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Paper Citation Record · LEDGER

Point-LN: A Lightweight Framework for Efficient Point Cloud Classification Using Non-Parametric Positional Encoding

As of 18 August 2026, this Paper Citation Record lists 34 of 34 outbound references and 0 inbound Pith citation observations for arXiv:2501.14238.

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

pith.paper-citation-record.v1
2501.14238 v2

Coverage vector

measured 34 of 34 reference resolution

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Source: paper_references, paper_reference_links, observed 2026-08-10T15:17:57.962327Z

measured 34 of 34 standing notices

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measured 0 of 0 inbound itemization

Pith citing papers itemized under the disclosed page cap.

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measured 0 of 1 external citation measurements

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Reference resolution

34 of 34 outbound references displayed

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Outbound references

Observation 9159b0f0-7a3b-4392-8df5-43b615401056 · outbound

This paper cites A joint bayesian framework based on partial least squares discriminant analysis for finger vein recognition,.

Point-LN: A Lightweight Framework for Efficient Point Cloud Classification Using Non-Parametric Positional Encoding A joint bayesian framework based on partial least squares discriminant analysis for finger vein recognition,

Reference 1

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Observation c66591e3-b4a2-4171-b596-15de27f57f67 · outbound

This paper cites Hcfnn: high- order coverage function neural network for image classification,.

Point-LN: A Lightweight Framework for Efficient Point Cloud Classification Using Non-Parametric Positional Encoding Hcfnn: high- order coverage function neural network for image classification,

Reference 2

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Observation b34f3e72-8a97-4e66-8a46-9d94ec68e854 · outbound

This paper cites Jwsaa: joint weak saliency and attention aware for person re-identification,.

Point-LN: A Lightweight Framework for Efficient Point Cloud Classification Using Non-Parametric Positional Encoding Jwsaa: joint weak saliency and attention aware for person re-identification,

Reference 3

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Observation 9c253b76-df44-4dc1-8569-e2d35583fcb0 · outbound

This paper cites Long-term estimation of human spatial interactions through multiple laser ranging sensors,.

Point-LN: A Lightweight Framework for Efficient Point Cloud Classification Using Non-Parametric Positional Encoding Long-term estimation of human spatial interactions through multiple laser ranging sensors,

Reference 4

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Observation 9912a030-d2d7-48b0-979e-9a6ccf218e6b · outbound

This paper cites Beyond triplet loss: person re-identification with fine-grained difference-aware pairwise loss,.

Point-LN: A Lightweight Framework for Efficient Point Cloud Classification Using Non-Parametric Positional Encoding Beyond triplet loss: person re-identification with fine-grained difference-aware pairwise loss,

Reference 5

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Observation 937cc5cb-7973-4f14-984d-544008fa0c72 · outbound

This paper cites A camera and lidar data fusion method for railway object detection,.

Point-LN: A Lightweight Framework for Efficient Point Cloud Classification Using Non-Parametric Positional Encoding A camera and lidar data fusion method for railway object detection,

Reference 6

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Observation f53d9149-cadf-4e68-86b9-0996682addd3 · outbound

This paper cites Automated reconstruction of building lods from airborne lidar point clouds using an improved morphological scale space,.

Point-LN: A Lightweight Framework for Efficient Point Cloud Classification Using Non-Parametric Positional Encoding Automated reconstruction of building lods from airborne lidar point clouds using an improved morphological scale space,

Reference 7

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Observation 511be564-afdf-4314-b079-b36204560319 · outbound

This paper cites Discov- ering new shadow patterns for black-box attacks on lane detection of autonomous vehicles,.

Point-LN: A Lightweight Framework for Efficient Point Cloud Classification Using Non-Parametric Positional Encoding Discov- ering new shadow patterns for black-box attacks on lane detection of autonomous vehicles,

Reference 8

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Observation 96b0172c-ab73-47a1-b194-2651176f7de5 · outbound

This paper cites Wip: A first look at employing large multimodal models against autonomous vehicle attacks,.

Point-LN: A Lightweight Framework for Efficient Point Cloud Classification Using Non-Parametric Positional Encoding Wip: A first look at employing large multimodal models against autonomous vehicle attacks,

Reference 9

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Observation e979b28c-9ca0-4f26-8ee8-a074c776b685 · outbound

This paper cites An initial exploration of employing large multimodal models in defending against autonomous vehicles attacks,.

