{"as_of":"2026-08-11T12:27:00Z","caps":{"database_statements":6,"inbound":100,"outbound":100},"context_digest":"sha256:82042a5bf243bab1e075a67f021bdd0245bf554a6743d705f9ba7efc2e669a47","coverage":[{"denominator":42,"lane":"reference_resolution","note":"Typed states for the displayed outbound observations.","records_observed":42,"source":"paper_references, paper_reference_links","source_observed_at":"2026-06-30T18:15:04.759721Z","state":"measured"},{"denominator":42,"lane":"standing_notices","note":"One-hop event checks from named stored sources.","records_observed":42,"source":"scholarly_work_events, retraction_status_cache","source_observed_at":"2026-08-11T06:34:44.6726+00:00","state":"measured"},{"denominator":0,"lane":"inbound_itemization","note":"Pith citing papers itemized under the disclosed page cap.","records_observed":0,"source":"paper_references, paper_reference_links","source_observed_at":null,"state":"measured"},{"denominator":1,"lane":"external_citation_measurements","note":"A source-named dated measurement, never combined with another source.","records_observed":0,"source":"cited_works","source_observed_at":null,"state":"measured"}],"external_citation_measurements":[],"inbound":[],"links":{"evidence":"/evidence","html":"/paper/2605.20301/citation-record","integrity":"/paper/2605.20301/integrity","json":"/paper/2605.20301/citation-record.json","paper":"/paper/2605.20301"},"outbound":[{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-07-08T05:44:36.278003Z","title":"Robustness-aware 3d object detection in autonomous driving: A review and outlook.IEEE Transactions on Intelligent Transportation Systems, 2024","venue":null,"work_id":"5f438674-1232-46a0-bbec-b434ca608c37","year":2024},"citing_paper":{"arxiv_id":"2605.20301","last_updated":"2026-06-01T02:49:14Z","snapshot_observed_at":"2026-08-04T12:53:21.630996Z","submitted_at":"2026-05-19T12:36:09Z","title":"Co-Fusion4D: Spatio-temporal Collaborative Fusion for Robust 3D Object Detection","version":2},"reference_index":1,"source":"pdf_text","source_observed_at":"2026-06-30T18:15:04.759721Z"},"links":{"citing_paper":"/paper/2605.20301"},"observation_digest":"sha256:a55e9b04161ed8fa7707e2a4eccc8c0f753348e044f6bf33180d52e041b4c5d9","observation_id":"21d0333a-b095-4b94-b50d-fc20b350988b","resolution":{"observed_at":"2026-07-08T05:44:36.279203Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-11T06:34:44.6726+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-11T06:34:44.6726+00:00","source":"crossref"},{"observed_at":"2026-08-11T06:34:36.301508+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-07-08T05:44:36.346800Z","title":"Stereodetr: Stereo-based transformer for 3d object detection.IEEE Transactions on Circuits and Systems for Video Technology, 2025","venue":null,"work_id":"85e2cc7f-b100-499a-8f6c-a82c4414b08e","year":2025},"citing_paper":{"arxiv_id":"2605.20301","last_updated":"2026-06-01T02:49:14Z","snapshot_observed_at":"2026-08-04T12:53:21.630996Z","submitted_at":"2026-05-19T12:36:09Z","title":"Co-Fusion4D: Spatio-temporal Collaborative Fusion for Robust 3D Object Detection","version":2},"reference_index":2,"source":"pdf_text","source_observed_at":"2026-06-30T18:15:04.759721Z"},"links":{"citing_paper":"/paper/2605.20301"},"observation_digest":"sha256:46421c7648ff0529af8fc5f59b6d4870dc8d8a621b799fa3465aa32a8ae0334c","observation_id":"6e3f1b3e-4d9d-4520-814d-281b7c03b1b9","resolution":{"observed_at":"2026-07-08T05:44:36.348263Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-11T06:34:44.6726+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-11T06:34:44.6726+00:00","source":"crossref"},{"observed_at":"2026-08-11T06:34:36.301508+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-07-08T05:44:36.336568Z","title":"Bevfix: Deep feature enhancement for robust 3d object detection.Neural Networks, 190:107675, 2025","venue":null,"work_id":"382b9a0a-2638-4633-bbd0-22a8eecf6909","year":2025},"citing_paper":{"arxiv_id":"2605.20301","last_updated":"2026-06-01T02:49:14Z","snapshot_observed_at":"2026-08-04T12:53:21.630996Z","submitted_at":"2026-05-19T12:36:09Z","title":"Co-Fusion4D: Spatio-temporal Collaborative Fusion for Robust 3D Object Detection","version":2},"reference_index":3,"source":"pdf_text","source_observed_at":"2026-06-30T18:15:04.759721Z"},"links":{"citing_paper":"/paper/2605.20301"},"observation_digest":"sha256:0c99fcb579a8143034917e53c8e0d5a117622f89f34c75973b7c4ee90a9f3d48","observation_id":"ba3dee09-afbe-44a2-9f7a-5c64da3bb880","resolution":{"observed_at":"2026-07-08T05:44:36.338220Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-11T06:34:44.6726+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-11T06:34:44.6726+00:00","source":"crossref"},{"observed_at":"2026-08-11T06:34:36.301508+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-07-08T05:44:36.334782Z","title":"Iter3ddet: Depth-guided iterative fusion and refinement for monocular 3d object detection.IEEE Transactions on Circuits and Systems for Video Technology, 2025","venue":null,"work_id":"eab1faf0-a81a-4c66-856c-4328064c11ab","year":2025},"citing_paper":{"arxiv_id":"2605.20301","last_updated":"2026-06-01T02:49:14Z","snapshot_observed_at":"2026-08-04T12:53:21.630996Z","submitted_at":"2026-05-19T12:36:09Z","title":"Co-Fusion4D: Spatio-temporal Collaborative Fusion for Robust 3D Object Detection","version":2},"reference_index":4,"source":"pdf_text","source_observed_at":"2026-06-30T18:15:04.759721Z"},"links":{"citing_paper":"/paper/2605.20301"},"observation_digest":"sha256:3263c6f4a6a02e9006b8c1886458e50987e8464a26e801885e4999ae56a7c243","observation_id":"bdebb728-8bba-41a4-8118-007a5c294711","resolution":{"observed_at":"2026-07-08T05:44:36.336038Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-11T06:34:44.6726+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-11T06:34:44.6726+00:00","source":"crossref"},{"observed_at":"2026-08-11T06:34:36.301508+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-07-08T05:44:36.331231Z","title":"Vision-centric bev perception: A survey.IEEE Transactions on Pattern Analysis and Machine Intelligence, 46(12):10978–10997, 