{"as_of":"2026-08-20T14:42:00Z","caps":{"database_statements":6,"inbound":100,"outbound":100},"context_digest":"sha256:811d4d3e1a6882dceb2a1ced9ba0b96b5a3af8a4e82522b03413aebbbdee395b","coverage":[{"denominator":51,"lane":"reference_resolution","note":"Typed states for the displayed outbound observations.","records_observed":51,"source":"paper_references, paper_reference_links","source_observed_at":"2026-08-16T10:24:42.839305Z","state":"measured"},{"denominator":51,"lane":"standing_notices","note":"One-hop event checks from named stored sources.","records_observed":51,"source":"scholarly_work_events, retraction_status_cache","source_observed_at":"2026-08-20T06:33:59.587034+00:00","state":"measured"},{"denominator":0,"lane":"inbound_itemization","note":"Pith citing papers itemized under the disclosed page cap.","records_observed":0,"source":"paper_references, paper_reference_links","source_observed_at":null,"state":"measured"},{"denominator":1,"lane":"external_citation_measurements","note":"A source-named dated measurement, never combined with another source.","records_observed":0,"source":"cited_works","source_observed_at":null,"state":"measured"}],"external_citation_measurements":[],"inbound":[],"links":{"evidence":"/evidence","html":"/paper/2504.18203/citation-record","integrity":"/paper/2504.18203/integrity","json":"/paper/2504.18203/citation-record.json","paper":"/paper/2504.18203"},"outbound":[{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-16T10:24:43.582587Z","title":"Trains: The backbone of mobility,","venue":null,"work_id":"52fe4cc5-9ed6-4a1e-b3f8-120d9d63739e","year":2021},"citing_paper":{"arxiv_id":"2504.18203","last_updated":"2025-04-25T09:33:52Z","snapshot_observed_at":"2026-08-19T13:22:13.156508Z","submitted_at":"2025-04-25T09:33:52Z","title":"LiDAR-Guided Monocular 3D Object Detection for Long-Range Railway Monitoring","version":1},"reference_index":1,"source":"pdf_text","source_observed_at":"2026-08-16T10:24:42.616030Z"},"links":{"citing_paper":"/paper/2504.18203"},"observation_digest":"sha256:c239b50078a31577c95eb85ca7570678c0db3082a65ac419c54ed9d731a876df","observation_id":"c55ade13-3088-4e70-ba2f-c78dd87af708","resolution":{"observed_at":"2026-08-16T10:24:43.587459Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-20T06:33:59.587034+00:00","source":"crossref"},{"observed_at":"2026-08-20T06:33:54.927442+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-16T10:24:43.568476Z","title":"What is digitale schiene deutschland?","venue":null,"work_id":"b1b53a44-6434-4440-b926-5617721b2109","year":null},"citing_paper":{"arxiv_id":"2504.18203","last_updated":"2025-04-25T09:33:52Z","snapshot_observed_at":"2026-08-19T13:22:13.156508Z","submitted_at":"2025-04-25T09:33:52Z","title":"LiDAR-Guided Monocular 3D Object Detection for Long-Range Railway Monitoring","version":1},"reference_index":2,"source":"pdf_text","source_observed_at":"2026-08-16T10:24:42.621030Z"},"links":{"citing_paper":"/paper/2504.18203"},"observation_digest":"sha256:ef25617bb6aabf770fb5e2168d3177e9b22d81893f540e44a0df1a2b1481b2af","observation_id":"5fb61c98-e762-464b-99ef-60ad38fd35d4","resolution":{"observed_at":"2026-08-16T10:24:43.572992Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-20T06:33:59.587034+00:00","source":"crossref"},{"observed_at":"2026-08-20T06:33:54.927442+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-16T10:24:43.554658Z","title":"About shift2rail,","venue":null,"work_id":"89f9dd21-4dbe-43b5-9195-28d8f3420fc5","year":null},"citing_paper":{"arxiv_id":"2504.18203","last_updated":"2025-04-25T09:33:52Z","snapshot_observed_at":"2026-08-19T13:22:13.156508Z","submitted_at":"2025-04-25T09:33:52Z","title":"LiDAR-Guided Monocular 3D Object Detection for Long-Range Railway Monitoring","version":1},"reference_index":3,"source":"pdf_text","source_observed_at":"2026-08-16T10:24:42.625274Z"},"links":{"citing_paper":"/paper/2504.18203"},"observation_digest":"sha256:e78dc925e4801d7387b47792bc7eb874fe1de8d793555fc63d14cf787a394210","observation_id":"4130dbef-acc9-45c3-8ac8-2f90d08aeb76","resolution":{"observed_at":"2026-08-16T10:24:43.559168Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-20T06:33:59.587034+00:00","source":"crossref"},{"observed_at":"2026-08-20T06:33:54.927442+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-16T10:24:43.540766Z","title":"safe.train: Rethinking mobility","venue":null,"work_id":"5b72cd3d-b243-4496-8f8b-dd68a785c2ee","year":null},"citing_paper":{"arxiv_id":"2504.18203","last_updated":"2025-04-25T09:33:52Z","snapshot_observed_at":"2026-08-19T13:22:13.156508Z","submitted_at":"2025-04-25T09:33:52Z","title":"LiDAR-Guided Monocular 3D Object Detection for Long-Range Railway Monitoring","version":1},"reference_index":4,"source":"pdf_text","source_observed_at":"2026-08-16T10:24:42.629501Z"},"links":{"citing_paper":"/paper/2504.18203"},"observation_digest":"sha256:5c91671ac668b30876ab0a3ffa8a2579b71faaf75c71a1fd8484763c46b4492b","observation_id":"6d0266f4-aa9a-452a-832d-5193490c4fff","resolution":{"observed_at":"2026-08-16T10:24:43.545360Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-20T06:33:59.587034+00:00","source":"crossref"},{"observed_at":"2026-08-20T06:33:54.927442+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-16T10:24:43.526904Z","title":"[Online]","venue":null,"work_id":"d10c78ab-6e78-4927-a5b5-0f02b3da8cae","year":2023},"citing_paper":{"arxiv_id":"2504.18203","last_updated":"2025-04-25T09:33:52Z","snapshot_observed_at":"2026-08-19T13:22:13.156508Z","submitted_at":"2025-04-25T09:33:52Z","title":"LiDAR-Guided Monocular 3D Object Detection for Long-Range Railway Monitoring","version":1},"reference_index":5,"source":"pdf_text","source_observed_at":"2026-08-16T10:24:42.634189Z"},"links":{"citing_paper":"/paper/2504.18203"},"observation_digest":"sha256:31397a09ed3e0c461d2ba7d690b35d33dfd6a884a113204d12dd4ca26033fdc0","observation_id":"02d3a959-1eca-460a-9e91-f078af462bf6","resolution":{"observed_at":"2026-08-16T10:24:43.531341Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-20T06:33:59.587034+00:00","source":"crossref"},{"observed_at":"2026-08-20T06:33:54.927442+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-16T10:24:43.512828Z","title":"A Review of Vision-Based On-Board Obstacle Detection and Distance Estimation in Railways,","venue":null,"work_id":"bb8c4bbf-7c83-45af-a0f3-20f0d656e21a","year":2021},"citing_paper":{"arxiv_id":"2504.18203","last_updated":"2025-04-25T09:33:52Z","snapshot_observed_at":"2026-08-19T13:22:13.156508Z","submitted_at":"2025-04-25T09:33:52Z","title":"LiDAR-Guided Monocular 3D Object Detection for Long-Range Railway