{"as_of":"2026-08-12T17:03:00Z","caps":{"database_statements":6,"inbound":100,"outbound":100},"context_digest":"sha256:ddeaf0fbd04acb253993c7231532fab69c08590631494463fa2904f8674cc5cf","coverage":[{"denominator":47,"lane":"reference_resolution","note":"Typed states for the displayed outbound observations.","records_observed":47,"source":"paper_references, paper_reference_links","source_observed_at":"2026-08-11T16:28:36.781237Z","state":"measured"},{"denominator":47,"lane":"standing_notices","note":"One-hop event checks from named stored sources.","records_observed":47,"source":"scholarly_work_events, retraction_status_cache","source_observed_at":"2026-08-12T06:34:41.77262+00:00","state":"measured"},{"denominator":0,"lane":"inbound_itemization","note":"Pith citing papers itemized under the disclosed page cap.","records_observed":0,"source":"paper_references, paper_reference_links","source_observed_at":null,"state":"measured"},{"denominator":1,"lane":"external_citation_measurements","note":"A source-named dated measurement, never combined with another source.","records_observed":0,"source":"cited_works","source_observed_at":null,"state":"measured"}],"external_citation_measurements":[],"inbound":[],"links":{"evidence":"/evidence","html":"/paper/2412.10033/citation-record","integrity":"/paper/2412.10033/integrity","json":"/paper/2412.10033/citation-record.json","paper":"/paper/2412.10033"},"outbound":[{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-11T16:28:38.193574Z","title":"Monocular 3d object detection leveraging accurate proposals and shape reconstruction","venue":null,"work_id":"d89ce928-5872-4f42-b309-7767a69755ee","year":2019},"citing_paper":{"arxiv_id":"2412.10033","last_updated":"2024-12-13T10:48:38Z","snapshot_observed_at":"2026-08-12T09:04:07.560795Z","submitted_at":"2024-12-13T10:48:38Z","title":"Timealign: A multi-modal object detection method for time misalignment fusing in autonomous driving","version":1},"reference_index":1,"source":"pdf_text","source_observed_at":"2026-08-11T16:28:36.219030Z"},"links":{"citing_paper":"/paper/2412.10033"},"observation_digest":"sha256:7860fbb2417dc1bd5ead65c5c48e0590ea6f88512c1fdf739c88078c5193ad7f","observation_id":"a6d6e94e-7d90-4154-90e2-8d91f8712c55","resolution":{"observed_at":"2026-08-11T16:28:38.198814Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-12T06:34:41.77262+00:00","source":"crossref"},{"observed_at":"2026-08-12T06:34:36.333875+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-11T16:28:38.180724Z","title":"Autoshape: Real-time shape-aware monocular 3d object detection","venue":null,"work_id":"5d72b485-f5c6-4d30-ba02-c35400081ce2","year":2021},"citing_paper":{"arxiv_id":"2412.10033","last_updated":"2024-12-13T10:48:38Z","snapshot_observed_at":"2026-08-12T09:04:07.560795Z","submitted_at":"2024-12-13T10:48:38Z","title":"Timealign: A multi-modal object detection method for time misalignment fusing in autonomous driving","version":1},"reference_index":2,"source":"pdf_text","source_observed_at":"2026-08-11T16:28:36.254201Z"},"links":{"citing_paper":"/paper/2412.10033"},"observation_digest":"sha256:34e798c95e237e96d15831848c0d93e511ef7edac203da6fbb16e82067334e2d","observation_id":"c66dce80-1c06-458e-8dd7-44e2ad700e5c","resolution":{"observed_at":"2026-08-11T16:28:38.184980Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-12T06:34:41.77262+00:00","source":"crossref"},{"observed_at":"2026-08-12T06:34:36.333875+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-11T16:28:38.167475Z","title":"Pointrcnn: 3d object proposal generation and detection from point cloud","venue":null,"work_id":"2f1cac34-9423-4525-a3e4-6a0dfb066b7b","year":2019},"citing_paper":{"arxiv_id":"2412.10033","last_updated":"2024-12-13T10:48:38Z","snapshot_observed_at":"2026-08-12T09:04:07.560795Z","submitted_at":"2024-12-13T10:48:38Z","title":"Timealign: A multi-modal object detection method for time misalignment fusing in autonomous driving","version":1},"reference_index":3,"source":"pdf_text","source_observed_at":"2026-08-11T16:28:36.270993Z"},"links":{"citing_paper":"/paper/2412.10033"},"observation_digest":"sha256:883237f5dcceeab062ba4553880c3682e346c2f78a606f1566ac81f772f2a885","observation_id":"7ab7b4ba-1d30-48a4-9bb9-d256a8e309f5","resolution":{"observed_at":"2026-08-11T16:28:38.172200Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-12T06:34:41.77262+00:00","source":"crossref"},{"observed_at":"2026-08-12T06:34:36.333875+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":null,"snapshot_observed_at":"2026-08-11T16:28:36.304862Z","title":"Pointpillars: Fast encoders for object detection from point clouds","venue":null,"work_id":null,"year":2019},"citing_paper":{"arxiv_id":"2412.10033","last_updated":"2024-12-13T10:48:38Z","snapshot_observed_at":"2026-08-12T09:04:07.560795Z","submitted_at":"2024-12-13T10:48:38Z","title":"Timealign: A multi-modal object detection method for time misalignment fusing in autonomous driving","version":1},"reference_index":4,"source":"pdf_text","source_observed_at":"2026-08-11T16:28:36.304862Z"},"links":{"citing_paper":"/paper/2412.10033"},"observation_digest":"sha256:0ea81bf8b7a011ba7d81a5f916affaefeefff69ff8e6985ecdf5c2424b60d95f","observation_id":"5c6d05af-bb2f-4593-a025-0e03b1100d17","resolution":{"observed_at":"2026-08-11T16:28:36.304862Z","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":"2026-08-11T16:28:36.353178Z","title":"Center-based 3d object detection and tracking","venue":null,"work_id":null,"year":2021},"citing_paper":{"arxiv_id":"2412.10033","last_updated":"2024-12-13T10:48:38Z","snapshot_observed_at":"2026-08-12T09:04:07.560795Z","submitted_at":"2024-12-13T10:48:38Z","title":"Timealign: A multi-modal object detection method for time misalignment fusing in autonomous driving","version":1},"reference_index":5,"source":"pdf_text","source_observed_at":"2026-08-11T16:28:36.353178Z"},"links":{"citing_paper":"/paper/2412.10033"},"observation_digest":"sha256:b09f66941cbf1c9b3cfb8a11aadb7c390a6b873b863db52cd0e666c92f931c37","observation_id":"e87de81e-a4eb-40a7-b884-bdd6d0a9eb95","resolution":{"observed_at":"2026-08-11T16:28:36.353178Z","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":"2026-08-11T16:28:38.109206Z","title":"Pointfusion: Deep sensor fusion for 3d bounding box