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Paper Citation Record · LEDGER

Point-M2AE: Multi-scale Masked Autoencoders for Hierarchical Point Cloud Pre-training

As of 9 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 4 inbound Pith citation observations for arXiv:2205.14401.

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

pith.paper-citation-record.v1
2205.14401 v2

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 2026-08-09T00:14:59.645871Z

measured 0 of 1 external citation measurements

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 2026-08-09T06:31:02.800959+00:00.

source=arxiv_source observed=2026-05-14T23:07:42.245641Z digest=sha256:6083b79639751ef086a3377787010be6c0b3df73a10270ea2d9c9fb9dd14b579

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.

source=pdf_text observed=2026-08-09T00:14:59.645871Z digest=sha256:b0a14589dc9b03f6f90a4e4bc21ed72772bd1b1db381274a85d8808298560c22

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.

source=pdf_text observed=2026-08-07T12:22:13.630306Z digest=sha256:fbf49bf016d981e92a0e4c9260a947ca92fe33b62a5b1ccc35e4f4e27dc5f5a1

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.

source=pdf_text observed=2026-08-06T14:51:52.717350Z digest=sha256:ed544a664525dfd0d240f46f37882c7b6d193e85be17414740c3f12cbb245bcb