Monitoring","version":1},"reference_index":6,"source":"pdf_text","source_observed_at":"2026-08-16T10:24:42.638777Z"},"links":{"citing_paper":"/paper/2504.18203"},"observation_digest":"sha256:8393319ef23b3e887bd4d62cfd3450fe75ec63d50adb121db64bfce46a7a4226","observation_id":"a60d486f-573b-41c9-a2c5-dec38aa67699","resolution":{"observed_at":"2026-08-16T10:24:43.517710Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-20T06:33:59.587034+00:00","source":"crossref"},{"observed_at":"2026-08-20T06:33:54.927442+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-16T10:24:43.498722Z","title":"High-Precision Low-Cost Gimballing Platform for Long-Range Railway Obstacle Detection,","venue":null,"work_id":"3628cb5a-4e02-4187-a84e-d3c00b4ff4aa","year":2022},"citing_paper":{"arxiv_id":"2504.18203","last_updated":"2025-04-25T09:33:52Z","snapshot_observed_at":"2026-08-19T13:22:13.156508Z","submitted_at":"2025-04-25T09:33:52Z","title":"LiDAR-Guided Monocular 3D Object Detection for Long-Range Railway Monitoring","version":1},"reference_index":7,"source":"pdf_text","source_observed_at":"2026-08-16T10:24:42.643313Z"},"links":{"citing_paper":"/paper/2504.18203"},"observation_digest":"sha256:838c81cc0d5ee9bac2e8c2899c6ee5047365a18141d509519744ca3b646c23b1","observation_id":"a41e666e-1c74-4272-b1ba-29edd11aa8f9","resolution":{"observed_at":"2026-08-16T10:24:43.503427Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-20T06:33:59.587034+00:00","source":"crossref"},{"observed_at":"2026-08-20T06:33:54.927442+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-16T10:24:43.483297Z","title":"Improving distant 3d object detection using 2d box supervision,","venue":null,"work_id":"c6a9aeed-44c5-454f-9eb2-e36cf5be1b33","year":null},"citing_paper":{"arxiv_id":"2504.18203","last_updated":"2025-04-25T09:33:52Z","snapshot_observed_at":"2026-08-19T13:22:13.156508Z","submitted_at":"2025-04-25T09:33:52Z","title":"LiDAR-Guided Monocular 3D Object Detection for Long-Range Railway Monitoring","version":1},"reference_index":8,"source":"pdf_text","source_observed_at":"2026-08-16T10:24:42.647732Z"},"links":{"citing_paper":"/paper/2504.18203"},"observation_digest":"sha256:1c2592ab6d293e042f5a5b77b9330083380c4db682000197e90f8083d9fd0549","observation_id":"71b0af15-955b-4d13-9c8f-f0ba7dd59fd5","resolution":{"observed_at":"2026-08-16T10:24:43.488520Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-20T06:33:59.587034+00:00","source":"crossref"},{"observed_at":"2026-08-20T06:33:54.927442+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-16T10:24:43.468621Z","title":"Lidar on its way out? camera’s market size from 76% to 79% by 2033,","venue":null,"work_id":"90a0b600-77d5-4c5b-b2a8-d761840ace97","year":2023},"citing_paper":{"arxiv_id":"2504.18203","last_updated":"2025-04-25T09:33:52Z","snapshot_observed_at":"2026-08-19T13:22:13.156508Z","submitted_at":"2025-04-25T09:33:52Z","title":"LiDAR-Guided Monocular 3D Object Detection for Long-Range Railway Monitoring","version":1},"reference_index":9,"source":"pdf_text","source_observed_at":"2026-08-16T10:24:42.656831Z"},"links":{"citing_paper":"/paper/2504.18203"},"observation_digest":"sha256:033774675a38bbc9b55a1e69e70fd571b158ba840391bf554d0aafe8d104a0b0","observation_id":"a73e9cdb-7756-4233-884a-a03671ad817a","resolution":{"observed_at":"2026-08-16T10:24:43.473043Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-20T06:33:59.587034+00:00","source":"crossref"},{"observed_at":"2026-08-20T06:33:54.927442+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-16T10:24:43.454040Z","title":"Virtual Sparse Convolution for Multimodal 3D Object Detection,","venue":null,"work_id":"dd26de58-f157-4a1d-a352-c9cf009ee988","year":2023},"citing_paper":{"arxiv_id":"2504.18203","last_updated":"2025-04-25T09:33:52Z","snapshot_observed_at":"2026-08-19T13:22:13.156508Z","submitted_at":"2025-04-25T09:33:52Z","title":"LiDAR-Guided Monocular 3D Object Detection for Long-Range Railway Monitoring","version":1},"reference_index":10,"source":"pdf_text","source_observed_at":"2026-08-16T10:24:42.661164Z"},"links":{"citing_paper":"/paper/2504.18203"},"observation_digest":"sha256:f76e9d404370e791e2b0dd28962f1064406ef9baafafb0155bea3be742a28d92","observation_id":"95e4b3ad-9d83-4bf1-bf90-f4b4326f46d6","resolution":{"observed_at":"2026-08-16T10:24:43.458752Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-20T06:33:59.587034+00:00","source":"crossref"},{"observed_at":"2026-08-20T06:33:54.927442+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-16T10:24:43.440227Z","title":"LoGoNet: Towards Accurate 3D Object Detection With Local-to-Global Cross-Modal Fusion,","venue":null,"work_id":"979b852a-b050-4eab-a316-9b4d6fdfa360","year":2023},"citing_paper":{"arxiv_id":"2504.18203","last_updated":"2025-04-25T09:33:52Z","snapshot_observed_at":"2026-08-19T13:22:13.156508Z","submitted_at":"2025-04-25T09:33:52Z","title":"LiDAR-Guided Monocular 3D Object Detection for Long-Range Railway Monitoring","version":1},"reference_index":11,"source":"pdf_text","source_observed_at":"2026-08-16T10:24:42.665987Z"},"links":{"citing_paper":"/paper/2504.18203"},"observation_digest":"sha256:46d4bde5887423b08af06f96fd85eee3a0a40f14be4e32e7b739dc428d06ebb1","observation_id":"860307c6-d13f-4761-a0fc-0afa320694e9","resolution":{"observed_at":"2026-08-16T10:24:43.444825Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-20T06:33:59.587034+00:00","source":"crossref"},{"observed_at":"2026-08-20T06:33:54.927442+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-16T10:24:43.425438Z","title":"V oxel Field Fusion for 3D Object Detection,","venue":null,"work_id":"959531fc-a3ce-4295-b85d-f45eeffb81c7","year":2022},"citing_paper":{"arxiv_id":"2504.18203","last_updated":"2025-04-25T09:33:52Z","snapshot_observed_at":"2026-08-19T13:22:13.156508Z","submitted_at":"2025-04-25T09:33:52Z","title":"LiDAR-Guided Monocular 3D Object Detection for Long-Range Railway Monitoring","version":1},"reference_index":12,"source":"pdf_text","source_observed_at":"2026-08-16T10:24:42.671461Z"},"links":{"citing_paper":"/paper/2504.18203"},"observation_digest":"sha256:94bd3cc3ef8d4130ed8ee8b9753702559ddd3a41adb75c25e730bb1df79edb52","observation_id":"06b292af-3996-4b9a-a5a4-4b57199a9c2b","resolution":{"observed_at":"2026-08-16T10:24:43.429887Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-20T06:33:59.587034+00:00","source":"crossref"},{"observed_at":"2026-08-20T06:33:54.927442+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-16T10:24:43.411430Z","title":"Homogeneous Multi-modal Feature Fusion and Interaction for 3D Object Detection,","venue":null,"work_id":"7a31d0f4-c6d9-4c51-a6a3-a6421ba05909","year":2022},"citing_paper":{"arxiv_id":"2504.18203","last_updated":"2025-04-25T09:33:52Z","snapshot_observed_at":"2026-08-19T13:22:13.156508Z","submitted_at":"2025-04-25T09:33:52Z","title":"LiDAR-Guided Monocular 3D Object Detection for Long-Range Railway