estimation","venue":null,"work_id":"b7e1f638-b888-4d16-9270-ca6a656fc61a","year":2018},"citing_paper":{"arxiv_id":"2412.10033","last_updated":"2024-12-13T10:48:38Z","snapshot_observed_at":"2026-08-12T09:04:07.560795Z","submitted_at":"2024-12-13T10:48:38Z","title":"Timealign: A multi-modal object detection method for time misalignment fusing in autonomous driving","version":1},"reference_index":6,"source":"pdf_text","source_observed_at":"2026-08-11T16:28:36.386124Z"},"links":{"citing_paper":"/paper/2412.10033"},"observation_digest":"sha256:90e3b8ad3d47048684c8f06c1394e5c8da7a319807dab2288fc76ed665c194ae","observation_id":"e46ec249-3644-4a9b-a034-22b5c8974830","resolution":{"observed_at":"2026-08-11T16:28:38.141612Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-12T06:34:41.77262+00:00","source":"crossref"},{"observed_at":"2026-08-12T06:34:36.333875+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":null,"snapshot_observed_at":"2026-08-11T16:28:36.398238Z","title":"Pointpainting: Sequential fusion for 3d object detection","venue":null,"work_id":null,"year":2020},"citing_paper":{"arxiv_id":"2412.10033","last_updated":"2024-12-13T10:48:38Z","snapshot_observed_at":"2026-08-12T09:04:07.560795Z","submitted_at":"2024-12-13T10:48:38Z","title":"Timealign: A multi-modal object detection method for time misalignment fusing in autonomous driving","version":1},"reference_index":7,"source":"pdf_text","source_observed_at":"2026-08-11T16:28:36.398238Z"},"links":{"citing_paper":"/paper/2412.10033"},"observation_digest":"sha256:5cb62b8cd2bb2ba6d17146a0f2a5479c1b9fed24ecdff906b4fb059ca2a7607d","observation_id":"3f85dfd6-4e61-412c-8d3a-115a4ddd2746","resolution":{"observed_at":"2026-08-11T16:28:36.398238Z","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":"2026-08-11T16:28:38.030018Z","title":"Pointaugmenting: Cross-modal augmentation for 3d object detection","venue":null,"work_id":"e38db4d0-5da3-49c9-a409-4431cfd4d0da","year":2021},"citing_paper":{"arxiv_id":"2412.10033","last_updated":"2024-12-13T10:48:38Z","snapshot_observed_at":"2026-08-12T09:04:07.560795Z","submitted_at":"2024-12-13T10:48:38Z","title":"Timealign: A multi-modal object detection method for time misalignment fusing in autonomous driving","version":1},"reference_index":8,"source":"pdf_text","source_observed_at":"2026-08-11T16:28:36.403267Z"},"links":{"citing_paper":"/paper/2412.10033"},"observation_digest":"sha256:59e2aea6dc9864de6e1b446a2460f15f88220397e962d0f21ad37719b9dbde6a","observation_id":"935bb0a9-a61c-4344-a34f-28cf87bf02c0","resolution":{"observed_at":"2026-08-11T16:28:38.067433Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-12T06:34:41.77262+00:00","source":"crossref"},{"observed_at":"2026-08-12T06:34:36.333875+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":null,"snapshot_observed_at":"2026-08-11T16:28:36.407706Z","title":"Bevfusion: Multi-task multi-sensor fusion with unified bird’s-eye view representation","venue":null,"work_id":null,"year":2023},"citing_paper":{"arxiv_id":"2412.10033","last_updated":"2024-12-13T10:48:38Z","snapshot_observed_at":"2026-08-12T09:04:07.560795Z","submitted_at":"2024-12-13T10:48:38Z","title":"Timealign: A multi-modal object detection method for time misalignment fusing in autonomous driving","version":1},"reference_index":9,"source":"pdf_text","source_observed_at":"2026-08-11T16:28:36.407706Z"},"links":{"citing_paper":"/paper/2412.10033"},"observation_digest":"sha256:d52de20823565f6d6c13927ef383e74de7d7d0f7a23c27fee536d02b8242201d","observation_id":"534b6fb7-71ed-4616-b858-ccf4696ff581","resolution":{"observed_at":"2026-08-11T16:28:36.407706Z","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":"2026-08-11T16:28:37.954715Z","title":"Epnet: Enhancing point features with image semantics for 3d object detection","venue":null,"work_id":"c71782df-3cea-4b41-9f32-e598ae45a906","year":2020},"citing_paper":{"arxiv_id":"2412.10033","last_updated":"2024-12-13T10:48:38Z","snapshot_observed_at":"2026-08-12T09:04:07.560795Z","submitted_at":"2024-12-13T10:48:38Z","title":"Timealign: A multi-modal object detection method for time misalignment fusing in autonomous driving","version":1},"reference_index":10,"source":"pdf_text","source_observed_at":"2026-08-11T16:28:36.412248Z"},"links":{"citing_paper":"/paper/2412.10033"},"observation_digest":"sha256:1c55bbad835ea889f5278f33e9e171e3149291598f5012831bc6d4507f054911","observation_id":"ca898183-fdda-4bfc-af35-32ca340069f5","resolution":{"observed_at":"2026-08-11T16:28:37.959350Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-12T06:34:41.77262+00:00","source":"crossref"},{"observed_at":"2026-08-12T06:34:36.333875+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-11T16:28:37.940451Z","title":"Epnet++: Cascade bi-directional fusion for multi-modal 3d object detection","venue":null,"work_id":"0c92f17a-2642-4dd3-8848-1a24435be01a","year":2022},"citing_paper":{"arxiv_id":"2412.10033","last_updated":"2024-12-13T10:48:38Z","snapshot_observed_at":"2026-08-12T09:04:07.560795Z","submitted_at":"2024-12-13T10:48:38Z","title":"Timealign: A multi-modal object detection method for time misalignment fusing in autonomous driving","version":1},"reference_index":11,"source":"pdf_text","source_observed_at":"2026-08-11T16:28:36.417025Z"},"links":{"citing_paper":"/paper/2412.10033"},"observation_digest":"sha256:630039683cc73dc3ba48d839b926d62cf2a122cfa00496ccd777b67a3b9e110f","observation_id":"91f30c72-5d77-4f9f-b8f3-49e8dad30d30","resolution":{"observed_at":"2026-08-11T16:28:37.945664Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-12T06:34:41.77262+00:00","source":"crossref"},{"observed_at":"2026-08-12T06:34:36.333875+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-11T16:28:37.851295Z","title":"Deepfusion: Lidar-camera deep fusion for multi-modal 3d object detection","venue":null,"work_id":"e86eb900-f3f9-4686-8849-a89db1806693","year":2022},"citing_paper":{"arxiv_id":"2412.10033","last_updated":"2024-12-13T10:48:38Z","snapshot_observed_at":"2026-08-12T09:04:07.560795Z","submitted_at":"2024-12-13T10:48:38Z","title":"Timealign: A multi-modal object detection method for time misalignment fusing in autonomous