{"as_of":"2026-08-12T13:45:00Z","caps":{"database_statements":6,"inbound":100,"outbound":100},"context_digest":"sha256:af8b08c3a4d73cb9455a26e274183596090619bf7e5ab36b68078a22f1841a05","coverage":[{"denominator":71,"lane":"reference_resolution","note":"Typed states for the displayed outbound observations.","records_observed":71,"source":"paper_references, paper_reference_links","source_observed_at":"2026-08-10T15:42:53.670680Z","state":"measured"},{"denominator":71,"lane":"standing_notices","note":"One-hop event checks from named stored sources.","records_observed":71,"source":"scholarly_work_events, retraction_status_cache","source_observed_at":"2026-08-12T06:34:41.77262+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/2501.13710/citation-record","integrity":"/paper/2501.13710/integrity","json":"/paper/2501.13710/citation-record.json","paper":"/paper/2501.13710"},"outbound":[{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-10T15:42:54.355805Z","title":"Bot-sort: Robust associations multi-pedestrian tracking, 2022","venue":null,"work_id":"b6c21b4c-f7ee-4426-8a31-602a3a4ce5ba","year":2022},"citing_paper":{"arxiv_id":"2501.13710","last_updated":"2025-01-23T14:38:40Z","snapshot_observed_at":"2026-08-10T15:38:13.671148Z","submitted_at":"2025-01-23T14:38:40Z","title":"YOLO11-JDE: Fast and Accurate Multi-Object Tracking with Self-Supervised Re-ID","version":1},"reference_index":1,"source":"pdf_text","source_observed_at":"2026-08-10T15:42:53.446034Z"},"links":{"citing_paper":"/paper/2501.13710"},"observation_digest":"sha256:ecdf8a2cc83fb87a848e8c0bbf7e27bcff413534470dde9dafb0ca20fec61fa9","observation_id":"cc9a03d8-0927-41cf-ba65-8f005ee6d00a","resolution":{"observed_at":"2026-08-10T15:42:54.359223Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-12T06:34:41.77262+00:00","source":"crossref"},{"observed_at":"2026-08-12T06:34:36.333875+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":"2026-08-10T15:42:54.346341Z","title":"Towards collaborative robotics in top view surveillance: A framework for multiple object tracking by detection using deep learning","venue":null,"work_id":"07d20cae-39de-453d-9ea2-2eaaf942e5f3","year":2021},"citing_paper":{"arxiv_id":"2501.13710","last_updated":"2025-01-23T14:38:40Z","snapshot_observed_at":"2026-08-10T15:38:13.671148Z","submitted_at":"2025-01-23T14:38:40Z","title":"YOLO11-JDE: Fast and Accurate Multi-Object Tracking with Self-Supervised Re-ID","version":1},"reference_index":2,"source":"pdf_text","source_observed_at":"2026-08-10T15:42:53.449988Z"},"links":{"citing_paper":"/paper/2501.13710"},"observation_digest":"sha256:ee53a392c693cc53bf510e19e696e433015c3a7b79d7d09f8b3396ef4258cd20","observation_id":"525b8f75-0c61-4106-b5b7-de6c9d137b73","resolution":{"observed_at":"2026-08-10T15:42:54.349738Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-12T06:34:41.77262+00:00","source":"crossref"},{"observed_at":"2026-08-12T06:34:36.333875+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":"2026-08-10T15:42:54.337214Z","title":"Bakhtiar Hasan, A","venue":null,"work_id":"fe550407-36af-404b-9a18-975c4ed921ac","year":2022},"citing_paper":{"arxiv_id":"2501.13710","last_updated":"2025-01-23T14:38:40Z","snapshot_observed_at":"2026-08-10T15:38:13.671148Z","submitted_at":"2025-01-23T14:38:40Z","title":"YOLO11-JDE: Fast and Accurate Multi-Object Tracking with Self-Supervised Re-ID","version":1},"reference_index":3,"source":"pdf_text","source_observed_at":"2026-08-10T15:42:53.453171Z"},"links":{"citing_paper":"/paper/2501.13710"},"observation_digest":"sha256:db8fb2a7577190ed279826df7bbbcd0ffb538dc5b6b3b8c5fe44e2633345bb90","observation_id":"27f37892-82eb-4735-a439-f5b3ab131e3e","resolution":{"observed_at":"2026-08-10T15:42:54.340316Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-12T06:34:41.77262+00:00","source":"crossref"},{"observed_at":"2026-08-12T06:34:36.333875+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":"2026-08-10T15:42:54.328201Z","title":"Evaluating mul- tiple object tracking performance: The clear mot metrics","venue":null,"work_id":"5fdffded-fba2-4623-91b1-a073dc837b21","year":2008},"citing_paper":{"arxiv_id":"2501.13710","last_updated":"2025-01-23T14:38:40Z","snapshot_observed_at":"2026-08-10T15:38:13.671148Z","submitted_at":"2025-01-23T14:38:40Z","title":"YOLO11-JDE: Fast and Accurate Multi-Object Tracking with Self-Supervised Re-ID","version":1},"reference_index":4,"source":"pdf_text","source_observed_at":"2026-08-10T15:42:53.456487Z"},"links":{"citing_paper":"/paper/2501.13710"},"observation_digest":"sha256:1894c4cc9da4197d1c6112287e103931ef89cf99120b66eae75fbf694dd01fa4","observation_id":"c8d23886-13de-409e-98a8-187711d0e41f","resolution":{"observed_at":"2026-08-10T15:42:54.331357Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-12T06:34:41.77262+00:00","source":"crossref"},{"observed_at":"2026-08-12T06:34:36.333875+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":"2026-08-10T15:42:54.318587Z","title":"Simple online and realtime tracking","venue":null,"work_id":"50a56e55-9088-4f4e-a86a-70858a672c73","year":2016},"citing_paper":{"arxiv_id":"2501.13710","last_updated":"2025-01-23T14:38:40Z","snapshot_observed_at":"2026-08-10T15:38:13.671148Z","submitted_at":"2025-01-23T14:38:40Z","title":"YOLO11-JDE: Fast and Accurate Multi-Object Tracking with Self-Supervised Re-ID","version":1},"reference_index":5,"source":"pdf_text","source_observed_at":"2026-08-10T15:42:53.460054Z"},"links":{"citing_paper":"/paper/2501.13710"},"observation_digest":"sha256:2cd2ff09de3030ae9bbd0fb2a794083811d9576a5aef0b165ddb8785409d3bd6","observation_id":"eb945bdf-4236-4a16-8d8e-30b0b7916d7a","resolution":{"observed_at":"2026-08-10T15:42:54.322164Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-12T06:34:41.77262+00:00","source":"crossref"},{"observed_at":"2026-08-12T06:34:36.333875+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":"2026-08-10T15:42:54.308755Z","title":"Yolov4: Optimal speed and accuracy of object detection, 2020","venue":null,"work_id":"80dee2d3-ac74-4ae2-a297-1455dccbe0b7","year":2020},"citing_paper":{"arxiv_id":"2501.13710","last_updated":"2025-01-23T14:38:40Z","snapshot_observed_at":"2026-08-10T15:38:13.671148Z","submitted_at":"2025-01-23T14:38:40Z","title":"YOLO11-JDE: Fast and Accurate Multi-Object Tracking with Self-Supervised Re-ID","version":1},"reference_index":6,"source":"pdf_text","source_observed_at":"2026-08-10T15:42:53.463430Z"},"links":{"citing_paper":"/paper/2501.13710"},"observation_digest":"sha256:1da6cfa4aaa55e0116a0f170c2adef52223a79982bf1431280658a5b6bb7c70a","observation_id":"f614b52b-064d-4ece-8ae8-85a6d389714a","resolution":{"observed_at":"2026-08-10T15:42:54.312314Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-12T06:34:41.77262+00:00","source":"crossref"},{"observed_at":"2026-08-12T06:34:36.333875+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":"2026-08-10T15:42:54.299185Z","title":"A unifying mutual information view of metric learn- ing: cross-entropy vs","venue":null,"work_id":"07de1c83-d5c4-4832-b23c-2f4b00c23af0","year":2021},"citing_paper":{"arxiv_id":"2501.13710","last_updated":"2025-01-23T14:38:40Z","snapshot_observed_at":"2026-08-10T15:38:13.671148Z","submitted_at":"2025-01-23T14:38:40Z","title":"YOLO11-JDE: Fast and Accurate Multi-Object Tracking with Self-Supervised Re-ID","version":1},"reference_index":7,"source":"pdf_text","source_observed_at":"2026-08-10T15:42:53.466767Z"},"links":{"citing_paper":"/paper/2501.13710"},"observation_digest":"sha256:71d6065d21fd4ec5ec8189cce138b5faa14ab073f29cc418edbe6b9007594b46","observation_id":"9bcfd8e5-97e4-4d20-bbe6-d7f50e4a57ce","resolution":{"observed_at":"2026-08-10T15:42:54.302761Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-12T06:34:41.77262+00:00","source":"crossref"},{"observed_at":"2026-08-12T06:34:36.333875+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":"2026-08-10T15:42:54.289588Z","title":"Ross Beveridge, and Stephen O’Hara","venue":null,"work_id":"940591dc-c4da-4347-932f-48616b24f8a9","year":null},"citing_paper":{"arxiv_id":"2501.13710","last_updated":"2025-01-23T14:38:40Z","snapshot_observed_at":"2026-08-10T15:38:13.671148Z","submitted_at":"2025-01-23T14:38:40Z","title":"YOLO11-JDE: Fast and Accurate Multi-Object Tracking with Self-Supervised Re-ID","version":1},"reference_index":8,"source":"pdf_text","source_observed_at":"2026-08-10T15:42:53.469886Z"},"links":{"citing_paper":"/paper/2501.13710"},"observation_digest":"sha256:ea27d05718c31e3b9786e11309fb41a96584a1601010c084964164cd084e9d71","observation_id":"25988aa7-3029-4878-93b4-0fdfbd4f88ba","resolution":{"observed_at":"2026-08-10T15:42:54.293083Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-12T06:34:41.77262+00:00","source":"crossref"},{"observed_at":"2026-08-12T06:34:36.333875+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":"2026-08-10T15:42:54.280046Z","title":"Large scale