2024","venue":null,"work_id":"6b4de487-6483-4331-80d3-42f75884738a","year":2024},"citing_paper":{"arxiv_id":"2605.20301","last_updated":"2026-06-01T02:49:14Z","snapshot_observed_at":"2026-08-04T12:53:21.630996Z","submitted_at":"2026-05-19T12:36:09Z","title":"Co-Fusion4D: Spatio-temporal Collaborative Fusion for Robust 3D Object Detection","version":2},"reference_index":5,"source":"pdf_text","source_observed_at":"2026-06-30T18:15:04.759721Z"},"links":{"citing_paper":"/paper/2605.20301"},"observation_digest":"sha256:cf70d1a8300ed2afa766c1170374f0deb041fa40e3038d55630d2e11d3c5ad79","observation_id":"99e7947b-21c7-46df-949c-1139b9017e85","resolution":{"observed_at":"2026-07-08T05:44:36.332446Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-11T06:34:44.6726+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-11T06:34:44.6726+00:00","source":"crossref"},{"observed_at":"2026-08-11T06:34:36.301508+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-07-08T05:44:36.319925Z","title":"Dgfusion: Dual-guided fusion for robust multi-modal 3d object detection.IEEE Transactions on Circuits and Systems for Video Technology, 2025","venue":null,"work_id":"a2d96a8b-b0db-43bb-b6d9-0eff0003a8b5","year":2025},"citing_paper":{"arxiv_id":"2605.20301","last_updated":"2026-06-01T02:49:14Z","snapshot_observed_at":"2026-08-04T12:53:21.630996Z","submitted_at":"2026-05-19T12:36:09Z","title":"Co-Fusion4D: Spatio-temporal Collaborative Fusion for Robust 3D Object Detection","version":2},"reference_index":6,"source":"pdf_text","source_observed_at":"2026-06-30T18:15:04.759721Z"},"links":{"citing_paper":"/paper/2605.20301"},"observation_digest":"sha256:55297de797b4b8bf1f07a4b65927fc5c0b3f3ecf3238243ee32eb5bdb575d8d9","observation_id":"0c2218ac-cb7a-4ec4-beb9-2d88f1a60c82","resolution":{"observed_at":"2026-07-08T05:44:36.321474Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-11T06:34:44.6726+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-11T06:34:44.6726+00:00","source":"crossref"},{"observed_at":"2026-08-11T06:34:36.301508+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-07-08T05:44:36.292903Z","title":"Fastpillars: A deployment-friendly pillar-based 3d detector","venue":null,"work_id":"315b8a36-0732-4770-8a6a-069c936a2ad0","year":2025},"citing_paper":{"arxiv_id":"2605.20301","last_updated":"2026-06-01T02:49:14Z","snapshot_observed_at":"2026-08-04T12:53:21.630996Z","submitted_at":"2026-05-19T12:36:09Z","title":"Co-Fusion4D: Spatio-temporal Collaborative Fusion for Robust 3D Object Detection","version":2},"reference_index":7,"source":"pdf_text","source_observed_at":"2026-06-30T18:15:04.759721Z"},"links":{"citing_paper":"/paper/2605.20301"},"observation_digest":"sha256:2ba46c6ae5b0f30ea273d9b8a77e379d61fb4ee762deaf82a84130dad9c156d2","observation_id":"2965290a-2225-40a9-b385-296e162d8e04","resolution":{"observed_at":"2026-07-08T05:44:36.294368Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-11T06:34:44.6726+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-11T06:34:44.6726+00:00","source":"crossref"},{"observed_at":"2026-08-11T06:34:36.301508+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"2303.17099","last_updated":"2023-03-30T02:18:07Z","snapshot_observed_at":"2026-08-09T20:13:34.136612Z","submitted_at":"2023-03-30T02:18:07Z","title":"BEVFusion4D: Learning LiDAR-Camera Fusion Under Bird's-Eye-View via Cross-Modality Guidance and Temporal Aggregation","version":1},"cited_work":{"arxiv_id":"2303.17099","doi":null,"metadata_source":"arxiv_reference","pith_arxiv_id":"2303.17099","snapshot_observed_at":"2026-07-01T15:05:47.851672Z","title":"Bevfusion4d: Learning lidar-camera fusion under bird’s-eye-view via cross-modality guidance and temporal aggregation","venue":null,"work_id":"e4815434-40a4-493e-95b6-046ebc4ada2c","year":2023},"citing_paper":{"arxiv_id":"2605.20301","last_updated":"2026-06-01T02:49:14Z","snapshot_observed_at":"2026-08-04T12:53:21.630996Z","submitted_at":"2026-05-19T12:36:09Z","title":"Co-Fusion4D: Spatio-temporal Collaborative Fusion for Robust 3D Object Detection","version":2},"reference_index":8,"source":"pdf_text","source_observed_at":"2026-06-30T18:15:04.759721Z"},"links":{"cited_paper":"/paper/2303.17099","citing_paper":"/paper/2605.20301"},"observation_digest":"sha256:34b8d74852046c62424d6f38f9fd1ac5979343fb4bb07fd6c85b2113849b6bad","observation_id":"58e6d5b6-0b19-4845-8aa3-7399f38d9575","resolution":{"observed_at":"2026-07-01T15:05:47.853244Z","resolver_source":"arxiv_id","status":"verified_exact"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-11T06:34:44.6726+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-11T06:34:44.6726+00:00","source":"crossref"},{"observed_at":"2026-08-11T06:34:36.301508+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-07-08T05:44:36.338800Z","title":"Gafusion: Adaptive fusing lidar and camera with multiple guidance for 3d object detection","venue":null,"work_id":"763d7595-3aff-4b33-9a34-d3fc28653a87","year":2024},"citing_paper":{"arxiv_id":"2605.20301","last_updated":"2026-06-01T02:49:14Z","snapshot_observed_at":"2026-08-04T12:53:21.630996Z","submitted_at":"2026-05-19T12:36:09Z","title":"Co-Fusion4D: Spatio-temporal Collaborative Fusion for Robust 3D Object Detection","version":2},"reference_index":9,"source":"pdf_text","source_observed_at":"2026-06-30T18:15:04.759721Z"},"links":{"citing_paper":"/paper/2605.20301"},"observation_digest":"sha256:2f3815227e6f306b2fb702cf4a001d93f6c2a6f270f398e6858a5f3155e081f4","observation_id":"90074767-1985-4307-8b08-4a2cec9602ef","resolution":{"observed_at":"2026-07-08T05:44:36.340238Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-11T06:34:44.6726+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-11T06:34:44.6726+00:00","source":"crossref"},{"observed_at":"2026-08-11T06:34:36.301508+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"2408.07999","last_updated":"2024-11-15T04:09:34Z","snapshot_observed_at":"2026-08-08T10:34:34.830054Z","submitted_at":"2024-08-15T07:56:02Z","title":"Co-Fix3D: Enhancing 3D Object Detection with Collaborative