driving","version":1},"reference_index":12,"source":"pdf_text","source_observed_at":"2026-08-11T16:28:36.421206Z"},"links":{"citing_paper":"/paper/2412.10033"},"observation_digest":"sha256:ea576143635f7347fa0d6f46061e0508b325f457c353474ceb4ad3b28969fc05","observation_id":"41686913-e54e-4b90-83da-c1a932a35294","resolution":{"observed_at":"2026-08-11T16:28:37.871879Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-12T06:34:41.77262+00:00","source":"crossref"},{"observed_at":"2026-08-12T06:34:36.333875+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-11T16:28:37.800043Z","title":"Multi-modal 3d object detection in autonomous driving: A survey and taxonomy","venue":null,"work_id":"1ce57404-2139-404a-8fbc-35d08acae269","year":2023},"citing_paper":{"arxiv_id":"2412.10033","last_updated":"2024-12-13T10:48:38Z","snapshot_observed_at":"2026-08-12T09:04:07.560795Z","submitted_at":"2024-12-13T10:48:38Z","title":"Timealign: A multi-modal object detection method for time misalignment fusing in autonomous driving","version":1},"reference_index":13,"source":"pdf_text","source_observed_at":"2026-08-11T16:28:36.425807Z"},"links":{"citing_paper":"/paper/2412.10033"},"observation_digest":"sha256:c4502707241409e751f104651dffd74d42c2b19671247c8a13c653d3697964e6","observation_id":"5d591978-09c1-4ce8-9fd7-d4e7f9551911","resolution":{"observed_at":"2026-08-11T16:28:37.805947Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-12T06:34:41.77262+00:00","source":"crossref"},{"observed_at":"2026-08-12T06:34:36.333875+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"2306.02656","last_updated":"2023-06-05T07:42:53Z","snapshot_observed_at":"2026-07-06T15:37:58.467574Z","submitted_at":"2023-06-05T07:42:53Z","title":"Calib-Anything: Zero-training LiDAR-Camera Extrinsic Calibration Method Using Segment Anything","version":1},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2306.02656","snapshot_observed_at":"2026-08-11T16:28:36.430175Z","title":"Calib-anything: Zero-training lidar-camera extrinsic calibration method using segment anything","venue":null,"work_id":null,"year":2023},"citing_paper":{"arxiv_id":"2412.10033","last_updated":"2024-12-13T10:48:38Z","snapshot_observed_at":"2026-08-12T09:04:07.560795Z","submitted_at":"2024-12-13T10:48:38Z","title":"Timealign: A multi-modal object detection method for time misalignment fusing in autonomous driving","version":1},"reference_index":14,"source":"pdf_text","source_observed_at":"2026-08-11T16:28:36.430175Z"},"links":{"cited_paper":"/paper/2306.02656","citing_paper":"/paper/2412.10033"},"observation_digest":"sha256:088c8f05f0ae740860b6dac1014dd04d792f253cdd3ab922682c6ed5a684b4ca","observation_id":"7db2330b-81b9-4e2a-bafe-730a3adbc926","resolution":{"observed_at":"2026-08-11T16:28:36.430175Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2311.15241","last_updated":"2024-03-17T05:30:40Z","snapshot_observed_at":"2026-07-06T16:52:27.457437Z","submitted_at":"2023-11-26T08:59:30Z","title":"CalibFormer: A Transformer-based Automatic LiDAR-Camera Calibration Network","version":2},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2311.15241","snapshot_observed_at":"2026-08-11T16:28:36.435819Z","title":"Calibformer: A transformer-based automatic lidar-camera calibration network","venue":null,"work_id":null,"year":2023},"citing_paper":{"arxiv_id":"2412.10033","last_updated":"2024-12-13T10:48:38Z","snapshot_observed_at":"2026-08-12T09:04:07.560795Z","submitted_at":"2024-12-13T10:48:38Z","title":"Timealign: A multi-modal object detection method for time misalignment fusing in autonomous driving","version":1},"reference_index":15,"source":"pdf_text","source_observed_at":"2026-08-11T16:28:36.435819Z"},"links":{"cited_paper":"/paper/2311.15241","citing_paper":"/paper/2412.10033"},"observation_digest":"sha256:295a9dc56fff6a75b1db6fb37070f529ab743117496f57e45be8f15c3895826b","observation_id":"045a554c-dea6-41f3-ad0a-29b11aea37b4","resolution":{"observed_at":"2026-08-11T16:28:36.435819Z","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":"2026-08-11T16:28:37.781962Z","title":"Benchmarking robustness of 3d object detection to common corruptions","venue":null,"work_id":"e15459f2-7dce-4cd8-add3-48fe77c14ea2","year":2023},"citing_paper":{"arxiv_id":"2412.10033","last_updated":"2024-12-13T10:48:38Z","snapshot_observed_at":"2026-08-12T09:04:07.560795Z","submitted_at":"2024-12-13T10:48:38Z","title":"Timealign: A multi-modal object detection method for time misalignment fusing in autonomous driving","version":1},"reference_index":16,"source":"pdf_text","source_observed_at":"2026-08-11T16:28:36.440528Z"},"links":{"citing_paper":"/paper/2412.10033"},"observation_digest":"sha256:4e6ccd5e8172ad146063df9611578bf02c309d4a91eb0eb8efe83732a3b85710","observation_id":"6a90f981-2173-4080-b803-2d1861f24430","resolution":{"observed_at":"2026-08-11T16:28:37.787317Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-12T06:34:41.77262+00:00","source":"crossref"},{"observed_at":"2026-08-12T06:34:36.333875+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-11T16:28:37.766305Z","title":"Graphalign++: An accurate feature alignment by graph matching for multi-modal 3d object detection","venue":null,"work_id":"f84d8c61-0c18-4eb6-a4cb-31ebdeb48bb1","year":2024},"citing_paper":{"arxiv_id":"2412.10033","last_updated":"2024-12-13T10:48:38Z","snapshot_observed_at":"2026-08-12T09:04:07.560795Z","submitted_at":"2024-12-13T10:48:38Z","title":"Timealign: A multi-modal object detection method for time misalignment fusing in autonomous driving","version":1},"reference_index":17,"source":"pdf_text","source_observed_at":"2026-08-11T16:28:36.445013Z"},"links":{"citing_paper":"/paper/2412.10033"},"observation_digest":"sha256:6e2f0456be280ffbda5f528da3d94d540c7749e6cf4c32b9162e25fc1fe0f849","observation_id":"bc682ff8-84a6-4a04-9c45-bb27839642a8","resolution":{"observed_at":"2026-08-11T16:28:37.771637Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-12T06:34:41.77262+00:00","source":"crossref"},{"observed_at":"2026-08-12T06:34:36.333875+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-11T16:28:37.734946Z","title":"Benchmarking the robustness of lidar-camera fusion for 3d object detection","venue":null,"work_id":"a19d7c60-c40d-40ac-8426-de98d6b5a9c1","year":2023},"citing_paper":{"arxiv_id":"2412.10033","last_updated":"2024-12-13T10:48:38Z","snapshot_observed_at":"2026-08-12T09:04:07.560795Z","submitted_at":"2024-12-13T10:48:38Z","title":"Timealign: A multi-modal object detection method for time misalignment fusing in autonomous