online learning of image similarity through rank- ing","venue":null,"work_id":"5839cfc9-561c-45f0-b4c4-6532b6580fa2","year":2010},"citing_paper":{"arxiv_id":"2501.13710","last_updated":"2025-01-23T14:38:40Z","snapshot_observed_at":"2026-08-10T15:38:13.671148Z","submitted_at":"2025-01-23T14:38:40Z","title":"YOLO11-JDE: Fast and Accurate Multi-Object Tracking with Self-Supervised Re-ID","version":1},"reference_index":9,"source":"pdf_text","source_observed_at":"2026-08-10T15:42:53.473067Z"},"links":{"citing_paper":"/paper/2501.13710"},"observation_digest":"sha256:4319ea003b3112868bdf3359710497cf8c8911b792ca92a055dad22bc3902e1b","observation_id":"40f3af58-dbe0-4d5b-93ee-1dd0d4956f7d","resolution":{"observed_at":"2026-08-10T15:42:54.283400Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-12T06:34:41.77262+00:00","source":"crossref"},{"observed_at":"2026-08-12T06:34:36.333875+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":"2026-08-10T15:42:54.270245Z","title":"A simple framework for contrastive learning of visual representations, 2020","venue":null,"work_id":"52f64175-99f7-4c40-8d54-9f29ba39e78e","year":2020},"citing_paper":{"arxiv_id":"2501.13710","last_updated":"2025-01-23T14:38:40Z","snapshot_observed_at":"2026-08-10T15:38:13.671148Z","submitted_at":"2025-01-23T14:38:40Z","title":"YOLO11-JDE: Fast and Accurate Multi-Object Tracking with Self-Supervised Re-ID","version":1},"reference_index":10,"source":"pdf_text","source_observed_at":"2026-08-10T15:42:53.476077Z"},"links":{"citing_paper":"/paper/2501.13710"},"observation_digest":"sha256:f83652d5a96c0f6ab1bac33dfa3d8f78a34bb719a7b92106ea8cb5deb4a509cb","observation_id":"c39179b1-0fbb-412c-a527-453df67e9da6","resolution":{"observed_at":"2026-08-10T15:42:54.273688Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-12T06:34:41.77262+00:00","source":"crossref"},{"observed_at":"2026-08-12T06:34:36.333875+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":"2026-08-10T15:42:54.260534Z","title":"Deep learning in video multi-object tracking: A survey.Neu- rocomputing, 381:61–88, Mar","venue":null,"work_id":"c950f5b6-4ade-488d-b252-20126fec7856","year":2020},"citing_paper":{"arxiv_id":"2501.13710","last_updated":"2025-01-23T14:38:40Z","snapshot_observed_at":"2026-08-10T15:38:13.671148Z","submitted_at":"2025-01-23T14:38:40Z","title":"YOLO11-JDE: Fast and Accurate Multi-Object Tracking with Self-Supervised Re-ID","version":1},"reference_index":11,"source":"pdf_text","source_observed_at":"2026-08-10T15:42:53.479041Z"},"links":{"citing_paper":"/paper/2501.13710"},"observation_digest":"sha256:37183213026f5168718cb0f25d480a3959bc897a67695b1ef75a3d8c21c01a5c","observation_id":"40db92c5-f102-4640-9e4d-2ae57c7f39e4","resolution":{"observed_at":"2026-08-10T15:42:54.263948Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-12T06:34:41.77262+00:00","source":"crossref"},{"observed_at":"2026-08-12T06:34:36.333875+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":"2026-08-10T15:42:54.250953Z","title":"Soccernet-tracking: Multiple object track- ing dataset and benchmark in soccer videos, 2022","venue":null,"work_id":"e1b1f7fa-7020-42f4-8174-ee3bf6c9163b","year":2022},"citing_paper":{"arxiv_id":"2501.13710","last_updated":"2025-01-23T14:38:40Z","snapshot_observed_at":"2026-08-10T15:38:13.671148Z","submitted_at":"2025-01-23T14:38:40Z","title":"YOLO11-JDE: Fast and Accurate Multi-Object Tracking with Self-Supervised Re-ID","version":1},"reference_index":12,"source":"pdf_text","source_observed_at":"2026-08-10T15:42:53.482106Z"},"links":{"citing_paper":"/paper/2501.13710"},"observation_digest":"sha256:38872a38fd15a6160037c4548f84e88a6bebd0b42afffc3f16317dff7b4f9d57","observation_id":"4f3c4ab3-d619-48e0-bc0f-182c8c612823","resolution":{"observed_at":"2026-08-10T15:42:54.254374Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-12T06:34:41.77262+00:00","source":"crossref"},{"observed_at":"2026-08-12T06:34:36.333875+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":"2026-08-10T15:42:54.241250Z","title":"Motchallenge: A benchmark for single-camera multiple target tracking, 2020","venue":null,"work_id":"cba23036-24b2-4cb3-b7c2-f31ef243dccd","year":2020},"citing_paper":{"arxiv_id":"2501.13710","last_updated":"2025-01-23T14:38:40Z","snapshot_observed_at":"2026-08-10T15:38:13.671148Z","submitted_at":"2025-01-23T14:38:40Z","title":"YOLO11-JDE: Fast and Accurate Multi-Object Tracking with Self-Supervised Re-ID","version":1},"reference_index":13,"source":"pdf_text","source_observed_at":"2026-08-10T15:42:53.485357Z"},"links":{"citing_paper":"/paper/2501.13710"},"observation_digest":"sha256:9b6c4abaf60862c394e2ac06f09b2619295cde8c37d07efb3ecf0d9fc286f59d","observation_id":"729b7550-1f50-43af-81d0-4e7262daaeb4","resolution":{"observed_at":"2026-08-10T15:42:54.244825Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-12T06:34:41.77262+00:00","source":"crossref"},{"observed_at":"2026-08-12T06:34:36.333875+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":"2026-08-10T15:42:54.231168Z","title":"Mot20: A benchmark for multi object tracking in crowded scenes, 2020","venue":null,"work_id":"16c28ffc-0e71-46e1-9fef-ddf46ea0a3d1","year":2020},"citing_paper":{"arxiv_id":"2501.13710","last_updated":"2025-01-23T14:38:40Z","snapshot_observed_at":"2026-08-10T15:38:13.671148Z","submitted_at":"2025-01-23T14:38:40Z","title":"YOLO11-JDE: Fast and Accurate Multi-Object Tracking with Self-Supervised Re-ID","version":1},"reference_index":14,"source":"pdf_text","source_observed_at":"2026-08-10T15:42:53.488346Z"},"links":{"citing_paper":"/paper/2501.13710"},"observation_digest":"sha256:9cdc919eaede1955a87a142d146b420f04980ffc1a462d6cde3f3f7c6c3e3fa9","observation_id":"f67f6cf4-c853-4060-83f5-df90ef921f9e","resolution":{"observed_at":"2026-08-10T15:42:54.234811Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-12T06:34:41.77262+00:00","source":"crossref"},{"observed_at":"2026-08-12T06:34:36.333875+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":"2026-08-10T15:42:54.221242Z","title":"Pedestrian detection: A benchmark","venue":null,"work_id":"5e9c47ca-1748-429f-bc66-ccbc49e491b3","year":2009},"citing_paper":{"arxiv_id":"2501.13710","last_updated":"2025-01-23T14:38:40Z","snapshot_observed_at":"2026-08-10T15:38:13.671148Z","submitted_at":"2025-01-23T14:38:40Z","title":"YOLO11-JDE: Fast and Accurate Multi-Object Tracking with Self-Supervised Re-ID","version":1},"reference_index":15,"source":"pdf_text","source_observed_at":"2026-08-10T15:42:53.491272Z"},"links":{"citing_paper":"/paper/2501.13710"},"observation_digest":"sha256:9b22e725288f0a5c73425b9634d7216f4d072c8641af5cd4501906b4152ded11","observation_id":"db5b1a90-4e6b-433e-9946-d132d25a60ee","resolution":{"observed_at":"2026-08-10T15:42:54.224502Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-12T06:34:41.77262+00:00","source":"crossref"},{"observed_at":"2026-08-12T06:34:36.333875+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":"2026-08-10T15:42:54.211108Z","title":"Strongsort: Make deep- sort great again, 2023","venue":null,"work_id":"7113812a-4e2c-4c53-8060-bd38d5f9b540","year":2023},"citing_paper":{"arxiv_id":"2501.13710","last_updated":"2025-01-23T14:38:40Z","snapshot_observed_at":"2026-08-10T15:38:13.671148Z","submitted_at":"2025-01-23T14:38:40Z","title":"YOLO11-JDE: Fast and Accurate Multi-Object Tracking with Self-Supervised Re-ID","version":1},"reference_index":16,"source":"pdf_text","source_observed_at":"2026-08-10T15:42:53.494529Z"},"links":{"citing_paper":"/paper/2501.13710"},"observation_digest":"sha256:747d1454b31429acb8d25b06bdc32484dd2b6c8ea9ce43afc578f82fdcf7ed29","observation_id":"7541e86c-fbfc-450d-ad64-f629e2636d3e","resolution":{"observed_at":"2026-08-10T15:42:54.214531Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-12T06:34:41.77262+00:00","source":"crossref"},{"observed_at":"2026-08-12T06:34:36.333875+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":"2026-08-10T15:42:54.201541Z","title":"A mobile vision system for robust multi-person tracking","venue":null,"work_id":"4c51dcbe-8130-4656-885d-d99c0e9b0fd3","year":2008},"citing_paper":{"arxiv_id":"2501.13710","last_updated":"2025-01-23T14:38:40Z","snapshot_observed_at":"2026-08-10T15:38:13.671148Z","submitted_at":"2025-01-23T14:38:40Z","title":"YOLO11-JDE: Fast and Accurate Multi-Object Tracking with Self-Supervised Re-ID","version":1},"reference_index":17,"source":"pdf_text","source_observed_at":"2026-08-10T15:42:53.497589Z"},"links":{"citing_paper":"/paper/2501.13710"},"observation_digest":"sha256:86ef0d5d207306d4ab50c4c5b58ce4189cde96beebb54cdfd175e1a8b4046ee3","observation_id":"6c1b8d5d-774b-470a-934e-a5f28e8959f0","resolution":{"observed_at":"2026-08-10T15:42:54.204890Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-12T06:34:41.77262+00:00","source":"crossref"},{"observed_at":"2026-08-12T06:34:36.333875+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":"2026-08-10T15:42:54.191876Z","title":"Huang, Jiangmiao