Paper Citation Record · LEDGER

Cylindrical and Asymmetrical 3D Convolution Networks for LiDAR Segmentation

As of 9 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 4 inbound Pith citation observations for arXiv:2011.10033.

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

pith.paper-citation-record.v1
2011.10033 v1

Coverage vector

measured 0 of 0 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links

measured 4 of 4 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-09T06:31:02.800959+00:00

measured 4 of 4 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-08-09T00:21:15.525833Z

measured 0 of 1 external citation measurements

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

Source: pith, observed 2026-08-06T10:47:41.357003Z

Reference resolution

0 of 0 outbound references displayed

verified exact0
verified fuzzy0
unresolved0
parse uncertain0
malformed identifier0
metadata mismatch0

External citation measurements

No source-named external measurement is stored.

Outbound references

No outbound reference observations are available for this paper version.

Pith citing papers

Observation e5d14215-619f-485d-a96c-47b564b1a93e · inbound

LeAP: Consistent multi-domain 3D labeling using Foundation Models cites this paper.

LeAP: Consistent multi-domain 3D labeling using Foundation Models Cylindrical and Asymmetrical 3D Convolution Networks for LiDAR Segmentation

Reference 23

Resolution: unresolved; no resolver link, observed 2026-08-09T00:21:15.525833Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 233eb8ec-dcab-4b66-9b55-ecac8ed365fa · inbound

How Do Images Align and Complement LiDAR? Towards a Harmonized Multi-modal 3D Panoptic Segmentation cites this paper.

How Do Images Align and Complement LiDAR? Towards a Harmonized Multi-modal 3D Panoptic Segmentation Cylindrical and Asymmetrical 3D Convolution Networks for LiDAR Segmentation

Reference 61

Resolution: unresolved; no resolver link, observed 2026-08-07T14:27:36.259287Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 92869673-745d-4f5b-aa7c-3c598d3568e7 · inbound

LiDAR Based Semantic Perception for Forklifts in Outdoor Environments cites this paper.

LiDAR Based Semantic Perception for Forklifts in Outdoor Environments Cylindrical and Asymmetrical 3D Convolution Networks for LiDAR Segmentation

Reference 33

Resolution: unresolved; no resolver link, observed 2026-08-07T13:14:40.943800Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 8d9d7a5a-19d7-4f7f-85da-decbe3c64ec6 · inbound

FastPoint: Accelerating 3D Point Cloud Model Inference via Sample Point Distance Prediction cites this paper.

FastPoint: Accelerating 3D Point Cloud Model Inference via Sample Point Distance Prediction Cylindrical and Asymmetrical 3D Convolution Networks for LiDAR Segmentation

Reference 45

Resolution: verified exact; local_arxiv, observed 2026-08-06T10:47:41.362310Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.