{"as_of":"2026-08-05T17:13:00Z","caps":{"database_statements":6,"inbound":100,"outbound":100},"context_digest":"sha256:9eb91a42274781757710f2ade0f07690a60f92ccf32d9359d0fa8672902606bc","coverage":[{"denominator":51,"lane":"reference_resolution","note":"Typed states for the displayed outbound observations.","records_observed":51,"source":"paper_references, paper_reference_links","source_observed_at":"2026-05-13T17:11:52.457688Z","state":"measured"},{"denominator":51,"lane":"standing_notices","note":"One-hop event checks from named stored sources.","records_observed":51,"source":"scholarly_work_events, retraction_status_cache","source_observed_at":"2026-08-05T06:32:48.257954+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/2604.03747/citation-record","integrity":"/paper/2604.03747/integrity","json":"/paper/2604.03747/citation-record.json","paper":"/paper/2604.03747"},"outbound":[{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-06-05T21:23:00.469572Z","title":"Onboard sensors-based self-localization for autonomous vehicle with hierarchical map","venue":null,"work_id":"187e1e9f-9d10-4728-8efc-0482b6564ebf","year":2023},"citing_paper":{"arxiv_id":"2604.03747","last_updated":"2026-04-04T14:27:54Z","snapshot_observed_at":"2026-08-04T20:18:53.390138Z","submitted_at":"2026-04-04T14:27:54Z","title":"CT-VoxelMap: Efficient Continuous-Time LiDAR-Inertial Odometry with Probabilistic Adaptive Voxel Mapping","version":1},"reference_index":1,"source":"pdf_text","source_observed_at":"2026-05-13T17:11:52.457688Z"},"links":{"citing_paper":"/paper/2604.03747"},"observation_digest":"sha256:d9c50ca9cbc92415118c2dc0a5f24b09cc899d0ee4cc26d5a61db74143163933","observation_id":"7844413f-a857-4587-8ee3-58654266eb76","resolution":{"observed_at":"2026-05-13T17:13:01.863414Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-05T06:32:48.257954+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-05T06:32:48.257954+00:00","source":"crossref"},{"observed_at":"2026-08-05T06:32:44.755628+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":"2026-06-05T21:23:00.469572Z","title":"Slope inspection under dense vegetation using lidar-based quadrotors","venue":null,"work_id":"f3b875dd-ce17-411c-a5f3-13d20c42353a","year":2025},"citing_paper":{"arxiv_id":"2604.03747","last_updated":"2026-04-04T14:27:54Z","snapshot_observed_at":"2026-08-04T20:18:53.390138Z","submitted_at":"2026-04-04T14:27:54Z","title":"CT-VoxelMap: Efficient Continuous-Time LiDAR-Inertial Odometry with Probabilistic Adaptive Voxel Mapping","version":1},"reference_index":2,"source":"pdf_text","source_observed_at":"2026-05-13T17:11:52.457688Z"},"links":{"citing_paper":"/paper/2604.03747"},"observation_digest":"sha256:fe510631c4624b76c6fd0bab193b96357aea2c69dbac44838e7bd26b0396d560","observation_id":"a62a505f-9a25-4cc5-bf28-007aca130b6d","resolution":{"observed_at":"2026-05-13T17:13:01.861616Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-05T06:32:48.257954+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-05T06:32:48.257954+00:00","source":"crossref"},{"observed_at":"2026-08-05T06:32:44.755628+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":"2026-07-07T19:34:07.684526Z","title":"A self-rotating, single-actuated uav with extended sensor field of view for autonomous navigation","venue":null,"work_id":"2c35aeaf-4bca-4aeb-b18b-f31e4f53f509","year":2023},"citing_paper":{"arxiv_id":"2604.03747","last_updated":"2026-04-04T14:27:54Z","snapshot_observed_at":"2026-08-04T20:18:53.390138Z","submitted_at":"2026-04-04T14:27:54Z","title":"CT-VoxelMap: Efficient Continuous-Time LiDAR-Inertial Odometry with Probabilistic Adaptive Voxel Mapping","version":1},"reference_index":3,"source":"pdf_text","source_observed_at":"2026-05-13T17:11:52.457688Z"},"links":{"citing_paper":"/paper/2604.03747"},"observation_digest":"sha256:7312d5261dcf36468ef63ebdcfdfabc963d800fd2c2d390a041d5439e8f504f3","observation_id":"fedb5239-30de-46d7-962e-3b1d1c166880","resolution":{"observed_at":"2026-05-13T17:13:01.859718Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-05T06:32:48.257954+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-05T06:32:48.257954+00:00","source":"crossref"},{"observed_at":"2026-08-05T06:32:44.755628+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":"2026-06-05T21:23:00.469572Z","title":"Rolo-slam: rotation-optimized lidar-only slam in uneven terrain with ground vehicle","venue":null,"work_id":"0de30245-50db-41ad-a625-6a2fb90f5504","year":2025},"citing_paper":{"arxiv_id":"2604.03747","last_updated":"2026-04-04T14:27:54Z","snapshot_observed_at":"2026-08-04T20:18:53.390138Z","submitted_at":"2026-04-04T14:27:54Z","title":"CT-VoxelMap: Efficient Continuous-Time LiDAR-Inertial Odometry with Probabilistic Adaptive Voxel Mapping","version":1},"reference_index":4,"source":"pdf_text","source_observed_at":"2026-05-13T17:11:52.457688Z"},"links":{"citing_paper":"/paper/2604.03747"},"observation_digest":"sha256:7d5e1632f7ba0e2d8a3caf3892c11d7e4b79dce23fba1bfd9b8b358e6c172a79","observation_id":"b915bdf6-473b-4a48-b2e9-c7fd48e7e1d2","resolution":{"observed_at":"2026-05-13T17:13:01.865423Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-05T06:32:48.257954+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-05T06:32:48.257954+00:00","source":"crossref"},{"observed_at":"2026-08-05T06:32:44.755628+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":"2026-06-05T21:23:00.469572Z","title":"Mne-slam: Multi-agent neural slam for mobile robots","venue":null,"work_id":"4c6a038e-6668-4254-8c8d-5a8cfdbdfa8c","year":2025},"citing_paper":{"arxiv_id":"2604.03747","last_updated":"2026-04-04T14:27:54Z","snapshot_observed_at":"2026-08-04T20:18:53.390138Z","submitted_at":"2026-04-04T14:27:54Z","title":"CT-VoxelMap: Efficient Continuous-Time LiDAR-Inertial Odometry with Probabilistic Adaptive Voxel Mapping","version":1},"reference_index":5,"source":"pdf_text","source_observed_at":"2026-05-13T17:11:52.457688Z"},"links":{"citing_paper":"/paper/2604.03747"},"observation_digest":"sha256:eaa2fa8429bb21ab8b68b159461befa1a9acf401dade4ea38f739d8d9d0dbe12","observation_id":"8598597f-752d-46ad-8a12-5e393649b95a","resolution":{"observed_at":"2026-05-13T17:13:01.857461Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-05T06:32:48.257954+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-05T06:32:48.257954+00:00","source":"crossref"},{"observed_at":"2026-08-05T06:32:44.755628+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":"2026-06-05T21:23:00.469572Z","title":"Targetless calibration of lidar-imu system based on continuous-time batch estimation","venue":null,"work_id":"5d9f3d41-456c-4f31-879c-8ad4b99740fb","year":2020},"citing_paper":{"arxiv_id":"2604.03747","last_updated":"2026-04-04T14:27:54Z","snapshot_observed_at":"2026-08-04T20:18:53.390138Z","submitted_at":"2026-04-04T14:27:54Z","title":"CT-VoxelMap: Efficient Continuous-Time LiDAR-Inertial Odometry with Probabilistic Adaptive Voxel Mapping","version":1},"reference_index":6,"source":"pdf_text","source_observed_at":"2026-05-13T17:11:52.457688Z"},"links":{"citing_paper":"/paper/2604.03747"},"observation_digest":"sha256:11f82733b8c0850f3b8aeb9e5ecc3b4c81524451837fef6240f9be21e21c64fc","observation_id":"1b6fde56-a89d-4375-9b00-cfb5f2ddfbd3","resolution":{"observed_at":"2026-05-13T17:13:01.855215Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-05T06:32:48.257954+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-05T06:32:48.257954+00:00","source":"crossref"},{"observed_at":"2026-08-05T06:32:44.755628+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":"2026-06-05T21:23:00.469572Z","title":"Liwo: Lidar-inertial-wheel odometry","venue":null,"work_id":"ec851802-c017-4f9d-ae52-59bb9d98eef1","year":2023},"citing_paper":{"arxiv_id":"2604.03747","last_updated":"2026-04-04T14:27:54Z","snapshot_observed_at":"2026-08-04T20:18:53.390138Z","submitted_at":"2026-04-04T14:27:54Z","title":"CT-VoxelMap: Efficient Continuous-Time LiDAR-Inertial Odometry with Probabilistic Adaptive Voxel Mapping","version":1},"reference_index":7,"source":"pdf_text","source_observed_at":"2026-05-13T17:11:52.457688Z"},"links":{"citing_paper":"/paper/2604.03747"},"observation_digest":"sha256:74ee486f82df24a6517e0dd76d91d35a08accf6a3f55ec803defe8a36e7b52f6","observation_id":"07be0a7b-e91a-4c36-a0a6-0ddb2d6bd159","resolution":{"observed_at":"2026-05-13T17:13:01.867559Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-05T06:32:48.257954+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-05T06:32:48.257954+00:00","source":"crossref"},{"observed_at":"2026-08-05T06:32:44.755628+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":"2026-06-05T21:23:00.469572Z","title":"Lic-fusion: Lidar- inertial-camera odometry","venue":null,"work_id":"9ad576d1-8321-48b8-8adc-5107f53e17e3","year":2019},"citing_paper":{"arxiv_id":"2604.03747","last_updated":"2026-04-04T14:27:54Z","snapshot_observed_at":"2026-08-04T20:18:53.390138Z","submitted_at":"2026-04-04T14:27:54Z","title":"CT-VoxelMap: Efficient Continuous-Time LiDAR-Inertial Odometry with Probabilistic Adaptive Voxel Mapping","version":1},"reference_index":8,"source":"pdf_text","source_observed_at":"2026-05-13T17:11:52.457688Z"},"links":{"citing_paper":"/paper/2604.03747"},"observation_digest":"sha256:f92efd243469e3005f97d12b407e0b53328d9ce79663364003be2a619b6a2a8c","observation_id":"db668952-4e11-47f0-8fa6-af40b48ddc8e","resolution":{"observed_at":"2026-05-13T17:13:01.873342Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-05T06:32:48.257954+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-05T06:32:48.257954+00:00","source":"crossref"},{"observed_at":"2026-08-05T06:32:44.755628+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":"2026-06-05T21:23:00.469572Z","title":"Lic-fusion 2.0: Lidar-inertial-camera odometry with sliding-window plane-feature tracking","venue":null,"work_id":"93cee817-0a16-4442-95db-d89a2bc509ee","year":2020},"citing_paper":{"arxiv_id":"2604.03747","last_updated":"2026-04-04T14:27:54Z","snapshot_observed_at":"2026-08-04T20:18:53.390138Z","submitted_at":"2026-04-04T14:27:54Z","title":"CT-VoxelMap: Efficient Continuous-Time LiDAR-Inertial Odometry with Probabilistic Adaptive Voxel Mapping","version":1},"reference_index":9,"source":"pdf_text","source_observed_at":"2026-05-13T17:11:52.457688Z"},"links":{"citing_paper":"/paper/2604.03747"},"observation_digest":"sha256:dd2ffc48ace6d52ffa6bfd9dfbe0c0b9b7dc35efc9f8be93ad895151dfda4ac0","observation_id":"4f428baf-c440-43f0-8c3f-36eb43a22545","resolution":{"observed_at":"2026-05-13T17:13:01.877393Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-05T06:32:48.257954+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-05T06:32:48.257954+00:00","source":"crossref"},{"observed_at":"2026-08-05T06:32:44.755628+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":"2026-06-05T21:23:00.469572Z","title":"Fast-livo: Fast and tightly-coupled sparse-direct lidar-inertial-visual odometry","venue":null,"work_id":"9951d598-5b25-46f5-8053-67e47b7994fc","year":2022},"citing_paper":{"arxiv_id":"2604.03747","last_updated":"2026-04-04T14:27:54Z","snapshot_observed_at":"2026-08-04T20:18:53.390138Z","submitted_at":"2026-04-04T14:27:54Z","title":"CT-VoxelMap: Efficient Continuous-Time LiDAR-Inertial Odometry with Probabilistic Adaptive Voxel Mapping","version":1},"reference_index":10,"source":"pdf_text","source_observed_at":"2026-05-13T17:11:52.457688Z"},"links":{"citing_paper":"/paper/2604.03747"},"observation_digest":"sha256:278967bdac05c813384a2c42b2134c0b323a9a10cb0f9126b2ab66997bd90d19","observation_id":"0cd48042-ebf8-4edf-9b3c-6e3d4658df1c","resolution":{"observed_at":"2026-05-13T17:13:01.887666Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-05T06:32:48.257954+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-05T06:32:48.257954+00:00","source":"crossref"},{"observed_at":"2026-08-05T06:32:44.755628+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":"2026-07-08T13:04:57.225815Z","title":"Fast-lio: A fast, robust lidar-inertial odometry package by tightly-coupled iterated kalman filter","venue":null,"work_id":"77e4e21a-bf51-4daf-b73d-d064a9afd4bd","year":2021},"citing_paper":{"arxiv_id":"2604.03747","last_updated":"2026-04-04T14:27:54Z","snapshot_observed_at":"2026-08-04T20:18:53.390138Z","submitted_at":"2026-04-04T14:27:54Z","title":"CT-VoxelMap: Efficient Continuous-Time LiDAR-Inertial Odometry with Probabilistic Adaptive Voxel Mapping","version":1},"reference_index":11,"source":"pdf_text","source_observed_at":"2026-05-13T17:11:52.457688Z"},"links":{"citing_paper":"/paper/2604.03747"},"observation_digest":"sha256:21cea5825ae8564b3bdf94a755f19264734a3a2b28777c09608a61df5cc0f917","observation_id":"bd74a21c-6502-4c33-8c6d-5c6d621f000a","resolution":{"observed_at":"2026-05-13T17:13:01.889549Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-05T06:32:48.257954+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-05T06:32:48.257954+00:00","source":"crossref"},{"observed_at":"2026-08-05T06:32:44.755628+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":"2026-06-05T21:23:00.469572Z","title":"Lego-loam: Lightweight and ground-optimized lidar odometry and mapping on variable terrain","venue":null,"work_id":"0b4f356e-4578-4491-bbb4-4a51f0620ba0","year":2018},"citing_paper":{"arxiv_id":"2604.03747","last_updated":"2026-04-04T14:27:54Z","snapshot_observed_at":"2026-08-04T20:18:53.390138Z","submitted_at":"2026-04-04T14:27:54Z","title":"CT-VoxelMap: Efficient Continuous-Time LiDAR-Inertial Odometry with Probabilistic Adaptive Voxel Mapping","version":1},"reference_index":12,"source":"pdf_text","source_observed_at":"2026-05-13T17:11:52.457688Z"},"links":{"citing_paper":"/paper/2604.03747"},"observation_digest":"sha256:14ac0be23133707950c2cfeac471ccffbee2c70598bf5f1db0a71aa229c877f3","observation_id":"f2cc8083-316a-4099-9616-906625280299","resolution":{"observed_at":"2026-05-13T17:13:01.884754Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-05T06:32:48.257954+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-05T06:32:48.257954+00:00","source":"crossref"},{"observed_at":"2026-08-05T06:32:44.755628+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":"2026-06-05T21:23:00.469572Z","title":"Fast-livo2: Fast, direct lidar–inertial–visual odometry","venue":null,"work_id":"51db34f2-5534-4fef-b7c8-a2dfdbaa6ad1","year":2025},"citing_paper":{"arxiv_id":"2604.03747","last_updated":"2026-04-04T14:27:54Z","snapshot_observed_at":"2026-08-04T20:18:53.390138Z","submitted_at":"2026-04-04T14:27:54Z","title":"CT-VoxelMap: Efficient Continuous-Time LiDAR-Inertial Odometry with Probabilistic Adaptive Voxel