Pang, Linlu Qiu, Haofeng Chen, Trevor Darrell, and Fisher Yu","venue":null,"work_id":"d71e4211-544b-4159-895e-b02c0169a5e9","year":2023},"citing_paper":{"arxiv_id":"2501.13710","last_updated":"2025-01-23T14:38:40Z","snapshot_observed_at":"2026-08-10T15:38:13.671148Z","submitted_at":"2025-01-23T14:38:40Z","title":"YOLO11-JDE: Fast and Accurate Multi-Object Tracking with Self-Supervised Re-ID","version":1},"reference_index":18,"source":"pdf_text","source_observed_at":"2026-08-10T15:42:53.500637Z"},"links":{"citing_paper":"/paper/2501.13710"},"observation_digest":"sha256:8efe823d346880432353cc8d020f380a622522439b2c3872e0eb139c7529bcbe","observation_id":"cac4f333-0968-4135-8204-efc7bef7475e","resolution":{"observed_at":"2026-08-10T15:42:54.195328Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-12T06:34:41.77262+00:00","source":"crossref"},{"observed_at":"2026-08-12T06:34:36.333875+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":"2026-08-10T15:42:54.182012Z","title":"Unsuper- vised pre-training for person re-identification, 2021","venue":null,"work_id":"6ffcfc85-b03c-4bdd-a56c-66169a4ffb8e","year":2021},"citing_paper":{"arxiv_id":"2501.13710","last_updated":"2025-01-23T14:38:40Z","snapshot_observed_at":"2026-08-10T15:38:13.671148Z","submitted_at":"2025-01-23T14:38:40Z","title":"YOLO11-JDE: Fast and Accurate Multi-Object Tracking with Self-Supervised Re-ID","version":1},"reference_index":19,"source":"pdf_text","source_observed_at":"2026-08-10T15:42:53.503596Z"},"links":{"citing_paper":"/paper/2501.13710"},"observation_digest":"sha256:3859c1733159b4ba4ffcd745eacb4ef3f5b993b5685fc30d1e39ee66626aa830","observation_id":"1807ccf1-18e3-4a53-98b3-6b1b910c4d57","resolution":{"observed_at":"2026-08-10T15:42:54.185449Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-12T06:34:41.77262+00:00","source":"crossref"},{"observed_at":"2026-08-12T06:34:36.333875+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":"2026-08-10T15:42:53.506622Z","title":"Yolox: Exceeding yolo series in 2021, 2021","venue":null,"work_id":null,"year":2021},"citing_paper":{"arxiv_id":"2501.13710","last_updated":"2025-01-23T14:38:40Z","snapshot_observed_at":"2026-08-10T15:38:13.671148Z","submitted_at":"2025-01-23T14:38:40Z","title":"YOLO11-JDE: Fast and Accurate Multi-Object Tracking with Self-Supervised Re-ID","version":1},"reference_index":20,"source":"pdf_text","source_observed_at":"2026-08-10T15:42:53.506622Z"},"links":{"citing_paper":"/paper/2501.13710"},"observation_digest":"sha256:83466238189258dafcd7ec0d154fae914fb8e9d09e532545a9742a6345b09a86","observation_id":"4f65cdc4-b529-4f1e-8714-748f8068d1c0","resolution":{"observed_at":"2026-08-10T15:42:53.506622Z","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":"2026-08-10T15:42:54.166143Z","title":"Momentum contrast for unsupervised visual rep- resentation learning, 2020","venue":null,"work_id":"6b917b05-a4ce-491a-96a8-1ea6866ead3d","year":2020},"citing_paper":{"arxiv_id":"2501.13710","last_updated":"2025-01-23T14:38:40Z","snapshot_observed_at":"2026-08-10T15:38:13.671148Z","submitted_at":"2025-01-23T14:38:40Z","title":"YOLO11-JDE: Fast and Accurate Multi-Object Tracking with Self-Supervised Re-ID","version":1},"reference_index":21,"source":"pdf_text","source_observed_at":"2026-08-10T15:42:53.509952Z"},"links":{"citing_paper":"/paper/2501.13710"},"observation_digest":"sha256:946abf1e5f60aade7ca9541500a625fa35275e09021bf3ceb698ea8ba8904928","observation_id":"e0464811-c11a-4733-a75b-387df38f08ff","resolution":{"observed_at":"2026-08-10T15:42:54.170038Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-12T06:34:41.77262+00:00","source":"crossref"},{"observed_at":"2026-08-12T06:34:36.333875+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"2006.02631","last_updated":"2020-07-15T03:33:02Z","snapshot_observed_at":"2026-08-10T02:14:15.507596Z","submitted_at":"2020-06-04T03:51:43Z","title":"FastReID: A Pytorch Toolbox for General Instance Re-identification","version":4},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2006.02631","snapshot_observed_at":"2026-08-10T15:42:53.513095Z","title":"Fastreid: A pytorch toolbox for general instance re-identification","venue":null,"work_id":null,"year":2006},"citing_paper":{"arxiv_id":"2501.13710","last_updated":"2025-01-23T14:38:40Z","snapshot_observed_at":"2026-08-10T15:38:13.671148Z","submitted_at":"2025-01-23T14:38:40Z","title":"YOLO11-JDE: Fast and Accurate Multi-Object Tracking with Self-Supervised Re-ID","version":1},"reference_index":22,"source":"pdf_text","source_observed_at":"2026-08-10T15:42:53.513095Z"},"links":{"cited_paper":"/paper/2006.02631","citing_paper":"/paper/2501.13710"},"observation_digest":"sha256:44a78609eb0599e2f4d9a2dfb2c2d4f162cdd415ed636159013326d7aa8f9f02","observation_id":"6cc65fda-9f4a-4e58-ae94-741f5a92768a","resolution":{"observed_at":"2026-08-10T15:42:53.513095Z","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":"2026-08-10T15:42:54.156598Z","title":"In de- fense of the triplet loss for person re-identification, 2017","venue":null,"work_id":"10176dc1-b523-443a-976c-5901c614a513","year":2017},"citing_paper":{"arxiv_id":"2501.13710","last_updated":"2025-01-23T14:38:40Z","snapshot_observed_at":"2026-08-10T15:38:13.671148Z","submitted_at":"2025-01-23T14:38:40Z","title":"YOLO11-JDE: Fast and Accurate Multi-Object Tracking with Self-Supervised Re-ID","version":1},"reference_index":23,"source":"pdf_text","source_observed_at":"2026-08-10T15:42:53.517149Z"},"links":{"citing_paper":"/paper/2501.13710"},"observation_digest":"sha256:3ed68842ee76e00bb51f343839a6b07bb9c81e4f273cbcbf550cb7ce6a32b33d","observation_id":"e60822e0-f194-4546-9a21-4234725a4f73","resolution":{"observed_at":"2026-08-10T15:42:54.159988Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-12T06:34:41.77262+00:00","source":"crossref"},{"observed_at":"2026-08-12T06:34:36.333875+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":"2026-08-10T15:42:54.146934Z","title":"Joint monocular 3d vehicle detection and tracking, 2019","venue":null,"work_id":"c723a85b-39bd-4def-8970-0a60abacee3a","year":2019},"citing_paper":{"arxiv_id":"2501.13710","last_updated":"2025-01-23T14:38:40Z","snapshot_observed_at":"2026-08-10T15:38:13.671148Z","submitted_at":"2025-01-23T14:38:40Z","title":"YOLO11-JDE: Fast and Accurate Multi-Object Tracking with Self-Supervised Re-ID","version":1},"reference_index":24,"source":"pdf_text","source_observed_at":"2026-08-10T15:42:53.520676Z"},"links":{"citing_paper":"/paper/2501.13710"},"observation_digest":"sha256:e6d83960245d5a6aa28b738ed5416fa4a5fdcdca5cfa37759a472da0688a115e","observation_id":"b97a2a0b-9ae8-4400-9eef-e292b3afa3ec","resolution":{"observed_at":"2026-08-10T15:42:54.150384Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-12T06:34:41.77262+00:00","source":"crossref"},{"observed_at":"2026-08-12T06:34:36.333875+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":"2026-08-10T15:42:54.137252Z","title":"Ultralytics yolov5, 2020","venue":null,"work_id":"91a306da-37e5-4ac3-918a-7fe4919a7713","year":2020},"citing_paper":{"arxiv_id":"2501.13710","last_updated":"2025-01-23T14:38:40Z","snapshot_observed_at":"2026-08-10T15:38:13.671148Z","submitted_at":"2025-01-23T14:38:40Z","title":"YOLO11-JDE: Fast and Accurate Multi-Object Tracking with Self-Supervised Re-ID","version":1},"reference_index":25,"source":"pdf_text","source_observed_at":"2026-08-10T15:42:53.523802Z"},"links":{"citing_paper":"/paper/2501.13710"},"observation_digest":"sha256:7f6fc7b5a874d0b822c1989afe54bb0f4f4d84e1f18ff58cbb55d30505b89c95","observation_id":"0c6614f5-fb55-4365-bf7b-55d16e387d11","resolution":{"observed_at":"2026-08-10T15:42:54.140522Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-12T06:34:41.77262+00:00","source":"crossref"},{"observed_at":"2026-08-12T06:34:36.333875+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":"2026-08-10T15:42:53.527029Z","title":"Ultralytics yolo11, 2024","venue":null,"work_id":null,"year":2024},"citing_paper":{"arxiv_id":"2501.13710","last_updated":"2025-01-23T14:38:40Z","snapshot_observed_at":"2026-08-10T15:38:13.671148Z","submitted_at":"2025-01-23T14:38:40Z","title":"YOLO11-JDE: Fast and Accurate Multi-Object Tracking with Self-Supervised Re-ID","version":1},"reference_index":26,"source":"pdf_text","source_observed_at":"2026-08-10T15:42:53.527029Z"},"links":{"citing_paper":"/paper/2501.13710"},"observation_digest":"sha256:3be0e286265c57e4e4655ad9a0538df42dbce807b82a1a9642f8ef163217972c","observation_id":"a00e18ae-8336-47b5-a816-8ef09c90f32d","resolution":{"observed_at":"2026-08-10T15:42:53.527029Z","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":"2026-08-10T15:42:54.122072Z","title":"Ultralytics YOLO, Jan","venue":null,"work_id":"bc4c740c-1699-4cbe-b8b8-de6da312eb61","year":2023},"citing_paper":{"arxiv_id":"2501.13710","last_updated":"2025-01-23T14:38:40Z","snapshot_observed_at":"2026-08-10T15:38:13.671148Z","submitted_at":"2025-01-23T14:38:40Z","title":"YOLO11-JDE: Fast and Accurate Multi-Object Tracking with Self-Supervised Re-ID","version":1},"reference_index":27,"source":"pdf_text","source_observed_at":"2026-08-10T15:42:53.530231Z"},"links":{"citing_paper":"/paper/2501.13710"},"observation_digest":"sha256:91fb320db2da335ea521e87c04fd15fe01f1842d9328bd3351b5b8418c6f1f64","observation_id":"6a155e79-a535-4ccf-8468-c8c746d44eea","resolution":{"observed_at":"2026-08-10T15:42:54.125357Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-12T06:34:41.77262+00:00","source":"crossref"},{"observed_at":"2026-08-12T06:34:36.333875+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":"2026-08-10T15:42:54.110130Z","title":"Conftrack: Kalman filter-based multi- person tracking by utilizing confidence score of detection box","venue":null,"work_id":"ea3f5cd8-a46e-463f-a23d-9516e33c056a","year":2024},"citing_paper":{"arxiv_id":"2501.13710","last_updated":"2025-01-23T14:38:40Z","snapshot_observed_at":"2026-08-10T15:38:13.671148Z","submitted_at":"2025-01-23T14:38:40Z","title":"YOLO11-JDE: Fast and Accurate Multi-Object Tracking with Self-Supervised Re-ID","version":1},"reference_index":28,"source":"pdf_text","source_observed_at":"2026-08-10T15:42:53.533378Z"},"links":{"citing_paper":"/paper/2501.13710"},"observation_digest":"sha256:0d76e671df41221b0e657b1f06b645d92906d5b0e9b2366deb81122d6f8be4d4","observation_id":"04356408-760a-4c85-ba75-8de466fe30ca","resolution":{"observed_at":"2026-08-10T15:42:54.113491Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-12T06:34:41.77262+00:00","source":"crossref"},{"observed_at":"2026-08-12T06:34:36.333875+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":"2026-08-10T15:42:54.100365Z","title":"Multi- ple object tracking for football game analysis","venue":null,"work_id":"a38cb9b8-b784-46ac-ac04-3818cde24e7b","year":2022},"citing_paper":{"arxiv_id":"2501.13710","last_updated":"2025-01-23T14:38:40Z","snapshot_observed_at":"2026-08-10T15:38:13.671148Z","submitted_at":"2025-01-23T14:38:40Z","title":"YOLO11-JDE: Fast and Accurate Multi-Object Tracking with Self-Supervised Re-ID","version":1},"reference_index":29,"source":"pdf_text","source_observed_at":"2026-08-10T15:42:53.536732Z"},"links":{"citing_paper":"/paper/2501.13710"},"observation_digest":"sha256:6bfb5455bb630088fe2b27d5913c001cbf569bee6de4a936e9a7883f84bae88c","observation_id":"14159da6-3658-4da3-bd87-597a1398d770","resolution":{"observed_at":"2026-08-10T15:42:54.104056Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-12T06:34:41.77262+00:00","source":"crossref"},{"observed_at":"2026-08-12T06:34:36.333875+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":"2026-08-10T15:42:54.090561Z","title":null,"venue":null,"work_id":"a8acd0c0-908d-4c7d-8a74-0b3b940a2fba","year":1960},"citing_paper":{"arxiv_id":"2501.13710","last_updated":"2025-01-23T14:38:40Z","snapshot_observed_at":"2026-08-10T15:38:13.671148Z","submitted_at":"2025-01-23T14:38:40Z","title":"YOLO11-JDE: Fast and Accurate Multi-Object Tracking with Self-Supervised Re-ID","version":1},"reference_index":30,"source":"pdf_text","source_observed_at":"2026-08-10T15:42:53.539976Z"},"links":{"citing_paper":"/paper/2501.13710"},"observation_digest":"sha256:53601f090a02e4a24585e89f4496f7d932af74748e8fd757b9983a9e9d7e5e96","observation_id":"395c9ba9-5725-46cb-a262-90289cd14335","resolution":{"observed_at":"2026-08-10T15:42:54.094088Z","resolver_source":"raw_fallback","status":"unresolved"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-12T06:34:41.77262+00:00","source":"crossref"},{"observed_at":"2026-08-12T06:34:36.333875+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":"2026-08-10T15:42:54.080715Z","title":null,"venue":null,"work_id":"30efb449-e1e7-4655-83f0-e3eac3187191","year":null},"citing_paper":{"arxiv_id":"2501.13710","last_updated":"2025-01-23T14:38:40Z","snapshot_observed_at":"2026-08-10T15:38:13.671148Z","submitted_at":"2025-01-23T14:38:40Z","title":"YOLO11-JDE: Fast and Accurate Multi-Object Tracking with Self-Supervised Re-ID","version":1},"reference_index":31,"source":"pdf_text","source_observed_at":"2026-08-10T15:42:53.543115Z"},"links":{"citing_paper":"/paper/2501.13710"},"observation_digest":"sha256:64ec2083215ce33634730496fecf84ff46716fdd730de4bee4f995deeaf2718d","observation_id":"660a4a4b-319d-4edb-8315-3cd23bfd6e50","resolution":{"observed_at":"2026-08-10T15:42:54.083937Z","resolver_source":"raw_fallback","status":"unresolved"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-12T06:34:41.77262+00:00","source":"crossref"},{"observed_at":"2026-08-12T06:34:36.333875+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":"2026-08-10T15:42:54.071017Z","title":"Simpletrack: Re- thinking and improving the jde approach for multi-object tracking, 2022","venue":null,"work_id":"e293d498-6663-453c-81a9-4bcd89458fb9","year":2022},"citing_paper":{"arxiv_id":"2501.13710","last_updated":"2025-01-23T14:38:40Z","snapshot_observed_at":"2026-08-10T15:38:13.671148Z","submitted_at":"2025-01-23T14:38:40Z","title":"YOLO11-JDE: Fast and Accurate Multi-Object Tracking with Self-Supervised Re-ID","version":1},"reference_index":32,"source":"pdf_text","source_observed_at":"2026-08-10T15:42:53.546383Z"},"links":{"citing_paper":"/paper/2501.13710"},"observation_digest":"sha256:01a112d8d5a85b8d209ddf2973f55f905df80f8f94133966433d8d29991bff8f","observation_id":"71f49c73-aa0d-4773-b8b7-f8f41a7f372a","resolution":{"observed_at":"2026-08-10T15:42:54.074465Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-12T06:34:41.77262+00:00","source":"crossref"},{"observed_at":"2026-08-12T06:34:36.333875+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":"2026-08-10T15:42:54.060983Z","title":"One more check: Making ”fake background” be tracked again, 2021","venue":null,"work_id":"759bb027-3206-4a4a-a4ab-88e4cfd5af3c","year":2021},"citing_paper":{"arxiv_id":"2501.13710","last_updated":"2025-01-23T14:38:40Z","snapshot_observed_at":"2026-08-10T15:38:13.671148Z","submitted_at":"2025-01-23T14:38:40Z","title":"YOLO11-JDE: Fast and Accurate Multi-Object Tracking with Self-Supervised Re-ID","version":1},"reference_index":33,"source":"pdf_text","source_observed_at":"2026-08-10T15:42:53.549401Z"},"links":{"citing_paper":"/paper/2501.13710"},"observation_digest":"sha256:1988ce0dc3824141d7a70a265a0fd3e7dd5f3c0eaa4d1b3ab42989ae9757f87d","observation_id":"5a3a8dd4-52e3-4919-a016-b501551956c6","resolution":{"observed_at":"2026-08-10T15:42:54.064351Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-12T06:34:41.77262+00:00","source":"crossref"},{"observed_at":"2026-08-12T06:34:36.333875+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":"2026-08-10T15:42:54.050516Z","title":"Rethinking the competition between detection and reid in multi-object tracking, 2022","venue":null,"work_id":"ab0b3762-fb88-4bb1-a05f-7d0553c87fad","year":2022},"citing_paper":{"arxiv_id":"2501.13710","last_updated":"2025-01-23T14:38:40Z","snapshot_observed_at":"2026-08-10T15:38:13.671148Z","submitted_at":"2025-01-23T14:38:40Z","title":"YOLO11-JDE: Fast and Accurate Multi-Object Tracking with Self-Supervised Re-ID","version":1},"reference_index":34,"source":"pdf_text","source_observed_at":"2026-08-10T15:42:53.552601Z"},"links":{"citing_paper":"/paper/2501.13710"},"observation_digest":"sha256:848de14babb9ed051b6271299052e9c532455bd97f3d2bad2fa547842762e638","observation_id":"7adc1865-413c-4c77-88a9-334877c007bb","resolution":{"observed_at":"2026-08-10T15:42:54.054039Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-12T06:34:41.77262+00:00","source":"crossref"},{"observed_at":"2026-08-12T06:34:36.333875+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":"2026-08-10T15:42:54.040720Z","title":"Focal loss for dense object detection, 2018","venue":null,"work_id":"55fc6f01-d86d-4c04-a059-25901dae537e","year":2018},"citing_paper":{"arxiv_id":"2501.13710","last_updated":"2025-01-23T14:38:40Z","snapshot_observed_at":"2026-08-10T15:38:13.671148Z","submitted_at":"2025-01-23T14:38:40Z","title":"YOLO11-JDE: Fast and Accurate Multi-Object Tracking with Self-Supervised Re-ID","version":1},"reference_index":35,"source":"pdf_text","source_observed_at":"2026-08-10T15:42:53.555715Z"},"links":{"citing_paper":"/paper/2501.13710"},"observation_digest":"sha256:9c762ac8be4e75fc57f1e0dc4fc8c8e529f458caf864681d5f14bde66a5d0511","observation_id":"b9f1c797-eed4-4799-99fe-c0195a3f9166","resolution":{"observed_at":"2026-08-10T15:42:54.044194Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-12T06:34:41.77262+00:00","source":"crossref"},{"observed_at":"2026-08-12T06:34:36.333875+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":"2026-08-10T15:42:53.558888Z","title":"Lawrence Zitnick, and Piotr Doll ´ar","venue":null,"work_id":null,"year":2015},"citing_paper":{"arxiv_id":"2501.13710","last_updated":"2025-01-23T14:38:40Z","snapshot_observed_at":"2026-08-10T15:38:13.671148Z","submitted_at":"2025-01-23T14:38:40Z","title":"YOLO11-JDE: Fast and Accurate Multi-Object Tracking with Self-Supervised Re-ID","version":1},"reference_index":36,"source":"pdf_text","source_observed_at":"2026-08-10T15:42:53.558888Z"},"links":{"citing_paper":"/paper/2501.13710"},"observation_digest":"sha256:d33995d70fef29828a8682403b7def0affa3a63c3bc2b0406ba1be86d387a17e","observation_id":"11dda27a-4b54-42c8-ad9a-fcd0630b36a8","resolution":{"observed_at":"2026-08-10T15:42:53.558888Z","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":"2026-08-10T15:42:54.023668Z","title":"Unsupervised person re-identification via softened similarity learning","venue":null,"work_id":"66bb2dbf-52db-4fd2-a414-e454205f260d","year":2020},"citing_paper":{"arxiv_id":"2501.13710","last_updated":"2025-01-23T14:38:40Z","snapshot_observed_at":"2026-08-10T15:38:13.671148Z","submitted_at":"2025-01-23T14:38:40Z","title":"YOLO11-JDE: Fast and Accurate Multi-Object Tracking with Self-Supervised Re-ID","version":1},"reference_index":37,"source":"pdf_text","source_observed_at":"2026-08-10T15:42:53.562236Z"},"links":{"citing_paper":"/paper/2501.13710"},"observation_digest":"sha256:38abcb1b18cffe1720795fe25fb11b751a027b39efab7062b768776ddb74bfd4","observation_id":"2879abc7-9630-401d-a9fa-0398283570bb","resolution":{"observed_at":"2026-08-10T15:42:54.027532Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-12T06:34:41.77262+00:00","source":"crossref"},{"observed_at":"2026-08-12T06:34:36.333875+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":"2026-08-10T15:42:54.012869Z","title":"Retinatrack: Online single stage joint detection and tracking, 2020","venue":null,"work_id":"fa584591-23b7-49ef-866c-ea04b95db6b7","year":2020},"citing_paper":{"arxiv_id":"2501.13710","last_updated":"2025-01-23T14:38:40Z","snapshot_observed_at":"2026-08-10T15:38:13.671148Z","submitted_at":"2025-01-23T14:38:40Z","title":"YOLO11-JDE: Fast and Accurate Multi-Object Tracking with Self-Supervised Re-ID","version":1},"reference_index":38,"source":"pdf_text","source_observed_at":"2026-08-10T15:42:53.565516Z"},"links":{"citing_paper":"/paper/2501.13710"},"observation_digest":"sha256:f1243be4a06353dad1cbff7423a682f6cd457247ed30d4edb01435ae53dfb9f6","observation_id":"6ddbd47e-0207-446f-b0bb-e304fb7eec77","resolution":{"observed_at":"2026-08-10T15:42:54.016505Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-12T06:34:41.77262+00:00","source":"crossref"},{"observed_at":"2026-08-12T06:34:36.333875+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":"2026-08-10T15:42:54.002886Z","title":"Hota: A higher order metric for evaluating multi- object tracking","venue":null,"work_id":"a75615b2-6cb9-4116-9abe-e9fba565a77b","year":2020},"citing_paper":{"arxiv_id":"2501.13710","last_updated":"2025-01-23T14:38:40Z","snapshot_observed_at":"2026-08-10T15:38:13.671148Z","submitted_at":"2025-01-23T14:38:40Z","title":"YOLO11-JDE: Fast and Accurate Multi-Object Tracking with Self-Supervised Re-ID","version":1},"reference_index":39,"source":"pdf_text","source_observed_at":"2026-08-10T15:42:53.568667Z"},"links":{"citing_paper":"/paper/2501.13710"},"observation_digest":"sha256:7f43b32845bdd6cb5f1c5e116e7e9a0ce85797142bff5be86a68ea763e75917b","observation_id":"4c408b47-6aae-4550-906f-0f60703ae6c7","resolution":{"observed_at":"2026-08-10T15:42:54.006377Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-12T06:34:41.77262+00:00","source":"crossref"},{"observed_at":"2026-08-12T06:34:36.333875+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":"2026-08-10T15:42:53.993318Z","title":"Mot16: A benchmark for multi-object tracking, 2016","venue":null,"work_id":"7e7049c1-368b-472c-a74e-ecc8b4f43fa7","year":2016},"citing_paper":{"arxiv_id":"2501.13710","last_updated":"2025-01-23T14:38:40Z","snapshot_observed_at":"2026-08-10T15:38:13.671148Z","submitted_at":"2025-01-23T14:38:40Z","title":"YOLO11-JDE: Fast and Accurate Multi-Object Tracking with Self-Supervised Re-ID","version":1},"reference_index":40,"source":"pdf_text","source_observed_at":"2026-08-10T15:42:53.571845Z"},"links":{"citing_paper":"/paper/2501.13710"},"observation_digest":"sha256:669ededc1db39559e208b2f4d87bdbc38b289a2ae3a1a6f2755a914dab40caf7","observation_id":"686031ec-2c24-42bf-b587-24c39754738a","resolution":{"observed_at":"2026-08-10T15:42:53.996742Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-12T06:34:41.77262+00:00","source":"crossref"},{"observed_at":"2026-08-12T06:34:36.333875+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"2008.09164","last_updated":"2020-08-20T19:08:56Z","snapshot_observed_at":"2026-08-12T11:07:33.427213Z","submitted_at":"2020-08-20T19:08:56Z","title":"PyTorch Metric Learning","version":1},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2008.09164","snapshot_observed_at":"2026-08-10T15:42:53.574784Z","title":"Belongie, and Ser-Nam Lim","venue":null,"work_id":null,"year":2008},"citing_paper":{"arxiv_id":"2501.13710","last_updated":"2025-01-23T14:38:40Z","snapshot_observed_at":"2026-08-10T15:38:13.671148Z","submitted_at":"2025-01-23T14:38:40Z","title":"YOLO11-JDE: Fast and Accurate Multi-Object Tracking with Self-Supervised Re-ID","version":1},"reference_index":41,"source":"pdf_text","source_observed_at":"2026-08-10T15:42:53.574784Z"},"links":{"cited_paper":"/paper/2008.09164","citing_paper":"/paper/2501.13710"},"observation_digest":"sha256:871e4d1de15bb85a243ebb48302bd49fb6acbca62137522bd44ba0f27f880e56","observation_id":"5be918df-e36d-41a7-ab7c-db0027cd73b1","resolution":{"observed_at":"2026-08-10T15:42:53.574784Z","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":"2026-08-10T15:42:53.983327Z","title":"Sort and deep-sort based multi-object tracking for mobile robotics: Evaluation with new data association metrics","venue":null,"work_id":"e8fbdd66-3700-4ca4-aeb6-889d5dce9473","year":2022},"citing_paper":{"arxiv_id":"2501.13710","last_updated":"2025-01-23T14:38:40Z","snapshot_observed_at":"2026-08-10T15:38:13.671148Z","submitted_at":"2025-01-23T14:38:40Z","title":"YOLO11-JDE: Fast and Accurate Multi-Object Tracking with Self-Supervised Re-ID","version":1},"reference_index":42,"source":"pdf_text","source_observed_at":"2026-08-10T15:42:53.578254Z"},"links":{"citing_paper":"/paper/2501.13710"},"observation_digest":"sha256:e0c58aef41058bb190663c98a5b0674a9d6b8b791346df9c3ae0b66e5ebc6e85","observation_id":"898e9a0e-4e5b-432f-9bd8-6751fab6efc4","resolution":{"observed_at":"2026-08-10T15:42:53.986829Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-12T06:34:41.77262+00:00","source":"crossref"},{"observed_at":"2026-08-12T06:34:36.333875+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":"2026-08-10T15:42:53.973706Z","title":"Yolov3: An incremental improvement, 2018","venue":null,"work_id":"e56bf29e-7ce6-4bad-b43f-073c7461f2ee","year":2018},"citing_paper":{"arxiv_id":"2501.13710","last_updated":"2025-01-23T14:38:40Z","snapshot_observed_at":"2026-08-10T15:38:13.671148Z","submitted_at":"2025-01-23T14:38:40Z","title":"YOLO11-JDE: Fast and Accurate Multi-Object Tracking with Self-Supervised Re-ID","version":1},"reference_index":43,"source":"pdf_text","source_observed_at":"2026-08-10T15:42:53.581326Z"},"links":{"citing_paper":"/paper/2501.13710"},"observation_digest":"sha256:82eb454297e2076933a916fdc76567582a8d4b0b7b765121b085f5e58dcc5282","observation_id":"540e5262-2e96-47fc-9ef9-4ecf363ff31b","resolution":{"observed_at":"2026-08-10T15:42:53.976986Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-12T06:34:41.77262+00:00","source":"crossref"},{"observed_at":"2026-08-12T06:34:36.333875+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":"2026-08-10T15:42:53.584363Z","title":"Faster r-cnn: Towards real-time object detection with region proposal networks, 2016","venue":null,"work_id":null,"year":2016},"citing_paper":{"arxiv_id":"2501.13710","last_updated":"2025-01-23T14:38:40Z","snapshot_observed_at":"2026-08-10T15:38:13.671148Z","submitted_at":"2025-01-23T14:38:40Z","title":"YOLO11-JDE: Fast and Accurate Multi-Object Tracking with Self-Supervised Re-ID","version":1},"reference_index":44,"source":"pdf_text","source_observed_at":"2026-08-10T15:42:53.584363Z"},"links":{"citing_paper":"/paper/2501.13710"},"observation_digest":"sha256:a4f4cf2f1c61cb81f0a3b400cffe30b6baae6dbbee4f4892dc5ac2ec390f6cb1","observation_id":"4a5f6309-35ed-4c97-95ef-ed79db8b4b46","resolution":{"observed_at":"2026-08-10T15:42:53.584363Z","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":"2026-08-10T15:42:53.958259Z","title":"Joint counting, detection and re- identification for multi-object tracking, 2024","venue":null,"work_id":"39130738-079b-488e-9eb0-8f631d7339d3","year":2024},"citing_paper":{"arxiv_id":"2501.13710","last_updated":"2025-01-23T14:38:40Z","snapshot_observed_at":"2026-08-10T15:38:13.671148Z","submitted_at":"2025-01-23T14:38:40Z","title":"YOLO11-JDE: