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Paper Citation Record · LEDGER

PointCNN: Convolution On $\mathcal{X}$-Transformed Points

As of 17 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 5 inbound Pith citation observations for arXiv:1801.07791.

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

pith.paper-citation-record.v1
1801.07791 v5

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 2026-08-17T06:30:58.91139+00:00

measured 5 of 5 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-08-14T14:58:17.815512Z

measured 0 of 1 external citation measurements

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

Source: arxiv_reference, observed 2026-05-10T08:58:13.715819Z

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 a9c07efa-5042-4d4f-aaa7-9404223646cf · inbound

Point Cloud Super Resolution with Adversarial Residual Graph Networks cites this paper.

Point Cloud Super Resolution with Adversarial Residual Graph Networks PointCNN: Convolution On $\mathcal{X}$-Transformed Points

Reference 20

Resolution
unresolved
no resolver link, observed 2026-08-14T14:58:17.815512Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-14T14:58:17.815512Z digest=sha256:faa74acfdb47cb3a0b16477ad6551d607d5fc26d4a2f8d7148ed85001eb7bf59

Observation 439bd562-d763-4ed9-8ff0-6e62e079bbd9 · inbound

Blended Convolution and Synthesis for Efficient Discrimination of 3D Shapes cites this paper.

Blended Convolution and Synthesis for Efficient Discrimination of 3D Shapes PointCNN: Convolution On $\mathcal{X}$-Transformed Points

Reference 36

Resolution
unresolved
no resolver link, observed 2026-08-14T11:28:58.362053Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-14T11:28:58.362053Z digest=sha256:72661891fac94569a125cc04072d7e88c008ad70c415a679b107543b539e17c3

Observation 415ed98e-a0ab-4389-b296-b07cc3417cc2 · inbound

Enhancing Human-Robot Collaboration: A Sim2Real Domain Adaptation Algorithm for Point Cloud Segmentation in Industrial Environments cites this paper.

Enhancing Human-Robot Collaboration: A Sim2Real Domain Adaptation Algorithm for Point Cloud Segmentation in Industrial Environments PointCNN: Convolution On $\mathcal{X}$-Transformed Points

Reference 22

Resolution
unresolved
no resolver link, observed 2026-08-07T04:50:30.478254Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-07T04:50:30.478254Z digest=sha256:e3926a413764e6c27622633a8f4febd8c0c1c4f87bf43cfa18d5758c61c58613

Observation 8386de1e-33b4-4bde-82f0-4cb3d8abbfbd · inbound

AirCANS: CFD 2D Mesh Optimisation-based Airfoil Classification and Assessment using Neural Networks cites this paper.

AirCANS: CFD 2D Mesh Optimisation-based Airfoil Classification and Assessment using Neural Networks PointCNN: Convolution On $\mathcal{X}$-Transformed Points

Reference 28

Resolution
unresolved
no resolver link, observed 2026-08-06T22:05:08.052170Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-06T22:05:08.052170Z digest=sha256:0b3b4f37134a8bcfba3e6b18558caac3c84312d51debfb5499b0cb84f04883a7

Observation 235a692b-6a57-4ed1-aeaa-327a96fd617e · inbound

LOD-Net: Locality-Aware 3D Object Detection Using Multi-Scale Transformer Network cites this paper.

LOD-Net: Locality-Aware 3D Object Detection Using Multi-Scale Transformer Network PointCNN: Convolution On $\mathcal{X}$-Transformed Points

Reference 10

Resolution
verified exact
arxiv_id, observed 2026-07-04T23:10:32.529819Z

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.

source=pdf_text observed=2026-05-10T08:30:32.631251Z digest=sha256:458c9de4a70d8589920facf5405424b1f380fcb4a019038fe7be06c7ee99dcf6