driving","version":1},"reference_index":18,"source":"pdf_text","source_observed_at":"2026-08-11T16:28:36.449405Z"},"links":{"citing_paper":"/paper/2412.10033"},"observation_digest":"sha256:8da7e1bcebc4b86da16e107a16637d3ffad921e0c4d68b174d263dd61516cc25","observation_id":"8bf511ef-b8eb-454b-b119-c4ea9bb01606","resolution":{"observed_at":"2026-08-11T16:28:37.740725Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-12T06:34:41.77262+00:00","source":"crossref"},{"observed_at":"2026-08-12T06:34:36.333875+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"2303.17099","last_updated":"2023-03-30T02:18:07Z","snapshot_observed_at":"2026-08-11T16:50:38.479796Z","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":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2303.17099","snapshot_observed_at":"2026-08-11T16:28:36.456559Z","title":"Bevfusion4d: Learning lidar-camera fusion under bird’s-eye-view via cross-modality guidance and temporal aggregation","venue":null,"work_id":null,"year":2023},"citing_paper":{"arxiv_id":"2412.10033","last_updated":"2024-12-13T10:48:38Z","snapshot_observed_at":"2026-08-12T09:04:07.560795Z","submitted_at":"2024-12-13T10:48:38Z","title":"Timealign: A multi-modal object detection method for time misalignment fusing in autonomous driving","version":1},"reference_index":19,"source":"pdf_text","source_observed_at":"2026-08-11T16:28:36.456559Z"},"links":{"cited_paper":"/paper/2303.17099","citing_paper":"/paper/2412.10033"},"observation_digest":"sha256:ffbc9f89a900c4a0a82631686670a5c99cf56dadfe6fa27dc18de3e780572d68","observation_id":"aecf6176-01da-4373-804d-230870ca9d4a","resolution":{"observed_at":"2026-08-11T16:28:36.456559Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2403.11848","last_updated":"2025-03-13T06:23:17Z","snapshot_observed_at":"2026-08-04T15:56:28.684219Z","submitted_at":"2024-03-18T15:00:38Z","title":"GraphBEV: Towards Robust BEV Feature Alignment for Multi-Modal 3D Object Detection","version":4},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2403.11848","snapshot_observed_at":"2026-08-11T16:28:36.463525Z","title":"Graphbev: Towards robust bev feature alignment for multi-modal 3d object detection","venue":null,"work_id":null,"year":2024},"citing_paper":{"arxiv_id":"2412.10033","last_updated":"2024-12-13T10:48:38Z","snapshot_observed_at":"2026-08-12T09:04:07.560795Z","submitted_at":"2024-12-13T10:48:38Z","title":"Timealign: A multi-modal object detection method for time misalignment fusing in autonomous driving","version":1},"reference_index":20,"source":"pdf_text","source_observed_at":"2026-08-11T16:28:36.463525Z"},"links":{"cited_paper":"/paper/2403.11848","citing_paper":"/paper/2412.10033"},"observation_digest":"sha256:2573014284e97e033b83d9a15d97bd7d7fa3aa69509e2ac59b92e3efcfb3c978","observation_id":"468ae198-3fcc-4022-a49d-9542644fb0ed","resolution":{"observed_at":"2026-08-11T16:28:36.463525Z","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":"2026-08-11T16:28:37.717853Z","title":"3d object detection using scale invariant and feature reweighting networks","venue":null,"work_id":"5235c5f8-863f-407c-bf26-666854edcba5","year":2019},"citing_paper":{"arxiv_id":"2412.10033","last_updated":"2024-12-13T10:48:38Z","snapshot_observed_at":"2026-08-12T09:04:07.560795Z","submitted_at":"2024-12-13T10:48:38Z","title":"Timealign: A multi-modal object detection method for time misalignment fusing in autonomous driving","version":1},"reference_index":21,"source":"pdf_text","source_observed_at":"2026-08-11T16:28:36.470560Z"},"links":{"citing_paper":"/paper/2412.10033"},"observation_digest":"sha256:c5adfdfa1ee1e7ac0d6ef09fedaa182151c74f481d5612bf9c61ad8f0a2e5fce","observation_id":"bd63c229-6ceb-4700-baf9-fd5419803254","resolution":{"observed_at":"2026-08-11T16:28:37.723637Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-12T06:34:41.77262+00:00","source":"crossref"},{"observed_at":"2026-08-12T06:34:36.333875+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"2203.17054","last_updated":"2022-06-16T09:44:08Z","snapshot_observed_at":"2026-07-06T12:55:16.868412Z","submitted_at":"2022-03-31T14:21:19Z","title":"BEVDet4D: Exploit Temporal Cues in Multi-camera 3D Object Detection","version":3},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2203.17054","snapshot_observed_at":"2026-08-11T16:28:36.475856Z","title":"Bevdet4d: Exploit temporal cues in multi-camera 3d object detection","venue":null,"work_id":null,"year":2022},"citing_paper":{"arxiv_id":"2412.10033","last_updated":"2024-12-13T10:48:38Z","snapshot_observed_at":"2026-08-12T09:04:07.560795Z","submitted_at":"2024-12-13T10:48:38Z","title":"Timealign: A multi-modal object detection method for time misalignment fusing in autonomous driving","version":1},"reference_index":22,"source":"pdf_text","source_observed_at":"2026-08-11T16:28:36.475856Z"},"links":{"cited_paper":"/paper/2203.17054","citing_paper":"/paper/2412.10033"},"observation_digest":"sha256:8c5d252dd7395399f2c5095dac0e9f70e669bb24b8dc2826245d7e259e0f169d","observation_id":"35c79c78-90a1-4390-b29f-b6d1fbec27f7","resolution":{"observed_at":"2026-08-11T16:28:36.475856Z","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":"2026-08-11T16:28:37.701019Z","title":"Communication challenges in infrastructure-vehicle cooperative autonomous driving: A field deployment perspective","venue":null,"work_id":"c40a0430-d1e3-4844-9ab8-4f90e1e2f7c4","year":2022},"citing_paper":{"arxiv_id":"2412.10033","last_updated":"2024-12-13T10:48:38Z","snapshot_observed_at":"2026-08-12T09:04:07.560795Z","submitted_at":"2024-12-13T10:48:38Z","title":"Timealign: A multi-modal object detection method for time misalignment fusing in autonomous driving","version":1},"reference_index":23,"source":"pdf_text","source_observed_at":"2026-08-11T16:28:36.482316Z"},"links":{"citing_paper":"/paper/2412.10033"},"observation_digest":"sha256:33617ca84076f434da83c8ee6c337f4d94ce634973a627752a3cb66320893dc5","observation_id":"93894b02-c9bc-4e7d-811d-dae78ac6f690","resolution":{"observed_at":"2026-08-11T16:28:37.708438Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-12T06:34:41.77262+00:00","source":"crossref"},{"observed_at":"2026-08-12T06:34:36.333875+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-11T16:28:37.684182Z","title":"Computing systems for autonomous driving: State of the art and