Fast and Accurate Multi-Object Tracking with Self-Supervised Re-ID","version":1},"reference_index":45,"source":"pdf_text","source_observed_at":"2026-08-10T15:42:53.587846Z"},"links":{"citing_paper":"/paper/2501.13710"},"observation_digest":"sha256:5f68aa342ec83fb8637f7d007838a5af9ae656f6398fc634970569859d00bdaf","observation_id":"d8ab971c-8e4b-4087-a4d5-c891ca7c2893","resolution":{"observed_at":"2026-08-10T15:42:53.961753Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-12T06:34:41.77262+00:00","source":"crossref"},{"observed_at":"2026-08-12T06:34:36.333875+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":"2026-08-10T15:42:53.948678Z","title":"Zou, Rita Cuc- chiara, and Carlo Tomasi","venue":null,"work_id":"f106be47-06ee-4c2c-9a63-877fdfca1fb1","year":2016},"citing_paper":{"arxiv_id":"2501.13710","last_updated":"2025-01-23T14:38:40Z","snapshot_observed_at":"2026-08-10T15:38:13.671148Z","submitted_at":"2025-01-23T14:38:40Z","title":"YOLO11-JDE: Fast and Accurate Multi-Object Tracking with Self-Supervised Re-ID","version":1},"reference_index":46,"source":"pdf_text","source_observed_at":"2026-08-10T15:42:53.590928Z"},"links":{"citing_paper":"/paper/2501.13710"},"observation_digest":"sha256:1c8aab3e237e781ee88970426f5204900a73c7af33e9d1d34fd16c27987b51d0","observation_id":"67479902-1047-4edd-b1b9-5d9133fa384e","resolution":{"observed_at":"2026-08-10T15:42:53.952134Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-12T06:34:41.77262+00:00","source":"crossref"},{"observed_at":"2026-08-12T06:34:36.333875+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":"2026-08-10T15:42:53.938789Z","title":"Rousseeuw","venue":null,"work_id":"d5867962-9383-4d34-b05c-e5f899290c9b","year":1987},"citing_paper":{"arxiv_id":"2501.13710","last_updated":"2025-01-23T14:38:40Z","snapshot_observed_at":"2026-08-10T15:38:13.671148Z","submitted_at":"2025-01-23T14:38:40Z","title":"YOLO11-JDE: Fast and Accurate Multi-Object Tracking with Self-Supervised Re-ID","version":1},"reference_index":47,"source":"pdf_text","source_observed_at":"2026-08-10T15:42:53.593929Z"},"links":{"citing_paper":"/paper/2501.13710"},"observation_digest":"sha256:e520403a195ac481ec3ea238b62ceeeb9d1767d5839e2686181e14a199bc14ea","observation_id":"3ec9254c-24d9-4345-8691-07bf7cff96f6","resolution":{"observed_at":"2026-08-10T15:42:53.942409Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-12T06:34:41.77262+00:00","source":"crossref"},{"observed_at":"2026-08-12T06:34:36.333875+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":"2026-08-10T15:42:53.596984Z","title":"Facenet: A unified embedding for face recognition and clus- tering","venue":null,"work_id":null,"year":2015},"citing_paper":{"arxiv_id":"2501.13710","last_updated":"2025-01-23T14:38:40Z","snapshot_observed_at":"2026-08-10T15:38:13.671148Z","submitted_at":"2025-01-23T14:38:40Z","title":"YOLO11-JDE: Fast and Accurate Multi-Object Tracking with Self-Supervised Re-ID","version":1},"reference_index":48,"source":"pdf_text","source_observed_at":"2026-08-10T15:42:53.596984Z"},"links":{"citing_paper":"/paper/2501.13710"},"observation_digest":"sha256:3ed3dbe8e308919ac7d0d65da5901ae74a85413bed9e767954850d8445122a79","observation_id":"91e06b60-d2e1-401f-9c3a-4d405c1390e3","resolution":{"observed_at":"2026-08-10T15:42:53.596984Z","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":"2026-08-10T15:42:53.923092Z","title":"Crowdhuman: A benchmark for detecting human in a crowd, 2018","venue":null,"work_id":"d0c46257-fa52-4ae1-a4ee-5be0dc3b2b55","year":2018},"citing_paper":{"arxiv_id":"2501.13710","last_updated":"2025-01-23T14:38:40Z","snapshot_observed_at":"2026-08-10T15:38:13.671148Z","submitted_at":"2025-01-23T14:38:40Z","title":"YOLO11-JDE: Fast and Accurate Multi-Object Tracking with Self-Supervised Re-ID","version":1},"reference_index":49,"source":"pdf_text","source_observed_at":"2026-08-10T15:42:53.600058Z"},"links":{"citing_paper":"/paper/2501.13710"},"observation_digest":"sha256:42f81eb9dc32f5b9b9149290c76f92941c74e0b4ffe294844969b4263e8e7826","observation_id":"a70c6689-8891-4146-b0f8-9dd10295e0c9","resolution":{"observed_at":"2026-08-10T15:42:53.926582Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-12T06:34:41.77262+00:00","source":"crossref"},{"observed_at":"2026-08-12T06:34:36.333875+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":"2026-08-10T15:42:53.913300Z","title":"Boost- track: boosting the similarity measure and detection confi- dence for improved multiple object tracking.Machine Vision and Applications, 35(3), 2024","venue":null,"work_id":"261d9c20-937b-427b-be6d-1ad03a21254b","year":2024},"citing_paper":{"arxiv_id":"2501.13710","last_updated":"2025-01-23T14:38:40Z","snapshot_observed_at":"2026-08-10T15:38:13.671148Z","submitted_at":"2025-01-23T14:38:40Z","title":"YOLO11-JDE: Fast and Accurate Multi-Object Tracking with Self-Supervised Re-ID","version":1},"reference_index":50,"source":"pdf_text","source_observed_at":"2026-08-10T15:42:53.603260Z"},"links":{"citing_paper":"/paper/2501.13710"},"observation_digest":"sha256:b4f84108d86c24db4f5e1683191a5b27e4208cd7a59b464ec8d013e8dc735941","observation_id":"a70e9876-15fb-43d8-876b-9c928dbd9b28","resolution":{"observed_at":"2026-08-10T15:42:53.916674Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-12T06:34:41.77262+00:00","source":"crossref"},{"observed_at":"2026-08-12T06:34:36.333875+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":"2026-08-10T15:42:53.903600Z","title":"Online and real-time tracking in a surveillance scenario, 2021","venue":null,"work_id":"bda87f55-13cc-4585-8408-23fcf395c2ca","year":2021},"citing_paper":{"arxiv_id":"2501.13710","last_updated":"2025-01-23T14:38:40Z","snapshot_observed_at":"2026-08-10T15:38:13.671148Z","submitted_at":"2025-01-23T14:38:40Z","title":"YOLO11-JDE: Fast and Accurate Multi-Object Tracking with Self-Supervised Re-ID","version":1},"reference_index":51,"source":"pdf_text","source_observed_at":"2026-08-10T15:42:53.606440Z"},"links":{"citing_paper":"/paper/2501.13710"},"observation_digest":"sha256:3dc9957a999a4bd2c811b79d2118ff699a5d62cd328562b6ca1c836369604e57","observation_id":"57bb23d8-9acf-4389-bc24-a17290005d1d","resolution":{"observed_at":"2026-08-10T15:42:53.907235Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-12T06:34:41.77262+00:00","source":"crossref"},{"observed_at":"2026-08-12T06:34:36.333875+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":"2026-08-10T15:42:53.894102Z","title":"Repre- sentation learning with contrastive predictive coding, 2019","venue":null,"work_id":"a91d0b66-05bd-49f7-9327-5a42ae63d168","year":2019},"citing_paper":{"arxiv_id":"2501.13710","last_updated":"2025-01-23T14:38:40Z","snapshot_observed_at":"2026-08-10T15:38:13.671148Z","submitted_at":"2025-01-23T14:38:40Z","title":"YOLO11-JDE: Fast and Accurate Multi-Object Tracking with Self-Supervised Re-ID","version":1},"reference_index":52,"source":"pdf_text","source_observed_at":"2026-08-10T15:42:53.609675Z"},"links":{"citing_paper":"/paper/2501.13710"},"observation_digest":"sha256:56a12006611bc9fd0c2758411fefb9e31482e9a9777fd62ca5135173a34bdcca","observation_id":"93645a70-706f-4439-93a4-a9c651b4a733","resolution":{"observed_at":"2026-08-10T15:42:53.897577Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-12T06:34:41.77262+00:00","source":"crossref"},{"observed_at":"2026-08-12T06:34:36.333875+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":"2026-08-10T15:42:53.884246Z","title":"Clausi, and John Zelek","venue":null,"work_id":"54ad40df-c91c-448b-8c08-522434c820a5","year":2021},"citing_paper":{"arxiv_id":"2501.13710","last_updated":"2025-01-23T14:38:40Z","snapshot_observed_at":"2026-08-10T15:38:13.671148Z","submitted_at":"2025-01-23T14:38:40Z","title":"YOLO11-JDE: Fast and Accurate Multi-Object Tracking with Self-Supervised Re-ID","version":1},"reference_index":53,"source":"pdf_text","source_observed_at":"2026-08-10T15:42:53.612981Z"},"links":{"citing_paper":"/paper/2501.13710"},"observation_digest":"sha256:18d91e4ecbe6617050d23f59b8423bab88bd10df0b9199541747fbfbfd4208ca","observation_id":"0b766ccf-3738-4695-a7d0-5e324142b4f9","resolution":{"observed_at":"2026-08-10T15:42:53.887686Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-12T06:34:41.77262+00:00","source":"crossref"},{"observed_at":"2026-08-12T06:34:36.333875+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":"2026-08-10T15:42:53.874455Z","title":"Deep metric learning with angular loss, 2017","venue":null,"work_id":"42ece017-960f-4168-abde-76220c50bda5","year":2017},"citing_paper":{"arxiv_id":"2501.13710","last_updated":"2025-01-23T14:38:40Z","snapshot_observed_at":"2026-08-10T15:38:13.671148Z","submitted_at":"2025-01-23T14:38:40Z","title":"YOLO11-JDE: Fast and Accurate Multi-Object Tracking with Self-Supervised