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Paper Citation Record · LEDGER

Self-supervised Learning for Pre-Training 3D Point Clouds: A Survey

As of 7 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 5 inbound Pith citation observations for arXiv:2305.04691.

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

pith.paper-citation-record.v1
2305.04691 v1

Coverage vector

measured 0 of 0 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links

measured 5 of 5 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-07T06:34:17.273281+00:00

measured 5 of 5 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-08-07T05:06:57.857443Z

measured 0 of 1 external citation measurements

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

Source: pith, observed 2026-08-05T22:26:38.544916Z

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 9cb8d37b-4d14-4765-96b0-ff64a2583848 · inbound

Gaussian2Scene: 3D Scene Representation Learning via Self-supervised Learning with 3D Gaussian Splatting cites this paper.

Gaussian2Scene: 3D Scene Representation Learning via Self-supervised Learning with 3D Gaussian Splatting Self-supervised Learning for Pre-Training 3D Point Clouds: A Survey

Reference 5

Resolution
unresolved
no resolver link, observed 2026-08-07T05:06:57.857443Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-07T05:06:57.857443Z digest=sha256:4dfa4fddfc81fd9c1f8ea22564674e4854b0346e94219314333d60323017afd2

Observation 09b7ce61-5385-443e-93c9-a44772952a87 · inbound

Asymmetric Dual Self-Distillation for 3D Self-Supervised Representation Learning cites this paper.

Asymmetric Dual Self-Distillation for 3D Self-Supervised Representation Learning Self-supervised Learning for Pre-Training 3D Point Clouds: A Survey

Reference 6

Resolution
unresolved
no resolver link, observed 2026-08-06T22:26:20.519733Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-06T22:26:20.519733Z digest=sha256:d90378258b54ab548de68231c5a528740102a88255633e6f27347a7322c72ef3

Observation 1df6bd2d-f8d4-4bfd-9620-3d819e7ded50 · inbound

Beyond One Shot, Beyond One Perspective: Cross-View and Long-Horizon Distillation for Better LiDAR Representations cites this paper.

Beyond One Shot, Beyond One Perspective: Cross-View and Long-Horizon Distillation for Better LiDAR Representations Self-supervised Learning for Pre-Training 3D Point Clouds: A Survey

Reference 15

Resolution
unresolved
no resolver link, observed 2026-08-06T19:32:29.977440Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-06T19:32:29.977440Z digest=sha256:829fea993b7aa98741fe81b94d9de38feb9e8079bd8437c2a1fb848d177f1f72

Observation 8b70df00-f2d6-4d7a-a5b1-27cc903c92bd · 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 Self-supervised Learning for Pre-Training 3D Point Clouds: A Survey

Reference 1

Resolution
unresolved
no resolver link, observed 2026-08-06T14:51:52.710758Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-06T14:51:52.710758Z digest=sha256:b6aef2a242d0dc2b4f337c44d92ed88321928461ee88eef6075d5deb5676a708

Observation 9eb698ac-7bf4-4e94-85e2-30afbe705f82 · inbound

ED-DiT: Physics-Guided Diffusion Pretraining for Transferable Molecular Representations from Electron Density cites this paper.

ED-DiT: Physics-Guided Diffusion Pretraining for Transferable Molecular Representations from Electron Density Self-supervised Learning for Pre-Training 3D Point Clouds: A Survey

Reference 19

Resolution
verified exact
local_arxiv, observed 2026-08-05T22:26:38.549759Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

source=pdf_text observed=2026-08-05T22:26:38.464189Z digest=sha256:e9b5b2435cbc19adbe664c9111058d84b973daeffb9e1cf105a534301900e28f