index":13,"source":"pdf_text","source_observed_at":"2026-08-10T04:29:49.308779Z"},"links":{"citing_paper":"/paper/2501.17977"},"observation_digest":"sha256:13c5ef38fe3bab7c906ae6ead10fe4facf8e86686676a9cdc2c3f1ff3601731e","observation_id":"120354bb-cb5c-4572-9e58-583f608a82e0","resolution":{"observed_at":"2026-08-10T04:29:50.037240Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-11T06:34:44.6726+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-11T06:34:44.6726+00:00","source":"crossref"},{"observed_at":"2026-08-11T06:34:36.301508+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":"2026-08-10T04:29:49.312402Z","title":"Raw high-definition radar for multi-task learning,","venue":null,"work_id":null,"year":2022},"citing_paper":{"arxiv_id":"2501.17977","last_updated":"2025-01-29T20:21:41Z","snapshot_observed_at":"2026-08-10T04:23:56.826114Z","submitted_at":"2025-01-29T20:21:41Z","title":"TransRAD: Retentive Vision Transformer for Enhanced Radar Object Detection","version":1},"reference_index":14,"source":"pdf_text","source_observed_at":"2026-08-10T04:29:49.312402Z"},"links":{"citing_paper":"/paper/2501.17977"},"observation_digest":"sha256:c59212f24f0f41878ceb943a83770f4e4bfc5442446b67dcf16f0d7df0a31542","observation_id":"2a3de1d2-0ca9-4172-ace1-f74d2ec89226","resolution":{"observed_at":"2026-08-10T04:29:49.312402Z","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":"2026-08-10T04:29:50.011701Z","title":"Deep-learning based multi-object detection and tracking using range-angle map in automotive radar sys- tems,","venue":null,"work_id":"97275a5f-f370-470b-b739-1cf3762457b0","year":2022},"citing_paper":{"arxiv_id":"2501.17977","last_updated":"2025-01-29T20:21:41Z","snapshot_observed_at":"2026-08-10T04:23:56.826114Z","submitted_at":"2025-01-29T20:21:41Z","title":"TransRAD: Retentive Vision Transformer for Enhanced Radar Object Detection","version":1},"reference_index":15,"source":"pdf_text","source_observed_at":"2026-08-10T04:29:49.316010Z"},"links":{"citing_paper":"/paper/2501.17977"},"observation_digest":"sha256:1357e1043a5f614f7921243e3e04e3677cbef4d6a8c77f9c11c88c85478be077","observation_id":"02857bf6-f36d-4181-b6f4-e9f3c786edd4","resolution":{"observed_at":"2026-08-10T04:29:50.016209Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-11T06:34:44.6726+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-11T06:34:44.6726+00:00","source":"crossref"},{"observed_at":"2026-08-11T06:34:36.301508+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":"2026-08-10T04:29:49.319655Z","title":"T-rodnet: Transformer for vehicular millimeter-wave radar object detection,","venue":null,"work_id":null,"year":2022},"citing_paper":{"arxiv_id":"2501.17977","last_updated":"2025-01-29T20:21:41Z","snapshot_observed_at":"2026-08-10T04:23:56.826114Z","submitted_at":"2025-01-29T20:21:41Z","title":"TransRAD: Retentive Vision Transformer for Enhanced Radar Object Detection","version":1},"reference_index":16,"source":"pdf_text","source_observed_at":"2026-08-10T04:29:49.319655Z"},"links":{"citing_paper":"/paper/2501.17977"},"observation_digest":"sha256:261737ad244e302029d2066d1991425b8938fa4dded6a4354dc00a5935b7fb59","observation_id":"e27c022c-ee39-41ad-a50a-ed8853f47ab2","resolution":{"observed_at":"2026-08-10T04:29:49.319655Z","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":"2026-08-10T04:29:49.991712Z","title":"mmwave-yolo: A mmwave imaging radar-based real-time multiclass object recognition system for adas applications,","venue":null,"work_id":"3e4e0560-8233-4605-a859-8dfe8a490c09","year":2022},"citing_paper":{"arxiv_id":"2501.17977","last_updated":"2025-01-29T20:21:41Z","snapshot_observed_at":"2026-08-10T04:23:56.826114Z","submitted_at":"2025-01-29T20:21:41Z","title":"TransRAD: Retentive Vision Transformer for Enhanced Radar Object Detection","version":1},"reference_index":17,"source":"pdf_text","source_observed_at":"2026-08-10T04:29:49.323149Z"},"links":{"citing_paper":"/paper/2501.17977"},"observation_digest":"sha256:b064aeb8f55b176ee6640bf2b1283a9f72556fbc4a588a81e68036f0896a9a58","observation_id":"4be5290a-3f82-497d-a9df-0254cd8d2719","resolution":{"observed_at":"2026-08-10T04:29:49.995728Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-11T06:34:44.6726+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-11T06:34:44.6726+00:00","source":"crossref"},{"observed_at":"2026-08-11T06:34:36.301508+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":"2026-08-10T04:29:49.980447Z","title":"Rodnet: Radar object detection using cross-modal supervision,","venue":null,"work_id":"b13e67cb-d333-4ecc-a49a-54138614e45c","year":2021},"citing_paper":{"arxiv_id":"2501.17977","last_updated":"2025-01-29T20:21:41Z","snapshot_observed_at":"2026-08-10T04:23:56.826114Z","submitted_at":"2025-01-29T20:21:41Z","title":"TransRAD: Retentive Vision Transformer for Enhanced Radar Object Detection","version":1},"reference_index":18,"source":"pdf_text","source_observed_at":"2026-08-10T04:29:49.326749Z"},"links":{"citing_paper":"/paper/2501.17977"},"observation_digest":"sha256:f7accddbf40fbffc7ce45946a8436a867943b825c54d60453c7499f09e9b87f2","observation_id":"c359dfc5-1588-4354-bb92-0950623fb3e5","resolution":{"observed_at":"2026-08-10T04:29:49.984493Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-11T06:34:44.6726+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-11T06:34:44.6726+00:00","source":"crossref"},{"observed_at":"2026-08-11T06:34:36.301508+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":"2026-08-10T04:29:49.967868Z","title":"Transrss: Transformer-based radar semantic segmentation,","venue":null,"work_id":"ffb3ce55-00a3-41bf-9869-07114071a475","year":2023},"citing_paper":{"arxiv_id":"2501.17977","last_updated":"2025-01-29T20:21:41Z","snapshot_observed_at":"2026-08-10T04:23:56.826114Z","submitted_at":"2025-01-29T20:21:41Z","title":"TransRAD: Retentive Vision Transformer for Enhanced Radar Object Detection","version":1},"reference_index":19,"source":"pdf_text","source_observed_at":"2026-08-10T04:29:49.330222Z"},"links":{"citing_paper":"/paper/2501.17977"},"observation_digest":"sha256:4f4b49f5bdd7752dcdd62ed3eeb819f4594b026bd34891540456fc3b7cac6e3e","observation_id":"451ebbb9-c4db-470f-bdd2-e7fe9c49a6b2","resolution":{"observed_at":"2026-08-10T04:29:49.971945Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-11T06:34:44.6726+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-11T06:34:44.6726+00:00","source":"crossref"},{"observed_at":"2026-08-11T06:34:36.301508+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":"2026-08-10T04:29:49.333997Z","title":"T-fftradnet: Object detection with swin vision transformers from raw adc radar signals,","venue":null,"work_id":null,"year":2023},"citing_paper":{"arxiv_id":"2501.17977","last_updated":"2025-01-29T20:21:41Z","snapshot_observed_at":"2026-08-10T04:23:56.826114Z","submitted_at":"2025-01-29T20:21:41Z","title":"TransRAD: Retentive Vision Transformer for Enhanced Radar Object Detection","version":1},"reference_index":20,"source":"pdf_text","source_observed_at":"2026-08-10T04:29:49.333997Z"},"links":{"citing_paper":"/paper/2501.17977"},"observation_digest":"sha256:0bd268693dae81befa9255075473e013962dc3095d173f80c12fe3abac37ad9c","observation_id":"e3300797-054b-416b-969d-621265dfc0fd","resolution":{"observed_at":"2026-08-10T04:29:49.333997Z","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":"2026-08-10T04:29:49.337879Z","title":"Deep radar detector,","venue":null,"work_id":null,"year":2019},"citing_paper":{"arxiv_id":"2501.17977","last_updated":"2025-01-29T20:21:41Z","snapshot_observed_at":"2026-08-10T04:23:56.826114Z","submitted_at":"2025-01-29T20:21:41Z","title":"TransRAD: Retentive Vision Transformer for Enhanced Radar Object Detection","version":1},"reference_index":21,"source":"pdf_text","source_observed_at":"2026-08-10T04:29:49.337879Z"},"links":{"citing_paper":"/paper/2501.17977"},"observation_digest":"sha256:ef674640ec36aede5942566d4e4b2e1ff732c0ab8a4e8a095abb836ac65716f6","observation_id":"9007369d-0e32-4a2e-9bb7-09838fad3909","resolution":{"observed_at":"2026-08-10T04:29:49.337879Z","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":"2026-08-10T04:29:49.941470Z","title":"Effective mmwave radar object detection pre-training based on masked image modeling,","venue":null,"work_id":"d1fc9532-1ccf-4c83-a887-ac28191613dd","year":2023},"citing_paper":{"arxiv_id":"2501.17977","last_updated":"2025-01-29T20:21:41Z","snapshot_observed_at":"2026-08-10T04:23:56.826114Z","submitted_at":"2025-01-29T20:21:41Z","title":"TransRAD: Retentive Vision Transformer for Enhanced Radar Object Detection","version":1},"reference_index":22,"source":"pdf_text","source_observed_at":"2026-08-10T04:29:49.341296Z"},"links":{"citing_paper":"/paper/2501.17977"},"observation_digest":"sha256:71a18eddd8b8064615e93bcbfba6deaf1d99e64be2979b2989426e0bc436dfbe","observation_id":"170896f7-f0cd-4864-aaf8-d9ff846bfd37","resolution":{"observed_at":"2026-08-10T04:29:49.946407Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-11T06:34:44.6726+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-11T06:34:44.6726+00:00","source":"crossref"},{"observed_at":"2026-08-11T06:34:36.301508+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":"2026-08-10T04:29:49.929750Z","title":"Vehicle detec- tion with automotive radar using deep learning on range-azimuth-doppler tensors,","venue":null,"work_id":"65c6e555-74e1-4265-bceb-acefc15b84bf","year":2019},"citing_paper":{"arxiv_id":"2501.17977","last_updated":"2025-01-29T20:21:41Z","snapshot_observed_at":"2026-08-10T04:23:56.826114Z","submitted_at":"2025-01-29T20:21:41Z","title":"TransRAD: Retentive Vision Transformer for Enhanced Radar Object Detection","version":1},"reference_index":23,"source":"pdf_text","source_observed_at":"2026-08-10T04:29:49.344830Z"},"links":{"citing_paper":"/paper/2501.17977"},"observation_digest":"sha256:f8635229621c91b8a129237653ec2c4a56f7bb08a97ad4cce540c7d0e4fb794b","observation_id":"3dee85b4-9421-46b9-9ea2-47d0da4de615","resolution":{"observed_at":"2026-08-10T04:29:49.933992Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-11T06:34:44.6726+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-11T06:34:44.6726+00:00","source":"crossref"},{"observed_at":"2026-08-11T06:34:36.301508+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":"2026-08-10T04:29:49.348266Z","title":"Rodnet: A real-time radar object detection network cross-supervised by camera- radar fused object 3d localization,","venue":null,"work_id":null,"year":2021},"citing_paper":{"arxiv_id":"2501.17977","last_updated":"2025-01-29T20:21:41Z","snapshot_observed_at":"2026-08-10T04:23:56.826114Z","submitted_at":"2025-01-29T20:21:41Z","title":"TransRAD: Retentive Vision Transformer for Enhanced Radar Object Detection","version":1},"reference_index":24,"source":"pdf_text","source_observed_at":"2026-08-10T04:29:49.348266Z"},"links":{"citing_paper":"/paper/2501.17977"},"observation_digest":"sha256:5f0ce9c658820e3bd8790b196128e397a688ae423379d10f0e2890a23519489d","observation_id":"38a4789c-3573-41a4-924f-7ad8b96033eb","resolution":{"observed_at":"2026-08-10T04:29:49.348266Z","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":"2026-08-10T04:29:49.910060Z","title":"Yolo-ore: A deep learning-aided object recognition approach for radar systems,","venue":null,"work_id":"61bb9aed-a1d3-465d-94cb-3de0263138f5","year":2022},"citing_paper":{"arxiv_id":"2501.17977","last_updated":"2025-01-29T20:21:41Z","snapshot_observed_at":"2026-08-10T04:23:56.826114Z","submitted_at":"2025-01-29T20:21:41Z","title":"TransRAD: Retentive Vision Transformer for Enhanced Radar Object Detection","version":1},"reference_index":25,"source":"pdf_text","source_observed_at":"2026-08-10T04:29:49.351784Z"},"links":{"citing_paper":"/paper/2501.17977"},"observation_digest":"sha256:16c03a1371d2abedee0237152f5ef6e943406e6df356599df885223c5136c26f","observation_id":"e7cdba28-bef9-4c5b-b6b1-f2ba69c50e2b","resolution":{"observed_at":"2026-08-10T04:29:49.914870Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-11T06:34:44.6726+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-11T06:34:44.6726+00:00","source":"crossref"},{"observed_at":"2026-08-11T06:34:36.301508+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":"2026-08-10T04:29:49.898133Z","title":"Danet: Dimension apart network for radar object detection,","venue":null,"work_id":"0823ee3f-0e21-4473-915b-d1cbbbe1c532","year":2021},"citing_paper":{"arxiv_id":"2501.17977","last_updated":"2025-01-29T20:21:41Z","snapshot_observed_at":"2026-08-10T04:23:56.826114Z","submitted_at":"2025-01-29T20:21:41Z","title":"TransRAD: Retentive Vision Transformer for Enhanced Radar Object Detection","version":1},"reference_index":26,"source":"pdf_text","source_observed_at":"2026-08-10T04:29:49.355426Z"},"links":{"citing_paper":"/paper/2501.17977"},"observation_digest":"sha256:552497de7a8174c2669f724bba71533278e6609f688f1390d44bbdb8e132b22e","observation_id":"1051f8f6-4e27-480f-990d-bca94381d941","resolution":{"observed_at":"2026-08-10T04:29:49.902193Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-11T06:34:44.6726+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-11T06:34:44.6726+00:00","source":"crossref"},{"observed_at":"2026-08-11T06:34:36.301508+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":"2026-08-10T04:29:49.886767Z","title":"Object detection and heading estimation from radar raw data,","venue":null,"work_id":"78221b60-2bb6-49cd-a38e-18721a7e6d8d","year":2023},"citing_paper":{"arxiv_id":"2501.17977","last_updated":"2025-01-29T20:21:41Z","snapshot_observed_at":"2026-08-10T04:23:56.826114Z","submitted_at":"2025-01-29T20:21:41Z","title":"TransRAD: Retentive Vision Transformer for Enhanced Radar Object Detection","version":1},"reference_index":27,"source":"pdf_text","source_observed_at":"2026-08-10T04:29:49.359118Z"},"links":{"citing_paper":"/paper/2501.17977"},"observation_digest":"sha256:666e4f1a39c2d5650d00a34918b9abe6b83314025150709b99604f9c48655026","observation_id":"734fddcb-d744-4481-80bf-6c08caf46d12","resolution":{"observed_at":"2026-08-10T04:29:49.890744Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-11T06:34:44.6726+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-11T06:34:44.6726+00:00","source":"crossref"},{"observed_at":"2026-08-11T06:34:36.301508+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":"2026-08-10T04:29:49.362798Z","title":"Transradar: Adaptive- directional transformer for real-time multi-view radar semantic seg- mentation,","venue":null,"work_id":null,"year":2024},"citing_paper":{"arxiv_id":"2501.17977","last_updated":"2025-01-29T20:21:41Z","snapshot_observed_at":"2026-08-10T04:23:56.826114Z","submitted_at":"2025-01-29T20:21:41Z","title":"TransRAD: Retentive Vision Transformer for Enhanced Radar Object Detection","version":1},"reference_index":28,"source":"pdf_text","source_observed_at":"2026-08-10T04:29:49.362798Z"},"links":{"citing_paper":"/paper/2501.17977"},"observation_digest":"sha256:d5dd01f8738f12172e1390c47705a3a3cd3d336485dbd8cc84302bdd66eabcd1","observation_id":"9703eb4b-97e0-45a1-b1b1-e1510a35abf2","resolution":{"observed_at":"2026-08-10T04:29:49.362798Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2203.01536","last_updated":"2023-10-17T06:05:41Z","snapshot_observed_at":"2026-08-07T20:24:22.607229Z","submitted_at":"2022-03-03T06:17:03Z","title":"Recent Advances in Vision Transformer: A Survey and Outlook of Recent Work","version":5},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2203.01536","snapshot_observed_at":"2026-08-10T04:29:49.366744Z","title":"Recent advances in vision transformer: A survey and outlook of recent work,","venue":null,"work_id":null,"year":2022},"citing_paper":{"arxiv_id":"2501.17977","last_updated":"2025-01-29T20:21:41Z","snapshot_observed_at":"2026-08-10T04:23:56.826114Z","submitted_at":"2025-01-29T20:21:41Z","title":"TransRAD: Retentive Vision Transformer for Enhanced Radar Object Detection","version":1},"reference_index":29,"source":"pdf_text","source_observed_at":"2026-08-10T04:29:49.366744Z"},"links":{"cited_paper":"/paper/2203.01536","citing_paper":"/paper/2501.17977"},"observation_digest":"sha256:258d721cf12b526d716c610e45e627ab7180d74f1416ddc3fabeaaf62ed1d5e3","observation_id":"b68ebba6-5d47-4e6d-a250-2cd44588cfd1","resolution":{"observed_at":"2026-08-10T04:29:49.366744Z","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":"2026-08-10T04:29:49.865687Z","title":"Rmt: Retentive networks meet vision transformers,","venue":null,"work_id":"257517f1-26f7-44ae-8968-6d8392887147","year":2024},"citing_paper":{"arxiv_id":"2501.17977","last_updated":"2025-01-29T20:21:41Z","snapshot_observed_at":"2026-08-10T04:23:56.826114Z","submitted_at":"2025-01-29T20:21:41Z","title":"TransRAD: Retentive Vision Transformer for Enhanced Radar Object Detection","version":1},"reference_index":30,"source":"pdf_text","source_observed_at":"2026-08-10T04:29:49.370855Z"},"links":{"citing_paper":"/paper/2501.17977"},"observation_digest":"sha256:2f3f1df4b2736427467904c8d31ab0c8f5beabb327fe23b31904abea0f6a3664","observation_id":"104d6cce-0c2c-4fa3-bd93-25b2036b390a","resolution":{"observed_at":"2026-08-10T04:29:49.870034Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-11T06:34:44.6726+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-11T06:34:44.6726+00:00","source":"crossref"},{"observed_at":"2026-08-11T06:34:36.301508+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":"2026-08-10T04:29:49.374504Z","title":"Feature pyramid networks for object detection,","venue":null,"work_id":null,"year":2017},"citing_paper":{"arxiv_id":"2501.17977","last_updated":"2025-01-29T20:21:41Z","snapshot_observed_at":"2026-08-10T04:23:56.826114Z","submitted_at":"2025-01-29T20:21:41Z","title":"TransRAD: Retentive Vision Transformer for Enhanced Radar Object Detection","version":1},"reference_index":31,"source":"pdf_text","source_observed_at":"2026-08-10T04:29:49.374504Z"},"links":{"citing_paper":"/paper/2501.17977"},"observation_digest":"sha256:2c375d49e67bc67fa149242e76027b1e844a083549c1da665492a98b5aafc63d","observation_id":"fa8f95bf-dedd-43fe-9e1d-60fcc5ef4ec8","resolution":{"observed_at":"2026-08-10T04:29:49.374504Z","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":"2026-08-10T04:29:49.844044Z","title":null,"venue":null,"work_id":"2a177170-d5fa-418e-be1a-e4b4f0ee03a0","year":2023},"citing_paper":{"arxiv_id":"2501.17977","last_updated":"2025-01-29T20:21:41Z","snapshot_observed_at":"2026-08-10T04:23:56.826114Z","submitted_at":"2025-01-29T20:21:41Z","title":"TransRAD: Retentive Vision Transformer for Enhanced Radar Object