Mapping","version":1},"reference_index":13,"source":"pdf_text","source_observed_at":"2026-05-13T17:11:52.457688Z"},"links":{"citing_paper":"/paper/2604.03747"},"observation_digest":"sha256:e9d2de807bc3414b4b7d0536b8565fd3dd8b9cbec43a70675e566da87713ac23","observation_id":"9aab4b44-3e3b-4cda-9f09-c2c82dcb94c7","resolution":{"observed_at":"2026-05-13T17:13:01.881222Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-05T06:32:48.257954+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-05T06:32:48.257954+00:00","source":"crossref"},{"observed_at":"2026-08-05T06:32:44.755628+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":"2026-06-05T21:23:00.469572Z","title":"Continuous- time fixed-lag smoothing for lidar-inertial-camera slam","venue":null,"work_id":"e503298b-ce35-4a00-8dec-6fd9c68d36a9","year":2023},"citing_paper":{"arxiv_id":"2604.03747","last_updated":"2026-04-04T14:27:54Z","snapshot_observed_at":"2026-08-04T20:18:53.390138Z","submitted_at":"2026-04-04T14:27:54Z","title":"CT-VoxelMap: Efficient Continuous-Time LiDAR-Inertial Odometry with Probabilistic Adaptive Voxel Mapping","version":1},"reference_index":14,"source":"pdf_text","source_observed_at":"2026-05-13T17:11:52.457688Z"},"links":{"citing_paper":"/paper/2604.03747"},"observation_digest":"sha256:76bdac61d7b021771e80cc9ea637bad5730bfa7c55de7c94971a1b05c3f67553","observation_id":"8bbe2da7-5b90-4cf2-9910-d08879dc9ed9","resolution":{"observed_at":"2026-05-13T17:13:01.883042Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-05T06:32:48.257954+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-05T06:32:48.257954+00:00","source":"crossref"},{"observed_at":"2026-08-05T06:32:44.755628+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":"2026-06-05T21:23:00.469572Z","title":"Lio-sam: Tightly-coupled lidar inertial odometry via smoothing and mapping","venue":null,"work_id":"4225f52c-4333-43b3-90c5-da612dcf7877","year":2020},"citing_paper":{"arxiv_id":"2604.03747","last_updated":"2026-04-04T14:27:54Z","snapshot_observed_at":"2026-08-04T20:18:53.390138Z","submitted_at":"2026-04-04T14:27:54Z","title":"CT-VoxelMap: Efficient Continuous-Time LiDAR-Inertial Odometry with Probabilistic Adaptive Voxel Mapping","version":1},"reference_index":15,"source":"pdf_text","source_observed_at":"2026-05-13T17:11:52.457688Z"},"links":{"citing_paper":"/paper/2604.03747"},"observation_digest":"sha256:2536dce925f82ab4ffbe92efcd1eca5ec8ac0f8061b82c9c2858533f9a546e63","observation_id":"cf105e8a-e460-4f25-a965-66c43639ab81","resolution":{"observed_at":"2026-05-13T17:13:01.879395Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-05T06:32:48.257954+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-05T06:32:48.257954+00:00","source":"crossref"},{"observed_at":"2026-08-05T06:32:44.755628+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":"2026-06-05T21:23:00.469572Z","title":"Traj-lo: In defense of lidar-only odometry using an effective continuous-time trajectory","venue":null,"work_id":"fe36a1bd-6e59-4eb4-9fc6-472bc190f9ad","year":1961},"citing_paper":{"arxiv_id":"2604.03747","last_updated":"2026-04-04T14:27:54Z","snapshot_observed_at":"2026-08-04T20:18:53.390138Z","submitted_at":"2026-04-04T14:27:54Z","title":"CT-VoxelMap: Efficient Continuous-Time LiDAR-Inertial Odometry with Probabilistic Adaptive Voxel Mapping","version":1},"reference_index":16,"source":"pdf_text","source_observed_at":"2026-05-13T17:11:52.457688Z"},"links":{"citing_paper":"/paper/2604.03747"},"observation_digest":"sha256:5657d4d86446bbe7f559d2ce3ce9ce97215db573fc9ba615d5e21fb9adcabc18","observation_id":"0daea98d-a27b-4c5e-a283-7ad943a3ad5d","resolution":{"observed_at":"2026-05-13T17:13:01.853229Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-05T06:32:48.257954+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-05T06:32:48.257954+00:00","source":"crossref"},{"observed_at":"2026-08-05T06:32:44.755628+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":"2026-06-05T21:23:00.469572Z","title":"Ct-icp: Real-time elastic lidar odometry with loop closure","venue":null,"work_id":"16247c5e-f8c7-460b-a78a-726120a8ea69","year":2022},"citing_paper":{"arxiv_id":"2604.03747","last_updated":"2026-04-04T14:27:54Z","snapshot_observed_at":"2026-08-04T20:18:53.390138Z","submitted_at":"2026-04-04T14:27:54Z","title":"CT-VoxelMap: Efficient Continuous-Time LiDAR-Inertial Odometry with Probabilistic Adaptive Voxel Mapping","version":1},"reference_index":17,"source":"pdf_text","source_observed_at":"2026-05-13T17:11:52.457688Z"},"links":{"citing_paper":"/paper/2604.03747"},"observation_digest":"sha256:4cddf1509c410f55ecafb42bee1ed6b4685acba63e43aef5066267a3ff19b142","observation_id":"8aaf9f0b-3ff3-4bea-b140-6b7caf3a7dae","resolution":{"observed_at":"2026-05-13T17:13:01.869481Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-05T06:32:48.257954+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-05T06:32:48.257954+00:00","source":"crossref"},{"observed_at":"2026-08-05T06:32:44.755628+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":"2026-06-05T21:23:00.469572Z","title":"Continuous-time state estimation methods in robotics: A survey","venue":null,"work_id":"9ea77692-f0fa-446f-a8a3-838a941b8868","year":2025},"citing_paper":{"arxiv_id":"2604.03747","last_updated":"2026-04-04T14:27:54Z","snapshot_observed_at":"2026-08-04T20:18:53.390138Z","submitted_at":"2026-04-04T14:27:54Z","title":"CT-VoxelMap: Efficient Continuous-Time LiDAR-Inertial Odometry with Probabilistic Adaptive Voxel Mapping","version":1},"reference_index":18,"source":"pdf_text","source_observed_at":"2026-05-13T17:11:52.457688Z"},"links":{"citing_paper":"/paper/2604.03747"},"observation_digest":"sha256:29d609522c73f0bb3a257f0c81d2e5fbbecf490c27e919d9f5dcfdb9d544fde8","observation_id":"44728b72-1187-4cca-ae3c-9b1295301c0b","resolution":{"observed_at":"2026-05-13T17:13:01.871492Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-05T06:32:48.257954+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-05T06:32:48.257954+00:00","source":"crossref"},{"observed_at":"2026-08-05T06:32:44.755628+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":"2026-06-05T21:23:00.469572Z","title":"Gaussian process gauss– newton for non-parametric simultaneous localization and mapping","venue":null,"work_id":"c4b567f2-172f-4a74-8efd-a1f26e4a6783","year":2013},"citing_paper":{"arxiv_id":"2604.03747","last_updated":"2026-04-04T14:27:54Z","snapshot_observed_at":"2026-08-04T20:18:53.390138Z","submitted_at":"2026-04-04T14:27:54Z","title":"CT-VoxelMap: Efficient Continuous-Time LiDAR-Inertial Odometry with Probabilistic Adaptive Voxel Mapping","version":1},"reference_index":19,"source":"pdf_text","source_observed_at":"2026-05-13T17:11:52.457688Z"},"links":{"citing_paper":"/paper/2604.03747"},"observation_digest":"sha256:b4c630873c98243efd67d34985915838524782f59da66c195785acfcef98b54c","observation_id":"d3e64bda-4a3a-40ff-b539-0ed906decd53","resolution":{"observed_at":"2026-05-13T17:13:01.875481Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-05T06:32:48.257954+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-05T06:32:48.257954+00:00","source":"crossref"},{"observed_at":"2026-08-05T06:32:44.755628+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":"2026-06-05T21:23:00.469572Z","title":"Batch continuous-time trajectory estimation as exactly sparse gaussian process