Typed states for the displayed outbound observations.
Source: paper_references, paper_reference_links
Paper Citation Record · LEDGER
Point-M2AE: Multi-scale Masked Autoencoders for Hierarchical Point Cloud Pre-training
As of 21 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 5 inbound Pith citation observations for arXiv:2205.14401.
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 2026-08-21T06:32:19.484+00:00
Pith citing papers itemized under the disclosed page cap.
Source: paper_references, paper_reference_links, observed 2026-08-15T17:34:14.838496Z
A source-named dated measurement, never combined with another source.
Source: arxiv_reference, observed 2026-05-14T23:07:42.455868Z
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 ccde35ad-6b3e-431b-9af8-f0c3e9b6443e · 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 Point-M2AE: Multi-scale Masked Autoencoders for Hierarchical Point Cloud Pre-training
Reference 213
- Resolution
- verified exact
- arxiv_id, observed 2026-05-14T23:07:42.459388Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.
Observation 98f95ce3-0f1a-42b3-afc6-28b8e55cd2ee · inbound
HEP-JEPA: A foundation model for collider physics using joint embedding predictive architecture cites this paper.
HEP-JEPA: A foundation model for collider physics using joint embedding predictive architecture Point-M2AE: Multi-scale Masked Autoencoders for Hierarchical Point Cloud Pre-training
Reference 26
- Resolution
- unresolved
- no resolver link, observed 2026-08-09T00:14:59.645871Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation 6eaf8c6f-f863-483b-8400-d2c116757cf7 · inbound
A Cross Branch Fusion-Based Contrastive Learning Framework for Point Cloud Self-supervised Learning cites this paper.
A Cross Branch Fusion-Based Contrastive Learning Framework for Point Cloud Self-supervised Learning Point-M2AE: Multi-scale Masked Autoencoders for Hierarchical Point Cloud Pre-training
Reference 71
- Resolution
- unresolved
- no resolver link, observed 2026-08-07T12:22:13.630306Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation 88684cbf-eae9-48e3-9446-9eedd51f4530 · inbound
Multi-modal Multi-task Pre-training for Improved Point Cloud Understanding cites this paper.
Multi-modal Multi-task Pre-training for Improved Point Cloud Understanding Point-M2AE: Multi-scale Masked Autoencoders for Hierarchical Point Cloud Pre-training
Reference 2022
- Resolution
- unresolved
- no resolver link, observed 2026-08-06T14:51:52.717350Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation 6ebb6807-1075-4e86-aff8-0d62b2eda51a · inbound
Ultra Ethernet's Design Principles and Architectural Innovations cites this paper.
Ultra Ethernet's Design Principles and Architectural Innovations Point-M2AE: Multi-scale Masked Autoencoders for Hierarchical Point Cloud Pre-training
Reference 81
- Resolution
- unresolved
- no resolver link, observed 2026-08-15T17:34:14.838496Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.