Refinement","version":2},"cited_work":{"arxiv_id":"2408.07999","doi":null,"metadata_source":"arxiv_reference","pith_arxiv_id":"2408.07999","snapshot_observed_at":"2026-07-01T15:05:47.848561Z","title":"Co- fix3d: Enhancing 3d object detection with collaborative refinement","venue":null,"work_id":"17c0827a-8911-4ed2-af15-1d6d279145da","year":2024},"citing_paper":{"arxiv_id":"2605.20301","last_updated":"2026-06-01T02:49:14Z","snapshot_observed_at":"2026-08-04T12:53:21.630996Z","submitted_at":"2026-05-19T12:36:09Z","title":"Co-Fusion4D: Spatio-temporal Collaborative Fusion for Robust 3D Object Detection","version":2},"reference_index":10,"source":"pdf_text","source_observed_at":"2026-06-30T18:15:04.759721Z"},"links":{"cited_paper":"/paper/2408.07999","citing_paper":"/paper/2605.20301"},"observation_digest":"sha256:114b83fd31cbd4688bfdf62ff5dae63d69ae9131ecb7a6521d270ab490631263","observation_id":"c857f0ee-4e7c-4b27-a4e9-bc139facd3c9","resolution":{"observed_at":"2026-07-01T15:05:47.850597Z","resolver_source":"arxiv_id","status":"verified_exact"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-11T06:34:44.6726+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-11T06:34:44.6726+00:00","source":"crossref"},{"observed_at":"2026-08-11T06:34:36.301508+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-07-08T05:44:36.340788Z","title":"Pointnet: Deep learning on point sets for 3d classification and segmentation","venue":null,"work_id":"5ccf1f26-66c6-4e0b-92ba-af4ef229ea11","year":2017},"citing_paper":{"arxiv_id":"2605.20301","last_updated":"2026-06-01T02:49:14Z","snapshot_observed_at":"2026-08-04T12:53:21.630996Z","submitted_at":"2026-05-19T12:36:09Z","title":"Co-Fusion4D: Spatio-temporal Collaborative Fusion for Robust 3D Object Detection","version":2},"reference_index":11,"source":"pdf_text","source_observed_at":"2026-06-30T18:15:04.759721Z"},"links":{"citing_paper":"/paper/2605.20301"},"observation_digest":"sha256:7284bc191beaa77656d816cfc841ce17c3c865db4d74068af670c6e23072f7fd","observation_id":"7b9f606a-b775-4736-81fd-1ebc6d299f44","resolution":{"observed_at":"2026-07-08T05:44:36.342325Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-11T06:34:44.6726+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-11T06:34:44.6726+00:00","source":"crossref"},{"observed_at":"2026-08-11T06:34:36.301508+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-07-08T05:44:36.348772Z","title":"Pointnet++: Deep hierarchical feature learning on point sets in a metric space.Advances in neural information processing systems, 30","venue":null,"work_id":"20799e7f-1c59-4a17-b58e-0c0626f114eb","year":2017},"citing_paper":{"arxiv_id":"2605.20301","last_updated":"2026-06-01T02:49:14Z","snapshot_observed_at":"2026-08-04T12:53:21.630996Z","submitted_at":"2026-05-19T12:36:09Z","title":"Co-Fusion4D: Spatio-temporal Collaborative Fusion for Robust 3D Object Detection","version":2},"reference_index":12,"source":"pdf_text","source_observed_at":"2026-06-30T18:15:04.759721Z"},"links":{"citing_paper":"/paper/2605.20301"},"observation_digest":"sha256:7c7b511ea431c8a2279f780f89969a8faf8702950d7633d1f07230147d45a5e1","observation_id":"66e375b0-47b6-4657-9c75-8d6cebdb47dd","resolution":{"observed_at":"2026-07-08T05:44:36.349988Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-11T06:34:44.6726+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-11T06:34:44.6726+00:00","source":"crossref"},{"observed_at":"2026-08-11T06:34:36.301508+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-07-08T05:44:36.327406Z","title":"Pointrcnn: 3d object proposal generation and detection from point cloud","venue":null,"work_id":"f53e3879-7f68-4d06-b124-52418cdbfa87","year":2019},"citing_paper":{"arxiv_id":"2605.20301","last_updated":"2026-06-01T02:49:14Z","snapshot_observed_at":"2026-08-04T12:53:21.630996Z","submitted_at":"2026-05-19T12:36:09Z","title":"Co-Fusion4D: Spatio-temporal Collaborative Fusion for Robust 3D Object Detection","version":2},"reference_index":13,"source":"pdf_text","source_observed_at":"2026-06-30T18:15:04.759721Z"},"links":{"citing_paper":"/paper/2605.20301"},"observation_digest":"sha256:4d70972cfa877ef510c00741ceb77c23979d4316432971b1da9fe04c12722566","observation_id":"47d41853-93d5-43e4-b256-56e8c84795a5","resolution":{"observed_at":"2026-07-08T05:44:36.328821Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-11T06:34:44.6726+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-11T06:34:44.6726+00:00","source":"crossref"},{"observed_at":"2026-08-11T06:34:36.301508+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-07-08T05:44:36.322040Z","title":"V oxelnet: End-to-end learning for point cloud based 3d object detection","venue":null,"work_id":"4f9ad99a-de33-40dc-ab62-91055db7484e","year":2018},"citing_paper":{"arxiv_id":"2605.20301","last_updated":"2026-06-01T02:49:14Z","snapshot_observed_at":"2026-08-04T12:53:21.630996Z","submitted_at":"2026-05-19T12:36:09Z","title":"Co-Fusion4D: Spatio-temporal Collaborative Fusion for Robust 3D Object Detection","version":2},"reference_index":14,"source":"pdf_text","source_observed_at":"2026-06-30T18:15:04.759721Z"},"links":{"citing_paper":"/paper/2605.20301"},"observation_digest":"sha256:b0ca473ffba713c299e2a940c862abec5a5c01780f0f729cd935450ca95b1948","observation_id":"d49a9044-a371-43cd-894e-e36e326a16e6","resolution":{"observed_at":"2026-07-08T05:44:36.323322Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-11T06:34:44.6726+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-11T06:34:44.6726+00:00","source":"crossref"},{"observed_at":"2026-08-11T06:34:36.301508+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-07-08T05:44:36.323874Z","title":"Second: Sparsely embedded convolutional detection.Sensors, 18(10):3337, 2018","venue":null,"work_id":"4f9f243a-c6fb-44ac-bc21-298873631f94","year":2018},"citing_paper":{"arxiv_id":"2605.20301","last_updated":"2026-06-01T02:49:14Z","snapshot_observed_at":"2026-08-04T12:53:21.630996Z","submitted_at":"2026-05-19T12:36:09Z","title":"Co-Fusion4D: Spatio-temporal Collaborative Fusion for Robust 3D Object