challenges","venue":null,"work_id":"a6ef8e4e-97c5-4458-b808-c1101dcc77e5","year":2020},"citing_paper":{"arxiv_id":"2412.10033","last_updated":"2024-12-13T10:48:38Z","snapshot_observed_at":"2026-08-12T09:04:07.560795Z","submitted_at":"2024-12-13T10:48:38Z","title":"Timealign: A multi-modal object detection method for time misalignment fusing in autonomous driving","version":1},"reference_index":24,"source":"pdf_text","source_observed_at":"2026-08-11T16:28:36.487593Z"},"links":{"citing_paper":"/paper/2412.10033"},"observation_digest":"sha256:5031eb5c2589645f9ef14344c6c2b1bfb6a50431bfd67c87c78e661f51d3fe14","observation_id":"bf8c8a9d-4b1a-40c2-b736-4c3d3c6696d1","resolution":{"observed_at":"2026-08-11T16:28:37.689062Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-12T06:34:41.77262+00:00","source":"crossref"},{"observed_at":"2026-08-12T06:34:36.333875+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-11T16:28:37.669017Z","title":"Sensing and communication integrated system for autonomous driving vehicles","venue":null,"work_id":"41fa12f7-b8dd-45c2-801b-758ca7cef420","year":2020},"citing_paper":{"arxiv_id":"2412.10033","last_updated":"2024-12-13T10:48:38Z","snapshot_observed_at":"2026-08-12T09:04:07.560795Z","submitted_at":"2024-12-13T10:48:38Z","title":"Timealign: A multi-modal object detection method for time misalignment fusing in autonomous driving","version":1},"reference_index":25,"source":"pdf_text","source_observed_at":"2026-08-11T16:28:36.495441Z"},"links":{"citing_paper":"/paper/2412.10033"},"observation_digest":"sha256:4c85a781952b38afe5cee35f2adc71fc239c312c8ac5d232083ed7f630148577","observation_id":"0e1adbc7-58b2-48a8-9a9e-4671c56e65e7","resolution":{"observed_at":"2026-08-11T16:28:37.673680Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-12T06:34:41.77262+00:00","source":"crossref"},{"observed_at":"2026-08-12T06:34:36.333875+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-11T16:28:37.647030Z","title":"Image data compression: A review","venue":null,"work_id":"7d2de779-5339-4b05-a04f-612207c33f9a","year":1981},"citing_paper":{"arxiv_id":"2412.10033","last_updated":"2024-12-13T10:48:38Z","snapshot_observed_at":"2026-08-12T09:04:07.560795Z","submitted_at":"2024-12-13T10:48:38Z","title":"Timealign: A multi-modal object detection method for time misalignment fusing in autonomous driving","version":1},"reference_index":26,"source":"pdf_text","source_observed_at":"2026-08-11T16:28:36.500045Z"},"links":{"citing_paper":"/paper/2412.10033"},"observation_digest":"sha256:900aae12adbd5ae2f1a3935cd3771aa75171674ea2e3a33a86f15b12289d3149","observation_id":"beab6383-8ea6-4cbb-93eb-1b90d70cf611","resolution":{"observed_at":"2026-08-11T16:28:37.656040Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-12T06:34:41.77262+00:00","source":"crossref"},{"observed_at":"2026-08-12T06:34:36.333875+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-11T16:28:37.558065Z","title":"Swinlstm: Improving spatiotemporal prediction accuracy using swin transformer and lstm","venue":null,"work_id":"3ba1a7bc-6788-4819-acc4-00cf0ee9e9af","year":2023},"citing_paper":{"arxiv_id":"2412.10033","last_updated":"2024-12-13T10:48:38Z","snapshot_observed_at":"2026-08-12T09:04:07.560795Z","submitted_at":"2024-12-13T10:48:38Z","title":"Timealign: A multi-modal object detection method for time misalignment fusing in autonomous driving","version":1},"reference_index":27,"source":"pdf_text","source_observed_at":"2026-08-11T16:28:36.505148Z"},"links":{"citing_paper":"/paper/2412.10033"},"observation_digest":"sha256:d463e8f284cfd438910416dbe67695d7ca7f6ff187287eaa2e4318b469c92a17","observation_id":"afd30f4f-015e-421b-9bb6-6f158068e448","resolution":{"observed_at":"2026-08-11T16:28:37.617845Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-12T06:34:41.77262+00:00","source":"crossref"},{"observed_at":"2026-08-12T06:34:36.333875+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-11T16:28:37.469381Z","title":"Fusionpainting: Multimodal fusion with adaptive attention for 3d object detection","venue":null,"work_id":"02d518ef-c7ff-421b-a7a3-1d42b5820ac7","year":2021},"citing_paper":{"arxiv_id":"2412.10033","last_updated":"2024-12-13T10:48:38Z","snapshot_observed_at":"2026-08-12T09:04:07.560795Z","submitted_at":"2024-12-13T10:48:38Z","title":"Timealign: A multi-modal object detection method for time misalignment fusing in autonomous driving","version":1},"reference_index":28,"source":"pdf_text","source_observed_at":"2026-08-11T16:28:36.540490Z"},"links":{"citing_paper":"/paper/2412.10033"},"observation_digest":"sha256:e2e20246a90213550b302170c50bdd90c929079f1fc46ed4e19acfbdd0c77397","observation_id":"e2b5432f-15fe-4e31-a338-f9ff1b2e5a60","resolution":{"observed_at":"2026-08-11T16:28:37.508104Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-12T06:34:41.77262+00:00","source":"crossref"},{"observed_at":"2026-08-12T06:34:36.333875+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-11T16:28:37.423648Z","title":"Transfusion medicine—blood transfusion","venue":null,"work_id":"74664388-2867-4d50-8c14-b5b05240400b","year":1999},"citing_paper":{"arxiv_id":"2412.10033","last_updated":"2024-12-13T10:48:38Z","snapshot_observed_at":"2026-08-12T09:04:07.560795Z","submitted_at":"2024-12-13T10:48:38Z","title":"Timealign: A multi-modal object detection method for time misalignment fusing in autonomous driving","version":1},"reference_index":29,"source":"pdf_text","source_observed_at":"2026-08-11T16:28:36.583625Z"},"links":{"citing_paper":"/paper/2412.10033"},"observation_digest":"sha256:f61ecea01096a68201affa16d5f581c77195345097f75b15cb75278fd1d29ffe","observation_id":"1e2f069c-56f1-42d1-8ae0-6f39b81647f4","resolution":{"observed_at":"2026-08-11T16:28:37.429159Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-12T06:34:41.77262+00:00","source":"crossref"},{"observed_at":"2026-08-12T06:34:36.333875+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-11T16:28:37.405317Z","title":"Bevfusion: A simple and robust lidar-camera fusion framework","venue":null,"work_id":"de416027-1044-4f5e-a254-3b652e2bc4d3","year":2022},"citing_paper":{"arxiv_id":"2412.10033","last_updated":"2024-12-13T10:48:38Z","snapshot_observed_at":"2026-08-12T09:04:07.560795Z","submitted_at":"2024-12-13T10:48:38Z","title":"Timealign: A multi-modal object detection method for time misalignment fusing in autonomous