Typed states for the displayed outbound observations.
Source: paper_references, paper_reference_links
Paper Citation Record · LEDGER
Joint-MAE: 2D-3D Joint Masked Autoencoders for 3D Point Cloud Pre-training
As of 17 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 5 inbound Pith citation observations for arXiv:2302.14007.
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 2026-08-17T06:30:58.91139+00:00
Pith citing papers itemized under the disclosed page cap.
Source: paper_references, paper_reference_links, observed 2026-08-10T21:22:17.649284Z
A source-named dated measurement, never combined with another source.
Source: arxiv_reference, observed 2026-05-14T23:07:42.833248Z
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 e59591fe-4eb0-4c56-973c-920e41ffca91 · inbound
LLaMA-Adapter: Efficient Fine-tuning of Language Models with Zero-init Attention cites this paper.
LLaMA-Adapter: Efficient Fine-tuning of Language Models with Zero-init Attention Joint-MAE: 2D-3D Joint Masked Autoencoders for 3D Point Cloud Pre-training
Reference 189
- Resolution
- verified exact
- arxiv_id, observed 2026-05-14T23:07:42.836122Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.
Observation 47fd427e-1f5c-4d50-8e64-e91a40a52417 · inbound
Advancing ALS Applications with Large-Scale Pre-training: Dataset Development and Downstream Assessment cites this paper.
Advancing ALS Applications with Large-Scale Pre-training: Dataset Development and Downstream Assessment Joint-MAE: 2D-3D Joint Masked Autoencoders for 3D Point Cloud Pre-training
Reference 52
- Resolution
- unresolved
- no resolver link, observed 2026-08-10T21:22:17.649284Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation b66b8a6a-133d-4cbb-8cfd-c6d6bc5fe5eb · inbound
StruMamba3D: Exploring Structural Mamba for Self-supervised Point Cloud Representation Learning cites this paper.
StruMamba3D: Exploring Structural Mamba for Self-supervised Point Cloud Representation Learning Joint-MAE: 2D-3D Joint Masked Autoencoders for 3D Point Cloud Pre-training
Reference 14
- Resolution
- unresolved
- no resolver link, observed 2026-08-06T22:31:38.846248Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation 3b893064-dba0-4fe3-9606-5cc310dcbf84 · inbound
Harnessing Text-to-Image Diffusion Models for Point Cloud Self-Supervised Learning cites this paper.
Harnessing Text-to-Image Diffusion Models for Point Cloud Self-Supervised Learning Joint-MAE: 2D-3D Joint Masked Autoencoders for 3D Point Cloud Pre-training
Reference 19
- Resolution
- unresolved
- no resolver link, observed 2026-08-06T18:10:13.986793Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation b72c5d02-8db7-4219-a092-f0e4ea5d1041 · inbound
Towards More Diverse and Challenging Pre-training for Point Cloud Learning: Self-Supervised Cross Reconstruction with Decoupled Views cites this paper.
Towards More Diverse and Challenging Pre-training for Point Cloud Learning: Self-Supervised Cross Reconstruction with Decoupled Views Joint-MAE: 2D-3D Joint Masked Autoencoders for 3D Point Cloud Pre-training
Reference 18
- Resolution
- unresolved
- no resolver link, observed 2026-08-05T12:47:49.159320Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.