regression","venue":null,"work_id":"32f91681-5411-403d-adbe-15fac11f795a","year":2014},"citing_paper":{"arxiv_id":"2604.03747","last_updated":"2026-04-04T14:27:54Z","snapshot_observed_at":"2026-08-04T20:18:53.390138Z","submitted_at":"2026-04-04T14:27:54Z","title":"CT-VoxelMap: Efficient Continuous-Time LiDAR-Inertial Odometry with Probabilistic Adaptive Voxel Mapping","version":1},"reference_index":20,"source":"pdf_text","source_observed_at":"2026-05-13T17:11:52.457688Z"},"links":{"citing_paper":"/paper/2604.03747"},"observation_digest":"sha256:9401191869c6b0c71c9d7293caa0574c8f7cee1ae136155f3670ff7d9cb1b2b7","observation_id":"2e43dd34-cf98-4727-a4e4-7cadd751103f","resolution":{"observed_at":"2026-05-13T17:13:01.905719Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-05T06:32:48.257954+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-05T06:32:48.257954+00:00","source":"crossref"},{"observed_at":"2026-08-05T06:32:44.755628+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"1705.06020","last_updated":"2017-05-17T06:09:52Z","snapshot_observed_at":"2026-07-06T05:43:00.217098Z","submitted_at":"2017-05-17T06:09:52Z","title":"Sparse Gaussian Processes for Continuous-Time Trajectory Estimation on Matrix Lie Groups","version":1},"cited_work":{"arxiv_id":"1705.06020","doi":null,"metadata_source":"pith","pith_arxiv_id":"1705.06020","snapshot_observed_at":"2026-06-05T21:23:00.469572Z","title":"Sparse Gaussian Processes for Continuous-Time Trajectory Estimation on Matrix Lie Groups","venue":"cs.RO","work_id":"1d1e7572-48fd-424d-9197-5e9a5420df2a","year":2017},"citing_paper":{"arxiv_id":"2604.03747","last_updated":"2026-04-04T14:27:54Z","snapshot_observed_at":"2026-08-04T20:18:53.390138Z","submitted_at":"2026-04-04T14:27:54Z","title":"CT-VoxelMap: Efficient Continuous-Time LiDAR-Inertial Odometry with Probabilistic Adaptive Voxel Mapping","version":1},"reference_index":21,"source":"pdf_text","source_observed_at":"2026-05-13T17:11:52.457688Z"},"links":{"cited_paper":"/paper/1705.06020","citing_paper":"/paper/2604.03747"},"observation_digest":"sha256:d66332e0ce303c23a22de99b1dee80b1b5b69ce0ac060fdb44f2f0ab7771dcf0","observation_id":"9bedef87-fc49-453f-859a-46b7e69cc23c","resolution":{"observed_at":"2026-05-13T17:13:01.135459Z","resolver_source":"arxiv_id","status":"verified_exact"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-05T06:32:48.257954+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-05T06:32:48.257954+00:00","source":"crossref"},{"observed_at":"2026-08-05T06:32:44.755628+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":"2026-06-05T21:23:00.469572Z","title":"The numerical evaluation of b-splines","venue":null,"work_id":"c4267fc5-33f8-47a1-b96c-15039f26e38d","year":1972},"citing_paper":{"arxiv_id":"2604.03747","last_updated":"2026-04-04T14:27:54Z","snapshot_observed_at":"2026-08-04T20:18:53.390138Z","submitted_at":"2026-04-04T14:27:54Z","title":"CT-VoxelMap: Efficient Continuous-Time LiDAR-Inertial Odometry with Probabilistic Adaptive Voxel Mapping","version":1},"reference_index":22,"source":"pdf_text","source_observed_at":"2026-05-13T17:11:52.457688Z"},"links":{"citing_paper":"/paper/2604.03747"},"observation_digest":"sha256:2f0bfd49ee8ce73722def21d098b7913394ff881c98ce1f980f1284f35c14810","observation_id":"6d79a59d-0c99-4c4f-b7cc-7b4465e248a2","resolution":{"observed_at":"2026-05-13T17:13:01.950092Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-05T06:32:48.257954+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-05T06:32:48.257954+00:00","source":"crossref"},{"observed_at":"2026-08-05T06:32:44.755628+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":"2026-06-05T21:23:00.469572Z","title":"On calculating with b-splines","venue":null,"work_id":"8d3a7cab-efda-414a-832d-e73ff094194b","year":1972},"citing_paper":{"arxiv_id":"2604.03747","last_updated":"2026-04-04T14:27:54Z","snapshot_observed_at":"2026-08-04T20:18:53.390138Z","submitted_at":"2026-04-04T14:27:54Z","title":"CT-VoxelMap: Efficient Continuous-Time LiDAR-Inertial Odometry with Probabilistic Adaptive Voxel Mapping","version":1},"reference_index":23,"source":"pdf_text","source_observed_at":"2026-05-13T17:11:52.457688Z"},"links":{"citing_paper":"/paper/2604.03747"},"observation_digest":"sha256:f4a95f42659d26d82b29b0189b6a6b08981f319444f1f2602ba0fb9b887728de","observation_id":"835c30f9-cb52-426b-a9c2-3dc442339024","resolution":{"observed_at":"2026-05-13T17:13:01.945909Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-05T06:32:48.257954+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-05T06:32:48.257954+00:00","source":"crossref"},{"observed_at":"2026-08-05T06:32:44.755628+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":"2026-06-05T21:23:00.469572Z","title":"Efficient derivative computation for cumulative b-splines on lie groups","venue":null,"work_id":"8219ddc9-6598-455b-9960-49055a370e62","year":2020},"citing_paper":{"arxiv_id":"2604.03747","last_updated":"2026-04-04T14:27:54Z","snapshot_observed_at":"2026-08-04T20:18:53.390138Z","submitted_at":"2026-04-04T14:27:54Z","title":"CT-VoxelMap: Efficient Continuous-Time LiDAR-Inertial Odometry with Probabilistic Adaptive Voxel Mapping","version":1},"reference_index":24,"source":"pdf_text","source_observed_at":"2026-05-13T17:11:52.457688Z"},"links":{"citing_paper":"/paper/2604.03747"},"observation_digest":"sha256:ddee665131eb2b9dd56d1909b0a212f3ae2c160213227b5711bc47e922bae7fd","observation_id":"2e9f45d1-d89e-4cba-97b9-e935b526ecf9","resolution":{"observed_at":"2026-05-13T17:13:01.943767Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-05T06:32:48.257954+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-05T06:32:48.257954+00:00","source":"crossref"},{"observed_at":"2026-08-05T06:32:44.755628+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":"2026-06-05T21:23:00.469572Z","title":"Clins: Continuous- time trajectory estimation for lidar-inertial system","venue":null,"work_id":"9e4c91a3-699a-4b75-980c-f0535ab2df6a","year":2021},"citing_paper":{"arxiv_id":"2604.03747","last_updated":"2026-04-04T14:27:54Z","snapshot_observed_at":"2026-08-04T20:18:53.390138Z","submitted_at":"2026-04-04T14:27:54Z","title":"CT-VoxelMap: Efficient Continuous-Time LiDAR-Inertial Odometry with Probabilistic Adaptive Voxel Mapping","version":1},"reference_index":25,"source":"pdf_text","source_observed_at":"2026-05-13T17:11:52.457688Z"},"links":{"citing_paper":"/paper/2604.03747"},"observation_digest":"sha256:28108808a40c23f367d4e7704da3271fc4880f0fc1e886f4e61896188731ddd0","observation_id":"d7c92723-f0ae-440e-a8c6-2836fc379595","resolution":{"observed_at":"2026-05-13T17:13:01.897567Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-05T06:32:48.257954+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-05T06:32:48.257954+00:00","source":"crossref"},{"observed_at":"2026-08-05T06:32:44.755628+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":"2026-06-05T21:23:00.469572Z","title":"Eigen is all you need: Efficient lidar-inertial continuous-time odometry with internal association","venue":null,"work_id":"291171eb-42b8-4edd-a1d1-f435e06c395e","year":2024},"citing_paper":{"arxiv_id":"2604.03747","last_updated":"2026-04-04T14:27:54Z","snapshot_observed_at":"2026-08-04T20:18:53.390138Z","submitted_at":"2026-04-04T14:27:54Z","title":"CT-VoxelMap: Efficient Continuous-Time