Paper Citation Record · LEDGER

Efficient Active Training for Deep LiDAR Odometry

As of 19 August 2026, this Paper Citation Record lists 35 of 35 outbound references and 0 inbound Pith citation observations for arXiv:2509.03211.

A citation records a reference. It does not transfer a finding from one paper to another.

pith.paper-citation-record.v1
2509.03211 v1

Coverage vector

measured 35 of 35 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links, observed 2026-08-15T16:39:40.364152Z

measured 35 of 35 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-19T06:32:44.657259+00:00

measured 0 of 0 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links

measured 0 of 1 external citation measurements

A source-named dated measurement, never combined with another source.

Source: cited_works

Reference resolution

35 of 35 outbound references displayed

verified exact0
verified fuzzy29
unresolved6
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External citation measurements

No source-named external measurement is stored.

Outbound references

Observation 0699d878-feb6-4ae1-8c3c-726fca4b79c5 · outbound

This paper cites Gaussian splatting slam,.

Efficient Active Training for Deep LiDAR Odometry Gaussian splatting slam,

Reference 1

Resolution: verified fuzzy; raw_fallback, observed 2026-08-15T16:39:40.966600Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

Observation ab063cda-7c9a-48b4-a067-f2189d36877e · outbound

This paper cites Fast-lidar-slam: A robust and real-time factor graph for urban scenarios with unstable gps signals,.

Efficient Active Training for Deep LiDAR Odometry Fast-lidar-slam: A robust and real-time factor graph for urban scenarios with unstable gps signals,

Reference 2

Resolution: verified fuzzy; raw_fallback, observed 2026-08-15T16:39:40.950415Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

Observation 1cd45eba-fb69-4d8f-bd34-543b6311e288 · outbound

This paper cites Dynamic semantic slam based on panoramic camera and lidar fusion for autonomous driving,.

Efficient Active Training for Deep LiDAR Odometry Dynamic semantic slam based on panoramic camera and lidar fusion for autonomous driving,

Reference 3

Resolution: verified fuzzy; raw_fallback, observed 2026-08-15T16:39:40.934104Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

Observation 32acc288-7dee-4ab0-b9a3-e2016d311119 · outbound

This paper cites Perception and sensing for autonomous vehicles under adverse weather conditions: A survey,.

Efficient Active Training for Deep LiDAR Odometry Perception and sensing for autonomous vehicles under adverse weather conditions: A survey,

Reference 4

Resolution: verified fuzzy; raw_fallback, observed 2026-08-15T16:39:40.917347Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

Observation 5b00d344-afa3-4c58-9296-8561dd6c653f · outbound

This paper cites Libre: The multiple 3d lidar dataset,.

Efficient Active Training for Deep LiDAR Odometry Libre: The multiple 3d lidar dataset,

Reference 5

Resolution: verified fuzzy; raw_fallback, observed 2026-08-15T16:39:40.898399Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

Observation 90f69312-4f31-474c-a1fa-f9fe923a3622 · outbound

This paper cites The perception system of intelligent ground vehicles in all weather conditions: A systematic literature review,.

Efficient Active Training for Deep LiDAR Odometry The perception system of intelligent ground vehicles in all weather conditions: A systematic literature review,

Reference 6

Resolution: verified fuzzy; raw_fallback, observed 2026-08-15T16:39:40.881947Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

Observation 8ef9f92b-bd8b-492c-a912-ff57d0d83435 · outbound

This paper cites Robust object detection in challenging weather conditions,.

Efficient Active Training for Deep LiDAR Odometry Robust object detection in challenging weather conditions,

Reference 7

Resolution: verified fuzzy; raw_fallback, observed 2026-08-15T16:39:40.864174Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

Observation 42712da6-d2f5-49e2-96ac-a2d8c9bfe397 · outbound

This paper cites Multi-agent trajectory prediction by combining egocentric and allocentric views,.

Efficient Active Training for Deep LiDAR Odometry Multi-agent trajectory prediction by combining egocentric and allocentric views,

Reference 8

Resolution: verified fuzzy; raw_fallback, observed 2026-08-15T16:39:40.846143Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

Observation 5d8bfe01-3d2e-43a8-be8f-b640312584d1 · outbound

This paper cites Hdgt: Heterogeneous driving graph transformer for multi-agent trajectory prediction via scene encoding,.

Efficient Active Training for Deep LiDAR Odometry Hdgt: Heterogeneous driving graph transformer for multi-agent trajectory prediction via scene encoding,

Reference 9

Resolution: verified fuzzy; raw_fallback, observed 2026-08-15T16:39:40.829770Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

Observation 498fc2e3-3d7e-4156-a2e2-b3dcf7a9540b · outbound

This paper cites Motion transformer with global intention localization and local movement refinement,.

Efficient Active Training for Deep LiDAR Odometry Motion transformer with global intention localization and local movement refinement,

Reference 10

Resolution: verified fuzzy; raw_fallback, observed 2026-08-15T16:39:40.814204Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

Observation 1809756c-2bab-47a7-bd3d-0767f990f929 · outbound

This paper cites Pointpainting: Sequential fusion for 3d object detection,.

