Typed states for the displayed outbound observations.
Source: paper_references, paper_reference_links
Paper Citation Record · LEDGER
Occupancy-MAE: Self-supervised Pre-training Large-scale LiDAR Point Clouds with Masked Occupancy Autoencoders
As of 14 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 3 inbound Pith citation observations for arXiv:2206.09900.
A citation records a reference. It does not transfer a finding from one paper to another.
Coverage vector
One-hop event checks from named stored sources.
Source: scholarly_work_events, retraction_status_cache, observed 2026-08-13T06:32:02.005865+00:00
Pith citing papers itemized under the disclosed page cap.
Source: paper_references, paper_reference_links, observed 2026-08-12T15:05:27.266517Z
A source-named dated measurement, never combined with another source.
Source: arxiv_reference, observed 2026-07-01T10:05:41.629655Z
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 d3440214-7ec2-433a-9352-7229afe9559a · inbound
VisionPAD: A Vision-Centric Pre-training Paradigm for Autonomous Driving cites this paper.
VisionPAD: A Vision-Centric Pre-training Paradigm for Autonomous Driving Occupancy-MAE: Self-supervised Pre-training Large-scale LiDAR Point Clouds with Masked Occupancy Autoencoders
Reference 28
- Resolution
- unresolved
- no resolver link, observed 2026-08-12T15:05:27.266517Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation 763ddcc8-90f7-434c-8329-72c51434dae1 · inbound
Point Cloud Understanding via Attention-Driven Contrastive Learning cites this paper.
Point Cloud Understanding via Attention-Driven Contrastive Learning Occupancy-MAE: Self-supervised Pre-training Large-scale LiDAR Point Clouds with Masked Occupancy Autoencoders
Reference 29
- Resolution
- unresolved
- no resolver link, observed 2026-08-12T15:02:29.414364Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation 360d4095-f021-4ad5-a5cc-9e161d3d37fc · inbound
Mitigating Positional Leakage in 3D Masked Autoencoders for Robust Representation Learning cites this paper.
Mitigating Positional Leakage in 3D Masked Autoencoders for Robust Representation Learning Occupancy-MAE: Self-supervised Pre-training Large-scale LiDAR Point Clouds with Masked Occupancy Autoencoders
Reference 21
- Resolution
- verified exact
- arxiv_id, observed 2026-07-01T10:05:41.631159Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.