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Paper Citation Record · LEDGER

MeshConv3D: Efficient convolution and pooling operators for triangular 3D meshes

As of 11 August 2026, this Paper Citation Record lists 21 of 21 outbound references and 0 inbound Pith citation observations for arXiv:2501.03830.

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

pith.paper-citation-record.v1
2501.03830 v1

Coverage vector

measured 21 of 21 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links, observed 2026-08-10T21:50:05.994779Z

measured 21 of 21 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-11T06:34:44.6726+00:00

measured 0 of 0 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links

measured 0 of 1 external citation measurements

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

Source: cited_works

Reference resolution

21 of 21 outbound references displayed

  • verified exact7
  • verified fuzzy0
  • unresolved11
  • parse uncertain0
  • malformed identifier0
  • metadata mismatch3

External citation measurements

No source-named external measurement is stored.

Outbound references

Observation 5323a92e-221b-4867-bbb8-61223beb9248 · outbound

This paper cites ExMeshCNN: An Explainable Convolutional Neural Network Architecture for 3D Shape Analysis,.

MeshConv3D: Efficient convolution and pooling operators for triangular 3D meshes ExMeshCNN: An Explainable Convolutional Neural Network Architecture for 3D Shape Analysis,

Reference 1

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Observation 9b432210-fdbf-40d8-a1c6-271dab4f49ed · outbound

This paper cites MeshCNN: A Network with an Edge,.

MeshConv3D: Efficient convolution and pooling operators for triangular 3D meshes MeshCNN: A Network with an Edge,

Reference 3

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Observation 143213eb-83dd-4a50-82cc-751cbc2c3a5e · outbound

This paper cites an unresolved cited work.

MeshConv3D: Efficient convolution and pooling operators for triangular 3D meshes Unresolved cited work

Reference 4

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No event found in the named queried sources as of 2026-08-11T06:34:44.6726+00:00.

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Observation 8b8285e5-b873-4eca-8a61-cc9db592da75 · outbound

This paper cites Subdivision-Based Mesh Convolution Networks,.

MeshConv3D: Efficient convolution and pooling operators for triangular 3D meshes Subdivision-Based Mesh Convolution Networks,

Reference 5

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verified exact
doi, observed 2026-08-10T21:50:06.181115Z

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No event found in the named queried sources as of 2026-08-11T06:34:44.6726+00:00.

source=pdf_text observed=2026-08-10T21:50:05.906190Z digest=sha256:a5b3bf161dfc3b26eac53ee091fd9f1d7b95ee2b099fec56ba34784bd3f13809

Observation a076b4b7-619e-4d04-86ed-f82fd79769c1 · outbound

This paper cites Multi-view Convolutional Neural Networks for 3D Shape Recognition,.

MeshConv3D: Efficient convolution and pooling operators for triangular 3D meshes Multi-view Convolutional Neural Networks for 3D Shape Recognition,

Reference 6

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Observation 3ef15f8b-d74a-4b69-b6a3-2368d710e424 · outbound

This paper cites DeepPano: Deep Panoramic Representation for 3-D Shape Recognition,.

MeshConv3D: Efficient convolution and pooling operators for triangular 3D meshes DeepPano: Deep Panoramic Representation for 3-D Shape Recognition,

Reference 7

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raw_fallback, observed 2026-08-10T21:50:06.738372Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-11T06:34:44.6726+00:00.

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Observation 22af03c5-26bf-4123-84de-0225995a7a52 · outbound

This paper cites Mesh Convolutional Autoencoder for Semi-Regular Meshes of Different Sizes,.

MeshConv3D: Efficient convolution and pooling operators for triangular 3D meshes Mesh Convolutional Autoencoder for Semi-Regular Meshes of Different Sizes,

Reference 10

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source=pdf_text observed=2026-08-10T21:50:05.939510Z digest=sha256:9320e4677459987a6292ec704b4ecbaa6d3c70c4e727845762dfe7447865f970

Observation 00333a20-4df3-4743-b436-6c10fdd3ccbe · outbound

This paper cites Geodesic Convolutional Neural Networks on Riemannian Manifolds,.

MeshConv3D: Efficient convolution and pooling operators for triangular 3D meshes Geodesic Convolutional Neural Networks on Riemannian Manifolds,

Reference 12

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doi, observed 2026-08-10T21:50:06.121062Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-11T06:34:44.6726+00:00.

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Observation 038a1796-f895-4389-aaa0-afbb8af8a452 · outbound

This paper cites DiffusionNet: Discretization Agnostic Learning on Surfaces.

MeshConv3D: Efficient convolution and pooling operators for triangular 3D meshes DiffusionNet: Discretization Agnostic Learning on Surfaces

Reference 13

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source=pdf_text observed=2026-08-10T21:50:05.955556Z digest=sha256:056546f4a5aa70fe9ed8c869b65b9256bb42b1b8059acad73912295cdb9beace

Observation ab32fa1e-cfc7-4934-b3b4-fabbcbf116bd · outbound

This paper cites Primal-Dual Mesh Convolutional Neural Networks.