Re-ID","version":1},"reference_index":54,"source":"pdf_text","source_observed_at":"2026-08-10T15:42:53.616272Z"},"links":{"citing_paper":"/paper/2501.13710"},"observation_digest":"sha256:f7b06afd691c8b35c618551b0f47ed25dcfe93738d6adf65b57b55e113c36aad","observation_id":"a179f5ca-d2f3-41e1-ac8b-35006c159fc8","resolution":{"observed_at":"2026-08-10T15:42:53.877802Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-12T06:34:41.77262+00:00","source":"crossref"},{"observed_at":"2026-08-12T06:34:36.333875+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":"2026-08-10T15:42:53.864179Z","title":null,"venue":null,"work_id":"3205fa50-2a4f-4cba-8c07-957cd2d370a3","year":2020},"citing_paper":{"arxiv_id":"2501.13710","last_updated":"2025-01-23T14:38:40Z","snapshot_observed_at":"2026-08-10T15:38:13.671148Z","submitted_at":"2025-01-23T14:38:40Z","title":"YOLO11-JDE: Fast and Accurate Multi-Object Tracking with Self-Supervised Re-ID","version":1},"reference_index":55,"source":"pdf_text","source_observed_at":"2026-08-10T15:42:53.619432Z"},"links":{"citing_paper":"/paper/2501.13710"},"observation_digest":"sha256:53175fee8c48a7a59b0f8e36892a8eb561c5a055086b1ca191f606491c45c1fd","observation_id":"929afb34-991f-4aab-a521-274110162d72","resolution":{"observed_at":"2026-08-10T15:42:53.868227Z","resolver_source":"raw_fallback","status":"unresolved"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-12T06:34:41.77262+00:00","source":"crossref"},{"observed_at":"2026-08-12T06:34:36.333875+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":"2026-08-10T15:42:53.854436Z","title":"Smiletrack: Simi- larity learning for occlusion-aware multiple object tracking,","venue":null,"work_id":"1325b550-ffbc-4957-8bed-86e5728d89c7","year":null},"citing_paper":{"arxiv_id":"2501.13710","last_updated":"2025-01-23T14:38:40Z","snapshot_observed_at":"2026-08-10T15:38:13.671148Z","submitted_at":"2025-01-23T14:38:40Z","title":"YOLO11-JDE: Fast and Accurate Multi-Object Tracking with Self-Supervised Re-ID","version":1},"reference_index":56,"source":"pdf_text","source_observed_at":"2026-08-10T15:42:53.622435Z"},"links":{"citing_paper":"/paper/2501.13710"},"observation_digest":"sha256:db627dc5bb1ab961aa9b43327343ad0d53e1ce210eb0c00815c968a32cf6ad46","observation_id":"df4b8054-2c2e-4a4c-a7b6-6514682d0901","resolution":{"observed_at":"2026-08-10T15:42:53.857891Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-12T06:34:41.77262+00:00","source":"crossref"},{"observed_at":"2026-08-12T06:34:36.333875+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":"2026-08-10T15:42:53.844553Z","title":"Towards real-time multi-object tracking,","venue":null,"work_id":"e447573b-6521-4154-b2c9-31ac4afabd7a","year":null},"citing_paper":{"arxiv_id":"2501.13710","last_updated":"2025-01-23T14:38:40Z","snapshot_observed_at":"2026-08-10T15:38:13.671148Z","submitted_at":"2025-01-23T14:38:40Z","title":"YOLO11-JDE: Fast and Accurate Multi-Object Tracking with Self-Supervised Re-ID","version":1},"reference_index":57,"source":"pdf_text","source_observed_at":"2026-08-10T15:42:53.626307Z"},"links":{"citing_paper":"/paper/2501.13710"},"observation_digest":"sha256:44579335fc88892c7f6941acda2dc6c5056f2829a7cee43e44e83d0ae1cf4f6e","observation_id":"bcf5a771-06d4-42ec-a1a3-0b2c6f6a156f","resolution":{"observed_at":"2026-08-10T15:42:53.848059Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-12T06:34:41.77262+00:00","source":"crossref"},{"observed_at":"2026-08-12T06:34:36.333875+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":"2026-08-10T15:42:53.834980Z","title":null,"venue":null,"work_id":"f082d54d-5a54-41cc-a383-127372e1c6af","year":2020},"citing_paper":{"arxiv_id":"2501.13710","last_updated":"2025-01-23T14:38:40Z","snapshot_observed_at":"2026-08-10T15:38:13.671148Z","submitted_at":"2025-01-23T14:38:40Z","title":"YOLO11-JDE: Fast and Accurate Multi-Object Tracking with Self-Supervised Re-ID","version":1},"reference_index":58,"source":"pdf_text","source_observed_at":"2026-08-10T15:42:53.629530Z"},"links":{"citing_paper":"/paper/2501.13710"},"observation_digest":"sha256:c42ceab7cc41263506f310f16d84675657a471e07a7121c4be78a95a5362a5a2","observation_id":"90a75f70-dd05-4ea6-95e6-67a93525c860","resolution":{"observed_at":"2026-08-10T15:42:53.838175Z","resolver_source":"raw_fallback","status":"unresolved"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-12T06:34:41.77262+00:00","source":"crossref"},{"observed_at":"2026-08-12T06:34:36.333875+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":"2026-08-10T15:42:53.632530Z","title":"Simple online and realtime tracking with a deep association metric,","venue":null,"work_id":null,"year":null},"citing_paper":{"arxiv_id":"2501.13710","last_updated":"2025-01-23T14:38:40Z","snapshot_observed_at":"2026-08-10T15:38:13.671148Z","submitted_at":"2025-01-23T14:38:40Z","title":"YOLO11-JDE: Fast and Accurate Multi-Object Tracking with Self-Supervised Re-ID","version":1},"reference_index":59,"source":"pdf_text","source_observed_at":"2026-08-10T15:42:53.632530Z"},"links":{"citing_paper":"/paper/2501.13710"},"observation_digest":"sha256:9f92f39417cc09f389d623b7197fc52e33c4809bc2e73820cb3d70589981de6b","observation_id":"46d8b6be-a5a3-4813-880d-d77a7ae2adfd","resolution":{"observed_at":"2026-08-10T15:42:53.632530Z","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":"2026-08-10T15:42:53.819419Z","title":"Joint detection and identification feature learn- ing for person search, 2017","venue":null,"work_id":"cc2c9caa-3ecd-4689-83e0-7439bcbb31fa","year":2017},"citing_paper":{"arxiv_id":"2501.13710","last_updated":"2025-01-23T14:38:40Z","snapshot_observed_at":"2026-08-10T15:38:13.671148Z","submitted_at":"2025-01-23T14:38:40Z","title":"YOLO11-JDE: Fast and Accurate Multi-Object Tracking with Self-Supervised Re-ID","version":1},"reference_index":60,"source":"pdf_text","source_observed_at":"2026-08-10T15:42:53.635907Z"},"links":{"citing_paper":"/paper/2501.13710"},"observation_digest":"sha256:53f1476bb4fb55d6f3f522bda5c33e75856225449d3e69ed4aa9a1d650cc78a9","observation_id":"7384025e-a799-4de4-87e4-432cb7e2455f","resolution":{"observed_at":"2026-08-10T15:42:53.822694Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-12T06:34:41.77262+00:00","source":"crossref"},{"observed_at":"2026-08-12T06:34:36.333875+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":"2026-08-10T15:42:53.809292Z","title":"Hard to track objects with irregular motions and sim- ilar appearances? make it easier by buffering the matching space, 2023","venue":null,"work_id":"8c0ffb81-b847-4c32-a904-f169bb1e8b83","year":2023},"citing_paper":{"arxiv_id":"2501.13710","last_updated":"2025-01-23T14:38:40Z","snapshot_observed_at":"2026-08-10T15:38:13.671148Z","submitted_at":"2025-01-23T14:38:40Z","title":"YOLO11-JDE: Fast and Accurate Multi-Object Tracking with Self-Supervised Re-ID","version":1},"reference_index":61,"source":"pdf_text","source_observed_at":"2026-08-10T15:42:53.639289Z"},"links":{"citing_paper":"/paper/2501.13710"},"observation_digest":"sha256:76c588e4d3d4936483432fac4cebb13757b6252643b2c00abaf8058c8c8c76c8","observation_id":"ad16186a-97f0-4a32-a4af-35b70d2abcd0","resolution":{"observed_at":"2026-08-10T15:42:53.812740Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-12T06:34:41.77262+00:00","source":"crossref"},{"observed_at":"2026-08-12T06:34:36.333875+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":"2026-08-10T15:42:53.799644Z","title":"Utm: A unified multiple object tracking model with identity- aware feature enhancement","venue":null,"work_id":"b0521d4c-6a82-466f-8de8-c31033ed296f","year":2023},"citing_paper":{"arxiv_id":"2501.13710","last_updated":"2025-01-23T14:38:40Z","snapshot_observed_at":"2026-08-10T15:38:13.671148Z","submitted_at":"2025-01-23T14:38:40Z","title":"YOLO11-JDE: Fast and Accurate Multi-Object Tracking with Self-Supervised Re-ID","version":1},"reference_index":62,"source":"pdf_text","source_observed_at":"2026-08-10T15:42:53.642407Z"},"links":{"citing_paper":"/paper/2501.13710"},"observation_digest":"sha256:3cde3d8c8c2a64da8aa5ca86cfa1da566a73c524b3c0243dc44b79efa201eb52","observation_id":"d895088f-9b9c-4879-8c93-a0d8648c5956","resolution":{"observed_at":"2026-08-10T15:42:53.802991Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-12T06:34:41.77262+00:00","source":"crossref"},{"observed_at":"2026-08-12T06:34:36.333875+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":"2026-08-10T15:42:53.789520Z","title":"Relationtrack: Relation-aware multiple object tracking with decoupled representation, 2021","venue":null,"work_id":"4accf815-39bc-4972-8667-eaaeb2ca6669","year":2021},"citing_paper":{"arxiv_id":"2501.13710","last_updated":"2025-01-23T14:38:40Z","snapshot_observed_at":"2026-08-10T15:38:13.671148Z","submitted_at":"2025-01-23T14:38:40Z","title":"YOLO11-JDE: Fast and Accurate Multi-Object Tracking with Self-Supervised