Detection","version":1},"reference_index":32,"source":"pdf_text","source_observed_at":"2026-08-10T04:29:49.378114Z"},"links":{"citing_paper":"/paper/2501.17977"},"observation_digest":"sha256:9f1e235c60801ab06fb76bedad6b906900a2acb16c96a9f7cd27d0b3e063a7a7","observation_id":"45538783-d61d-4f7a-b24a-fd223e44b21a","resolution":{"observed_at":"2026-08-10T04:29:49.848260Z","resolver_source":"raw_fallback","status":"unresolved"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-11T06:34:44.6726+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-11T06:34:44.6726+00:00","source":"crossref"},{"observed_at":"2026-08-11T06:34:36.301508+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":"2026-08-10T04:29:49.831568Z","title":"Freeanchor: Learning to match anchors for visual object detection,","venue":null,"work_id":"99519845-ff2c-4293-a059-32fecafcd279","year":2019},"citing_paper":{"arxiv_id":"2501.17977","last_updated":"2025-01-29T20:21:41Z","snapshot_observed_at":"2026-08-10T04:23:56.826114Z","submitted_at":"2025-01-29T20:21:41Z","title":"TransRAD: Retentive Vision Transformer for Enhanced Radar Object Detection","version":1},"reference_index":33,"source":"pdf_text","source_observed_at":"2026-08-10T04:29:49.381789Z"},"links":{"citing_paper":"/paper/2501.17977"},"observation_digest":"sha256:4d0c440ed688fbfbe4ab05d8a7e242467152c28ba28dd09a22106dc9e42c4937","observation_id":"210c0075-53ea-4f43-a2fc-3252bd555419","resolution":{"observed_at":"2026-08-10T04:29:49.836276Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-11T06:34:44.6726+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-11T06:34:44.6726+00:00","source":"crossref"},{"observed_at":"2026-08-11T06:34:36.301508+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":"2026-08-10T04:29:49.818740Z","title":"Corner pro- posal network for anchor-free, two-stage object detection,","venue":null,"work_id":"4e2f7ecb-4513-4fbe-92b7-33358270fc78","year":2020},"citing_paper":{"arxiv_id":"2501.17977","last_updated":"2025-01-29T20:21:41Z","snapshot_observed_at":"2026-08-10T04:23:56.826114Z","submitted_at":"2025-01-29T20:21:41Z","title":"TransRAD: Retentive Vision Transformer for Enhanced Radar Object Detection","version":1},"reference_index":34,"source":"pdf_text","source_observed_at":"2026-08-10T04:29:49.385528Z"},"links":{"citing_paper":"/paper/2501.17977"},"observation_digest":"sha256:c84bac06ec26607d8458598b5d95c03b9eafc9c7955932a66d0fdb1d50dc6051","observation_id":"e34df36e-6b97-4b92-a1cd-7baea8459b22","resolution":{"observed_at":"2026-08-10T04:29:49.823513Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-11T06:34:44.6726+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-11T06:34:44.6726+00:00","source":"crossref"},{"observed_at":"2026-08-11T06:34:36.301508+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":"2026-08-10T04:29:49.803993Z","title":"An anchor-free detector with channel-based prior and bottom-enhancement for underwater object detection,","venue":null,"work_id":"b2619f41-9089-4b0e-939e-e392f4e80e11","year":2023},"citing_paper":{"arxiv_id":"2501.17977","last_updated":"2025-01-29T20:21:41Z","snapshot_observed_at":"2026-08-10T04:23:56.826114Z","submitted_at":"2025-01-29T20:21:41Z","title":"TransRAD: Retentive Vision Transformer for Enhanced Radar Object Detection","version":1},"reference_index":35,"source":"pdf_text","source_observed_at":"2026-08-10T04:29:49.389181Z"},"links":{"citing_paper":"/paper/2501.17977"},"observation_digest":"sha256:9ef49692dee13e2c4e0d3481d8ca1825c73f48514cad16d6b0ea030e327f6b7e","observation_id":"c9491e2a-047b-4ea1-9be0-1114d8eaea2d","resolution":{"observed_at":"2026-08-10T04:29:49.808975Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-11T06:34:44.6726+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-11T06:34:44.6726+00:00","source":"crossref"},{"observed_at":"2026-08-11T06:34:36.301508+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"1904.01355","last_updated":"2019-08-20T11:26:21Z","snapshot_observed_at":"2026-08-06T12:11:08.352588Z","submitted_at":"2019-04-02T11:56:36Z","title":"FCOS: Fully Convolutional One-Stage Object Detection","version":5},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"1904.01355","snapshot_observed_at":"2026-08-10T04:29:49.392708Z","title":"Fcos: Fully convolutional one- stage object detection. arxiv 2019,","venue":null,"work_id":null,"year":2019},"citing_paper":{"arxiv_id":"2501.17977","last_updated":"2025-01-29T20:21:41Z","snapshot_observed_at":"2026-08-10T04:23:56.826114Z","submitted_at":"2025-01-29T20:21:41Z","title":"TransRAD: Retentive Vision Transformer for Enhanced Radar Object Detection","version":1},"reference_index":36,"source":"pdf_text","source_observed_at":"2026-08-10T04:29:49.392708Z"},"links":{"cited_paper":"/paper/1904.01355","citing_paper":"/paper/2501.17977"},"observation_digest":"sha256:60abdf93428804124b17dfae457085b09b0d1df9416466e2d61190e8ea582a0c","observation_id":"6077f2cb-4409-41d0-816e-e487adb8699c","resolution":{"observed_at":"2026-08-10T04:29:49.392708Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2107.08430","last_updated":"2021-08-06T03:22:14Z","snapshot_observed_at":"2026-07-06T11:30:06.143581Z","submitted_at":"2021-07-18T12:55:11Z","title":"YOLOX: Exceeding YOLO Series in 2021","version":2},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2107.08430","snapshot_observed_at":"2026-08-10T04:29:49.396976Z","title":"Yolox: Exceeding yolo series in 2021,","venue":null,"work_id":null,"year":2021},"citing_paper":{"arxiv_id":"2501.17977","last_updated":"2025-01-29T20:21:41Z","snapshot_observed_at":"2026-08-10T04:23:56.826114Z","submitted_at":"2025-01-29T20:21:41Z","title":"TransRAD: Retentive Vision Transformer for Enhanced Radar Object Detection","version":1},"reference_index":37,"source":"pdf_text","source_observed_at":"2026-08-10T04:29:49.396976Z"},"links":{"cited_paper":"/paper/2107.08430","citing_paper":"/paper/2501.17977"},"observation_digest":"sha256:86984556ba8a229b3c1fb4aec3d7b314d02b25a2b48852184f8ed28f11fc98fc","observation_id":"a6c25d68-7326-4545-8d86-f89cfb31e88e","resolution":{"observed_at":"2026-08-10T04:29:49.396976Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2312.04861","last_updated":"2025-04-21T08:37:24Z","snapshot_observed_at":"2026-07-06T16:58:43.934362Z","submitted_at":"2023-12-08T06:31:19Z","title":"Exploring Radar Data Representations in Autonomous Driving: A Comprehensive Review","version":3},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2312.04861","snapshot_observed_at":"2026-08-10T04:29:49.400844Z","title":"Radar