Monitoring","version":1},"reference_index":13,"source":"pdf_text","source_observed_at":"2026-08-16T10:24:42.676014Z"},"links":{"citing_paper":"/paper/2504.18203"},"observation_digest":"sha256:4bf374374f61fcc0375bf9baab9763807028c981eda7d5a8b262eaf0ecefa859","observation_id":"f26dca34-e5bc-4c90-b8d0-d4e6b1f1ad2c","resolution":{"observed_at":"2026-08-16T10:24:43.415945Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-20T06:33:59.587034+00:00","source":"crossref"},{"observed_at":"2026-08-20T06:33:54.927442+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-16T10:24:43.397006Z","title":"Chapter 13 - 3D object detection and tracking,","venue":null,"work_id":"2314fc7f-b91d-46d7-ba1c-2fe3a3b7a9aa","year":2022},"citing_paper":{"arxiv_id":"2504.18203","last_updated":"2025-04-25T09:33:52Z","snapshot_observed_at":"2026-08-19T13:22:13.156508Z","submitted_at":"2025-04-25T09:33:52Z","title":"LiDAR-Guided Monocular 3D Object Detection for Long-Range Railway Monitoring","version":1},"reference_index":14,"source":"pdf_text","source_observed_at":"2026-08-16T10:24:42.680180Z"},"links":{"citing_paper":"/paper/2504.18203"},"observation_digest":"sha256:44db8ff40578c987388e499ba905b536b0b9f8964742bf83000e97c3688b5e21","observation_id":"cf3ac740-8fc9-448e-8698-2bb90daade1d","resolution":{"observed_at":"2026-08-16T10:24:43.401767Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-20T06:33:59.587034+00:00","source":"crossref"},{"observed_at":"2026-08-20T06:33:54.927442+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-16T10:24:43.382285Z","title":"MonoDETR: Depth-guided Transformer for Monocular 3D Object Detection,","venue":null,"work_id":"4b88d59c-e967-44cf-a154-6f95d10484a0","year":2023},"citing_paper":{"arxiv_id":"2504.18203","last_updated":"2025-04-25T09:33:52Z","snapshot_observed_at":"2026-08-19T13:22:13.156508Z","submitted_at":"2025-04-25T09:33:52Z","title":"LiDAR-Guided Monocular 3D Object Detection for Long-Range Railway Monitoring","version":1},"reference_index":15,"source":"pdf_text","source_observed_at":"2026-08-16T10:24:42.684603Z"},"links":{"citing_paper":"/paper/2504.18203"},"observation_digest":"sha256:aa15cb38a856591690743552195f49435f3f7bb2d249b4f88ca22b53a096eebc","observation_id":"4c9f842d-de09-4aec-bf58-4166ae440f21","resolution":{"observed_at":"2026-08-16T10:24:43.387417Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-20T06:33:59.587034+00:00","source":"crossref"},{"observed_at":"2026-08-20T06:33:54.927442+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-16T10:24:43.367187Z","title":"Pseudo-LiDAR++: Accurate Depth for 3D Object Detection in Autonomous Driving,","venue":null,"work_id":"3fa3403d-db9d-43f9-bd65-6d49d95e2c5e","year":2020},"citing_paper":{"arxiv_id":"2504.18203","last_updated":"2025-04-25T09:33:52Z","snapshot_observed_at":"2026-08-19T13:22:13.156508Z","submitted_at":"2025-04-25T09:33:52Z","title":"LiDAR-Guided Monocular 3D Object Detection for Long-Range Railway Monitoring","version":1},"reference_index":16,"source":"pdf_text","source_observed_at":"2026-08-16T10:24:42.688837Z"},"links":{"citing_paper":"/paper/2504.18203"},"observation_digest":"sha256:28dc78bc8fc824685d205c76d349d5d6c976d4477d1f6c103bbb6f99bad8e183","observation_id":"574754ad-e48f-4c26-8ce9-bcbe80c7a830","resolution":{"observed_at":"2026-08-16T10:24:43.371901Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-20T06:33:59.587034+00:00","source":"crossref"},{"observed_at":"2026-08-20T06:33:54.927442+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-16T10:24:43.351555Z","title":"BEVDepth: Acquisition of Reliable Depth for Multi-View 3D Object Detection,","venue":null,"work_id":"93ac0587-a9ca-4848-bb26-4da6e2a17ad0","year":2023},"citing_paper":{"arxiv_id":"2504.18203","last_updated":"2025-04-25T09:33:52Z","snapshot_observed_at":"2026-08-19T13:22:13.156508Z","submitted_at":"2025-04-25T09:33:52Z","title":"LiDAR-Guided Monocular 3D Object Detection for Long-Range Railway Monitoring","version":1},"reference_index":17,"source":"pdf_text","source_observed_at":"2026-08-16T10:24:42.692881Z"},"links":{"citing_paper":"/paper/2504.18203"},"observation_digest":"sha256:49126bfe6421978ba2423098c96a8d86d56fc372eaa0cc641aee82a84cd33adc","observation_id":"e86080fc-d58e-4824-a84d-e8df876c5d9a","resolution":{"observed_at":"2026-08-16T10:24:43.356019Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-20T06:33:59.587034+00:00","source":"crossref"},{"observed_at":"2026-08-20T06:33:54.927442+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"2402.18573","last_updated":"2024-09-23T14:55:21Z","snapshot_observed_at":"2026-08-19T00:08:09.557612Z","submitted_at":"2024-02-28T18:59:31Z","title":"Towards Unified 3D Object Detection via Algorithm and Data Unification","version":5},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2402.18573","snapshot_observed_at":"2026-08-16T10:24:42.697256Z","title":"Towards unified 3d object detection via algorithm and data unification,","venue":null,"work_id":null,"year":2024},"citing_paper":{"arxiv_id":"2504.18203","last_updated":"2025-04-25T09:33:52Z","snapshot_observed_at":"2026-08-19T13:22:13.156508Z","submitted_at":"2025-04-25T09:33:52Z","title":"LiDAR-Guided Monocular 3D Object Detection for Long-Range Railway Monitoring","version":1},"reference_index":18,"source":"pdf_text","source_observed_at":"2026-08-16T10:24:42.697256Z"},"links":{"cited_paper":"/paper/2402.18573","citing_paper":"/paper/2504.18203"},"observation_digest":"sha256:0fc9dceea1d83522d086fd98ed547a3919d53aa3277ce9c23ff7acdde9176656","observation_id":"f62f58ba-f738-4b78-a223-79a9da043abd","resolution":{"observed_at":"2026-08-16T10:24:42.697256Z","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":"2026-08-16T10:24:43.337306Z","title":"Collision avoidance route planning for autonomous medical devices using multiple depth cameras,","venue":null,"work_id":"60c9ee2e-55bc-4a8e-acb4-ce716d61867b","year":2022},"citing_paper":{"arxiv_id":"2504.18203","last_updated":"2025-04-25T09:33:52Z","snapshot_observed_at":"2026-08-19T13:22:13.156508Z","submitted_at":"2025-04-25T09:33:52Z","title":"LiDAR-Guided Monocular 3D Object Detection for Long-Range Railway Monitoring","version":1},"reference_index":19,"source":"pdf_text","source_observed_at":"2026-08-16T10:24:42.701728Z"},"links":{"citing_paper":"/paper/2504.18203"},"observation_digest":"sha256:9881ccae02af984d90a275708a9c14d1bee7af921f25150d857490669752a44e","observation_id":"ec5e6ab5-0845-47cd-b1c0-ee12abe678b2","resolution":{"observed_at":"2026-08-16T10:24:43.342005Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-20T06:33:59.587034+00:00","source":"crossref"},{"observed_at":"2026-08-20T06:33:54.927442+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-16T10:24:43.322746Z","title":"Frustum PointNets for 3D Object Detection From RGB-D