Detection","version":2},"reference_index":15,"source":"pdf_text","source_observed_at":"2026-06-30T18:15:04.759721Z"},"links":{"citing_paper":"/paper/2605.20301"},"observation_digest":"sha256:826c8a6ba0bd6c229f5894b54d8c68a95b0731ac121fcd824355a140d9e3152e","observation_id":"dac8d81a-1f80-40d9-ba20-083a65d33fda","resolution":{"observed_at":"2026-07-08T05:44:36.324995Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-11T06:34:44.6726+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-11T06:34:44.6726+00:00","source":"crossref"},{"observed_at":"2026-08-11T06:34:36.301508+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-07-08T05:44:36.325613Z","title":"Pv-rcnn: Point-voxel feature set abstraction for 3d object detection","venue":null,"work_id":"faf23c2f-e806-4a8e-9f10-f6e8b4aaaf40","year":2020},"citing_paper":{"arxiv_id":"2605.20301","last_updated":"2026-06-01T02:49:14Z","snapshot_observed_at":"2026-08-04T12:53:21.630996Z","submitted_at":"2026-05-19T12:36:09Z","title":"Co-Fusion4D: Spatio-temporal Collaborative Fusion for Robust 3D Object Detection","version":2},"reference_index":16,"source":"pdf_text","source_observed_at":"2026-06-30T18:15:04.759721Z"},"links":{"citing_paper":"/paper/2605.20301"},"observation_digest":"sha256:0ade3d4a23064330158d7481a61ba2b3facd2d4b8f243adf1fd533c1064f45ce","observation_id":"f175f583-1654-434b-bffa-5ea297882da2","resolution":{"observed_at":"2026-07-08T05:44:36.326843Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-11T06:34:44.6726+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-11T06:34:44.6726+00:00","source":"crossref"},{"observed_at":"2026-08-11T06:34:36.301508+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-07-08T05:44:36.352781Z","title":"Dsc3d: Deformable sampling constraints in stereo 3d object detection for autonomous driving.IEEE Transactions on Circuits and Systems for Video Technology, 35(3):2794–2805, 2024","venue":null,"work_id":"f00234ea-03d4-49bc-8b92-7760ee5c8f01","year":2024},"citing_paper":{"arxiv_id":"2605.20301","last_updated":"2026-06-01T02:49:14Z","snapshot_observed_at":"2026-08-04T12:53:21.630996Z","submitted_at":"2026-05-19T12:36:09Z","title":"Co-Fusion4D: Spatio-temporal Collaborative Fusion for Robust 3D Object Detection","version":2},"reference_index":17,"source":"pdf_text","source_observed_at":"2026-06-30T18:15:04.759721Z"},"links":{"citing_paper":"/paper/2605.20301"},"observation_digest":"sha256:0919c04a80138e3bfc11443b4136b079c6c0f981052061922d40e546a8fc9ca3","observation_id":"5a6d4186-1391-4f4b-9767-4ba3a93e379e","resolution":{"observed_at":"2026-07-08T05:44:36.354031Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-11T06:34:44.6726+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-11T06:34:44.6726+00:00","source":"crossref"},{"observed_at":"2026-08-11T06:34:36.301508+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-07-08T05:44:36.309170Z","title":"Tinyfusiondet: Hardware-efficient lidar-camera fusion framework for 3d object detection at edge.IEEE Transactions on Circuits and Systems for Video Technology, 2025","venue":null,"work_id":"0c4e4649-9ab1-430f-874f-a3d176048755","year":2025},"citing_paper":{"arxiv_id":"2605.20301","last_updated":"2026-06-01T02:49:14Z","snapshot_observed_at":"2026-08-04T12:53:21.630996Z","submitted_at":"2026-05-19T12:36:09Z","title":"Co-Fusion4D: Spatio-temporal Collaborative Fusion for Robust 3D Object Detection","version":2},"reference_index":18,"source":"pdf_text","source_observed_at":"2026-06-30T18:15:04.759721Z"},"links":{"citing_paper":"/paper/2605.20301"},"observation_digest":"sha256:5fda293656cdc73a34b652c66ebf44a6457664a98c6c2cbbf5edd9b8f4517bc9","observation_id":"58e01a75-8dd2-44c3-848c-d3c86d226127","resolution":{"observed_at":"2026-07-08T05:44:36.311090Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-11T06:34:44.6726+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-11T06:34:44.6726+00:00","source":"crossref"},{"observed_at":"2026-08-11T06:34:36.301508+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-07-08T05:44:36.333084Z","title":"Deformable feature aggregation for dynamic multi- modal 3d object detection","venue":null,"work_id":"840ec834-6981-4e3b-a6b1-247a9a3b8b03","year":2022},"citing_paper":{"arxiv_id":"2605.20301","last_updated":"2026-06-01T02:49:14Z","snapshot_observed_at":"2026-08-04T12:53:21.630996Z","submitted_at":"2026-05-19T12:36:09Z","title":"Co-Fusion4D: Spatio-temporal Collaborative Fusion for Robust 3D Object Detection","version":2},"reference_index":19,"source":"pdf_text","source_observed_at":"2026-06-30T18:15:04.759721Z"},"links":{"citing_paper":"/paper/2605.20301"},"observation_digest":"sha256:8ca3774df0cae8ac305dbd002be09bba92d845df90f0a57589d6234a93f85d9b","observation_id":"b9bb9e19-3bad-45e4-902d-a3708519ef3c","resolution":{"observed_at":"2026-07-08T05:44:36.334238Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-11T06:34:44.6726+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-11T06:34:44.6726+00:00","source":"crossref"},{"observed_at":"2026-08-11T06:34:36.301508+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-07-08T05:44:36.305042Z","title":"Fusionpainting: Multimodal fusion with adaptive attention for 3d object detection","venue":null,"work_id":"6ea0f7a9-7bba-43a2-8eb6-86f139aa7b17","year":2021},"citing_paper":{"arxiv_id":"2605.20301","last_updated":"2026-06-01T02:49:14Z","snapshot_observed_at":"2026-08-04T12:53:21.630996Z","submitted_at":"2026-05-19T12:36:09Z","title":"Co-Fusion4D: Spatio-temporal Collaborative Fusion for Robust 3D Object Detection","version":2},"reference_index":20,"source":"pdf_text","source_observed_at":"2026-06-30T18:15:04.759721Z"},"links":{"citing_paper":"/paper/2605.20301"},"observation_digest":"sha256:ccf7d7cec77a5ffddbed628a89f7802210ac0dc58d0f9ad58372143c0eb33136","observation_id":"dc9596f9-d5a2-4d29-a1c1-28e1b55c23a4","resolution":{"observed_at":"2026-07-08T05:44:36.306443Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-11T06:34:44.6726+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-11T06:34:44.6726+00:00","source":"crossref"},{"observed_at":"2026-08-11T06:34:36.301508+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-07-08T05:44:36.350558Z","title":"V oxel field fusion for 3d object