Re-ID","version":1},"reference_index":63,"source":"pdf_text","source_observed_at":"2026-08-10T15:42:53.645323Z"},"links":{"citing_paper":"/paper/2501.13710"},"observation_digest":"sha256:ee17ac12af34f5b0975b9303781b1d960f221756f96fbfbef4c30da861135a1b","observation_id":"25860692-002f-439e-a9d0-48f6785fab2e","resolution":{"observed_at":"2026-08-10T15:42:53.793295Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-12T06:34:41.77262+00:00","source":"crossref"},{"observed_at":"2026-08-12T06:34:36.333875+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":"2026-08-10T15:42:53.779464Z","title":"Poi: Multiple object tracking with high per- formance detection and appearance feature, 2016","venue":null,"work_id":"cee25ead-816b-4243-a94f-09a5514bfa47","year":2016},"citing_paper":{"arxiv_id":"2501.13710","last_updated":"2025-01-23T14:38:40Z","snapshot_observed_at":"2026-08-10T15:38:13.671148Z","submitted_at":"2025-01-23T14:38:40Z","title":"YOLO11-JDE: Fast and Accurate Multi-Object Tracking with Self-Supervised Re-ID","version":1},"reference_index":64,"source":"pdf_text","source_observed_at":"2026-08-10T15:42:53.648470Z"},"links":{"citing_paper":"/paper/2501.13710"},"observation_digest":"sha256:7e8853d5479664686238602219f940af6f0f723b13ddbae4b8589079d1e5b959","observation_id":"38636eed-9754-4732-add0-9fbdbb755d74","resolution":{"observed_at":"2026-08-10T15:42:53.782940Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-12T06:34:41.77262+00:00","source":"crossref"},{"observed_at":"2026-08-12T06:34:36.333875+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":"2026-08-10T15:42:53.651561Z","title":"Dauphin, and David Lopez-Paz","venue":null,"work_id":null,"year":2018},"citing_paper":{"arxiv_id":"2501.13710","last_updated":"2025-01-23T14:38:40Z","snapshot_observed_at":"2026-08-10T15:38:13.671148Z","submitted_at":"2025-01-23T14:38:40Z","title":"YOLO11-JDE: Fast and Accurate Multi-Object Tracking with Self-Supervised Re-ID","version":1},"reference_index":65,"source":"pdf_text","source_observed_at":"2026-08-10T15:42:53.651561Z"},"links":{"citing_paper":"/paper/2501.13710"},"observation_digest":"sha256:3e7da73433df82457fa591e91883e6e162a11b4263e0243d7012cd21bca069b7","observation_id":"938de5d8-6b72-4589-a9c5-d71e793f7458","resolution":{"observed_at":"2026-08-10T15:42:53.651561Z","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":"2026-08-10T15:42:53.763722Z","title":"Citypersons: A diverse dataset for pedestrian detection,","venue":null,"work_id":"e81e9168-3f9e-47a4-86cd-676f7c4ce94c","year":null},"citing_paper":{"arxiv_id":"2501.13710","last_updated":"2025-01-23T14:38:40Z","snapshot_observed_at":"2026-08-10T15:38:13.671148Z","submitted_at":"2025-01-23T14:38:40Z","title":"YOLO11-JDE: Fast and Accurate Multi-Object Tracking with Self-Supervised Re-ID","version":1},"reference_index":66,"source":"pdf_text","source_observed_at":"2026-08-10T15:42:53.654747Z"},"links":{"citing_paper":"/paper/2501.13710"},"observation_digest":"sha256:ee87fb516e1c9e00e02bbd99cf3adfcebca8503e3078e2d45ece4febe2384120","observation_id":"41a9b9be-604e-43ee-b259-6dbb23f7c2b0","resolution":{"observed_at":"2026-08-10T15:42:53.767213Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-12T06:34:41.77262+00:00","source":"crossref"},{"observed_at":"2026-08-12T06:34:36.333875+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":"2026-08-10T15:42:53.753705Z","title":"Tempo- ral correlation meets embedding: Towards a 2nd generation of jde-based real-time multi-object tracking, 2024","venue":null,"work_id":"31ec56a8-02cc-4cd0-968b-5eadb7776df1","year":2024},"citing_paper":{"arxiv_id":"2501.13710","last_updated":"2025-01-23T14:38:40Z","snapshot_observed_at":"2026-08-10T15:38:13.671148Z","submitted_at":"2025-01-23T14:38:40Z","title":"YOLO11-JDE: Fast and Accurate Multi-Object Tracking with Self-Supervised Re-ID","version":1},"reference_index":67,"source":"pdf_text","source_observed_at":"2026-08-10T15:42:53.658070Z"},"links":{"citing_paper":"/paper/2501.13710"},"observation_digest":"sha256:59e73cec13f59fc7143df55a3eef4c8986cc079469808a62186a356e531e9753","observation_id":"a0d020f8-4a90-4fdf-8da5-216d08313bca","resolution":{"observed_at":"2026-08-10T15:42:53.757272Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-12T06:34:41.77262+00:00","source":"crossref"},{"observed_at":"2026-08-12T06:34:36.333875+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":"2026-08-10T15:42:53.661256Z","title":"Bytetrack: Multi-object tracking by associating every detection box, 2022","venue":null,"work_id":null,"year":2022},"citing_paper":{"arxiv_id":"2501.13710","last_updated":"2025-01-23T14:38:40Z","snapshot_observed_at":"2026-08-10T15:38:13.671148Z","submitted_at":"2025-01-23T14:38:40Z","title":"YOLO11-JDE: Fast and Accurate Multi-Object Tracking with Self-Supervised Re-ID","version":1},"reference_index":68,"source":"pdf_text","source_observed_at":"2026-08-10T15:42:53.661256Z"},"links":{"citing_paper":"/paper/2501.13710"},"observation_digest":"sha256:60ef9649c060d1790a1f509e62732ba52857063825fdae79f7c5ee5878e03351","observation_id":"a22c32c7-4fe1-4b31-9b3a-2713911ef700","resolution":{"observed_at":"2026-08-10T15:42:53.661256Z","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":"2026-08-10T15:42:53.736914Z","title":"Fairmot: On the fairness of detection and re- identification in multiple object tracking","venue":null,"work_id":"41f193ea-fca6-46ae-9a48-84510db08b72","year":2021},"citing_paper":{"arxiv_id":"2501.13710","last_updated":"2025-01-23T14:38:40Z","snapshot_observed_at":"2026-08-10T15:38:13.671148Z","submitted_at":"2025-01-23T14:38:40Z","title":"YOLO11-JDE: Fast and Accurate Multi-Object Tracking with Self-Supervised Re-ID","version":1},"reference_index":69,"source":"pdf_text","source_observed_at":"2026-08-10T15:42:53.664483Z"},"links":{"citing_paper":"/paper/2501.13710"},"observation_digest":"sha256:4da22e1ac0d5c8010140d984ee1368564644803447a9f92c5a225862bc7c4096","observation_id":"173d80ee-3c5c-4291-8d7e-2ade12265cc1","resolution":{"observed_at":"2026-08-10T15:42:53.741173Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-12T06:34:41.77262+00:00","source":"crossref"},{"observed_at":"2026-08-12T06:34:36.333875+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":"2026-08-10T15:42:53.727006Z","title":"Person re-identification in the wild, 2017","venue":null,"work_id":"8140c64e-5cf6-4079-a6a9-e686e79b486a","year":2017},"citing_paper":{"arxiv_id":"2501.13710","last_updated":"2025-01-23T14:38:40Z","snapshot_observed_at":"2026-08-10T15:38:13.671148Z","submitted_at":"2025-01-23T14:38:40Z","title":"YOLO11-JDE: Fast and Accurate Multi-Object Tracking with Self-Supervised Re-ID","version":1},"reference_index":70,"source":"pdf_text","source_observed_at":"2026-08-10T15:42:53.667604Z"},"links":{"citing_paper":"/paper/2501.13710"},"observation_digest":"sha256:5f2b290f903dcdfe940b4cd934ee2eac59738642eb1c7b05ff42b24ed03c8af4","observation_id":"c334804b-c5f3-468d-a787-7206de5e529e","resolution":{"observed_at":"2026-08-10T15:42:53.730374Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-12T06:34:41.77262+00:00","source":"crossref"},{"observed_at":"2026-08-12T06:34:36.333875+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":"2026-08-10T15:42:53.715674Z","title":"Ob- jects as points, 2019","venue":null,"work_id":"4e3d9647-38d7-4e63-a578-a75d7655903d","year":2019},"citing_paper":{"arxiv_id":"2501.13710","last_updated":"2025-01-23T14:38:40Z","snapshot_observed_at":"2026-08-10T15:38:13.671148Z","submitted_at":"2025-01-23T14:38:40Z","title":"YOLO11-JDE: Fast and Accurate Multi-Object Tracking with Self-Supervised Re-ID","version":1},"reference_index":71,"source":"pdf_text","source_observed_at":"2026-08-10T15:42:53.670680Z"},"links":{"citing_paper":"/paper/2501.13710"},"observation_digest":"sha256:f902782a479bd2ebf845a3083442f6846e8338c82c1c7bd5277d3f9369196242","observation_id":"2f849073-a376-44f8-8674-0acabc199af6","resolution":{"observed_at":"2026-08-10T15:42:53.720316Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-12T06:34:41.77262+00:00","source":"crossref"},{"observed_at":"2026-08-12T06:34:36.333875+00:00","source":"retraction_watch"}],"state":"measured"}}],"paper":{"arxiv_id":"2501.13710","last_updated":"2025-01-23T14:38:40Z","latest_version":1,"primary_category":"cs.CV","snapshot_observed_at":"2026-08-10T15:38:13.671148Z","submitted_at":"2025-01-23T14:38:40Z","title":"YOLO11-JDE: Fast and Accurate Multi-Object Tracking with Self-Supervised Re-ID"},"reference_resolution":{"displayed":71,"state_counts":{"malformed_identifier":0,"metadata_mismatch":0,"parse_uncertain":0,"unresolved":14,"verified_exact":0,"verified_fuzzy":57},"total_outbound_references":71},"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":"2026-08-12T06:34:41.77262+00:00","source":"crossref"},{"observed_at":"2026-08-12T06:34:36.333875+00:00","source":"retraction_watch"}],"thesis":"As of 12 August 2026, this Paper Citation Record lists 71 of 71 outbound references and 0 inbound Pith citation observations for arXiv:2501.13710."}