LiDAR-Inertial Odometry with Probabilistic Adaptive Voxel Mapping","version":1},"reference_index":26,"source":"pdf_text","source_observed_at":"2026-05-13T17:11:52.457688Z"},"links":{"citing_paper":"/paper/2604.03747"},"observation_digest":"sha256:6a9cf72f43e290ab061de8c04d3976f7fbf2c3b60b04b11648f97e197668e53e","observation_id":"7fb4fd94-da69-48c0-a999-ae815b3c87ce","resolution":{"observed_at":"2026-05-13T17:13:01.937299Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-05T06:32:48.257954+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-05T06:32:48.257954+00:00","source":"crossref"},{"observed_at":"2026-08-05T06:32:44.755628+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":"2026-06-05T21:23:00.469572Z","title":"Resple: Recursive spline estimation for lidar-based odometry","venue":null,"work_id":"ad684b9f-3450-4a77-8e86-a828209ffa68","year":2025},"citing_paper":{"arxiv_id":"2604.03747","last_updated":"2026-04-04T14:27:54Z","snapshot_observed_at":"2026-08-04T20:18:53.390138Z","submitted_at":"2026-04-04T14:27:54Z","title":"CT-VoxelMap: Efficient Continuous-Time LiDAR-Inertial Odometry with Probabilistic Adaptive Voxel Mapping","version":1},"reference_index":27,"source":"pdf_text","source_observed_at":"2026-05-13T17:11:52.457688Z"},"links":{"citing_paper":"/paper/2604.03747"},"observation_digest":"sha256:dbf77f0d114e398ff6978dc62721008500de9cba27dfb1bd71702bc1b1ee7ff4","observation_id":"933d6b42-c2ad-494c-ab7a-02180487f9a5","resolution":{"observed_at":"2026-05-13T17:13:01.952088Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-05T06:32:48.257954+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-05T06:32:48.257954+00:00","source":"crossref"},{"observed_at":"2026-08-05T06:32:44.755628+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":"2026-06-05T21:23:00.469572Z","title":"Mars-lvig dataset: A multi-sensor aerial robots slam dataset for lidar-visual-inertial-gnss fusion","venue":null,"work_id":"93affff1-3adf-43f9-a88b-e5f36676e299","year":2024},"citing_paper":{"arxiv_id":"2604.03747","last_updated":"2026-04-04T14:27:54Z","snapshot_observed_at":"2026-08-04T20:18:53.390138Z","submitted_at":"2026-04-04T14:27:54Z","title":"CT-VoxelMap: Efficient Continuous-Time LiDAR-Inertial Odometry with Probabilistic Adaptive Voxel Mapping","version":1},"reference_index":28,"source":"pdf_text","source_observed_at":"2026-05-13T17:11:52.457688Z"},"links":{"citing_paper":"/paper/2604.03747"},"observation_digest":"sha256:011f16f80eff74541e9bf05cb9a61a6ec90b58e4d8fa236ea6b4092f47876e1c","observation_id":"44bb17d8-7e7f-4f67-b831-f67575aee071","resolution":{"observed_at":"2026-05-13T17:13:01.939586Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-05T06:32:48.257954+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-05T06:32:48.257954+00:00","source":"crossref"},{"observed_at":"2026-08-05T06:32:44.755628+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":"2026-06-05T21:23:00.469572Z","title":"M2ud: A multi-model, multi-scenario, uneven-terrain dataset for ground robot with localization and mapping evaluation","venue":null,"work_id":"06f6f9d7-e6e9-44aa-9c92-e125671ab7d0","year":2025},"citing_paper":{"arxiv_id":"2604.03747","last_updated":"2026-04-04T14:27:54Z","snapshot_observed_at":"2026-08-04T20:18:53.390138Z","submitted_at":"2026-04-04T14:27:54Z","title":"CT-VoxelMap: Efficient Continuous-Time LiDAR-Inertial Odometry with Probabilistic Adaptive Voxel Mapping","version":1},"reference_index":29,"source":"pdf_text","source_observed_at":"2026-05-13T17:11:52.457688Z"},"links":{"citing_paper":"/paper/2604.03747"},"observation_digest":"sha256:399b04963f8a1c29e0fece811508af9ace88d44e5d5d99b5e66ff8b234183939","observation_id":"92931b2d-1ead-4de8-b109-43568bfdd9cf","resolution":{"observed_at":"2026-05-13T17:13:01.903790Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-05T06:32:48.257954+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-05T06:32:48.257954+00:00","source":"crossref"},{"observed_at":"2026-08-05T06:32:44.755628+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":"2026-06-05T21:23:00.469572Z","title":"Mcd: Diverse large-scale multi-campus dataset for robot perception","venue":null,"work_id":"9debb0ba-9fa3-4f4d-9e34-43321cddfc34","year":2024},"citing_paper":{"arxiv_id":"2604.03747","last_updated":"2026-04-04T14:27:54Z","snapshot_observed_at":"2026-08-04T20:18:53.390138Z","submitted_at":"2026-04-04T14:27:54Z","title":"CT-VoxelMap: Efficient Continuous-Time LiDAR-Inertial Odometry with Probabilistic Adaptive Voxel Mapping","version":1},"reference_index":30,"source":"pdf_text","source_observed_at":"2026-05-13T17:11:52.457688Z"},"links":{"citing_paper":"/paper/2604.03747"},"observation_digest":"sha256:94531e3917597d7bce46d5fd2e93bc410bb17f896e8cfa17ab7a3fd84c9e0281","observation_id":"585938c2-1992-47e4-814f-3e88c6214a75","resolution":{"observed_at":"2026-05-13T17:13:01.935292Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-05T06:32:48.257954+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-05T06:32:48.257954+00:00","source":"crossref"},{"observed_at":"2026-08-05T06:32:44.755628+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":"2026-06-05T21:23:00.469572Z","title":"Diter++: Diverse terrain and multi-modal dataset for multi-robot slam in multi-session environments","venue":null,"work_id":"b2564b45-5377-4688-9380-d5d152c54daa","year":2025},"citing_paper":{"arxiv_id":"2604.03747","last_updated":"2026-04-04T14:27:54Z","snapshot_observed_at":"2026-08-04T20:18:53.390138Z","submitted_at":"2026-04-04T14:27:54Z","title":"CT-VoxelMap: Efficient Continuous-Time LiDAR-Inertial Odometry with Probabilistic Adaptive Voxel Mapping","version":1},"reference_index":31,"source":"pdf_text","source_observed_at":"2026-05-13T17:11:52.457688Z"},"links":{"citing_paper":"/paper/2604.03747"},"observation_digest":"sha256:c47e96c949a154ad669233a6883c143ddc9e41830d8cbe3594c0d2407c9dc84a","observation_id":"f77d09a0-00c4-4d1d-8669-425e64167cbf","resolution":{"observed_at":"2026-05-13T17:13:01.933008Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-05T06:32:48.257954+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-05T06:32:48.257954+00:00","source":"crossref"},{"observed_at":"2026-08-05T06:32:44.755628+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":"2026-06-05T21:23:00.469572Z","title":"A flexible and scalable slam system with full 3d motion estimation","venue":null,"work_id":"60bbcbe9-d61a-4e2c-aa75-42158273b56a","year":2011},"citing_paper":{"arxiv_id":"2604.03747","last_updated":"2026-04-04T14:27:54Z","snapshot_observed_at":"2026-08-04T20:18:53.390138Z","submitted_at":"2026-04-04T14:27:54Z","title":"CT-VoxelMap: Efficient Continuous-Time LiDAR-Inertial Odometry with Probabilistic Adaptive Voxel Mapping","version":1},"reference_index":32,"source":"pdf_text","source_observed_at":"2026-05-13T17:11:52.457688Z"},"links":{"citing_paper":"/paper/2604.03747"},"observation_digest":"sha256:6aeb38513655d10995ccb63bd1742e8385df9a9bb9df4a24a1fb5c6568ccea7c","observation_id":"fcfa9fc1-55a8-4dd3-bd07-a9d6c5696f11","resolution":{"observed_at":"2026-05-13T17:13:01.893386Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-05T06:32:48.257954+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-05T06:32:48.257954+00:00","source":"crossref"},{"observed_at":"2026-08-05T06:32:44.755628+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":"2026-06-05T21:23:00.469572Z","title":"Loam: Lidar odometry and mapping in real- time","venue":null,"work_id":"fcc190a5-d839-4bbd-8a74-e49e66ae9089","year":2014},"citing_paper":{"arxiv_id":"2604.03747","last_updated":"2026-04-04T14:27:54Z","snapshot_observed_at":"2026-08-04T20:18:53.390138Z","submitted_at":"2026-04-04T14:27:54Z","title":"CT-VoxelMap: Efficient Continuous-Time LiDAR-Inertial Odometry with Probabilistic Adaptive Voxel Mapping","version":1},"reference_index":33,"source":"pdf_text","source_observed_at":"2026-05-13T17:11:52.457688Z"},"links":{"citing_paper":"/paper/2604.03747"},"observation_digest":"sha256:a2370c3b13e7e58b2e391a6c5bbe494e61bdbb5b89c26589358aef2ffa79a9dc","observation_id":"b8fdceaa-bb91-4eda-a4c3-31a36b1da3da","resolution":{"observed_at":"2026-05-13T17:13:01.948029Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-05T06:32:48.257954+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-05T06:32:48.257954+00:00","source":"crossref"},{"observed_at":"2026-08-05T06:32:44.755628+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":"2026-06-05T21:23:00.469572Z","title":"Ekf-loam: An adaptive fusion of lidar slam with wheel odometry and inertial data for confined spaces with few geometric features","venue":null,"work_id":"d441b088-d2f0-4267-9018-364689b588f0","year":2022},"citing_paper":{"arxiv_id":"2604.03747","last_updated":"2026-04-04T14:27:54Z","snapshot_observed_at":"2026-08-04T20:18:53.390138Z","submitted_at":"2026-04-04T14:27:54Z","title":"CT-VoxelMap: Efficient Continuous-Time LiDAR-Inertial Odometry with Probabilistic Adaptive Voxel Mapping","version":1},"reference_index":34,"source":"pdf_text","source_observed_at":"2026-05-13T17:11:52.457688Z"},"links":{"citing_paper":"/paper/2604.03747"},"observation_digest":"sha256:519ad652e5e1a542fc620293c21bb249b8bf4dcb2d2d3a668b52432a320339db","observation_id":"701b9049-d603-4c83-845d-d1947ab06165","resolution":{"observed_at":"2026-05-13T17:13:01.915287Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-05T06:32:48.257954+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-05T06:32:48.257954+00:00","source":"crossref"},{"observed_at":"2026-08-05T06:32:44.755628+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":"2026-06-05T21:23:00.469572Z","title":"A multi-state constraint kalman filter for vision-aided inertial navigation","venue":null,"work_id":"aac15403-5f94-4c54-b3e5-cd9f79579f52","year":2007},"citing_paper":{"arxiv_id":"2604.03747","last_updated":"2026-04-04T14:27:54Z","snapshot_observed_at":"2026-08-04T20:18:53.390138Z","submitted_at":"2026-04-04T14:27:54Z","title":"CT-VoxelMap: Efficient Continuous-Time LiDAR-Inertial Odometry with Probabilistic Adaptive Voxel Mapping","version":1},"reference_index":35,"source":"pdf_text","source_observed_at":"2026-05-13T17:11:52.457688Z"},"links":{"citing_paper":"/paper/2604.03747"},"observation_digest":"sha256:4a299c0f8d4d18ada53222121e9373161d481b51025e30750f5ee729ee051f18","observation_id":"e20f8502-9e7e-4914-b80b-e7b060b1d442","resolution":{"observed_at":"2026-05-13T17:13:01.909290Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-05T06:32:48.257954+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-05T06:32:48.257954+00:00","source":"crossref"},{"observed_at":"2026-08-05T06:32:44.755628+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":"2026-06-05T21:23:00.469572Z","title":"High-precision, consistent ekf-based visual- inertial odometry","venue":null,"work_id":"c99c40da-5a96-4483-8c5a-1211000a4c10","year":2013},"citing_paper":{"arxiv_id":"2604.03747","last_updated":"2026-04-04T14:27:54Z","snapshot_observed_at":"2026-08-04T20:18:53.390138Z","submitted_at":"2026-04-04T14:27:54Z","title":"CT-VoxelMap: Efficient Continuous-Time LiDAR-Inertial Odometry with Probabilistic Adaptive Voxel Mapping","version":1},"reference_index":36,"source":"pdf_text","source_observed_at":"2026-05-13T17:11:52.457688Z"},"links":{"citing_paper":"/paper/2604.03747"},"observation_digest":"sha256:b9e8525bd34da2cb64abe52aed661414fce4ecac0b1b6c954cfa04d975a98e25","observation_id":"7f335f54-1dde-42e4-b7bf-beca41b9d98f","resolution":{"observed_at":"2026-05-13T17:13:01.913092Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-05T06:32:48.257954+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-05T06:32:48.257954+00:00","source":"crossref"},{"observed_at":"2026-08-05T06:32:44.755628+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":"2026-06-05T21:23:00.469572Z","title":"Fast-lio2: Fast direct lidar-inertial odometry","venue":null,"work_id":"428a22ba-0419-4cf4-bfa3-d76464d6e3cc","year":2053},"citing_paper":{"arxiv_id":"2604.03747","last_updated":"2026-04-04T14:27:54Z","snapshot_observed_at":"2026-08-04T20:18:53.390138Z","submitted_at":"2026-04-04T14:27:54Z","title":"CT-VoxelMap: Efficient Continuous-Time LiDAR-Inertial Odometry with Probabilistic Adaptive Voxel Mapping","version":1},"reference_index":37,"source":"pdf_text","source_observed_at":"2026-05-13T17:11:52.457688Z"},"links":{"citing_paper":"/paper/2604.03747"},"observation_digest":"sha256:e50662b0e07c1cfa54373ca7faca7411ce6a6118364b386cb107bfe87899b71d","observation_id":"5feea8e6-9a05-4828-9c5b-7703fa97fb51","resolution":{"observed_at":"2026-05-13T17:13:01.907503Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-05T06:32:48.257954+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-05T06:32:48.257954+00:00","source":"crossref"},{"observed_at":"2026-08-05T06:32:44.755628+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":"2026-07-07T21:14:08.912680Z","title":"Efficient and probabilistic adaptive voxel mapping for accurate online lidar odometry","venue":null,"work_id":"83b2b6b4-4074-475a-abb9-568cb21b6eb7","year":2022},"citing_paper":{"arxiv_id":"2604.03747","last_updated":"2026-04-04T14:27:54Z","snapshot_observed_at":"2026-08-04T20:18:53.390138Z","submitted_at":"2026-04-04T14:27:54Z","title":"CT-VoxelMap: Efficient Continuous-Time LiDAR-Inertial Odometry with Probabilistic Adaptive Voxel Mapping","version":1},"reference_index":38,"source":"pdf_text","source_observed_at":"2026-05-13T17:11:52.457688Z"},"links":{"citing_paper":"/paper/2604.03747"},"observation_digest":"sha256:b1b6b429c2a0fa3de53eda456e0d05f6d5620abc1ad5cf321bae68b24a6d50a8","observation_id":"db6eb6f1-de60-4071-9e31-5db8f4bad275","resolution":{"observed_at":"2026-05-13T17:13:01.911327Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-05T06:32:48.257954+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-05T06:32:48.257954+00:00","source":"crossref"},{"observed_at":"2026-08-05T06:32:44.755628+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":"2026-06-05T21:23:00.469572Z","title":"Cte-mlo: Continuous-time and efficient multi-lidar odometry with localizability-aware point cloud sampling","venue":null,"work_id":"01eb2bfe-59c3-4e5d-96e0-daad5748f75b","year":2025},"citing_paper":{"arxiv_id":"2604.03747","last_updated":"2026-04-04T14:27:54Z","snapshot_observed_at":"2026-08-04T20:18:53.390138Z","submitted_at":"2026-04-04T14:27:54Z","title":"CT-VoxelMap: Efficient Continuous-Time LiDAR-Inertial Odometry with Probabilistic Adaptive Voxel