detection","venue":null,"work_id":"fec35a21-cf22-4c24-84dc-964e321a879d","year":2022},"citing_paper":{"arxiv_id":"2605.20301","last_updated":"2026-06-01T02:49:14Z","snapshot_observed_at":"2026-08-04T12:53:21.630996Z","submitted_at":"2026-05-19T12:36:09Z","title":"Co-Fusion4D: Spatio-temporal Collaborative Fusion for Robust 3D Object Detection","version":2},"reference_index":21,"source":"pdf_text","source_observed_at":"2026-06-30T18:15:04.759721Z"},"links":{"citing_paper":"/paper/2605.20301"},"observation_digest":"sha256:8ebf1fc0a806f12123fce16683ecbb1b32d4d3a8070f851be19834cc783024ea","observation_id":"ccfbb123-c4b0-4db1-93f0-dfdde1ec9282","resolution":{"observed_at":"2026-07-08T05:44:36.352042Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-11T06:34:44.6726+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-11T06:34:44.6726+00:00","source":"crossref"},{"observed_at":"2026-08-11T06:34:36.301508+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-07-08T05:44:36.342876Z","title":"Unifying voxel-based representation with transformer for 3d object detection.Advances in Neural Information Processing Systems, 35:18442–18455, 2022","venue":null,"work_id":"c6c32ea3-042c-44ab-a213-809d9ecb6380","year":2022},"citing_paper":{"arxiv_id":"2605.20301","last_updated":"2026-06-01T02:49:14Z","snapshot_observed_at":"2026-08-04T12:53:21.630996Z","submitted_at":"2026-05-19T12:36:09Z","title":"Co-Fusion4D: Spatio-temporal Collaborative Fusion for Robust 3D Object Detection","version":2},"reference_index":22,"source":"pdf_text","source_observed_at":"2026-06-30T18:15:04.759721Z"},"links":{"citing_paper":"/paper/2605.20301"},"observation_digest":"sha256:c12dcb15ec1ea7d0b35800123fecbc2371744daa5b4fe78b57283c9e33282248","observation_id":"29649fbc-7c78-4bb3-b374-94e0aaa2d607","resolution":{"observed_at":"2026-07-08T05:44:36.344228Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-11T06:34:44.6726+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-11T06:34:44.6726+00:00","source":"crossref"},{"observed_at":"2026-08-11T06:34:36.301508+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-07-08T05:44:36.294899Z","title":"Transfusion: Robust lidar-camera fusion for 3d object detection with transformers","venue":null,"work_id":"f69042f2-f7ef-40c0-ba9c-a89158210246","year":2022},"citing_paper":{"arxiv_id":"2605.20301","last_updated":"2026-06-01T02:49:14Z","snapshot_observed_at":"2026-08-04T12:53:21.630996Z","submitted_at":"2026-05-19T12:36:09Z","title":"Co-Fusion4D: Spatio-temporal Collaborative Fusion for Robust 3D Object Detection","version":2},"reference_index":23,"source":"pdf_text","source_observed_at":"2026-06-30T18:15:04.759721Z"},"links":{"citing_paper":"/paper/2605.20301"},"observation_digest":"sha256:023af2e33631add2684160f6882ea99477d768853d5d503361db16dffca83ca0","observation_id":"9432968d-83f1-4261-a63e-e4f4c5b2618e","resolution":{"observed_at":"2026-07-08T05:44:36.296553Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-11T06:34:44.6726+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-11T06:34:44.6726+00:00","source":"crossref"},{"observed_at":"2026-08-11T06:34:36.301508+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-07-08T05:44:36.315843Z","title":"Bevfusion: A simple and robust lidar-camera fusion framework.Advances in Neural Information Processing Systems, 35:10421–10434","venue":null,"work_id":"66bf3e64-91ed-49ff-aa17-3be1708fed7c","year":2022},"citing_paper":{"arxiv_id":"2605.20301","last_updated":"2026-06-01T02:49:14Z","snapshot_observed_at":"2026-08-04T12:53:21.630996Z","submitted_at":"2026-05-19T12:36:09Z","title":"Co-Fusion4D: Spatio-temporal Collaborative Fusion for Robust 3D Object Detection","version":2},"reference_index":24,"source":"pdf_text","source_observed_at":"2026-06-30T18:15:04.759721Z"},"links":{"citing_paper":"/paper/2605.20301"},"observation_digest":"sha256:fb343931ff4a553a40d10a0738389c1d954a275d87203bb385d483faa0ecc8da","observation_id":"1f58114e-186c-4ec7-b0f0-520012b31c87","resolution":{"observed_at":"2026-07-08T05:44:36.317128Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-11T06:34:44.6726+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-11T06:34:44.6726+00:00","source":"crossref"},{"observed_at":"2026-08-11T06:34:36.301508+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-07-08T05:44:36.302769Z","title":"Bevfusion: Multi-task multi-sensor fusion with unified bird’s-eye view representation","venue":null,"work_id":"6e1bb9ee-321e-4e0e-94fe-2b89a138c47d","year":2023},"citing_paper":{"arxiv_id":"2605.20301","last_updated":"2026-06-01T02:49:14Z","snapshot_observed_at":"2026-08-04T12:53:21.630996Z","submitted_at":"2026-05-19T12:36:09Z","title":"Co-Fusion4D: Spatio-temporal Collaborative Fusion for Robust 3D Object Detection","version":2},"reference_index":25,"source":"pdf_text","source_observed_at":"2026-06-30T18:15:04.759721Z"},"links":{"citing_paper":"/paper/2605.20301"},"observation_digest":"sha256:a11d889dcaddd2e5ddbebcbdd75de36fce16fc910e5dbbad8c3349e0a643491d","observation_id":"088d19bb-c6ee-4029-9e22-e458a39ed874","resolution":{"observed_at":"2026-07-08T05:44:36.304325Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-11T06:34:44.6726+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-11T06:34:44.6726+00:00","source":"crossref"},{"observed_at":"2026-08-11T06:34:36.301508+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-07-08T05:44:36.283623Z","title":"Multi-sensor fusion technology for 3d object detection in autonomous driving: A review","venue":null,"work_id":"8c079a02-6c70-4d0e-be7c-bc79ffe27447","year":2023},"citing_paper":{"arxiv_id":"2605.20301","last_updated":"2026-06-01T02:49:14Z","snapshot_observed_at":"2026-08-04T12:53:21.630996Z","submitted_at":"2026-05-19T12:36:09Z","title":"Co-Fusion4D: Spatio-temporal Collaborative Fusion for Robust 3D Object Detection","version":2},"reference_index":26,"source":"pdf_text","source_observed_at":"2026-06-30T18:15:04.759721Z"},"links":{"citing_paper":"/paper/2605.20301"},"observation_digest":"sha256:9c9e6719de3d480827df9cdf658cbba3ad1f77ea0199cc6c23cfb3ddbb250662","observation_id":"750125c6-a21b-4890-880b-f44dd59e11b5","resolution":{"observed_at":"2026-07-08T05:44:36.284810Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-11T06:34:44.6726+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-11T06:34:44.6726+00:00","source":"crossref"},{"observed_at":"2026-08-11T06:34:36.301508+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-07-08T05:44:36.329388Z","title":"Transformer-based