perception in autonomous driving: Exploring different data representations,","venue":null,"work_id":null,"year":2023},"citing_paper":{"arxiv_id":"2501.17977","last_updated":"2025-01-29T20:21:41Z","snapshot_observed_at":"2026-08-10T04:23:56.826114Z","submitted_at":"2025-01-29T20:21:41Z","title":"TransRAD: Retentive Vision Transformer for Enhanced Radar Object Detection","version":1},"reference_index":38,"source":"pdf_text","source_observed_at":"2026-08-10T04:29:49.400844Z"},"links":{"cited_paper":"/paper/2312.04861","citing_paper":"/paper/2501.17977"},"observation_digest":"sha256:027be66e6b1e91a688febd05ff259ba80367fed14cc5e82da8332213b8f07583","observation_id":"005f4880-971f-4ec3-94e8-c888c374638b","resolution":{"observed_at":"2026-08-10T04:29:49.400844Z","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":"2026-08-10T04:29:49.791567Z","title":"Deep learning-based object classification on automotive radar spectra,","venue":null,"work_id":"f30a36e4-160e-4c50-b81f-486123d4cc28","year":2019},"citing_paper":{"arxiv_id":"2501.17977","last_updated":"2025-01-29T20:21:41Z","snapshot_observed_at":"2026-08-10T04:23:56.826114Z","submitted_at":"2025-01-29T20:21:41Z","title":"TransRAD: Retentive Vision Transformer for Enhanced Radar Object Detection","version":1},"reference_index":39,"source":"pdf_text","source_observed_at":"2026-08-10T04:29:49.404681Z"},"links":{"citing_paper":"/paper/2501.17977"},"observation_digest":"sha256:3ff751eb1acf36f4249ca844017e39b13d5c7e5f0587a27f941b7c0e4cc4232c","observation_id":"1d74cc1f-52d2-43e4-8785-aeda10bd2bb9","resolution":{"observed_at":"2026-08-10T04:29:49.795604Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-11T06:34:44.6726+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-11T06:34:44.6726+00:00","source":"crossref"},{"observed_at":"2026-08-11T06:34:36.301508+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":"2026-08-10T04:29:49.778963Z","title":"Towards large-scale small object detection: Survey and benchmarks,","venue":null,"work_id":"8ef63a1c-1275-41ac-82c4-ab781884fdac","year":2023},"citing_paper":{"arxiv_id":"2501.17977","last_updated":"2025-01-29T20:21:41Z","snapshot_observed_at":"2026-08-10T04:23:56.826114Z","submitted_at":"2025-01-29T20:21:41Z","title":"TransRAD: Retentive Vision Transformer for Enhanced Radar Object Detection","version":1},"reference_index":40,"source":"pdf_text","source_observed_at":"2026-08-10T04:29:49.408243Z"},"links":{"citing_paper":"/paper/2501.17977"},"observation_digest":"sha256:6ec6ba9cabc1badfe5312837409fb2e85f83c28174de6981962862457fc6cb29","observation_id":"540f59ec-bfd6-4234-9171-d04a217981f6","resolution":{"observed_at":"2026-08-10T04:29:49.783338Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-11T06:34:44.6726+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-11T06:34:44.6726+00:00","source":"crossref"},{"observed_at":"2026-08-11T06:34:36.301508+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":"2026-08-10T04:29:49.766119Z","title":"Salient object detection in the deep learning era: An in-depth survey,","venue":null,"work_id":"64ea7e62-f131-4879-b23e-62b89b2b1434","year":2021},"citing_paper":{"arxiv_id":"2501.17977","last_updated":"2025-01-29T20:21:41Z","snapshot_observed_at":"2026-08-10T04:23:56.826114Z","submitted_at":"2025-01-29T20:21:41Z","title":"TransRAD: Retentive Vision Transformer for Enhanced Radar Object Detection","version":1},"reference_index":41,"source":"pdf_text","source_observed_at":"2026-08-10T04:29:49.411801Z"},"links":{"citing_paper":"/paper/2501.17977"},"observation_digest":"sha256:328a99aba47505f1bf92dee9d1a7940274fe265c9588e43cf07c83a4691c1619","observation_id":"f8802d8c-e33c-4c3e-a0a2-06083af99596","resolution":{"observed_at":"2026-08-10T04:29:49.770348Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-11T06:34:44.6726+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-11T06:34:44.6726+00:00","source":"crossref"},{"observed_at":"2026-08-11T06:34:36.301508+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"2203.12944","last_updated":"2022-03-24T09:09:00Z","snapshot_observed_at":"2026-07-06T12:51:55.231850Z","submitted_at":"2022-03-24T09:09:00Z","title":"Transformers Meet Visual Learning Understanding: A Comprehensive Review","version":1},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2203.12944","snapshot_observed_at":"2026-08-10T04:29:49.415176Z","title":"Transformers meet visual learning understanding: A comprehensive review,","venue":null,"work_id":null,"year":2022},"citing_paper":{"arxiv_id":"2501.17977","last_updated":"2025-01-29T20:21:41Z","snapshot_observed_at":"2026-08-10T04:23:56.826114Z","submitted_at":"2025-01-29T20:21:41Z","title":"TransRAD: Retentive Vision Transformer for Enhanced Radar Object Detection","version":1},"reference_index":42,"source":"pdf_text","source_observed_at":"2026-08-10T04:29:49.415176Z"},"links":{"cited_paper":"/paper/2203.12944","citing_paper":"/paper/2501.17977"},"observation_digest":"sha256:0faada326b961f81a7cb36b7286f66221fc03c77344eef4cef25981ee226a2ed","observation_id":"1e4917ca-a645-4bd1-bca1-97e342919c91","resolution":{"observed_at":"2026-08-10T04:29:49.415176Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2307.08621","last_updated":"2023-08-09T08:53:08Z","snapshot_observed_at":"2026-08-02T13:21:32.251959Z","submitted_at":"2023-07-17T16:40:01Z","title":"Retentive Network: A Successor to Transformer for Large Language Models","version":4},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2307.08621","snapshot_observed_at":"2026-08-10T04:29:49.419112Z","title":"Retentive network: A successor to transformer for large language models,","venue":null,"work_id":null,"year":2023},"citing_paper":{"arxiv_id":"2501.17977","last_updated":"2025-01-29T20:21:41Z","snapshot_observed_at":"2026-08-10T04:23:56.826114Z","submitted_at":"2025-01-29T20:21:41Z","title":"TransRAD: Retentive Vision Transformer for Enhanced Radar Object Detection","version":1},"reference_index":43,"source":"pdf_text","source_observed_at":"2026-08-10T04:29:49.419112Z"},"links":{"cited_paper":"/paper/2307.08621","citing_paper":"/paper/2501.17977"},"observation_digest":"sha256:52490479338757fabb25865f06d995cd1712191e1e1a533765f213d6416f9658","observation_id":"fb78a43b-bb4a-4532-80a2-95f734f5300f","resolution":{"observed_at":"2026-08-10T04:29:49.419112Z","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":"2026-08-10T04:29:49.754480Z","title":"Salient