Mapping","version":1},"reference_index":39,"source":"pdf_text","source_observed_at":"2026-05-13T17:11:52.457688Z"},"links":{"citing_paper":"/paper/2604.03747"},"observation_digest":"sha256:edc6a4daedbd8582f1966a2a4e13e6b146555c98ad51b4c55d63fb55437c4cf5","observation_id":"e0501db9-affd-49ee-ac95-e7d17dfd9fef","resolution":{"observed_at":"2026-05-13T17:13:01.891601Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-05T06:32:48.257954+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-05T06:32:48.257954+00:00","source":"crossref"},{"observed_at":"2026-08-05T06:32:44.755628+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":"2026-06-05T21:23:00.469572Z","title":"Cta-lo: Accurate and robust lidar odometry using continuous-time adaptive estimation","venue":null,"work_id":"a2c80699-bdab-4d52-8351-04d0e2fe808c","year":2024},"citing_paper":{"arxiv_id":"2604.03747","last_updated":"2026-04-04T14:27:54Z","snapshot_observed_at":"2026-08-04T20:18:53.390138Z","submitted_at":"2026-04-04T14:27:54Z","title":"CT-VoxelMap: Efficient Continuous-Time LiDAR-Inertial Odometry with Probabilistic Adaptive Voxel Mapping","version":1},"reference_index":40,"source":"pdf_text","source_observed_at":"2026-05-13T17:11:52.457688Z"},"links":{"citing_paper":"/paper/2604.03747"},"observation_digest":"sha256:0854503a5af8bdb8cd51caf4f94d1269c29878030d36c4d9bf8c99852c6120d2","observation_id":"27a597f4-0a00-45e1-9902-a1804b7308b4","resolution":{"observed_at":"2026-05-13T17:13:01.895491Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-05T06:32:48.257954+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-05T06:32:48.257954+00:00","source":"crossref"},{"observed_at":"2026-08-05T06:32:44.755628+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":"2026-06-05T21:23:00.469572Z","title":"A lidar-inertial odometry with principled un- certainty modeling","venue":null,"work_id":"b5ef6102-0f24-412d-adc4-c90def4b31f3","year":2022},"citing_paper":{"arxiv_id":"2604.03747","last_updated":"2026-04-04T14:27:54Z","snapshot_observed_at":"2026-08-04T20:18:53.390138Z","submitted_at":"2026-04-04T14:27:54Z","title":"CT-VoxelMap: Efficient Continuous-Time LiDAR-Inertial Odometry with Probabilistic Adaptive Voxel Mapping","version":1},"reference_index":41,"source":"pdf_text","source_observed_at":"2026-05-13T17:11:52.457688Z"},"links":{"citing_paper":"/paper/2604.03747"},"observation_digest":"sha256:e6e7796860c623c526320c31c7a00e2e50334a8ecf7a8e749def9b5053f7713d","observation_id":"5a58f621-77e4-4d58-b933-0211e79139ef","resolution":{"observed_at":"2026-05-13T17:13:01.941697Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-05T06:32:48.257954+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-05T06:32:48.257954+00:00","source":"crossref"},{"observed_at":"2026-08-05T06:32:44.755628+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":"2026-06-05T21:23:00.469572Z","title":"Log- lio2: A lidar-inertial odometry with efficient uncertainty analysis","venue":null,"work_id":"b4d98a13-9aa9-4ffd-aabf-07dcdb03be21","year":2024},"citing_paper":{"arxiv_id":"2604.03747","last_updated":"2026-04-04T14:27:54Z","snapshot_observed_at":"2026-08-04T20:18:53.390138Z","submitted_at":"2026-04-04T14:27:54Z","title":"CT-VoxelMap: Efficient Continuous-Time LiDAR-Inertial Odometry with Probabilistic Adaptive Voxel Mapping","version":1},"reference_index":42,"source":"pdf_text","source_observed_at":"2026-05-13T17:11:52.457688Z"},"links":{"citing_paper":"/paper/2604.03747"},"observation_digest":"sha256:f1fe8e485372d26fee9acf9779f016b225be23baa297b5a544cfcc9cddaeb99b","observation_id":"69785291-32e1-49bc-bb5d-c9d35f5dc6a0","resolution":{"observed_at":"2026-05-13T17:13:01.899598Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-05T06:32:48.257954+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-05T06:32:48.257954+00:00","source":"crossref"},{"observed_at":"2026-08-05T06:32:44.755628+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":"2026-06-05T21:23:00.469572Z","title":"Pixel-level extrinsic self cal- ibration of high resolution lidar and camera in targetless environments","venue":null,"work_id":"8c8d53d6-8c55-4f95-8ffa-c6b4e28a671e","year":2021},"citing_paper":{"arxiv_id":"2604.03747","last_updated":"2026-04-04T14:27:54Z","snapshot_observed_at":"2026-08-04T20:18:53.390138Z","submitted_at":"2026-04-04T14:27:54Z","title":"CT-VoxelMap: Efficient Continuous-Time LiDAR-Inertial Odometry with Probabilistic Adaptive Voxel Mapping","version":1},"reference_index":43,"source":"pdf_text","source_observed_at":"2026-05-13T17:11:52.457688Z"},"links":{"citing_paper":"/paper/2604.03747"},"observation_digest":"sha256:38dbaeb4f438f6f759a573b78fe507c32d31914468cc0f89883a20caff55527f","observation_id":"2b3e6a96-33b8-4c4e-b7a4-67fd20c3382f","resolution":{"observed_at":"2026-05-13T17:13:01.901790Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-05T06:32:48.257954+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-05T06:32:48.257954+00:00","source":"crossref"},{"observed_at":"2026-08-05T06:32:44.755628+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":"2026-06-05T21:23:00.469572Z","title":"X-icp: Localizability-aware lidar registration for robust localization in extreme environments","venue":null,"work_id":"0ed26545-62fb-4dc1-8c19-6b9072e2aa0b","year":2024},"citing_paper":{"arxiv_id":"2604.03747","last_updated":"2026-04-04T14:27:54Z","snapshot_observed_at":"2026-08-04T20:18:53.390138Z","submitted_at":"2026-04-04T14:27:54Z","title":"CT-VoxelMap: Efficient Continuous-Time LiDAR-Inertial Odometry with Probabilistic Adaptive Voxel Mapping","version":1},"reference_index":44,"source":"pdf_text","source_observed_at":"2026-05-13T17:11:52.457688Z"},"links":{"citing_paper":"/paper/2604.03747"},"observation_digest":"sha256:227c03b84dcf8ebb679b6722364399f2dbe56c403fde079f56116a4ca7b1820f","observation_id":"83ed9c5d-4fa1-40f2-814b-e1fa95f1b283","resolution":{"observed_at":"2026-05-13T17:13:01.838639Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-05T06:32:48.257954+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-05T06:32:48.257954+00:00","source":"crossref"},{"observed_at":"2026-08-05T06:32:44.755628+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":"2026-06-05T21:23:00.469572Z","title":"Balm: Bundle adjustment for lidar mapping","venue":null,"work_id":"8bf8243b-7272-4a0f-8337-e1da6a2527e4","year":2021},"citing_paper":{"arxiv_id":"2604.03747","last_updated":"2026-04-04T14:27:54Z","snapshot_observed_at":"2026-08-04T20:18:53.390138Z","submitted_at":"2026-04-04T14:27:54Z","title":"CT-VoxelMap: Efficient Continuous-Time LiDAR-Inertial Odometry with Probabilistic Adaptive Voxel Mapping","version":1},"reference_index":45,"source":"pdf_text","source_observed_at":"2026-05-13T17:11:52.457688Z"},"links":{"citing_paper":"/paper/2604.03747"},"observation_digest":"sha256:66b34ec463131de121793b6790a431664bc7e1365518df7383561e3e03b80d6d","observation_id":"085f4bb2-852c-4f84-999a-1fbb71fb36f6","resolution":{"observed_at":"2026-05-13T17:13:01.836469Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-05T06:32:48.257954+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-05T06:32:48.257954+00:00","source":"crossref"},{"observed_at":"2026-08-05T06:32:44.755628+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":"2026-06-05T21:23:00.469572Z","title":"Hierarchical distribution- based tightly-coupled lidar inertial odometry","venue":null,"work_id":"0f2af7e4-980a-4455-9338-33403ddf4438","year":2024},"citing_paper":{"arxiv_id":"2604.03747","last_updated":"2026-04-04T14:27:54Z","snapshot_observed_at":"2026-08-04T20:18:53.390138Z","submitted_at":"2026-04-04T14:27:54Z","title":"CT-VoxelMap: Efficient Continuous-Time LiDAR-Inertial Odometry with Probabilistic Adaptive Voxel Mapping","version":1},"reference_index":46,"source":"pdf_text","source_observed_at":"2026-05-13T17:11:52.457688Z"},"links":{"citing_paper":"/paper/2604.03747"},"observation_digest":"sha256:5a4181e892db25a2c9d906c09a576ac354f53afaa25d48f4ff0a021f7a052366","observation_id":"104e4bfc-14f5-4c63-b3f2-f53f5c693a87","resolution":{"observed_at":"2026-05-13T17:13:01.851050Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-05T06:32:48.257954+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-05T06:32:48.257954+00:00","source":"crossref"},{"observed_at":"2026-08-05T06:32:44.755628+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":"2026-06-05T21:23:00.469572Z","title":"3dmndt: 3d multi-view registration method based on the normal distributions transform","venue":null,"work_id":"f5216fee-f9e4-42fb-8e8e-2d5a5594e25b","year":2024},"citing_paper":{"arxiv_id":"2604.03747","last_updated":"2026-04-04T14:27:54Z","snapshot_observed_at":"2026-08-04T20:18:53.390138Z","submitted_at":"2026-04-04T14:27:54Z","title":"CT-VoxelMap: Efficient Continuous-Time LiDAR-Inertial Odometry with Probabilistic Adaptive Voxel Mapping","version":1},"reference_index":47,"source":"pdf_text","source_observed_at":"2026-05-13T17:11:52.457688Z"},"links":{"citing_paper":"/paper/2604.03747"},"observation_digest":"sha256:f136d96f12d34e196757002519ee67a78f1f38eaacb8bfcdc8506144232ff311","observation_id":"932c1a6d-3f0d-443d-9d41-457f25550af0","resolution":{"observed_at":"2026-05-13T17:13:01.840670Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-05T06:32:48.257954+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-05T06:32:48.257954+00:00","source":"crossref"},{"observed_at":"2026-08-05T06:32:44.755628+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":"2026-06-05T21:23:00.469572Z","title":"The normal distributions transform: a new approach to laser scan matching","venue":null,"work_id":"d6a99e39-8e30-4c4d-9ec1-76a012262513","year":2003},"citing_paper":{"arxiv_id":"2604.03747","last_updated":"2026-04-04T14:27:54Z","snapshot_observed_at":"2026-08-04T20:18:53.390138Z","submitted_at":"2026-04-04T14:27:54Z","title":"CT-VoxelMap: Efficient Continuous-Time LiDAR-Inertial Odometry with Probabilistic Adaptive Voxel Mapping","version":1},"reference_index":48,"source":"pdf_text","source_observed_at":"2026-05-13T17:11:52.457688Z"},"links":{"citing_paper":"/paper/2604.03747"},"observation_digest":"sha256:e8662e8361b16612d473bbbb8e0a4ad1307a026b878b6495646b94cb41545f16","observation_id":"0874fc9e-c789-4311-9210-3caad9f16207","resolution":{"observed_at":"2026-05-13T17:13:01.849092Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-05T06:32:48.257954+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-05T06:32:48.257954+00:00","source":"crossref"},{"observed_at":"2026-08-05T06:32:44.755628+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":"2026-06-05T21:23:00.469572Z","title":"Point-lio: robust high-bandwidth light detection and ranging inertial odometry","venue":null,"work_id":"cccb36c6-714d-4de9-a39a-7520b48a5caf","year":2023},"citing_paper":{"arxiv_id":"2604.03747","last_updated":"2026-04-04T14:27:54Z","snapshot_observed_at":"2026-08-04T20:18:53.390138Z","submitted_at":"2026-04-04T14:27:54Z","title":"CT-VoxelMap: Efficient Continuous-Time LiDAR-Inertial Odometry with Probabilistic Adaptive Voxel Mapping","version":1},"reference_index":49,"source":"pdf_text","source_observed_at":"2026-05-13T17:11:52.457688Z"},"links":{"citing_paper":"/paper/2604.03747"},"observation_digest":"sha256:bff89f0a90153a293357011ccd91ea40431d638ac44849f72e732a00a3bce110","observation_id":"df2d3c52-c255-4324-9495-72e2bcd7a32e","resolution":{"observed_at":"2026-05-13T17:13:01.842570Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-05T06:32:48.257954+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-05T06:32:48.257954+00:00","source":"crossref"},{"observed_at":"2026-08-05T06:32:44.755628+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":"2026-06-05T21:23:00.469572Z","title":"Maximum correntropy kalman filter","venue":null,"work_id":"656a8a55-2e7f-4bb8-9ed4-f6296babfe8f","year":2017},"citing_paper":{"arxiv_id":"2604.03747","last_updated":"2026-04-04T14:27:54Z","snapshot_observed_at":"2026-08-04T20:18:53.390138Z","submitted_at":"2026-04-04T14:27:54Z","title":"CT-VoxelMap: Efficient Continuous-Time LiDAR-Inertial Odometry with Probabilistic Adaptive Voxel Mapping","version":1},"reference_index":50,"source":"pdf_text","source_observed_at":"2026-05-13T17:11:52.457688Z"},"links":{"citing_paper":"/paper/2604.03747"},"observation_digest":"sha256:159773dfdd6aeb1f53e2c421e5675e8a93866199ccf57b98460f2666b1073647","observation_id":"113e265e-52a2-4eb1-ac84-2a2bb291deab","resolution":{"observed_at":"2026-05-13T17:13:01.845007Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-05T06:32:48.257954+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-05T06:32:48.257954+00:00","source":"crossref"},{"observed_at":"2026-08-05T06:32:44.755628+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":"2026-06-05T21:23:00.469572Z","title":"evo: Python package for the evaluation of odometry and slam","venue":null,"work_id":"957fa817-68d3-4ffc-b14c-9a021d1534b2","year":2017},"citing_paper":{"arxiv_id":"2604.03747","last_updated":"2026-04-04T14:27:54Z","snapshot_observed_at":"2026-08-04T20:18:53.390138Z","submitted_at":"2026-04-04T14:27:54Z","title":"CT-VoxelMap: Efficient Continuous-Time LiDAR-Inertial Odometry with Probabilistic Adaptive Voxel Mapping","version":1},"reference_index":51,"source":"pdf_text","source_observed_at":"2026-05-13T17:11:52.457688Z"},"links":{"citing_paper":"/paper/2604.03747"},"observation_digest":"sha256:5149208c2a71577a856d3faba196aa341ad6c4fd983c0dc89cea817849c8f0c4","observation_id":"079bee69-8386-4b0e-9a52-50b805fb2847","resolution":{"observed_at":"2026-05-13T17:13:01.847118Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-05T06:32:48.257954+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-05T06:32:48.257954+00:00","source":"crossref"},{"observed_at":"2026-08-05T06:32:44.755628+00:00","source":"retraction_watch"}],"state":"measured"}}],"paper":{"arxiv_id":"2604.03747","last_updated":"2026-04-04T14:27:54Z","latest_version":1,"primary_category":"cs.RO","snapshot_observed_at":"2026-08-04T20:18:53.390138Z","submitted_at":"2026-04-04T14:27:54Z","title":"CT-VoxelMap: Efficient Continuous-Time LiDAR-Inertial Odometry with Probabilistic Adaptive Voxel Mapping"},"reference_resolution":{"displayed":51,"state_counts":{"malformed_identifier":0,"metadata_mismatch":0,"parse_uncertain":0,"unresolved":0,"verified_exact":1,"verified_fuzzy":50},"total_outbound_references":51},"refusal":"A citation records a reference. It does not transfer a finding from one paper to another.","schema":"pith.paper-citation-record.v1","standing_sources":[{"observed_at":"2026-08-05T06:32:48.257954+00:00","source":"crossref"},{"observed_at":"2026-08-05T06:32:44.755628+00:00","source":"retraction_watch"}],"thesis":"As of 5 August 2026, this Paper Citation Record lists 51 of 51 outbound references and 0 inbound Pith citation observations for arXiv:2604.03747."}