Point-LN: A Lightweight Framework for Efficient Point Cloud Classification Using Non-Parametric Positional Encoding An initial exploration of employing large multimodal models in defending against autonomous vehicles attacks,

Reference 10

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Observation b0f25491-c5fd-4496-b975-eded787d91d6 · outbound

This paper cites Pointnet: Deep learning on point sets for 3d classification and segmentation,.

Point-LN: A Lightweight Framework for Efficient Point Cloud Classification Using Non-Parametric Positional Encoding Pointnet: Deep learning on point sets for 3d classification and segmentation,

Reference 11

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Observation b67d61c4-8794-4b37-8a97-8473a49dfbd8 · outbound

This paper cites Pointnet++: Deep hierarchical feature learning on point sets in a metric space,.

Point-LN: A Lightweight Framework for Efficient Point Cloud Classification Using Non-Parametric Positional Encoding Pointnet++: Deep hierarchical feature learning on point sets in a metric space,

Reference 12

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Observation 9e6d76c9-01f7-4049-a1a0-04256100c046 · outbound

This paper cites Pointconv: Deep convolutional networks on 3d point clouds,.

Point-LN: A Lightweight Framework for Efficient Point Cloud Classification Using Non-Parametric Positional Encoding Pointconv: Deep convolutional networks on 3d point clouds,

Reference 13

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Observation a288963d-36a8-4163-ab1d-835e48061a82 · outbound

This paper cites Rethinking Network Design and Local Geometry in Point Cloud: A Simple Residual MLP Framework.

Point-LN: A Lightweight Framework for Efficient Point Cloud Classification Using Non-Parametric Positional Encoding Rethinking Network Design and Local Geometry in Point Cloud: A Simple Residual MLP Framework

Reference 14

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Observation c65102ae-5bd8-48e5-a186-47af713174ca · outbound

This paper cites Parameter is Not All You Need: Starting from Non-Parametric Networks for 3D Point Cloud Analysis.

Point-LN: A Lightweight Framework for Efficient Point Cloud Classification Using Non-Parametric Positional Encoding Parameter is Not All You Need: Starting from Non-Parametric Networks for 3D Point Cloud Analysis

Reference 15

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Observation 89889ae0-7d7f-4b9b-a218-4dca00b4cf8c · outbound

This paper cites Point-GN: A Non-Parametric Network Using Gaussian Positional Encoding for Point Cloud Classification.

Point-LN: A Lightweight Framework for Efficient Point Cloud Classification Using Non-Parametric Positional Encoding Point-GN: A Non-Parametric Network Using Gaussian Positional Encoding for Point Cloud Classification

Reference 16

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Observation 4cc96207-4785-49c1-aa8d-1dfec463057f · outbound

This paper cites 3d shapenets: A deep representation for volumetric shapes,.

Point-LN: A Lightweight Framework for Efficient Point Cloud Classification Using Non-Parametric Positional Encoding 3d shapenets: A deep representation for volumetric shapes,

Reference 17

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Observation d18e8e37-2623-42d0-8a35-fa28d567b0c2 · outbound

This paper cites Re- visiting point cloud classification: A new benchmark dataset and clas- sification model on real-world data,.

Point-LN: A Lightweight Framework for Efficient Point Cloud Classification Using Non-Parametric Positional Encoding Re- visiting point cloud classification: A new benchmark dataset and clas- sification model on real-world data,

Reference 18

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Observation b962d58a-5072-4253-b6bb-3495188bcf60 · outbound

This paper cites Gift: A real- time and scalable 3d shape search engine,.

Point-LN: A Lightweight Framework for Efficient Point Cloud Classification Using Non-Parametric Positional Encoding Gift: A real- time and scalable 3d shape search engine,

Reference 19

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Observation c2dce430-7d65-4e53-8ddd-6e70e4bf2d12 · outbound

This paper cites Mvtn: Multi-view transforma- tion network for 3d shape recognition,.

Point-LN: A Lightweight Framework for Efficient Point Cloud Classification Using Non-Parametric Positional Encoding Mvtn: Multi-view transforma- tion network for 3d shape recognition,

Reference 20

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No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

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Observation 3e9e1512-465a-49f6-a28b-e607e158512d · outbound

This paper cites Voxelnet: End-to-end learning for point cloud based 3d object detection,.

Point-LN: A Lightweight Framework for Efficient Point Cloud Classification Using Non-Parametric Positional Encoding Voxelnet: End-to-end learning for point cloud based 3d object detection,

Reference 21

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Observation 1f615262-1299-478f-9f9a-c099ec20558f · outbound

This paper cites Fpnn: Field probing neural networks for 3d data,.