object detection by fusing local and global contexts,","venue":null,"work_id":"3f22ebb8-7e3d-440f-ae33-59ece3cd5830","year":2020},"citing_paper":{"arxiv_id":"2501.17977","last_updated":"2025-01-29T20:21:41Z","snapshot_observed_at":"2026-08-10T04:23:56.826114Z","submitted_at":"2025-01-29T20:21:41Z","title":"TransRAD: Retentive Vision Transformer for Enhanced Radar Object Detection","version":1},"reference_index":44,"source":"pdf_text","source_observed_at":"2026-08-10T04:29:49.423036Z"},"links":{"citing_paper":"/paper/2501.17977"},"observation_digest":"sha256:22dace69688f4413d7c05fba85e1fc276c6afe5af1015081321343b8247e7c93","observation_id":"29f454bc-6ea7-43bd-bfed-c053d8e4402c","resolution":{"observed_at":"2026-08-10T04:29:49.758503Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-11T06:34:44.6726+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-11T06:34:44.6726+00:00","source":"crossref"},{"observed_at":"2026-08-11T06:34:36.301508+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":"2026-08-10T04:29:49.426948Z","title":"A survey and performance evaluation of deep learning methods for small object detection,","venue":null,"work_id":null,"year":2021},"citing_paper":{"arxiv_id":"2501.17977","last_updated":"2025-01-29T20:21:41Z","snapshot_observed_at":"2026-08-10T04:23:56.826114Z","submitted_at":"2025-01-29T20:21:41Z","title":"TransRAD: Retentive Vision Transformer for Enhanced Radar Object Detection","version":1},"reference_index":45,"source":"pdf_text","source_observed_at":"2026-08-10T04:29:49.426948Z"},"links":{"citing_paper":"/paper/2501.17977"},"observation_digest":"sha256:5161504802adc09f8ffcf58853aa51106501c1f3f72e12bf7bb80e5c63f6ba57","observation_id":"0dea5130-2d64-4b0b-8988-b0ef14a3e4e2","resolution":{"observed_at":"2026-08-10T04:29:49.426948Z","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":"2026-08-10T04:29:49.735614Z","title":"Gcwnet: A global context-weaving network for object detection in remote sensing images,","venue":null,"work_id":"8c7c5286-c069-4d8d-b23f-ce04c46adddd","year":2022},"citing_paper":{"arxiv_id":"2501.17977","last_updated":"2025-01-29T20:21:41Z","snapshot_observed_at":"2026-08-10T04:23:56.826114Z","submitted_at":"2025-01-29T20:21:41Z","title":"TransRAD: Retentive Vision Transformer for Enhanced Radar Object Detection","version":1},"reference_index":46,"source":"pdf_text","source_observed_at":"2026-08-10T04:29:49.432858Z"},"links":{"citing_paper":"/paper/2501.17977"},"observation_digest":"sha256:4119425160badf2f8ef6ad53ab8973a10f79c187cac952b24687ff0126a31ba1","observation_id":"d82793f0-8915-48a7-8884-86185301d379","resolution":{"observed_at":"2026-08-10T04:29:49.739535Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-11T06:34:44.6726+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-11T06:34:44.6726+00:00","source":"crossref"},{"observed_at":"2026-08-11T06:34:36.301508+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":"2026-08-10T04:29:49.723608Z","title":"Global context-aware progres- sive aggregation network for salient object detection,","venue":null,"work_id":"968bfcd4-fb84-4588-a1d3-1279608dd58b","year":2020},"citing_paper":{"arxiv_id":"2501.17977","last_updated":"2025-01-29T20:21:41Z","snapshot_observed_at":"2026-08-10T04:23:56.826114Z","submitted_at":"2025-01-29T20:21:41Z","title":"TransRAD: Retentive Vision Transformer for Enhanced Radar Object Detection","version":1},"reference_index":47,"source":"pdf_text","source_observed_at":"2026-08-10T04:29:49.436934Z"},"links":{"citing_paper":"/paper/2501.17977"},"observation_digest":"sha256:421e55bf063243402505900c1487f77fe602531ef3cd363abf9e691f3cf79a68","observation_id":"db9e3550-5714-4ab2-bf3f-fbfb1f8f7fb5","resolution":{"observed_at":"2026-08-10T04:29:49.727909Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-11T06:34:44.6726+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-11T06:34:44.6726+00:00","source":"crossref"},{"observed_at":"2026-08-11T06:34:36.301508+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"2102.10882","last_updated":"2023-02-13T01:19:57Z","snapshot_observed_at":"2026-08-10T23:32:09.056322Z","submitted_at":"2021-02-22T10:29:55Z","title":"Conditional Positional Encodings for Vision Transformers","version":3},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2102.10882","snapshot_observed_at":"2026-08-10T04:29:49.440946Z","title":"Condi- tional positional encodings for vision transformers,","venue":null,"work_id":null,"year":2021},"citing_paper":{"arxiv_id":"2501.17977","last_updated":"2025-01-29T20:21:41Z","snapshot_observed_at":"2026-08-10T04:23:56.826114Z","submitted_at":"2025-01-29T20:21:41Z","title":"TransRAD: Retentive Vision Transformer for Enhanced Radar Object Detection","version":1},"reference_index":48,"source":"pdf_text","source_observed_at":"2026-08-10T04:29:49.440946Z"},"links":{"cited_paper":"/paper/2102.10882","citing_paper":"/paper/2501.17977"},"observation_digest":"sha256:644475700040bbc27192138813364e7feb09d01b9e2c2ca4c7edfccfdd3e04ac","observation_id":"331b60cc-d008-4ea1-8b28-a14c2f3c3bc2","resolution":{"observed_at":"2026-08-10T04:29:49.440946Z","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":"2026-08-10T04:29:49.712584Z","title":"The role of context for object detection and semantic segmentation in the wild,","venue":null,"work_id":"3d10094c-873e-4976-9957-b6a703d653ba","year":2014},"citing_paper":{"arxiv_id":"2501.17977","last_updated":"2025-01-29T20:21:41Z","snapshot_observed_at":"2026-08-10T04:23:56.826114Z","submitted_at":"2025-01-29T20:21:41Z","title":"TransRAD: Retentive Vision Transformer for Enhanced Radar Object Detection","version":1},"reference_index":49,"source":"pdf_text","source_observed_at":"2026-08-10T04:29:49.444988Z"},"links":{"citing_paper":"/paper/2501.17977"},"observation_digest":"sha256:8e16293474f883e30e91fa9e6753d9a54c39ef7f6033f53938a08bf6bad44d38","observation_id":"7a9b81f9-b6e9-4c05-aa4c-06b0545298a8","resolution":{"observed_at":"2026-08-10T04:29:49.716463Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-11T06:34:44.6726+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-11T06:34:44.6726+00:00","source":"crossref"},{"observed_at":"2026-08-11T06:34:36.301508+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":"2026-08-10T04:29:49.448980Z","title":"Bridging