sensor fusion for autonomous driving: A survey","venue":null,"work_id":"a36832b2-244a-4d06-a260-062836a9c70a","year":2023},"citing_paper":{"arxiv_id":"2605.20301","last_updated":"2026-06-01T02:49:14Z","snapshot_observed_at":"2026-08-04T12:53:21.630996Z","submitted_at":"2026-05-19T12:36:09Z","title":"Co-Fusion4D: Spatio-temporal Collaborative Fusion for Robust 3D Object Detection","version":2},"reference_index":27,"source":"pdf_text","source_observed_at":"2026-06-30T18:15:04.759721Z"},"links":{"citing_paper":"/paper/2605.20301"},"observation_digest":"sha256:27dbb5d8f75aadd7cb23f9910c49b240a139210a4378b746c8ad863bd7d01f01","observation_id":"e2fe6d87-ea44-4304-901a-c36f95d1231f","resolution":{"observed_at":"2026-07-08T05:44:36.330604Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-11T06:34:44.6726+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-11T06:34:44.6726+00:00","source":"crossref"},{"observed_at":"2026-08-11T06:34:36.301508+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-07-08T05:44:36.299188Z","title":"Bevformer: Learning bird’s- eye-view representation from multi-camera images via spatiotemporal transformers","venue":null,"work_id":"cbda6f43-38d7-4015-bf50-a90c0c4927ab","year":2022},"citing_paper":{"arxiv_id":"2605.20301","last_updated":"2026-06-01T02:49:14Z","snapshot_observed_at":"2026-08-04T12:53:21.630996Z","submitted_at":"2026-05-19T12:36:09Z","title":"Co-Fusion4D: Spatio-temporal Collaborative Fusion for Robust 3D Object Detection","version":2},"reference_index":28,"source":"pdf_text","source_observed_at":"2026-06-30T18:15:04.759721Z"},"links":{"citing_paper":"/paper/2605.20301"},"observation_digest":"sha256:c1237d26b67e6130c3cfa198ee75d9c600c07b2fc321951a77234b45daf2b0dd","observation_id":"9ef12724-d5b6-47de-8079-20e957996e07","resolution":{"observed_at":"2026-07-08T05:44:36.300631Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-11T06:34:44.6726+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-11T06:34:44.6726+00:00","source":"crossref"},{"observed_at":"2026-08-11T06:34:36.301508+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-07-08T05:44:36.344744Z","title":"Exploring object-centric temporal modeling for efficient multi-view 3d object detection","venue":null,"work_id":"6df0db35-b035-4fc7-9886-806b398b3a53","year":2023},"citing_paper":{"arxiv_id":"2605.20301","last_updated":"2026-06-01T02:49:14Z","snapshot_observed_at":"2026-08-04T12:53:21.630996Z","submitted_at":"2026-05-19T12:36:09Z","title":"Co-Fusion4D: Spatio-temporal Collaborative Fusion for Robust 3D Object Detection","version":2},"reference_index":29,"source":"pdf_text","source_observed_at":"2026-06-30T18:15:04.759721Z"},"links":{"citing_paper":"/paper/2605.20301"},"observation_digest":"sha256:0031e695b163b0315be9a53f903ca1bf0c4f3244956350accf105b145ca73eda","observation_id":"4d0cea70-84e6-4e8b-9922-b5f62b69246c","resolution":{"observed_at":"2026-07-08T05:44:36.346206Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-11T06:34:44.6726+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-11T06:34:44.6726+00:00","source":"crossref"},{"observed_at":"2026-08-11T06:34:36.301508+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-07-08T05:44:36.313964Z","title":"Focalfusion: An object-centric temporal fusion framework for multi-modal 3d detection","venue":null,"work_id":"9797960b-e5d3-4a89-8139-30c302512403","year":2025},"citing_paper":{"arxiv_id":"2605.20301","last_updated":"2026-06-01T02:49:14Z","snapshot_observed_at":"2026-08-04T12:53:21.630996Z","submitted_at":"2026-05-19T12:36:09Z","title":"Co-Fusion4D: Spatio-temporal Collaborative Fusion for Robust 3D Object Detection","version":2},"reference_index":30,"source":"pdf_text","source_observed_at":"2026-06-30T18:15:04.759721Z"},"links":{"citing_paper":"/paper/2605.20301"},"observation_digest":"sha256:2a6448772058bfc9a0a464ec2737c92b62d0953757a3afe450a53d14b98efce0","observation_id":"80879d6a-b94f-4aa5-ab7b-9117fff6f4a9","resolution":{"observed_at":"2026-07-08T05:44:36.315241Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-11T06:34:44.6726+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-11T06:34:44.6726+00:00","source":"crossref"},{"observed_at":"2026-08-11T06:34:36.301508+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-07-08T05:44:36.297140Z","title":"nuscenes: A multimodal dataset for autonomous driving","venue":null,"work_id":"3a95b8fb-7e29-4950-baa6-8a4c81b6acca","year":2020},"citing_paper":{"arxiv_id":"2605.20301","last_updated":"2026-06-01T02:49:14Z","snapshot_observed_at":"2026-08-04T12:53:21.630996Z","submitted_at":"2026-05-19T12:36:09Z","title":"Co-Fusion4D: Spatio-temporal Collaborative Fusion for Robust 3D Object Detection","version":2},"reference_index":31,"source":"pdf_text","source_observed_at":"2026-06-30T18:15:04.759721Z"},"links":{"citing_paper":"/paper/2605.20301"},"observation_digest":"sha256:3b67e019b4118d734581c2a015164326d89b2b690d6a1ef520bf7ad0c315b1c5","observation_id":"6f02d706-4636-436e-82a3-6683a713beee","resolution":{"observed_at":"2026-07-08T05:44:36.298631Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-11T06:34:44.6726+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-11T06:34:44.6726+00:00","source":"crossref"},{"observed_at":"2026-08-11T06:34:36.301508+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-07-10T03:56:45.106757Z","title":"Automatic differentiation in pytorch","venue":null,"work_id":"5a5818ac-37e1-444f-8802-6256d3fb52b9","year":2017},"citing_paper":{"arxiv_id":"2605.20301","last_updated":"2026-06-01T02:49:14Z","snapshot_observed_at":"2026-08-04T12:53:21.630996Z","submitted_at":"2026-05-19T12:36:09Z","title":"Co-Fusion4D: Spatio-temporal Collaborative Fusion for Robust 3D Object