driving","version":1},"reference_index":30,"source":"pdf_text","source_observed_at":"2026-08-11T16:28:36.608341Z"},"links":{"citing_paper":"/paper/2412.10033"},"observation_digest":"sha256:36d56c64b5643d62c71811baba942544b3bcbcdac510ee16616ebf21c8b9f450","observation_id":"2b9388c7-9efa-413b-a232-7cdd417faddf","resolution":{"observed_at":"2026-08-11T16:28:37.411503Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-12T06:34:41.77262+00:00","source":"crossref"},{"observed_at":"2026-08-12T06:34:36.333875+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-11T16:28:37.387370Z","title":"Objectfusion: Multi-modal 3d object detection with object-centric fusion","venue":null,"work_id":"8f36b63e-2c8d-4fc3-a309-cb50e5a4dbca","year":2023},"citing_paper":{"arxiv_id":"2412.10033","last_updated":"2024-12-13T10:48:38Z","snapshot_observed_at":"2026-08-12T09:04:07.560795Z","submitted_at":"2024-12-13T10:48:38Z","title":"Timealign: A multi-modal object detection method for time misalignment fusing in autonomous driving","version":1},"reference_index":31,"source":"pdf_text","source_observed_at":"2026-08-11T16:28:36.639281Z"},"links":{"citing_paper":"/paper/2412.10033"},"observation_digest":"sha256:09e0ddcb91ba9776903b1f59a5610e0838d4eeccf0589d12a840b38d0967e0c0","observation_id":"3335854b-e82f-4f1c-8fdc-6da28c6f3a91","resolution":{"observed_at":"2026-08-11T16:28:37.392491Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-12T06:34:41.77262+00:00","source":"crossref"},{"observed_at":"2026-08-12T06:34:36.333875+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"2304.09801","last_updated":"2023-04-19T16:37:17Z","snapshot_observed_at":"2026-08-10T11:01:46.705375Z","submitted_at":"2023-04-19T16:37:17Z","title":"MetaBEV: Solving Sensor Failures for BEV Detection and Map Segmentation","version":1},"cited_work":{"arxiv_id":"2304.09801","doi":null,"metadata_source":"pith","pith_arxiv_id":"2304.09801","snapshot_observed_at":"2026-08-11T16:28:36.874968Z","title":"MetaBEV: Solving Sensor Failures for BEV Detection and Map Segmentation","venue":"cs.CV","work_id":"6059965e-2a1c-4ae9-bcdc-390c18c757bc","year":2023},"citing_paper":{"arxiv_id":"2412.10033","last_updated":"2024-12-13T10:48:38Z","snapshot_observed_at":"2026-08-12T09:04:07.560795Z","submitted_at":"2024-12-13T10:48:38Z","title":"Timealign: A multi-modal object detection method for time misalignment fusing in autonomous driving","version":1},"reference_index":32,"source":"pdf_text","source_observed_at":"2026-08-11T16:28:36.671823Z"},"links":{"cited_paper":"/paper/2304.09801","citing_paper":"/paper/2412.10033"},"observation_digest":"sha256:64b0fe83857beaf35055a2ff417df37ee11264ba6d5ddd3ebea11315af5450f7","observation_id":"e973d329-b3ef-45d4-a464-b484227bbb31","resolution":{"observed_at":"2026-08-11T16:28:36.884918Z","resolver_source":"local_arxiv","status":"verified_exact"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-12T06:34:41.77262+00:00","source":"crossref"},{"observed_at":"2026-08-12T06:34:36.333875+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-11T16:28:37.371941Z","title":"Unibev: Multi-modal 3d object detection with uniform bev encoders for robustness against missing sensor modalities","venue":null,"work_id":"2d8b2862-a224-4754-a3a5-ba60e46fb260","year":2024},"citing_paper":{"arxiv_id":"2412.10033","last_updated":"2024-12-13T10:48:38Z","snapshot_observed_at":"2026-08-12T09:04:07.560795Z","submitted_at":"2024-12-13T10:48:38Z","title":"Timealign: A multi-modal object detection method for time misalignment fusing in autonomous driving","version":1},"reference_index":33,"source":"pdf_text","source_observed_at":"2026-08-11T16:28:36.692544Z"},"links":{"citing_paper":"/paper/2412.10033"},"observation_digest":"sha256:6efdb51309321d8250b390effed7d90a23399c091e8c707f50f2b4cc31e0fdbe","observation_id":"3b5d5954-26a2-4155-b4a4-4973e88ae3f5","resolution":{"observed_at":"2026-08-11T16:28:37.376390Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-12T06:34:41.77262+00:00","source":"crossref"},{"observed_at":"2026-08-12T06:34:36.333875+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"2405.16873","last_updated":"2025-08-19T08:07:30Z","snapshot_observed_at":"2026-07-06T18:20:22.759333Z","submitted_at":"2024-05-27T06:43:12Z","title":"ContrastAlign: Toward Robust BEV Feature Alignment via Contrastive Learning for Multi-Modal 3D Object Detection","version":3},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2405.16873","snapshot_observed_at":"2026-08-11T16:28:36.703250Z","title":"Contrastalign: Toward robust bev feature alignment via contrastive learning for multi-modal 3d object detection","venue":null,"work_id":null,"year":2024},"citing_paper":{"arxiv_id":"2412.10033","last_updated":"2024-12-13T10:48:38Z","snapshot_observed_at":"2026-08-12T09:04:07.560795Z","submitted_at":"2024-12-13T10:48:38Z","title":"Timealign: A multi-modal object detection method for time misalignment fusing in autonomous driving","version":1},"reference_index":34,"source":"pdf_text","source_observed_at":"2026-08-11T16:28:36.703250Z"},"links":{"cited_paper":"/paper/2405.16873","citing_paper":"/paper/2412.10033"},"observation_digest":"sha256:3ee1216d7d8437397eadedfe5d8fd4805ae1dc2e74cc024f2448347a95765e2f","observation_id":"89de27b0-9338-4567-8969-47309a5de528","resolution":{"observed_at":"2026-08-11T16:28:36.703250Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2408.05945","last_updated":"2025-07-03T05:37:48Z","snapshot_observed_at":"2026-07-06T18:59:29.568123Z","submitted_at":"2024-08-12T06:46:05Z","title":"MV2DFusion: Leveraging Modality-Specific Object Semantics for Multi-Modal 3D Detection","version":2},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2408.05945","snapshot_observed_at":"2026-08-11T16:28:36.712998Z","title":"Mv2dfusion: Leveraging modality-specific object semantics for multi-modal 3d detection","venue":null,"work_id":null,"year":2024},"citing_paper":{"arxiv_id":"2412.10033","last_updated":"2024-12-13T10:48:38Z","snapshot_observed_at":"2026-08-12T09:04:07.560795Z","submitted_at":"2024-12-13T10:48:38Z","title":"Timealign: A multi-modal object detection method for time misalignment fusing in autonomous