the gap between anchor-based and anchor-free detection via adaptive training sample selection,","venue":null,"work_id":null,"year":2020},"citing_paper":{"arxiv_id":"2501.17977","last_updated":"2025-01-29T20:21:41Z","snapshot_observed_at":"2026-08-10T04:23:56.826114Z","submitted_at":"2025-01-29T20:21:41Z","title":"TransRAD: Retentive Vision Transformer for Enhanced Radar Object Detection","version":1},"reference_index":50,"source":"pdf_text","source_observed_at":"2026-08-10T04:29:49.448980Z"},"links":{"citing_paper":"/paper/2501.17977"},"observation_digest":"sha256:249bd2a07eb9b19dc87b5d9f1427cf7a34cca25b84132722c2c620784efc5560","observation_id":"a7bfd74c-0fb7-4e16-ac05-75894d7cda77","resolution":{"observed_at":"2026-08-10T04:29:49.448980Z","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":"2026-08-10T04:29:49.452902Z","title":"Tood: Task- aligned one-stage object detection,","venue":null,"work_id":null,"year":2021},"citing_paper":{"arxiv_id":"2501.17977","last_updated":"2025-01-29T20:21:41Z","snapshot_observed_at":"2026-08-10T04:23:56.826114Z","submitted_at":"2025-01-29T20:21:41Z","title":"TransRAD: Retentive Vision Transformer for Enhanced Radar Object Detection","version":1},"reference_index":51,"source":"pdf_text","source_observed_at":"2026-08-10T04:29:49.452902Z"},"links":{"citing_paper":"/paper/2501.17977"},"observation_digest":"sha256:5b45ccc6ba544dcb570da2af123908fec140aad18fc2fdc0f9121bbc9f21fd51","observation_id":"940e08d4-0671-4a26-acd6-069c36c1c827","resolution":{"observed_at":"2026-08-10T04:29:49.452902Z","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":"2026-08-10T04:29:49.687929Z","title":"Revisiting the sibling head in object detector,","venue":null,"work_id":"5adbb649-8fbb-4fd1-ad09-e9ab77bf726e","year":2020},"citing_paper":{"arxiv_id":"2501.17977","last_updated":"2025-01-29T20:21:41Z","snapshot_observed_at":"2026-08-10T04:23:56.826114Z","submitted_at":"2025-01-29T20:21:41Z","title":"TransRAD: Retentive Vision Transformer for Enhanced Radar Object Detection","version":1},"reference_index":52,"source":"pdf_text","source_observed_at":"2026-08-10T04:29:49.456628Z"},"links":{"citing_paper":"/paper/2501.17977"},"observation_digest":"sha256:55998ed22c933bf0304fd0b3ee06cee3a6a2cfd9ddbdc4de433cb0d3178411a9","observation_id":"28c59dee-844e-43bf-a14d-76b982dd8fa0","resolution":{"observed_at":"2026-08-10T04:29:49.691736Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-11T06:34:44.6726+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-11T06:34:44.6726+00:00","source":"crossref"},{"observed_at":"2026-08-11T06:34:36.301508+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":"2026-08-10T04:29:49.675831Z","title":"A comprehensive survey of loss functions in machine learning,","venue":null,"work_id":"962b407e-8d5a-4e31-b37c-3f1b5bf00e75","year":2020},"citing_paper":{"arxiv_id":"2501.17977","last_updated":"2025-01-29T20:21:41Z","snapshot_observed_at":"2026-08-10T04:23:56.826114Z","submitted_at":"2025-01-29T20:21:41Z","title":"TransRAD: Retentive Vision Transformer for Enhanced Radar Object Detection","version":1},"reference_index":53,"source":"pdf_text","source_observed_at":"2026-08-10T04:29:49.460482Z"},"links":{"citing_paper":"/paper/2501.17977"},"observation_digest":"sha256:008276dd90c32c1e521c43deda0b05df71920be3e7b1ab5c6036416e31a60ce4","observation_id":"43db958e-b5c5-46e2-933d-ba927e3f4b34","resolution":{"observed_at":"2026-08-10T04:29:49.680223Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-11T06:34:44.6726+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-11T06:34:44.6726+00:00","source":"crossref"},{"observed_at":"2026-08-11T06:34:36.301508+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":"2026-08-10T04:29:49.464248Z","title":"Enhancing geometric factors in model learning and inference for object detection and instance segmentation,","venue":null,"work_id":null,"year":2021},"citing_paper":{"arxiv_id":"2501.17977","last_updated":"2025-01-29T20:21:41Z","snapshot_observed_at":"2026-08-10T04:23:56.826114Z","submitted_at":"2025-01-29T20:21:41Z","title":"TransRAD: Retentive Vision Transformer for Enhanced Radar Object Detection","version":1},"reference_index":54,"source":"pdf_text","source_observed_at":"2026-08-10T04:29:49.464248Z"},"links":{"citing_paper":"/paper/2501.17977"},"observation_digest":"sha256:3b7e6bbf218a1fa07ed32d005209d48ab30dad628458c2bf7a13980315297752","observation_id":"b22fca9f-7e67-46db-ae50-1a5d87187c54","resolution":{"observed_at":"2026-08-10T04:29:49.464248Z","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":"2026-08-10T04:29:49.467813Z","title":"Generalized focal loss: Learning qualified and distributed bounding boxes for dense object detection,","venue":null,"work_id":null,"year":2020},"citing_paper":{"arxiv_id":"2501.17977","last_updated":"2025-01-29T20:21:41Z","snapshot_observed_at":"2026-08-10T04:23:56.826114Z","submitted_at":"2025-01-29T20:21:41Z","title":"TransRAD: Retentive Vision Transformer for Enhanced Radar Object Detection","version":1},"reference_index":55,"source":"pdf_text","source_observed_at":"2026-08-10T04:29:49.467813Z"},"links":{"citing_paper":"/paper/2501.17977"},"observation_digest":"sha256:2e0d8abea546bd9ec4aa5904e8e4985f90c758fdd54576d26a34c9fd6da58967","observation_id":"e8cb1e2c-0e44-46d1-a46d-37d2fff972c1","resolution":{"observed_at":"2026-08-10T04:29:49.467813Z","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":"2026-08-10T04:29:49.471465Z","title":"Focal loss for dense object detection,","venue":null,"work_id":null,"year":2017},"citing_paper":{"arxiv_id":"2501.17977","last_updated":"2025-01-29T20:21:41Z","snapshot_observed_at":"2026-08-10T04:23:56.826114Z","submitted_at":"2025-01-29T20:21:41Z","title":"TransRAD: Retentive Vision Transformer for Enhanced Radar Object Detection","version":1},"reference_index":56,"source":"pdf_text","source_observed_at":"2026-08-10T04:29:49.471465Z"},"links":{"citing_paper":"/paper/2501.17977"},"observation_digest":"sha256:95151c155ec2a7b8ca906ab97f01812691ce3d0c4f6928907aaee6a3efa61c65","observation_id":"b4509e37-d8c4-4360-8c24-5df39fe7875c","resolution":{"observed_at":"2026-08-10T04:29:49.471465Z","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":"2026-08-10T04:29:49.475088Z","title":"Fast