Data,","venue":null,"work_id":"8c5c92f2-adb1-4f77-b68d-9f4c86b6e4b2","year":2018},"citing_paper":{"arxiv_id":"2504.18203","last_updated":"2025-04-25T09:33:52Z","snapshot_observed_at":"2026-08-19T13:22:13.156508Z","submitted_at":"2025-04-25T09:33:52Z","title":"LiDAR-Guided Monocular 3D Object Detection for Long-Range Railway Monitoring","version":1},"reference_index":20,"source":"pdf_text","source_observed_at":"2026-08-16T10:24:42.706480Z"},"links":{"citing_paper":"/paper/2504.18203"},"observation_digest":"sha256:8eca50831a46b775a9b167053cbc679f1b9f700e86db99750d69479ff1765c2d","observation_id":"c4bf43c7-d678-4d9c-9eeb-9b22a75196e4","resolution":{"observed_at":"2026-08-16T10:24:43.327465Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-20T06:33:59.587034+00:00","source":"crossref"},{"observed_at":"2026-08-20T06:33:54.927442+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-16T10:24:43.308946Z","title":"Faraway-Frustum: Dealing with Lidar Sparsity for 3D Object Detec- tion using Fusion,","venue":null,"work_id":"ba0340fa-3bc2-4cfd-a815-4d790c55b0aa","year":2021},"citing_paper":{"arxiv_id":"2504.18203","last_updated":"2025-04-25T09:33:52Z","snapshot_observed_at":"2026-08-19T13:22:13.156508Z","submitted_at":"2025-04-25T09:33:52Z","title":"LiDAR-Guided Monocular 3D Object Detection for Long-Range Railway Monitoring","version":1},"reference_index":21,"source":"pdf_text","source_observed_at":"2026-08-16T10:24:42.710965Z"},"links":{"citing_paper":"/paper/2504.18203"},"observation_digest":"sha256:fa8dd44878dba22db4d42897b7540b3b732908c5bc35b1ed4a359731fd6cbe4a","observation_id":"26e0bbe5-2ae8-4742-a4f7-6a4e35320abf","resolution":{"observed_at":"2026-08-16T10:24:43.313400Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-20T06:33:59.587034+00:00","source":"crossref"},{"observed_at":"2026-08-20T06:33:54.927442+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-16T10:24:43.294981Z","title":"Pv-rcnn: Point-voxel feature set abstraction for 3d object detection,","venue":null,"work_id":"88bc0a2d-0e38-4ca5-aa3c-d40c1f5ed5ff","year":null},"citing_paper":{"arxiv_id":"2504.18203","last_updated":"2025-04-25T09:33:52Z","snapshot_observed_at":"2026-08-19T13:22:13.156508Z","submitted_at":"2025-04-25T09:33:52Z","title":"LiDAR-Guided Monocular 3D Object Detection for Long-Range Railway Monitoring","version":1},"reference_index":22,"source":"pdf_text","source_observed_at":"2026-08-16T10:24:42.715246Z"},"links":{"citing_paper":"/paper/2504.18203"},"observation_digest":"sha256:dd6425a23c6d0deabfcfd720d03618e58128a44392caece03ee3a128203decd8","observation_id":"7d27efa9-f9fe-4655-a109-bee64a3a16fd","resolution":{"observed_at":"2026-08-16T10:24:43.299307Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-20T06:33:59.587034+00:00","source":"crossref"},{"observed_at":"2026-08-20T06:33:54.927442+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"1704.04861","last_updated":"2017-04-17T03:57:34Z","snapshot_observed_at":"2026-08-20T09:32:02.065929Z","submitted_at":"2017-04-17T03:57:34Z","title":"MobileNets: Efficient Convolutional Neural Networks for Mobile Vision Applications","version":1},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"1704.04861","snapshot_observed_at":"2026-08-16T10:24:42.725119Z","title":"Mobilenets: Efficient convolutional neural networks for mobile vision applications,","venue":null,"work_id":null,"year":2017},"citing_paper":{"arxiv_id":"2504.18203","last_updated":"2025-04-25T09:33:52Z","snapshot_observed_at":"2026-08-19T13:22:13.156508Z","submitted_at":"2025-04-25T09:33:52Z","title":"LiDAR-Guided Monocular 3D Object Detection for Long-Range Railway Monitoring","version":1},"reference_index":23,"source":"pdf_text","source_observed_at":"2026-08-16T10:24:42.725119Z"},"links":{"cited_paper":"/paper/1704.04861","citing_paper":"/paper/2504.18203"},"observation_digest":"sha256:24e7d8257f853e4a80da41fc3abd4ac2becdd54ba1d5ef64a7b33206dc3e4565","observation_id":"e5484776-e555-45e9-b4df-acd528597040","resolution":{"observed_at":"2026-08-16T10:24:42.725119Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":null,"snapshot_observed_at":"2026-08-16T10:24:42.729989Z","title":"Are we ready for autonomous driving? the kitti vision benchmark suite,","venue":null,"work_id":null,"year":2012},"citing_paper":{"arxiv_id":"2504.18203","last_updated":"2025-04-25T09:33:52Z","snapshot_observed_at":"2026-08-19T13:22:13.156508Z","submitted_at":"2025-04-25T09:33:52Z","title":"LiDAR-Guided Monocular 3D Object Detection for Long-Range Railway Monitoring","version":1},"reference_index":24,"source":"pdf_text","source_observed_at":"2026-08-16T10:24:42.729989Z"},"links":{"citing_paper":"/paper/2504.18203"},"observation_digest":"sha256:cac05c514f27b3da28bf77dd3062d790a8db3d4acbe92c8f1b0c8e960314499a","observation_id":"0c27e3e2-c9ec-4764-88c7-7fec54d75998","resolution":{"observed_at":"2026-08-16T10:24:42.729989Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":null,"snapshot_observed_at":"2026-08-16T10:24:42.734387Z","title":"You only look once: Unified, real-time object detection,","venue":null,"work_id":null,"year":2016},"citing_paper":{"arxiv_id":"2504.18203","last_updated":"2025-04-25T09:33:52Z","snapshot_observed_at":"2026-08-19T13:22:13.156508Z","submitted_at":"2025-04-25T09:33:52Z","title":"LiDAR-Guided Monocular 3D Object Detection for Long-Range Railway Monitoring","version":1},"reference_index":25,"source":"pdf_text","source_observed_at":"2026-08-16T10:24:42.734387Z"},"links":{"citing_paper":"/paper/2504.18203"},"observation_digest":"sha256:158c2b20e6c2c39690a556b14e937d218db6887b05301439fd92ae24fdc40357","observation_id":"37243d77-423e-4859-8f57-2e0be1fd8aa8","resolution":{"observed_at":"2026-08-16T10:24:42.734387Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2402.13616","last_updated":"2024-02-29T03:43:24Z","snapshot_observed_at":"2026-08-20T13:10:10.667116Z","submitted_at":"2024-02-21T08:42:53Z","title":"YOLOv9: Learning What You Want to Learn Using Programmable Gradient Information","version":2},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2402.13616","snapshot_observed_at":"2026-08-16T10:24:42.738379Z","title":"Yolov9: Learning what you want to learn using programmable gradient information,","venue":null,"work_id":null,"year":2024},"citing_paper":{"arxiv_id":"2504.18203","last_updated":"2025-04-25T09:33:52Z","snapshot_observed_at":"2026-08-19T13:22:13.156508Z","submitted_at":"2025-04-25T09:33:52Z","title":"LiDAR-Guided Monocular 3D Object Detection for Long-Range Railway Monitoring","version":1},"reference_index":26,"source":"pdf_text","source_observed_at":"2026-08-16T10:24:42.738379Z"},"links":{"cited_paper":"/paper/2402.13616","citing_paper":"/paper/2504.18203"},"observation_digest":"sha256:64921e5fc0182ed95b2e7aec8ddce697ea6892d3f41d113305aa525d49940a85","observation_id":"9ba76fd9-17bc-4b96-834a-3d94e1d42638","resolution":{"observed_at":"2026-08-16T10:24:42.738379Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2408.09332","last_updated":"2024-08-18T02:11:00Z","snapshot_observed_at":"2026-08-17T00:01:27.536013Z","submitted_at":"2024-08-18T02:11:00Z","title":"YOLOv1 