driving","version":1},"reference_index":35,"source":"pdf_text","source_observed_at":"2026-08-11T16:28:36.712998Z"},"links":{"cited_paper":"/paper/2408.05945","citing_paper":"/paper/2412.10033"},"observation_digest":"sha256:14b6808f3d82600ba9f634095ce524fefa5773f3d9b80209a92b007e79fe8e0a","observation_id":"b56ffba8-cfda-48c4-873b-379ce2e1fe22","resolution":{"observed_at":"2026-08-11T16:28:36.712998Z","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":"2026-08-11T16:28:37.356159Z","title":"4d-net for learned multi-modal alignment","venue":null,"work_id":"3727505c-c7c3-4d2d-a524-9ba6c948e75b","year":2021},"citing_paper":{"arxiv_id":"2412.10033","last_updated":"2024-12-13T10:48:38Z","snapshot_observed_at":"2026-08-12T09:04:07.560795Z","submitted_at":"2024-12-13T10:48:38Z","title":"Timealign: A multi-modal object detection method for time misalignment fusing in autonomous driving","version":1},"reference_index":36,"source":"pdf_text","source_observed_at":"2026-08-11T16:28:36.718525Z"},"links":{"citing_paper":"/paper/2412.10033"},"observation_digest":"sha256:a8f08414278ede37a0a2a77c306b72e9ba2d8cdff7d9af3f4049a8406cf8b3d9","observation_id":"d9f042ca-87bb-47a2-83b4-86b22e4556cf","resolution":{"observed_at":"2026-08-11T16:28:37.361235Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-12T06:34:41.77262+00:00","source":"crossref"},{"observed_at":"2026-08-12T06:34:36.333875+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-11T16:28:37.336775Z","title":"An lstm approach to temporal 3d object detection in lidar point clouds","venue":null,"work_id":"2bc9867b-a171-4219-bbe1-da41406bec58","year":2020},"citing_paper":{"arxiv_id":"2412.10033","last_updated":"2024-12-13T10:48:38Z","snapshot_observed_at":"2026-08-12T09:04:07.560795Z","submitted_at":"2024-12-13T10:48:38Z","title":"Timealign: A multi-modal object detection method for time misalignment fusing in autonomous driving","version":1},"reference_index":37,"source":"pdf_text","source_observed_at":"2026-08-11T16:28:36.724858Z"},"links":{"citing_paper":"/paper/2412.10033"},"observation_digest":"sha256:17397db8f9c368ff3d3bd18a487b4d9509cb2ab99be077e74c038bc437157c3e","observation_id":"1ba65dd3-eb27-432e-918b-f9252d20a74b","resolution":{"observed_at":"2026-08-11T16:28:37.344061Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-12T06:34:41.77262+00:00","source":"crossref"},{"observed_at":"2026-08-12T06:34:36.333875+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":null,"snapshot_observed_at":"2026-08-11T16:28:36.731450Z","title":"Scalability in perception for autonomous driving: Waymo open dataset","venue":null,"work_id":null,"year":2020},"citing_paper":{"arxiv_id":"2412.10033","last_updated":"2024-12-13T10:48:38Z","snapshot_observed_at":"2026-08-12T09:04:07.560795Z","submitted_at":"2024-12-13T10:48:38Z","title":"Timealign: A multi-modal object detection method for time misalignment fusing in autonomous driving","version":1},"reference_index":38,"source":"pdf_text","source_observed_at":"2026-08-11T16:28:36.731450Z"},"links":{"citing_paper":"/paper/2412.10033"},"observation_digest":"sha256:27e48be17e925bf4184e090bed8a1c23489043ff4449fc9deed5aee91b0764ed","observation_id":"15f1af9b-9800-4955-8600-7a17ff0b2a93","resolution":{"observed_at":"2026-08-11T16:28:36.731450Z","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":"2026-08-11T16:28:36.738020Z","title":"Bevformer: Learning bird’s-eye-view representation from multi-camera images via spatiotemporal transformers","venue":null,"work_id":null,"year":2022},"citing_paper":{"arxiv_id":"2412.10033","last_updated":"2024-12-13T10:48:38Z","snapshot_observed_at":"2026-08-12T09:04:07.560795Z","submitted_at":"2024-12-13T10:48:38Z","title":"Timealign: A multi-modal object detection method for time misalignment fusing in autonomous driving","version":1},"reference_index":39,"source":"pdf_text","source_observed_at":"2026-08-11T16:28:36.738020Z"},"links":{"citing_paper":"/paper/2412.10033"},"observation_digest":"sha256:af5b3b4d1dc7cd03bc02c9661a2a1d5d257e98fd1ac09bc658536323e9a478f0","observation_id":"1ce8a351-f158-4376-90e4-d7d1c85a7aa6","resolution":{"observed_at":"2026-08-11T16:28:36.738020Z","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":"2026-08-11T16:28:37.295711Z","title":"Lift: Learning 4d lidar image fusion transformer for 3d object detection","venue":null,"work_id":"530d20a3-a818-4827-8c44-606c659be60e","year":2022},"citing_paper":{"arxiv_id":"2412.10033","last_updated":"2024-12-13T10:48:38Z","snapshot_observed_at":"2026-08-12T09:04:07.560795Z","submitted_at":"2024-12-13T10:48:38Z","title":"Timealign: A multi-modal object detection method for time misalignment fusing in autonomous driving","version":1},"reference_index":40,"source":"pdf_text","source_observed_at":"2026-08-11T16:28:36.744630Z"},"links":{"citing_paper":"/paper/2412.10033"},"observation_digest":"sha256:40ee583fda9fa2d3f5b91ba15ab416cc1f4e98ec0ea098ae0c9bc987c6450538","observation_id":"408be19a-084e-4ec9-986b-2e044c881e3f","resolution":{"observed_at":"2026-08-11T16:28:37.301047Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-12T06:34:41.77262+00:00","source":"crossref"},{"observed_at":"2026-08-12T06:34:36.333875+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-11T16:28:37.278101Z","title":"Petrv2: A unified framework for 3d perception from multi-camera images","venue":null,"work_id":"555eb7c8-15e9-471d-86e8-85a014a7c6aa","year":2023},"citing_paper":{"arxiv_id":"2412.10033","last_updated":"2024-12-13T10:48:38Z","snapshot_observed_at":"2026-08-12T09:04:07.560795Z","submitted_at":"2024-12-13T10:48:38Z","title":"Timealign: A multi-modal object detection method for time misalignment fusing in autonomous driving","version":1},"reference_index":41,"source":"pdf_text","source_observed_at":"2026-08-11T16:28:36.748633Z"},"links":{"citing_paper":"/paper/2412.10033"},"observation_digest":"sha256:ce1b279af72ffc56f02e92643e825971fb9a28868884bd22df2841d655c239b8","observation_id":"139233fc-4a03-44c2-862d-cd655d5b2761","resolution":{"observed_at":"2026-08-11T16:28:37.284072Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-12T06:34:41.77262+00:00","source":"crossref"},{"observed_at":"2026-08-12T06:34:36.333875+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":null,"snapshot_observed_at":"2026-08-11T16:28:36.753440Z","title":"nuscenes: A multimodal dataset for autonomous driving","venue":null,"work_id":null,"year":2020},"citing_paper":{"arxiv_id":"2412.10033","last_updated":"2024-12-13T10:48:38Z","snapshot_observed_at":"2026-08-12T09:04:07.560795Z","submitted_at":"2024-12-13T10:48:38Z","title":"Timealign: A multi-modal object detection method for time misalignment fusing in autonomous driving","version":1},"reference_index":42,"source":"pdf_text","source_observed_at":"2026-08-11T16:28:36.753440Z"},"links":{"citing_paper":"/paper/2412.10033"},"observation_digest":"sha256:79c132be9c1bf092a22492ee78d9a6d480923696d577b63f3d0879c235e1fe85","observation_id":"42fa3256-d565-40fc-adfc-89aef3eb603e","resolution":{"observed_at":"2026-08-11T16:28:36.753440Z","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":"2026-08-11T16:28:37.237591Z","title":"Openpcdet: An open-source toolbox for 3d object detection from point clouds, 2020","venue":null,"work_id":"7dc806c7-2290-45c8-b5bd-14dc935c0058","year":2020},"citing_paper":{"arxiv_id":"2412.10033","last_updated":"2024-12-13T10:48:38Z","snapshot_observed_at":"2026-08-12T09:04:07.560795Z","submitted_at":"2024-12-13T10:48:38Z","title":"Timealign: A multi-modal object detection method for time misalignment fusing in autonomous driving","version":1},"reference_index":43,"source":"pdf_text","source_observed_at":"2026-08-11T16:28:36.758070Z"},"links":{"citing_paper":"/paper/2412.10033"},"observation_digest":"sha256:ff46d166ab539deef8722d87bff2a12fa01bb50c4c3755189792d7496487d23c","observation_id":"37eaa77b-6c9b-4136-b8ce-2596c11773ef","resolution":{"observed_at":"2026-08-11T16:28:37.244439Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-12T06:34:41.77262+00:00","source":"crossref"},{"observed_at":"2026-08-12T06:34:36.333875+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-11T16:28:37.179527Z","title":"Openstl: A comprehensive benchmark of spatio-temporal predictive learning","venue":null,"work_id":"43bed5f6-f3f0-4889-9941-492866f81c33","year":2023},"citing_paper":{"arxiv_id":"2412.10033","last_updated":"2024-12-13T10:48:38Z","snapshot_observed_at":"2026-08-12T09:04:07.560795Z","submitted_at":"2024-12-13T10:48:38Z","title":"Timealign: A multi-modal object detection method for time misalignment fusing in autonomous driving","version":1},"reference_index":44,"source":"pdf_text","source_observed_at":"2026-08-11T16:28:36.764031Z"},"links":{"citing_paper":"/paper/2412.10033"},"observation_digest":"sha256:558deed1ffa73959214e13b7252a716d313afaf1ced22a43900ec76f8166c428","observation_id":"82d3bd22-73cf-4187-94ca-332c485f262e","resolution":{"observed_at":"2026-08-11T16:28:37.215337Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-12T06:34:41.77262+00:00","source":"crossref"},{"observed_at":"2026-08-12T06:34:36.333875+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":null,"snapshot_observed_at":"2026-08-11T16:28:36.770162Z","title":"Swin transformer: Hierarchical vision transformer using shifted windows","venue":null,"work_id":null,"year":2021},"citing_paper":{"arxiv_id":"2412.10033","last_updated":"2024-12-13T10:48:38Z","snapshot_observed_at":"2026-08-12T09:04:07.560795Z","submitted_at":"2024-12-13T10:48:38Z","title":"Timealign: A multi-modal object detection method for time misalignment fusing in autonomous driving","version":1},"reference_index":45,"source":"pdf_text","source_observed_at":"2026-08-11T16:28:36.770162Z"},"links":{"citing_paper":"/paper/2412.10033"},"observation_digest":"sha256:5c6a581e36a959651aefc55eb111f855b1f2d1fcef3d66910921cb6ef2fa094d","observation_id":"78323282-6f1d-4d33-bb08-a57601fd5329","resolution":{"observed_at":"2026-08-11T16:28:36.770162Z","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":"2026-08-11T16:28:36.776231Z","title":"Second: Sparsely embedded convolutional detection.Sensors, 18(10):3337, 2018","venue":null,"work_id":null,"year":2018},"citing_paper":{"arxiv_id":"2412.10033","last_updated":"2024-12-13T10:48:38Z","snapshot_observed_at":"2026-08-12T09:04:07.560795Z","submitted_at":"2024-12-13T10:48:38Z","title":"Timealign: A multi-modal object detection method for time misalignment fusing in autonomous driving","version":1},"reference_index":46,"source":"pdf_text","source_observed_at":"2026-08-11T16:28:36.776231Z"},"links":{"citing_paper":"/paper/2412.10033"},"observation_digest":"sha256:5e9483e831628cb1fde280c883f165f078073310d42d86628fde8924e8ad88f4","observation_id":"760e6de8-2e53-4e16-9e93-c76578798f50","resolution":{"observed_at":"2026-08-11T16:28:36.776231Z","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":"2026-08-11T16:28:37.073755Z","title":"Lift, splat, shoot: Encoding images from arbitrary camera rigs by implicitly unprojecting to 3d","venue":null,"work_id":"24bd62c3-3f38-46e2-873a-a883e0050be0","year":2020},"citing_paper":{"arxiv_id":"2412.10033","last_updated":"2024-12-13T10:48:38Z","snapshot_observed_at":"2026-08-12T09:04:07.560795Z","submitted_at":"2024-12-13T10:48:38Z","title":"Timealign: A multi-modal object detection method for time misalignment fusing in autonomous driving","version":1},"reference_index":47,"source":"pdf_text","source_observed_at":"2026-08-11T16:28:36.781237Z"},"links":{"citing_paper":"/paper/2412.10033"},"observation_digest":"sha256:60c0d95c33700c936160607ada1c94edd209eccc5bb84dc42b34de5983206486","observation_id":"efc76959-07d8-41db-b466-3e02a69a80b9","resolution":{"observed_at":"2026-08-11T16:28:37.106691Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-12T06:34:41.77262+00:00","source":"crossref"},{"observed_at":"2026-08-12T06:34:36.333875+00:00","source":"retraction_watch"}],"state":"measured"}}],"paper":{"arxiv_id":"2412.10033","last_updated":"2024-12-13T10:48:38Z","latest_version":1,"primary_category":"cs.CV","snapshot_observed_at":"2026-08-12T09:04:07.560795Z","submitted_at":"2024-12-13T10:48:38Z","title":"Timealign: A multi-modal object detection method for time misalignment fusing in autonomous driving"},"reference_resolution":{"displayed":47,"state_counts":{"malformed_identifier":0,"metadata_mismatch":0,"parse_uncertain":0,"unresolved":16,"verified_exact":1,"verified_fuzzy":30},"total_outbound_references":47},"refusal":"A citation records a reference. It does not transfer a finding from one paper to another.","schema":"pith.paper-citation-record.v1","standing_sources":[{"observed_at":"2026-08-12T06:34:41.77262+00:00","source":"crossref"},{"observed_at":"2026-08-12T06:34:36.333875+00:00","source":"retraction_watch"}],"thesis":"As of 12 August 2026, this Paper Citation Record lists 47 of 47 outbound references and 0 inbound Pith citation observations for arXiv:2412.10033."}