Detection","version":2},"reference_index":32,"source":"pdf_text","source_observed_at":"2026-06-30T18:15:04.759721Z"},"links":{"citing_paper":"/paper/2605.20301"},"observation_digest":"sha256:4d928ea4af6fe718303f984bd9abd029cdf109b70bfc7666a1611a62a56c3b76","observation_id":"de662c1d-bad1-462b-a7a6-bdeeab0e5a0b","resolution":{"observed_at":"2026-07-08T05:44:36.302205Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-11T06:34:44.6726+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-11T06:34:44.6726+00:00","source":"crossref"},{"observed_at":"2026-08-11T06:34:36.301508+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-07-08T05:44:36.279953Z","title":"Mmdetection3d: Openmmlab next- generation platform for general 3d object detection, 2020","venue":null,"work_id":"cd43cc1a-d481-4539-91b1-d5f1ae6c1c5a","year":2020},"citing_paper":{"arxiv_id":"2605.20301","last_updated":"2026-06-01T02:49:14Z","snapshot_observed_at":"2026-08-04T12:53:21.630996Z","submitted_at":"2026-05-19T12:36:09Z","title":"Co-Fusion4D: Spatio-temporal Collaborative Fusion for Robust 3D Object Detection","version":2},"reference_index":33,"source":"pdf_text","source_observed_at":"2026-06-30T18:15:04.759721Z"},"links":{"citing_paper":"/paper/2605.20301"},"observation_digest":"sha256:b86b91134b2f2b4716d3289ba174509d3ea4c13591355e70a13607fa4ee432e8","observation_id":"b63c98a6-8dca-4e57-b6db-c584ca4bca64","resolution":{"observed_at":"2026-07-08T05:44:36.281204Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-11T06:34:44.6726+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-11T06:34:44.6726+00:00","source":"crossref"},{"observed_at":"2026-08-11T06:34:36.301508+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-07-08T05:44:36.285396Z","title":"Lidarmultinet: Towards a unified multi-task network for lidar perception","venue":null,"work_id":"5ded55bc-398d-470a-882e-30142b91bb9c","year":2023},"citing_paper":{"arxiv_id":"2605.20301","last_updated":"2026-06-01T02:49:14Z","snapshot_observed_at":"2026-08-04T12:53:21.630996Z","submitted_at":"2026-05-19T12:36:09Z","title":"Co-Fusion4D: Spatio-temporal Collaborative Fusion for Robust 3D Object Detection","version":2},"reference_index":34,"source":"pdf_text","source_observed_at":"2026-06-30T18:15:04.759721Z"},"links":{"citing_paper":"/paper/2605.20301"},"observation_digest":"sha256:085115cd6e64d57e3637dab48a315198ce8892aeca71f1c71ad7843f7a85cbc2","observation_id":"536e1901-a090-4264-9814-305f7ab06fcd","resolution":{"observed_at":"2026-07-08T05:44:36.286699Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-11T06:34:44.6726+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-11T06:34:44.6726+00:00","source":"crossref"},{"observed_at":"2026-08-11T06:34:36.301508+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-07-08T05:44:36.290993Z","title":"Focalformer3d: focusing on hard instance for 3d object detection","venue":null,"work_id":"8a415f49-4dc2-47fc-961f-d3da3d1ce03b","year":2023},"citing_paper":{"arxiv_id":"2605.20301","last_updated":"2026-06-01T02:49:14Z","snapshot_observed_at":"2026-08-04T12:53:21.630996Z","submitted_at":"2026-05-19T12:36:09Z","title":"Co-Fusion4D: Spatio-temporal Collaborative Fusion for Robust 3D Object Detection","version":2},"reference_index":35,"source":"pdf_text","source_observed_at":"2026-06-30T18:15:04.759721Z"},"links":{"citing_paper":"/paper/2605.20301"},"observation_digest":"sha256:3d9d67d12c06f1e1f8d95653056d80fcbb91d5ad6d0b4290081d53af7e72d400","observation_id":"676243d1-95fa-44cf-9c88-bcbd8f62b146","resolution":{"observed_at":"2026-07-08T05:44:36.292302Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-11T06:34:44.6726+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-11T06:34:44.6726+00:00","source":"crossref"},{"observed_at":"2026-08-11T06:34:36.301508+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-07-08T05:44:36.276271Z","title":"Ob- jectfusion: Multi-modal 3d object detection with object-centric fusion","venue":null,"work_id":"d8e212a7-5359-4509-a394-ae805edbd28a","year":2023},"citing_paper":{"arxiv_id":"2605.20301","last_updated":"2026-06-01T02:49:14Z","snapshot_observed_at":"2026-08-04T12:53:21.630996Z","submitted_at":"2026-05-19T12:36:09Z","title":"Co-Fusion4D: Spatio-temporal Collaborative Fusion for Robust 3D Object Detection","version":2},"reference_index":36,"source":"pdf_text","source_observed_at":"2026-06-30T18:15:04.759721Z"},"links":{"citing_paper":"/paper/2605.20301"},"observation_digest":"sha256:2b5236f6574d23ffc969b922139249a183f214f47e042a6206bb26cc4f7da4f4","observation_id":"b313e6c4-1503-40ea-9d06-60191776aefa","resolution":{"observed_at":"2026-07-08T05:44:36.277498Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-11T06:34:44.6726+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-11T06:34:44.6726+00:00","source":"crossref"},{"observed_at":"2026-08-11T06:34:36.301508+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-07-08T05:44:36.288995Z","title":"Msmdfusion: Fusing lidar and camera at multiple scales with multi-depth seeds for 3d object detection","venue":null,"work_id":"89f5abf1-151c-4d16-9536-5c2f650cfed7","year":2023},"citing_paper":{"arxiv_id":"2605.20301","last_updated":"2026-06-01T02:49:14Z","snapshot_observed_at":"2026-08-04T12:53:21.630996Z","submitted_at":"2026-05-19T12:36:09Z","title":"Co-Fusion4D: Spatio-temporal Collaborative Fusion for Robust 3D Object Detection","version":2},"reference_index":37,"source":"pdf_text","source_observed_at":"2026-06-30T18:15:04.759721Z"},"links":{"citing_paper":"/paper/2605.20301"},"observation_digest":"sha256:112588de54fce1365ee679b59bd29705b9a1ba01ee4d301102785e31f45bb457","observation_id":"fd3c244e-5feb-4ab4-b00d-5c1d6ce0bba4","resolution":{"observed_at":"2026-07-08T05:44:36.290298Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-11T06:34:44.6726+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-11T06:34:44.6726+00:00","source":"crossref"},{"observed_at":"2026-08-11T06:34:36.301508+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-07-08T05:44:36.317775Z","title":"Sparsefusion: Fusing multi-modal sparse representations for multi- sensor 3d object detection","venue":null,"work_id":"96b71252-7151-47fd-a629-9d59549b3f61","year":2023},"citing_paper":{"arxiv_id":"2605.20301","last_updated":"2026-06-01T02:49:14Z","snapshot_observed_at":"2026-08-04T12:53:21.630996Z","submitted_at":"2026-05-19T12:36:09Z","title":"Co-Fusion4D: Spatio-temporal Collaborative Fusion for Robust 3D Object Detection","version":2},"reference_index":38,"source":"pdf_text","source_observed_at":"2026-06-30T18:15:04.759721Z"},"links":{"citing_paper":"/paper/2605.20301"},"observation_digest":"sha256:81e81a5c65798c79160f7580d1861b1eb48b8304ee23ca08f9fcf3411f0b1c02","observation_id":"3645fbbf-e75b-4ea1-b63b-bd24c01d1577","resolution":{"observed_at":"2026-07-08T05:44:36.319128Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-11T06:34:44.6726+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-11T06:34:44.6726+00:00","source":"crossref"},{"observed_at":"2026-08-11T06:34:36.301508+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-07-08T05:44:36.287252Z","title":"Is-fusion: Instance-scene collaborative fusion for multimodal 3d object detection","venue":null,"work_id":"6f701dc2-f35f-4754-a3b4-4d331db37480","year":2024},"citing_paper":{"arxiv_id":"2605.20301","last_updated":"2026-06-01T02:49:14Z","snapshot_observed_at":"2026-08-04T12:53:21.630996Z","submitted_at":"2026-05-19T12:36:09Z","title":"Co-Fusion4D: Spatio-temporal Collaborative Fusion for Robust 3D Object Detection","version":2},"reference_index":39,"source":"pdf_text","source_observed_at":"2026-06-30T18:15:04.759721Z"},"links":{"citing_paper":"/paper/2605.20301"},"observation_digest":"sha256:f0948b52317a0c8c66dd0303474c1102cd130b68e9c85c9dbfad029647b80a4e","observation_id":"4e63c24d-766e-42db-bc7c-4d0c776921e4","resolution":{"observed_at":"2026-07-08T05:44:36.288449Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-11T06:34:44.6726+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-11T06:34:44.6726+00:00","source":"crossref"},{"observed_at":"2026-08-11T06:34:36.301508+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-07-08T05:44:36.281701Z","title":"Graphbev: Towards robust bev feature alignment for multi-modal 3d object detection","venue":null,"work_id":"cf7050e7-266c-4632-b2f1-77d95d85f625","year":2025},"citing_paper":{"arxiv_id":"2605.20301","last_updated":"2026-06-01T02:49:14Z","snapshot_observed_at":"2026-08-04T12:53:21.630996Z","submitted_at":"2026-05-19T12:36:09Z","title":"Co-Fusion4D: Spatio-temporal Collaborative Fusion for Robust 3D Object Detection","version":2},"reference_index":40,"source":"pdf_text","source_observed_at":"2026-06-30T18:15:04.759721Z"},"links":{"citing_paper":"/paper/2605.20301"},"observation_digest":"sha256:e06a5475bfcb3664a23cb9eb6a125fe04a80d0bd796f0d29c89f738009ed7ece","observation_id":"3141e316-1372-409e-83b9-72a8d4e68a09","resolution":{"observed_at":"2026-07-08T05:44:36.282848Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-11T06:34:44.6726+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-11T06:34:44.6726+00:00","source":"crossref"},{"observed_at":"2026-08-11T06:34:36.301508+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-07-08T05:44:36.307048Z","title":"A method of time alignment in bev features for multimodal fusion object detection of intelligent vehicles.IEEE Transactions on Intelligent Transportation Systems, 2025","venue":null,"work_id":"274f8349-8ee2-4d61-82ea-ed8d5fc3f549","year":2025},"citing_paper":{"arxiv_id":"2605.20301","last_updated":"2026-06-01T02:49:14Z","snapshot_observed_at":"2026-08-04T12:53:21.630996Z","submitted_at":"2026-05-19T12:36:09Z","title":"Co-Fusion4D: Spatio-temporal Collaborative Fusion for Robust 3D Object Detection","version":2},"reference_index":41,"source":"pdf_text","source_observed_at":"2026-06-30T18:15:04.759721Z"},"links":{"citing_paper":"/paper/2605.20301"},"observation_digest":"sha256:eb0a4eb9d38f4558dae52e854993b3dc2e658181071f80b2698f14a65db98ecd","observation_id":"6a7ef8a6-2be6-498c-88c2-8a1abcdbb9f2","resolution":{"observed_at":"2026-07-08T05:44:36.308510Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-11T06:34:44.6726+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-11T06:34:44.6726+00:00","source":"crossref"},{"observed_at":"2026-08-11T06:34:36.301508+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-07-08T05:44:36.311744Z","title":"Lift: Learning 4d lidar image fusion transformer for 3d object detection","venue":null,"work_id":"33f890b6-60f5-4c1b-922a-2aa0331d449d","year":2022},"citing_paper":{"arxiv_id":"2605.20301","last_updated":"2026-06-01T02:49:14Z","snapshot_observed_at":"2026-08-04T12:53:21.630996Z","submitted_at":"2026-05-19T12:36:09Z","title":"Co-Fusion4D: Spatio-temporal Collaborative Fusion for Robust 3D Object Detection","version":2},"reference_index":42,"source":"pdf_text","source_observed_at":"2026-06-30T18:15:04.759721Z"},"links":{"citing_paper":"/paper/2605.20301"},"observation_digest":"sha256:5b9870e4a17e6715af04ccb7c7785e7cbaf3467e38717b7843f9e4154e39573c","observation_id":"a8055fb8-551b-4f0f-86c4-9c7d8613dc20","resolution":{"observed_at":"2026-07-08T05:44:36.313339Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-11T06:34:44.6726+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-11T06:34:44.6726+00:00","source":"crossref"},{"observed_at":"2026-08-11T06:34:36.301508+00:00","source":"retraction_watch"}],"state":"measured"}}],"paper":{"arxiv_id":"2605.20301","last_updated":"2026-06-01T02:49:14Z","latest_version":2,"primary_category":"cs.CV","snapshot_observed_at":"2026-08-04T12:53:21.630996Z","submitted_at":"2026-05-19T12:36:09Z","title":"Co-Fusion4D: Spatio-temporal Collaborative Fusion for Robust 3D Object Detection"},"reference_resolution":{"displayed":42,"state_counts":{"malformed_identifier":0,"metadata_mismatch":0,"parse_uncertain":0,"unresolved":0,"verified_exact":2,"verified_fuzzy":40},"total_outbound_references":42},"refusal":"A citation records a reference. It does not transfer a finding from one paper to another.","schema":"pith.paper-citation-record.v1","standing_sources":[{"observed_at":"2026-08-11T06:34:44.6726+00:00","source":"crossref"},{"observed_at":"2026-08-11T06:34:36.301508+00:00","source":"retraction_watch"}],"thesis":"As of 11 August 2026, this Paper Citation Record lists 42 of 42 outbound references and 0 inbound Pith citation observations for arXiv:2605.20301."}