to YOLOv10: The fastest and most accurate real-time object detection systems","version":1},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2408.09332","snapshot_observed_at":"2026-08-16T10:24:42.743176Z","title":"Yolov1 to yolov10: The fastest and most accurate real-time object detection systems,","venue":null,"work_id":null,"year":2024},"citing_paper":{"arxiv_id":"2504.18203","last_updated":"2025-04-25T09:33:52Z","snapshot_observed_at":"2026-08-19T13:22:13.156508Z","submitted_at":"2025-04-25T09:33:52Z","title":"LiDAR-Guided Monocular 3D Object Detection for Long-Range Railway Monitoring","version":1},"reference_index":27,"source":"pdf_text","source_observed_at":"2026-08-16T10:24:42.743176Z"},"links":{"cited_paper":"/paper/2408.09332","citing_paper":"/paper/2504.18203"},"observation_digest":"sha256:423b3c9195696fdaaf9165bf80863142778fe42f3461db31bc48d141fe0f9019","observation_id":"17f5f13c-4b14-4b4c-9370-6a4197d28ae5","resolution":{"observed_at":"2026-08-16T10:24:42.743176Z","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":"2026-08-16T10:24:43.261780Z","title":"Machine learning techniques for autonomous multi- sensor long-range environmental perception system,","venue":null,"work_id":"0cccc466-21e1-46b1-938f-2bc80a128754","year":2021},"citing_paper":{"arxiv_id":"2504.18203","last_updated":"2025-04-25T09:33:52Z","snapshot_observed_at":"2026-08-19T13:22:13.156508Z","submitted_at":"2025-04-25T09:33:52Z","title":"LiDAR-Guided Monocular 3D Object Detection for Long-Range Railway Monitoring","version":1},"reference_index":28,"source":"pdf_text","source_observed_at":"2026-08-16T10:24:42.747723Z"},"links":{"citing_paper":"/paper/2504.18203"},"observation_digest":"sha256:b5cd925f8392ab4ec2110f8e4e7e01c439a3e2663a6eea503e0afe5d22d89d0f","observation_id":"5f80b35f-ce92-4b27-8a2f-194eca937605","resolution":{"observed_at":"2026-08-16T10:24:43.266297Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-20T06:33:59.587034+00:00","source":"crossref"},{"observed_at":"2026-08-20T06:33:54.927442+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-16T10:24:43.247700Z","title":"Dist-yolo: Fast object detection with distance estimation,","venue":null,"work_id":"4240d1d7-3f67-4a0a-9046-3c5922336f73","year":null},"citing_paper":{"arxiv_id":"2504.18203","last_updated":"2025-04-25T09:33:52Z","snapshot_observed_at":"2026-08-19T13:22:13.156508Z","submitted_at":"2025-04-25T09:33:52Z","title":"LiDAR-Guided Monocular 3D Object Detection for Long-Range Railway Monitoring","version":1},"reference_index":29,"source":"pdf_text","source_observed_at":"2026-08-16T10:24:42.752162Z"},"links":{"citing_paper":"/paper/2504.18203"},"observation_digest":"sha256:a93a70f36f00fd50afe6276a452fd3012d30b9aa8698e22fee775e2329eff787","observation_id":"601ac6ea-f4f3-456a-920d-6619228cfdee","resolution":{"observed_at":"2026-08-16T10:24:43.252060Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-20T06:33:59.587034+00:00","source":"crossref"},{"observed_at":"2026-08-20T06:33:54.927442+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":"10.3233/faia210151","metadata_source":"doi_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-16T10:24:42.869980Z","title":"Masoumian, D","venue":null,"work_id":"12ba5b1c-574e-469c-9d0b-81998abb7256","year":2021},"citing_paper":{"arxiv_id":"2504.18203","last_updated":"2025-04-25T09:33:52Z","snapshot_observed_at":"2026-08-19T13:22:13.156508Z","submitted_at":"2025-04-25T09:33:52Z","title":"LiDAR-Guided Monocular 3D Object Detection for Long-Range Railway Monitoring","version":1},"reference_index":30,"source":"pdf_text","source_observed_at":"2026-08-16T10:24:42.760739Z"},"links":{"citing_paper":"/paper/2504.18203"},"observation_digest":"sha256:8004fa72ae285951e5b986dd6b1ee8deba915e80e5317eb67f1f6eab1a67105c","observation_id":"a62b0c89-0bf5-44c3-b723-95c9e0996073","resolution":{"observed_at":"2026-08-16T10:24:42.875826Z","resolver_source":"doi","status":"verified_exact"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-20T06:33:59.587034+00:00","source":"crossref"},{"observed_at":"2026-08-20T06:33:54.927442+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"1907.01341","last_updated":"2020-08-25T09:37:24Z","snapshot_observed_at":"2026-08-19T13:18:49.220448Z","submitted_at":"2019-07-02T13:16:52Z","title":"Towards Robust Monocular Depth Estimation: Mixing Datasets for Zero-shot Cross-dataset Transfer","version":3},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"1907.01341","snapshot_observed_at":"2026-08-16T10:24:42.765172Z","title":"Towards robust monocular depth estimation: Mixing datasets for zero-shot cross-dataset transfer,","venue":null,"work_id":null,"year":2020},"citing_paper":{"arxiv_id":"2504.18203","last_updated":"2025-04-25T09:33:52Z","snapshot_observed_at":"2026-08-19T13:22:13.156508Z","submitted_at":"2025-04-25T09:33:52Z","title":"LiDAR-Guided Monocular 3D Object Detection for Long-Range Railway Monitoring","version":1},"reference_index":31,"source":"pdf_text","source_observed_at":"2026-08-16T10:24:42.765172Z"},"links":{"cited_paper":"/paper/1907.01341","citing_paper":"/paper/2504.18203"},"observation_digest":"sha256:d6ab31bf7104c7d3630c3143ed512ad79a946672656a59e14dce557cb968a7ee","observation_id":"e8103d8e-965a-4521-89dd-7116e34135d8","resolution":{"observed_at":"2026-08-16T10:24:42.765172Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"1812.11941","last_updated":"2019-03-10T07:46:03Z","snapshot_observed_at":"2026-08-15T10:04:49.697468Z","submitted_at":"2018-12-31T18:25:21Z","title":"High Quality Monocular Depth Estimation via Transfer Learning","version":2},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"1812.11941","snapshot_observed_at":"2026-08-16T10:24:42.769787Z","title":"High quality monocular depth estimation via transfer learning,","venue":null,"work_id":null,"year":2018},"citing_paper":{"arxiv_id":"2504.18203","last_updated":"2025-04-25T09:33:52Z","snapshot_observed_at":"2026-08-19T13:22:13.156508Z","submitted_at":"2025-04-25T09:33:52Z","title":"LiDAR-Guided Monocular 3D Object Detection for Long-Range Railway Monitoring","version":1},"reference_index":32,"source":"pdf_text","source_observed_at":"2026-08-16T10:24:42.769787Z"},"links":{"cited_paper":"/paper/1812.11941","citing_paper":"/paper/2504.18203"},"observation_digest":"sha256:af26aeacacd84202f2e4a84eb8c947eaad8b56cd81d2dfab3918360c48fec6f6","observation_id":"d1f44a9c-d5ba-49ca-bac9-f589046b9ec2","resolution":{"observed_at":"2026-08-16T10:24:42.769787Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"1608.06993","last_updated":"2018-01-28T17:12:02Z","snapshot_observed_at":"2026-08-14T21:42:53.838437Z","submitted_at":"2016-08-25T00:44:55Z","title":"Densely