r-cnn,","venue":null,"work_id":null,"year":2015},"citing_paper":{"arxiv_id":"2501.17977","last_updated":"2025-01-29T20:21:41Z","snapshot_observed_at":"2026-08-10T04:23:56.826114Z","submitted_at":"2025-01-29T20:21:41Z","title":"TransRAD: Retentive Vision Transformer for Enhanced Radar Object Detection","version":1},"reference_index":57,"source":"pdf_text","source_observed_at":"2026-08-10T04:29:49.475088Z"},"links":{"citing_paper":"/paper/2501.17977"},"observation_digest":"sha256:5ea16d0c3502f12d24b7328080a58f092cfec7385cbd4899f116788ced63faea","observation_id":"0e1620d3-cc1c-4a59-ad12-28b651c3d788","resolution":{"observed_at":"2026-08-10T04:29:49.475088Z","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":"2026-08-10T04:29:49.636052Z","title":"Neural attention-driven non-maximum suppression for person detection,","venue":null,"work_id":"28cba1d4-70fc-43fd-84e3-c1695503aeb7","year":2023},"citing_paper":{"arxiv_id":"2501.17977","last_updated":"2025-01-29T20:21:41Z","snapshot_observed_at":"2026-08-10T04:23:56.826114Z","submitted_at":"2025-01-29T20:21:41Z","title":"TransRAD: Retentive Vision Transformer for Enhanced Radar Object Detection","version":1},"reference_index":58,"source":"pdf_text","source_observed_at":"2026-08-10T04:29:49.478756Z"},"links":{"citing_paper":"/paper/2501.17977"},"observation_digest":"sha256:5db3014a85bf75d5c2da6034384748a0a858c99e1c7e41e0dff0e70f6103f209","observation_id":"809c6bf2-d3c4-4f89-a1dd-0ea84ad8656c","resolution":{"observed_at":"2026-08-10T04:29:49.640105Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-11T06:34:44.6726+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-11T06:34:44.6726+00:00","source":"crossref"},{"observed_at":"2026-08-11T06:34:36.301508+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":"2026-08-10T04:29:49.623782Z","title":"Survey: interpolation methods in medical image processing,","venue":null,"work_id":"50986ba5-360c-48e6-8cb2-3763003d27b1","year":1999},"citing_paper":{"arxiv_id":"2501.17977","last_updated":"2025-01-29T20:21:41Z","snapshot_observed_at":"2026-08-10T04:23:56.826114Z","submitted_at":"2025-01-29T20:21:41Z","title":"TransRAD: Retentive Vision Transformer for Enhanced Radar Object Detection","version":1},"reference_index":59,"source":"pdf_text","source_observed_at":"2026-08-10T04:29:49.482262Z"},"links":{"citing_paper":"/paper/2501.17977"},"observation_digest":"sha256:2aa9b6e8c1eef1926da7f92057d7b9f9c163447f838142d6615d8111309833f2","observation_id":"d08b8052-0c65-47bb-aa7d-6c5bfd331687","resolution":{"observed_at":"2026-08-10T04:29:49.627937Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-11T06:34:44.6726+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-11T06:34:44.6726+00:00","source":"crossref"},{"observed_at":"2026-08-11T06:34:36.301508+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":"2026-08-10T04:29:49.608594Z","title":"A survey on performance metrics for object-detection algorithms,","venue":null,"work_id":"1fc057b1-1566-4f4d-8fb0-8212e4748892","year":2020},"citing_paper":{"arxiv_id":"2501.17977","last_updated":"2025-01-29T20:21:41Z","snapshot_observed_at":"2026-08-10T04:23:56.826114Z","submitted_at":"2025-01-29T20:21:41Z","title":"TransRAD: Retentive Vision Transformer for Enhanced Radar Object Detection","version":1},"reference_index":60,"source":"pdf_text","source_observed_at":"2026-08-10T04:29:49.486047Z"},"links":{"citing_paper":"/paper/2501.17977"},"observation_digest":"sha256:e93e4b23e64ccc1be5506d4c76a6c96a4150d733ed6aa2278a92dc4bc9a0ec4c","observation_id":"4f7ba369-d4c5-4618-952e-37e3d8aea1ba","resolution":{"observed_at":"2026-08-10T04:29:49.614607Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-11T06:34:44.6726+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-11T06:34:44.6726+00:00","source":"crossref"},{"observed_at":"2026-08-11T06:34:36.301508+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"2003.13593","last_updated":"2020-04-09T11:21:07Z","snapshot_observed_at":"2026-08-09T22:02:30.759945Z","submitted_at":"2020-03-30T16:20:46Z","title":"How Not to Give a FLOP: Combining Regularization and Pruning for Efficient Inference","version":2},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2003.13593","snapshot_observed_at":"2026-08-10T04:29:49.489820Z","title":"How not to give a flop: combin- ing regularization and pruning for efficient inference,","venue":null,"work_id":null,"year":2003},"citing_paper":{"arxiv_id":"2501.17977","last_updated":"2025-01-29T20:21:41Z","snapshot_observed_at":"2026-08-10T04:23:56.826114Z","submitted_at":"2025-01-29T20:21:41Z","title":"TransRAD: Retentive Vision Transformer for Enhanced Radar Object Detection","version":1},"reference_index":61,"source":"pdf_text","source_observed_at":"2026-08-10T04:29:49.489820Z"},"links":{"cited_paper":"/paper/2003.13593","citing_paper":"/paper/2501.17977"},"observation_digest":"sha256:062cd3c80c59d716d7889a8c4340d60d7624c2e4f431653097b378f3aba6d402","observation_id":"56a78cbc-193e-49e0-acaa-b69e38a97ae2","resolution":{"observed_at":"2026-08-10T04:29:49.489820Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}}],"paper":{"arxiv_id":"2501.17977","last_updated":"2025-01-29T20:21:41Z","latest_version":1,"primary_category":"cs.CV","snapshot_observed_at":"2026-08-10T04:23:56.826114Z","submitted_at":"2025-01-29T20:21:41Z","title":"TransRAD: Retentive Vision Transformer for Enhanced Radar Object Detection"},"reference_resolution":{"displayed":61,"state_counts":{"malformed_identifier":0,"metadata_mismatch":0,"parse_uncertain":0,"unresolved":25,"verified_exact":0,"verified_fuzzy":36},"total_outbound_references":61},"refusal":"A citation records a reference. It does not transfer a finding from one paper to another.","schema":"pith.paper-citation-record.v1","standing_sources":[{"observed_at":"2026-08-11T06:34:44.6726+00:00","source":"crossref"},{"observed_at":"2026-08-11T06:34:36.301508+00:00","source":"retraction_watch"}],"thesis":"As of 11 August 2026, this Paper Citation Record lists 61 of 61 outbound references and 0 inbound Pith citation observations for arXiv:2501.17977."}