Point-LN: A Lightweight Framework for Efficient Point Cloud Classification Using Non-Parametric Positional Encoding Fpnn: Field probing neural networks for 3d data,

Reference 22

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Observation b142f6ee-42a0-4f02-ade1-ef44adfbd189 · outbound

This paper cites Multi-view convolutional neural networks for 3d shape recognition,.

Point-LN: A Lightweight Framework for Efficient Point Cloud Classification Using Non-Parametric Positional Encoding Multi-view convolutional neural networks for 3d shape recognition,

Reference 23

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Observation b6a201de-e1ec-4f3d-b3dc-a6e47c9f52e8 · outbound

This paper cites Voxnet: A 3d convolutional neural net- work for real-time object recognition,.

Point-LN: A Lightweight Framework for Efficient Point Cloud Classification Using Non-Parametric Positional Encoding Voxnet: A 3d convolutional neural net- work for real-time object recognition,

Reference 24

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Observation c7fb29c0-2dbd-487e-83d3-caf26f836d95 · outbound

This paper cites Pointcnn: Convolution on x-transformed points,.

Point-LN: A Lightweight Framework for Efficient Point Cloud Classification Using Non-Parametric Positional Encoding Pointcnn: Convolution on x-transformed points,

Reference 25

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Observation c65e63c4-68b7-4a54-b2a6-69310a0e17c3 · outbound

This paper cites Kpconv: Flexible and deformable convolution for point clouds,.

Point-LN: A Lightweight Framework for Efficient Point Cloud Classification Using Non-Parametric Positional Encoding Kpconv: Flexible and deformable convolution for point clouds,

Reference 26

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Observation 253fb358-60a1-4d6e-858f-80029bcbbe68 · outbound

This paper cites Point-planenet: Plane kernel based convolutional neural network for point clouds analysis,.

Point-LN: A Lightweight Framework for Efficient Point Cloud Classification Using Non-Parametric Positional Encoding Point-planenet: Plane kernel based convolutional neural network for point clouds analysis,

Reference 27

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Observation 27363755-7450-4669-a9d4-4172f720100c · outbound

This paper cites Pointngcnn: Deep convolutional networks on 3d point clouds with neighborhood graph filters,.

Point-LN: A Lightweight Framework for Efficient Point Cloud Classification Using Non-Parametric Positional Encoding Pointngcnn: Deep convolutional networks on 3d point clouds with neighborhood graph filters,

Reference 28

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Observation 7914a6d2-db27-4083-affc-0b6d8206bf23 · outbound

This paper cites Dynamic graph cnn for learning on point clouds,.

Point-LN: A Lightweight Framework for Efficient Point Cloud Classification Using Non-Parametric Positional Encoding Dynamic graph cnn for learning on point clouds,

Reference 29

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No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

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Observation 7d86a9be-e307-4a60-b466-076595909d90 · outbound

This paper cites Modeling point clouds with self-attention and gumbel subset sampling,.

Point-LN: A Lightweight Framework for Efficient Point Cloud Classification Using Non-Parametric Positional Encoding Modeling point clouds with self-attention and gumbel subset sampling,

Reference 30

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Observation da3c1cb8-23ab-4dbc-80d3-0b3c204160f8 · outbound

This paper cites Point transformer,.

Point-LN: A Lightweight Framework for Efficient Point Cloud Classification Using Non-Parametric Positional Encoding Point transformer,

Reference 31

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Observation f5170528-54da-4444-b627-7ce88c1ae445 · outbound

This paper cites Attention is all you need,.

Point-LN: A Lightweight Framework for Efficient Point Cloud Classification Using Non-Parametric Positional Encoding Attention is all you need,

Reference 32

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Observation 44550252-2fdf-464a-a48b-92ce062817ce · outbound

This paper cites Geometric back-projection net- work for point cloud classification,.

Point-LN: A Lightweight Framework for Efficient Point Cloud Classification Using Non-Parametric Positional Encoding Geometric back-projection net- work for point cloud classification,

Reference 33

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Observation 35a7bdb6-f27e-49b0-9df0-aefafe649918 · outbound

This paper cites Walk in the cloud: Learning curves for point clouds shape analysis,.

Point-LN: A Lightweight Framework for Efficient Point Cloud Classification Using Non-Parametric Positional Encoding Walk in the cloud: Learning curves for point clouds shape analysis,

Reference 34

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