Connected Convolutional Networks","version":5},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"1608.06993","snapshot_observed_at":"2026-08-16T10:24:42.774245Z","title":"Densely connected convolutional networks,","venue":null,"work_id":null,"year":2018},"citing_paper":{"arxiv_id":"2504.18203","last_updated":"2025-04-25T09:33:52Z","snapshot_observed_at":"2026-08-19T13:22:13.156508Z","submitted_at":"2025-04-25T09:33:52Z","title":"LiDAR-Guided Monocular 3D Object Detection for Long-Range Railway Monitoring","version":1},"reference_index":33,"source":"pdf_text","source_observed_at":"2026-08-16T10:24:42.774245Z"},"links":{"cited_paper":"/paper/1608.06993","citing_paper":"/paper/2504.18203"},"observation_digest":"sha256:cd0670c34ca1bac15ac32fffe0b1fcf11cc99c22df75dc250f8bac73cce0c414","observation_id":"dedec693-4702-48c4-99aa-d1772e7afd66","resolution":{"observed_at":"2026-08-16T10:24:42.774245Z","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":"2026-08-16T10:24:43.218588Z","title":"Colorization using optimiza- tion,","venue":null,"work_id":"d2cbfa30-da45-41ba-aa5c-33ee93ba772a","year":2004},"citing_paper":{"arxiv_id":"2504.18203","last_updated":"2025-04-25T09:33:52Z","snapshot_observed_at":"2026-08-19T13:22:13.156508Z","submitted_at":"2025-04-25T09:33:52Z","title":"LiDAR-Guided Monocular 3D Object Detection for Long-Range Railway Monitoring","version":1},"reference_index":34,"source":"pdf_text","source_observed_at":"2026-08-16T10:24:42.778978Z"},"links":{"citing_paper":"/paper/2504.18203"},"observation_digest":"sha256:6f00bdbef08d2a4ae3349e4b18872ef64895a98d5acd465f549d29b52bdd8ec3","observation_id":"f463552e-a28f-4e49-804c-8c9fb0f10d8f","resolution":{"observed_at":"2026-08-16T10:24:43.223445Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-20T06:33:59.587034+00:00","source":"crossref"},{"observed_at":"2026-08-20T06:33:54.927442+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":null,"snapshot_observed_at":"2026-08-16T10:24:42.783367Z","title":"Repurposing diffusion-based image generators for monocular depth estimation,","venue":null,"work_id":null,"year":2024},"citing_paper":{"arxiv_id":"2504.18203","last_updated":"2025-04-25T09:33:52Z","snapshot_observed_at":"2026-08-19T13:22:13.156508Z","submitted_at":"2025-04-25T09:33:52Z","title":"LiDAR-Guided Monocular 3D Object Detection for Long-Range Railway Monitoring","version":1},"reference_index":35,"source":"pdf_text","source_observed_at":"2026-08-16T10:24:42.783367Z"},"links":{"citing_paper":"/paper/2504.18203"},"observation_digest":"sha256:e8a8287a5bc64dc03d897b39a7613fe1897c4e0b59351e237168bd809d9d3d30","observation_id":"1bbba774-5bf3-45f4-a8a0-3d5d6787919e","resolution":{"observed_at":"2026-08-16T10:24:42.783367Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":null,"snapshot_observed_at":"2026-08-16T10:24:42.787816Z","title":"nuscenes: A multimodal dataset for autonomous driving,","venue":null,"work_id":null,"year":2020},"citing_paper":{"arxiv_id":"2504.18203","last_updated":"2025-04-25T09:33:52Z","snapshot_observed_at":"2026-08-19T13:22:13.156508Z","submitted_at":"2025-04-25T09:33:52Z","title":"LiDAR-Guided Monocular 3D Object Detection for Long-Range Railway Monitoring","version":1},"reference_index":36,"source":"pdf_text","source_observed_at":"2026-08-16T10:24:42.787816Z"},"links":{"citing_paper":"/paper/2504.18203"},"observation_digest":"sha256:37c2a3039fbfd5fa7362b3c812ea8883ed5cac6d982d06febd665f6e915aec5e","observation_id":"061d8a15-66ff-42ca-8df0-caa00fc77eb3","resolution":{"observed_at":"2026-08-16T10:24:42.787816Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2206.07704","last_updated":"2022-06-15T17:57:28Z","snapshot_observed_at":"2026-08-19T18:07:24.226652Z","submitted_at":"2022-06-15T17:57:28Z","title":"Waymo Open Dataset: Panoramic Video Panoptic Segmentation","version":1},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2206.07704","snapshot_observed_at":"2026-08-16T10:24:42.792104Z","title":"Waymo open dataset: Panoramic video panoptic segmentation,","venue":null,"work_id":null,"year":2022},"citing_paper":{"arxiv_id":"2504.18203","last_updated":"2025-04-25T09:33:52Z","snapshot_observed_at":"2026-08-19T13:22:13.156508Z","submitted_at":"2025-04-25T09:33:52Z","title":"LiDAR-Guided Monocular 3D Object Detection for Long-Range Railway Monitoring","version":1},"reference_index":37,"source":"pdf_text","source_observed_at":"2026-08-16T10:24:42.792104Z"},"links":{"cited_paper":"/paper/2206.07704","citing_paper":"/paper/2504.18203"},"observation_digest":"sha256:a34a9893f1427d1d651fff3da725536dea40098cfa7f4cd6ebdfbfdd2013b04a","observation_id":"366bea1a-9f63-424d-8f84-c07bfd597e6b","resolution":{"observed_at":"2026-08-16T10:24:42.792104Z","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":"2026-08-16T10:24:43.186361Z","title":"RailSem19: A Dataset for Semantic Rail Scene Understanding,","venue":null,"work_id":"19ca4b3d-25af-4047-aeb6-121f5e71e115","year":2019},"citing_paper":{"arxiv_id":"2504.18203","last_updated":"2025-04-25T09:33:52Z","snapshot_observed_at":"2026-08-19T13:22:13.156508Z","submitted_at":"2025-04-25T09:33:52Z","title":"LiDAR-Guided Monocular 3D Object Detection for Long-Range Railway Monitoring","version":1},"reference_index":38,"source":"pdf_text","source_observed_at":"2026-08-16T10:24:42.796665Z"},"links":{"citing_paper":"/paper/2504.18203"},"observation_digest":"sha256:02524175fd79d4c409d834f38935503541625c5928e48a415734eac3de9db3d7","observation_id":"88ea37a4-08d8-4cbc-be29-9aea2e6e8e4d","resolution":{"observed_at":"2026-08-16T10:24:43.190774Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-20T06:33:59.587034+00:00","source":"crossref"},{"observed_at":"2026-08-20T06:33:54.927442+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-16T10:24:43.171994Z","title":"Railnet: A segmentation network for railroad detection,","venue":null,"work_id":"f5c26109-46f3-4dd9-9cdf-ce7262989080","year":2019},"citing_paper":{"arxiv_id":"2504.18203","last_updated":"2025-04-25T09:33:52Z","snapshot_observed_at":"2026-08-19T13:22:13.156508Z","submitted_at":"2025-04-25T09:33:52Z","title":"LiDAR-Guided Monocular 3D Object Detection for Long-Range Railway Monitoring","version":1},"reference_index":39,"source":"pdf_text","source_observed_at":"2026-08-16T10:24:42.800876Z"},"links":{"citing_paper":"/paper/2504.18203"},"observation_digest":"sha256:1c2792ad0938ee0742143cfa4d8f8033cd09a5edc43c5f378ac6bae260fd0c1d","observation_id":"665946b4-5a8e-4fb6-a29b-2eeac6d3e130","resolution":{"observed_at":"2026-08-16T10:24:43.176772Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-20T06:33:59.587034+00:00","source":"crossref"},{"observed_at":"2026-08-20T06:33:54.927442+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"2002.05665","last_updated":"2020-02-05T15:08:15Z","snapshot_observed_at":"2026-08-14T08:36:42.411197Z","submitted_at":"2020-02-05T15:08:15Z","title":"FRSign: A Large-Scale Traffic Light Dataset for Autonomous Trains","version":1},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2002.05665","snapshot_observed_at":"2026-08-16T10:24:42.804986Z","title":"Frsign: A large-scale traffic light dataset for autonomous trains,","venue":null,"work_id":null,"year":2020},"citing_paper":{"arxiv_id":"2504.18203","last_updated":"2025-04-25T09:33:52Z","snapshot_observed_at":"2026-08-19T13:22:13.156508Z","submitted_at":"2025-04-25T09:33:52Z","title":"LiDAR-Guided Monocular 3D Object Detection for Long-Range Railway Monitoring","version":1},"reference_index":40,"source":"pdf_text","source_observed_at":"2026-08-16T10:24:42.804986Z"},"links":{"cited_paper":"/paper/2002.05665","citing_paper":"/paper/2504.18203"},"observation_digest":"sha256:552e350745c58fb3b8eb4be0a93e94003473205b4c1d737294d2377f63609c62","observation_id":"0e0bab53-0860-46f4-bcdf-007efcb827dc","resolution":{"observed_at":"2026-08-16T10:24:42.804986Z","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":"2026-08-16T10:24:43.157993Z","title":"A lightweight framework for obstacle detection in the railway image based on fast region proposal and improved yolo-tiny network,","venue":null,"work_id":"2e9c479c-1f28-4ce9-8c02-f779cc8ee5a4","year":2022},"citing_paper":{"arxiv_id":"2504.18203","last_updated":"2025-04-25T09:33:52Z","snapshot_observed_at":"2026-08-19T13:22:13.156508Z","submitted_at":"2025-04-25T09:33:52Z","title":"LiDAR-Guided Monocular 3D Object Detection for Long-Range Railway Monitoring","version":1},"reference_index":41,"source":"pdf_text","source_observed_at":"2026-08-16T10:24:42.809327Z"},"links":{"citing_paper":"/paper/2504.18203"},"observation_digest":"sha256:f62ab4717e9586e2c53225d7233da23d7f40820c96c4bb6d5fdbedd5e08df4c8","observation_id":"f04fa726-3c1d-4eb5-99df-cedfb0757b50","resolution":{"observed_at":"2026-08-16T10:24:43.162600Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-20T06:33:59.587034+00:00","source":"crossref"},{"observed_at":"2026-08-20T06:33:54.927442+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-16T10:24:43.144220Z","title":"Railset: A unique dataset for railway anomaly detection,","venue":null,"work_id":"6692cd9f-2a24-4258-bac8-483f9e2e7f6c","year":2022},"citing_paper":{"arxiv_id":"2504.18203","last_updated":"2025-04-25T09:33:52Z","snapshot_observed_at":"2026-08-19T13:22:13.156508Z","submitted_at":"2025-04-25T09:33:52Z","title":"LiDAR-Guided Monocular 3D Object Detection for Long-Range Railway Monitoring","version":1},"reference_index":42,"source":"pdf_text","source_observed_at":"2026-08-16T10:24:42.813814Z"},"links":{"citing_paper":"/paper/2504.18203"},"observation_digest":"sha256:3a94919f46a892386da0bbc70e47e29edaed2b2cdb0ba345675e6dc56eaf5362","observation_id":"d5716373-b2c3-4c07-b4aa-181c7a659780","resolution":{"observed_at":"2026-08-16T10:24:43.148668Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-20T06:33:59.587034+00:00","source":"crossref"},{"observed_at":"2026-08-20T06:33:54.927442+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-16T10:24:43.130429Z","title":"A lightweight lidar-camera sensing method of obstacles detection and classification for autonomous rail rapid transit,","venue":null,"work_id":"22839a71-ea15-4e8d-9559-0d678893f06f","year":2022},"citing_paper":{"arxiv_id":"2504.18203","last_updated":"2025-04-25T09:33:52Z","snapshot_observed_at":"2026-08-19T13:22:13.156508Z","submitted_at":"2025-04-25T09:33:52Z","title":"LiDAR-Guided Monocular 3D Object Detection for Long-Range Railway Monitoring","version":1},"reference_index":43,"source":"pdf_text","source_observed_at":"2026-08-16T10:24:42.817738Z"},"links":{"citing_paper":"/paper/2504.18203"},"observation_digest":"sha256:f7f19fd196227ef3d87cce5791aecc7fe701d50b7217a1d527edc7e9c6bcb38c","observation_id":"41bb45e2-61eb-4a7d-9467-664a72a1d6c7","resolution":{"observed_at":"2026-08-16T10:24:43.134915Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-20T06:33:59.587034+00:00","source":"crossref"},{"observed_at":"2026-08-20T06:33:54.927442+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-16T10:24:43.114997Z","title":"Road and Railway Smart Mobility: A High- Definition Ground Truth Hybrid Dataset,","venue":null,"work_id":"2e5f5d37-c614-4df3-a58c-295aed6dbd03","year":2022},"citing_paper":{"arxiv_id":"2504.18203","last_updated":"2025-04-25T09:33:52Z","snapshot_observed_at":"2026-08-19T13:22:13.156508Z","submitted_at":"2025-04-25T09:33:52Z","title":"LiDAR-Guided Monocular 3D Object Detection for Long-Range Railway Monitoring","version":1},"reference_index":44,"source":"pdf_text","source_observed_at":"2026-08-16T10:24:42.821878Z"},"links":{"citing_paper":"/paper/2504.18203"},"observation_digest":"sha256:493781304f0795cfebbb366d5f345d5d21c5cec855b2b73558966e2c65888d5b","observation_id":"04f10fbf-007a-45fb-9437-6681fecc3241","resolution":{"observed_at":"2026-08-16T10:24:43.120054Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-20T06:33:59.587034+00:00","source":"crossref"},{"observed_at":"2026-08-20T06:33:54.927442+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-16T10:24:43.101291Z","title":"3D Object Detection on Synthetic Point Clouds for Railway Applications,","venue":null,"work_id":"7c43ce9a-ca5a-4f90-8bc4-56096e026997","year":2022},"citing_paper":{"arxiv_id":"2504.18203","last_updated":"2025-04-25T09:33:52Z","snapshot_observed_at":"2026-08-19T13:22:13.156508Z","submitted_at":"2025-04-25T09:33:52Z","title":"LiDAR-Guided Monocular 3D Object Detection for Long-Range Railway Monitoring","version":1},"reference_index":45,"source":"pdf_text","source_observed_at":"2026-08-16T10:24:42.826216Z"},"links":{"citing_paper":"/paper/2504.18203"},"observation_digest":"sha256:d4a8823f7e0e60e041bf1105a701f809b5fd023af170ab5fb215a4e19ec56077","observation_id":"b08024ce-38aa-4380-bff7-1204036740bf","resolution":{"observed_at":"2026-08-16T10:24:43.105709Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-20T06:33:59.587034+00:00","source":"crossref"},{"observed_at":"2026-08-20T06:33:54.927442+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-16T10:24:43.087191Z","title":"Open sensor data for rail 2023,","venue":null,"work_id":"9957826c-c92c-4a63-8328-11f63a038c8b","year":2023},"citing_paper":{"arxiv_id":"2504.18203","last_updated":"2025-04-25T09:33:52Z","snapshot_observed_at":"2026-08-19T13:22:13.156508Z","submitted_at":"2025-04-25T09:33:52Z","title":"LiDAR-Guided Monocular 3D Object Detection for Long-Range Railway