MeshConv3D: Efficient convolution and pooling operators for triangular 3D meshes Primal-Dual Mesh Convolutional Neural Networks

Reference 15

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local_arxiv, observed 2026-08-10T21:50:06.076499Z

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Observation 4088f0c3-cf05-4541-809c-1a802bde653a · outbound

This paper cites Face-Based CNN on Triangular Mesh with Arbitrary Connectivity,.

MeshConv3D: Efficient convolution and pooling operators for triangular 3D meshes Face-Based CNN on Triangular Mesh with Arbitrary Connectivity,

Reference 16

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No event found in the named queried sources as of 2026-08-11T06:34:44.6726+00:00.

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Observation 55272df9-73ed-4b33-9397-df9200ca91a3 · outbound

This paper cites MAPS: multiresolution adaptive parameterization of surfaces,.

MeshConv3D: Efficient convolution and pooling operators for triangular 3D meshes MAPS: multiresolution adaptive parameterization of surfaces,

Reference 18

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No event found in the named queried sources as of 2026-08-11T06:34:44.6726+00:00.

source=pdf_text observed=2026-08-10T21:50:05.979715Z digest=sha256:100bc8014d508a5584c6b2dde18ccc89df51958d51862c1b092de4595492b4e4

Observation 2c7d7d52-51b2-4a16-978d-38e8304a9b8d · outbound

This paper cites Available: https://dl.acm.org/doi/abs/10.1145/3386569.3392418.

MeshConv3D: Efficient convolution and pooling operators for triangular 3D meshes Available: https://dl.acm.org/doi/abs/10.1145/3386569.3392418

Reference 19

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source=pdf_text observed=2026-08-10T21:50:05.984467Z digest=sha256:d11bd43ea9e719cb36552e882650edf1efe44b8e3ff72cb8f3fb4b3e89aca40a

Observation 85cd0c21-45cb-417d-978c-971b0b9f0333 · outbound

This paper cites 3D ShapeNets: A deep representation for volumetric shapes,.

MeshConv3D: Efficient convolution and pooling operators for triangular 3D meshes 3D ShapeNets: A deep representation for volumetric shapes,

Reference 20

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Observation 12296167-f8c7-4ca1-ba0d-32190bd831f4 · outbound

This paper cites MeshNet: Mesh Neural Network for 3D Shape Representation.

MeshConv3D: Efficient convolution and pooling operators for triangular 3D meshes MeshNet: Mesh Neural Network for 3D Shape Representation

Reference 21

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local_arxiv, observed 2026-08-10T21:50:06.040488Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-11T06:34:44.6726+00:00.

source=pdf_text observed=2026-08-10T21:50:05.994779Z digest=sha256:e2b8ef7785c5f6ca30f88fcfc57d413449815971cec202dfe611b4c4f7c22607

Observation cb730018-1d30-4dd0-bd15-c33382dcc0dd · outbound

This paper cites PointNet: Deep Learning on Point Sets for 3D Classification and Segmentation.

MeshConv3D: Efficient convolution and pooling operators for triangular 3D meshes PointNet: Deep Learning on Point Sets for 3D Classification and Segmentation

Reference 2017

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Observation 37b3e041-6335-4373-b080-088a42ff1692 · outbound

This paper cites HexaConv.

MeshConv3D: Efficient convolution and pooling operators for triangular 3D meshes HexaConv

Reference 2018

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source=pdf_text observed=2026-08-10T21:50:05.943973Z digest=sha256:eb0465a6e2956adb1828ad4d71ad24620a9ba506824bc8be5dc792b5ee4ab8da

Observation d611da89-22fd-4b5f-8a47-eba2760c8644 · outbound

This paper cites MeshWalker: Deep Mesh Understanding by Random Walks.

MeshConv3D: Efficient convolution and pooling operators for triangular 3D meshes MeshWalker: Deep Mesh Understanding by Random Walks

Reference 2020

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local_arxiv, observed 2026-08-10T21:50:06.094728Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-11T06:34:44.6726+00:00.

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Observation 76e91263-8347-428d-abd0-4b3f201a284d · outbound

This paper cites an unresolved cited work.

MeshConv3D: Efficient convolution and pooling operators for triangular 3D meshes Unresolved cited work

Reference 2022

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No event found in the named queried sources as of 2026-08-11T06:34:44.6726+00:00.

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Observation f6b0d130-ae31-4a67-8de5-64bfdb59d203 · outbound

This paper cites Relation-Shape Convolutional Neural Network for Point Cloud Analysis.

MeshConv3D: Efficient convolution and pooling operators for triangular 3D meshes Relation-Shape Convolutional Neural Network for Point Cloud Analysis

Reference 2023

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local_arxiv, observed 2026-08-10T21:50:06.643806Z

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No event found in the named queried sources as of 2026-08-11T06:34:44.6726+00:00.

source=pdf_text observed=2026-08-10T21:50:05.933026Z digest=sha256:d009d7d49b3b871714d5c0ac12b26982b5b4700af202ddf46a65e7ea19992397

Observation a31b3ffc-d956-4aec-b657-deaea1d27f5c · outbound

This paper cites Available: https://dl.acm.org/doi/abs/10.1145/3474085.3475468.

MeshConv3D: Efficient convolution and pooling operators for triangular 3D meshes Available: https://dl.acm.org/doi/abs/10.1145/3474085.3475468

Reference 2024

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Pith citing papers

No inbound Pith citation observations are available.