Efficient Active Training for Deep LiDAR Odometry Pointpainting: Sequential fusion for 3d object detection,

Reference 11

Resolution: verified fuzzy; raw_fallback, observed 2026-08-15T16:39:40.797882Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

Observation 71dc06f1-d4a0-4f29-b331-5d8504300dde · outbound

This paper cites ActiveAD: Planning-Oriented Active Learning for End-to-End Autonomous Driving.

Efficient Active Training for Deep LiDAR Odometry ActiveAD: Planning-Oriented Active Learning for End-to-End Autonomous Driving

Reference 12

Resolution: unresolved; no resolver link, observed 2026-08-15T16:39:40.235521Z

Source-reported events for the cited work

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Observation 7d02f78b-0ec5-4fa1-ae14-65a5cf5921af · outbound

This paper cites Deep learning- based robust positioning for all-weather autonomous driving,.

Efficient Active Training for Deep LiDAR Odometry Deep learning- based robust positioning for all-weather autonomous driving,

Reference 13

Resolution: verified fuzzy; raw_fallback, observed 2026-08-15T16:39:40.782070Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

Observation 8ff8c87b-5c54-424c-9692-eff45bc8bcaa · outbound

This paper cites Cnn for imu assisted odometry estimation using velodyne lidar,.

Efficient Active Training for Deep LiDAR Odometry Cnn for imu assisted odometry estimation using velodyne lidar,

Reference 14

Resolution: verified fuzzy; raw_fallback, observed 2026-08-15T16:39:40.763118Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

Observation ac550a0d-6685-4dcf-9a33-9e7ddb6f21de · outbound

This paper cites Deeppco: End-to-end point cloud odom- etry through deep parallel neural network,.

Efficient Active Training for Deep LiDAR Odometry Deeppco: End-to-end point cloud odom- etry through deep parallel neural network,

Reference 15

Resolution: unresolved; no resolver link, observed 2026-08-15T16:39:40.253143Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 15725c87-4db5-4bb7-b546-e6964a8f30c8 · outbound

This paper cites Dmlo: Deep matching lidar odometry,.

Efficient Active Training for Deep LiDAR Odometry Dmlo: Deep matching lidar odometry,

Reference 16

Resolution: verified fuzzy; raw_fallback, observed 2026-08-15T16:39:40.736079Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

Observation 4c5c80b9-b533-4d96-baa0-fc9b081478c3 · outbound

This paper cites Lodonet: A deep neural network with 2d keypoint matching for 3d lidar odometry estimation,.

Efficient Active Training for Deep LiDAR Odometry Lodonet: A deep neural network with 2d keypoint matching for 3d lidar odometry estimation,

Reference 17

Resolution: verified fuzzy; raw_fallback, observed 2026-08-15T16:39:40.718389Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

Observation e1fa2a7e-31ab-4278-a949-e5b6aef8f5cb · outbound

This paper cites Lidar odometry by deep learning-based feature points with two-step pose estimation,.

Efficient Active Training for Deep LiDAR Odometry Lidar odometry by deep learning-based feature points with two-step pose estimation,

Reference 18

Resolution: verified fuzzy; raw_fallback, observed 2026-08-15T16:39:40.697468Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

Observation ee5ce89c-3607-4406-9dea-7fd69f5fee3f · outbound

This paper cites Lo- net: Deep real-time lidar odometry,.

Efficient Active Training for Deep LiDAR Odometry Lo- net: Deep real-time lidar odometry,

Reference 19

Resolution: verified fuzzy; raw_fallback, observed 2026-08-15T16:39:40.678690Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

Observation 35ad4cca-a7db-4e73-8f2b-754cc7bec5a4 · outbound

This paper cites Pwclo-net: Deep lidar odometry in 3d point clouds using hierarchical embedding mask optimization,.

Efficient Active Training for Deep LiDAR Odometry Pwclo-net: Deep lidar odometry in 3d point clouds using hierarchical embedding mask optimization,

Reference 20

Resolution: verified fuzzy; raw_fallback, observed 2026-08-15T16:39:40.660669Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

Observation a04d5d21-56e3-4c0a-8e88-4ef8dcba4843 · outbound

This paper cites Delo: deep evidential lidar odometry using partial optimal transport,.

Efficient Active Training for Deep LiDAR Odometry Delo: deep evidential lidar odometry using partial optimal transport,

Reference 21

Resolution: verified fuzzy; raw_fallback, observed 2026-08-15T16:39:40.645762Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

Observation 0effe901-f36a-497c-8e9d-5b495ab6836f · outbound

This paper cites Efficient 3d deep lidar odometry,.

Efficient Active Training for Deep LiDAR Odometry Efficient 3d deep lidar odometry,

Reference 22

Resolution: verified fuzzy; raw_fallback, observed 2026-08-15T16:39:40.628702Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

Observation dfa65fca-3793-433a-aaa4-fcd912f12849 · outbound

This paper cites Unsupervised geometry-aware deep lidar odometry,.