Monitoring","version":1},"reference_index":46,"source":"pdf_text","source_observed_at":"2026-08-16T10:24:42.831125Z"},"links":{"citing_paper":"/paper/2504.18203"},"observation_digest":"sha256:bf7d1a7fb8a7124163f2cd5e59a7be97d602cca4d704f41058876825ff0cf416","observation_id":"f09e2df0-33c7-49d7-8263-5205a8497517","resolution":{"observed_at":"2026-08-16T10:24:43.091733Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-20T06:33:59.587034+00:00","source":"crossref"},{"observed_at":"2026-08-20T06:33:54.927442+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-16T10:24:43.071903Z","title":"Asam openlabel,","venue":null,"work_id":"d8675819-b84b-4cda-ae32-13048d641693","year":2021},"citing_paper":{"arxiv_id":"2504.18203","last_updated":"2025-04-25T09:33:52Z","snapshot_observed_at":"2026-08-19T13:22:13.156508Z","submitted_at":"2025-04-25T09:33:52Z","title":"LiDAR-Guided Monocular 3D Object Detection for Long-Range Railway Monitoring","version":1},"reference_index":47,"source":"pdf_text","source_observed_at":"2026-08-16T10:24:42.835222Z"},"links":{"citing_paper":"/paper/2504.18203"},"observation_digest":"sha256:7c70f4611345c986215ec244467d0ac093c6d02cea1e8814248397ca1bf3c1b3","observation_id":"993b6e41-2b3f-486c-a9c5-42559d4d34f7","resolution":{"observed_at":"2026-08-16T10:24:43.076714Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-20T06:33:59.587034+00:00","source":"crossref"},{"observed_at":"2026-08-20T06:33:54.927442+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-16T10:24:43.057371Z","title":"Multi-view 3d object detection network for autonomous driving,","venue":null,"work_id":"a6d74c02-253e-4bfa-9a89-622ed056349b","year":2017},"citing_paper":{"arxiv_id":"2504.18203","last_updated":"2025-04-25T09:33:52Z","snapshot_observed_at":"2026-08-19T13:22:13.156508Z","submitted_at":"2025-04-25T09:33:52Z","title":"LiDAR-Guided Monocular 3D Object Detection for Long-Range Railway Monitoring","version":1},"reference_index":48,"source":"pdf_text","source_observed_at":"2026-08-16T10:24:42.839305Z"},"links":{"citing_paper":"/paper/2504.18203"},"observation_digest":"sha256:9438c38cefaffcea329d808eaf1302468bbfa2171ec24c882604be154c443da5","observation_id":"a0bcad39-1cb9-4ebe-a769-3e298dedff25","resolution":{"observed_at":"2026-08-16T10:24:43.061891Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-20T06:33:59.587034+00:00","source":"crossref"},{"observed_at":"2026-08-20T06:33:54.927442+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"1912.13192","last_updated":"2021-04-09T06:37:15Z","snapshot_observed_at":"2026-08-14T09:34:46.315325Z","submitted_at":"2019-12-31T06:34:10Z","title":"PV-RCNN: Point-Voxel Feature Set Abstraction for 3D Object Detection","version":2},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"1912.13192","snapshot_observed_at":"2026-08-16T10:24:42.720212Z","title":"Available: https://arxiv.org/abs/1912.13192","venue":null,"work_id":null,"year":1912},"citing_paper":{"arxiv_id":"2504.18203","last_updated":"2025-04-25T09:33:52Z","snapshot_observed_at":"2026-08-19T13:22:13.156508Z","submitted_at":"2025-04-25T09:33:52Z","title":"LiDAR-Guided Monocular 3D Object Detection for Long-Range Railway Monitoring","version":1},"reference_index":2021,"source":"pdf_text","source_observed_at":"2026-08-16T10:24:42.720212Z"},"links":{"cited_paper":"/paper/1912.13192","citing_paper":"/paper/2504.18203"},"observation_digest":"sha256:a58f5173658bd49715830636a4096a7ce1e9d17a33beaedd31f4b5086f39849e","observation_id":"02c4274d-7d2e-4d80-ae91-1753840952f1","resolution":{"observed_at":"2026-08-16T10:24:42.720212Z","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":"2026-08-16T10:24:43.233648Z","title":"Available: https://www.mdpi.com/2076-3417/12/3/ 1354","venue":null,"work_id":"13df115e-26ea-4b38-87e9-357bb2d7d7c0","year":null},"citing_paper":{"arxiv_id":"2504.18203","last_updated":"2025-04-25T09:33:52Z","snapshot_observed_at":"2026-08-19T13:22:13.156508Z","submitted_at":"2025-04-25T09:33:52Z","title":"LiDAR-Guided Monocular 3D Object Detection for Long-Range Railway Monitoring","version":1},"reference_index":2022,"source":"pdf_text","source_observed_at":"2026-08-16T10:24:42.756572Z"},"links":{"citing_paper":"/paper/2504.18203"},"observation_digest":"sha256:28823cc8e230a286aeee6ef467d973ca5406e06877fbc2930e3dd63397d5262a","observation_id":"e2ee55de-5a40-4142-adec-28b7305f1e05","resolution":{"observed_at":"2026-08-16T10:24:43.238052Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-20T06:33:59.587034+00:00","source":"crossref"},{"observed_at":"2026-08-20T06:33:54.927442+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"2403.09230","last_updated":"2024-03-14T09:54:31Z","snapshot_observed_at":"2026-08-16T14:09:53.821358Z","submitted_at":"2024-03-14T09:54:31Z","title":"Improving Distant 3D Object Detection Using 2D Box Supervision","version":1},"cited_work":{"arxiv_id":"2403.09230","doi":null,"metadata_source":"pith","pith_arxiv_id":"2403.09230","snapshot_observed_at":"2026-08-16T10:24:43.040334Z","title":"Improving Distant 3D Object Detection Using 2D Box Supervision","venue":"cs.CV","work_id":"6b664072-e9c0-4c39-94a1-3319d3e8aa2d","year":2024},"citing_paper":{"arxiv_id":"2504.18203","last_updated":"2025-04-25T09:33:52Z","snapshot_observed_at":"2026-08-19T13:22:13.156508Z","submitted_at":"2025-04-25T09:33:52Z","title":"LiDAR-Guided Monocular 3D Object Detection for Long-Range Railway Monitoring","version":1},"reference_index":2024,"source":"pdf_text","source_observed_at":"2026-08-16T10:24:42.652286Z"},"links":{"cited_paper":"/paper/2403.09230","citing_paper":"/paper/2504.18203"},"observation_digest":"sha256:6b404ee2ea8a8f4ccff3a29840bc8ef73b62606467b59ca3feebdb403c4b8c0d","observation_id":"53ce90da-4917-4645-b844-31b594282278","resolution":{"observed_at":"2026-08-16T10:24:43.047098Z","resolver_source":"local_arxiv","status":"metadata_mismatch"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-20T06:33:59.587034+00:00","source":"crossref"},{"observed_at":"2026-08-20T06:33:54.927442+00:00","source":"retraction_watch"}],"state":"measured"}}],"paper":{"arxiv_id":"2504.18203","last_updated":"2025-04-25T09:33:52Z","latest_version":1,"primary_category":"cs.CV","snapshot_observed_at":"2026-08-19T13:22:13.156508Z","submitted_at":"2025-04-25T09:33:52Z","title":"LiDAR-Guided Monocular 3D Object Detection for Long-Range Railway Monitoring"},"reference_resolution":{"displayed":51,"state_counts":{"malformed_identifier":0,"metadata_mismatch":1,"parse_uncertain":0,"unresolved":14,"verified_exact":1,"verified_fuzzy":35},"total_outbound_references":51},"refusal":"A citation records a reference. It does not transfer a finding from one paper to another.","schema":"pith.paper-citation-record.v1","standing_sources":[{"observed_at":"2026-08-20T06:33:59.587034+00:00","source":"crossref"},{"observed_at":"2026-08-20T06:33:54.927442+00:00","source":"retraction_watch"}],"thesis":"As of 20 August 2026, this Paper Citation Record lists 51 of 51 outbound references and 0 inbound Pith citation observations for arXiv:2504.18203."}