Efficient Active Training for Deep LiDAR Odometry Unsupervised geometry-aware deep lidar odometry,

Reference 23

Resolution: verified fuzzy; raw_fallback, observed 2026-08-15T16:39:40.612843Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

Observation ac65c9de-8c8e-4ef5-83a8-0fceb6992fc9 · outbound

This paper cites Unsupervised learning of 3d scene flow with lidar odometry assistance,.

Efficient Active Training for Deep LiDAR Odometry Unsupervised learning of 3d scene flow with lidar odometry assistance,

Reference 24

Resolution: verified fuzzy; raw_fallback, observed 2026-08-15T16:39:40.597642Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

Observation e1710f59-a766-4d37-a300-a70a5aa5b091 · outbound

This paper cites DeepLO: Geometry-Aware Deep LiDAR Odometry.

Efficient Active Training for Deep LiDAR Odometry DeepLO: Geometry-Aware Deep LiDAR Odometry

Reference 25

Resolution: unresolved; no resolver link, observed 2026-08-15T16:39:40.308469Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 3efa08a2-44ac-43d5-b2b9-657835fdffdf · outbound

This paper cites Selfvoxelo: Self-supervised lidar odometry with voxel-based deep neural networks,.

Efficient Active Training for Deep LiDAR Odometry Selfvoxelo: Self-supervised lidar odometry with voxel-based deep neural networks,

Reference 26

Resolution: unresolved; no resolver link, observed 2026-08-15T16:39:40.313898Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation ab678ddc-1d94-43b4-8b46-85b0d4500081 · outbound

This paper cites Robust self- supervised lidar odometry via representative structure discovery and 3d inherent error modeling,.

Efficient Active Training for Deep LiDAR Odometry Robust self- supervised lidar odometry via representative structure discovery and 3d inherent error modeling,

Reference 27

Resolution: verified fuzzy; raw_fallback, observed 2026-08-15T16:39:40.572236Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

Observation a06361e4-ee5b-4509-a49e-8525439da723 · outbound

This paper cites Linear least-squares optimization for point-to-plane icp surface registration,.

Efficient Active Training for Deep LiDAR Odometry Linear least-squares optimization for point-to-plane icp surface registration,

Reference 28

Resolution: verified fuzzy; raw_fallback, observed 2026-08-15T16:39:40.554341Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

Observation 51d6335d-da8a-4a77-8413-a6cb2861ff12 · outbound

This paper cites Self-supervised learning of lidar odometry for robotic applications,.

Efficient Active Training for Deep LiDAR Odometry Self-supervised learning of lidar odometry for robotic applications,

Reference 29

Resolution: verified fuzzy; raw_fallback, observed 2026-08-15T16:39:40.538493Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

Observation 11b51d89-fb44-4b5d-9e21-5d8ff55d04e8 · outbound

This paper cites A 3d lidar odometry for ugvs using coarse-to-fine deep scene flow estimation,.

Efficient Active Training for Deep LiDAR Odometry A 3d lidar odometry for ugvs using coarse-to-fine deep scene flow estimation,

Reference 30

Resolution: unresolved; no resolver link, observed 2026-08-15T16:39:40.334601Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation bd3b25b0-840a-4636-b0a5-0fbddfc5f42a · outbound

This paper cites Self- supervised learning of lidar odometry based on spherical projection,.

Efficient Active Training for Deep LiDAR Odometry Self- supervised learning of lidar odometry based on spherical projection,

Reference 31

Resolution: verified fuzzy; raw_fallback, observed 2026-08-15T16:39:40.511584Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

Observation 0648e497-ab8d-4f2e-a307-9245fc175c40 · outbound

This paper cites Hpplo-net: Unsupervised lidar odometry using a hierarchical point-to-plane solver,.

Efficient Active Training for Deep LiDAR Odometry Hpplo-net: Unsupervised lidar odometry using a hierarchical point-to-plane solver,

Reference 32

Resolution: verified fuzzy; raw_fallback, observed 2026-08-15T16:39:40.492819Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

Observation 301a162e-dc3d-4f8d-bfa2-cdf4382f0d73 · outbound

This paper cites A-loam: Advanced implementation of loam,.

Efficient Active Training for Deep LiDAR Odometry A-loam: Advanced implementation of loam,

Reference 33

Resolution: verified fuzzy; raw_fallback, observed 2026-08-15T16:39:40.475066Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

Observation ff8822fa-e691-4e8d-a7d2-eedac20570e5 · outbound

This paper cites Pyicp slam.

Efficient Active Training for Deep LiDAR Odometry Pyicp slam

Reference 34

Resolution: unresolved; no resolver link, observed 2026-08-15T16:39:40.358766Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 5c7c5654-ee35-40e4-a597-989a203c9881 · outbound

This paper cites V oxelized gicp for fast and accurate 3d point cloud registration,.

Efficient Active Training for Deep LiDAR Odometry V oxelized gicp for fast and accurate 3d point cloud registration,

Reference 35

Resolution: verified fuzzy; raw_fallback, observed 2026-08-15T16:39:40.446140Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

Pith citing papers

No inbound Pith citation observations are available.