Paper Citation Record · LEDGER

Synthetic LiDAR Data Generation and Deterministic Downsampling for Point Cloud Classification on the Edge

As of 15 August 2026, this Paper Citation Record lists 35 of 35 outbound references and 0 inbound Pith citation observations for arXiv:2608.07106.

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

pith.paper-citation-record.v1
2608.07106 v1

Coverage vector

measured 35 of 35 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links, observed 2026-08-10T14:52:30.485638Z

measured 35 of 35 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-14T06:32:32.682623+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

35 of 35 outbound references displayed

verified exact5
verified fuzzy2
unresolved18
parse uncertain0
malformed identifier3
metadata mismatch7

External citation measurements

No source-named external measurement is stored.

Outbound references

Observation a13acee9-6fc5-45aa-9706-b86a88c9d505 · outbound

This paper cites Lidar for Autonomous Driving: The Principles, Chal- lenges, and Trends for Automotive Lidar and Perception Systems.

Synthetic LiDAR Data Generation and Deterministic Downsampling for Point Cloud Classification on the Edge Lidar for Autonomous Driving: The Principles, Chal- lenges, and Trends for Automotive Lidar and Perception Systems

Reference 1

Resolution: verified exact; raw_fallback, observed 2026-08-10T14:52:31.491482Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.

Observation 54765d46-262b-480e-992c-14c894634e5d · outbound

This paper cites AI-Powered LiDAR Point Cloud Understanding and Processing: An Up- dated Survey.

Synthetic LiDAR Data Generation and Deterministic Downsampling for Point Cloud Classification on the Edge AI-Powered LiDAR Point Cloud Understanding and Processing: An Up- dated Survey

Reference 2

Resolution: verified exact; raw_fallback, observed 2026-08-10T14:52:31.409074Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.

Observation 5477f951-2654-47a6-b445-051fcd5cfa6a · outbound

This paper cites Are we ready for autonomous driv- ing? The KITTI vision benchmark suite.

Synthetic LiDAR Data Generation and Deterministic Downsampling for Point Cloud Classification on the Edge Are we ready for autonomous driv- ing? The KITTI vision benchmark suite

Reference 3

Resolution: unresolved; no resolver link, observed 2026-08-10T14:52:30.360502Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation fad1c451-afa1-4fcd-90c1-36c060e98ca8 · outbound

This paper cites Vision meets robotics: The KITTI dataset.

Synthetic LiDAR Data Generation and Deterministic Downsampling for Point Cloud Classification on the Edge Vision meets robotics: The KITTI dataset

Reference 4

Resolution: unresolved; no resolver link, observed 2026-08-10T14:52:30.364532Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 6e83e2bb-048d-4804-b5e8-47ade5f7f11c · outbound

This paper cites 3D ShapeNets: A Deep Representation for Volumetric Shapes.

Synthetic LiDAR Data Generation and Deterministic Downsampling for Point Cloud Classification on the Edge 3D ShapeNets: A Deep Representation for Volumetric Shapes

Reference 5

Resolution: unresolved; no resolver link, observed 2026-08-10T14:52:30.368418Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 1492353c-ba5d-49c8-ba52-4c668d604047 · outbound

This paper cites Point Transformer V3: Sim- pler, Faster, Stronger.

Synthetic LiDAR Data Generation and Deterministic Downsampling for Point Cloud Classification on the Edge Point Transformer V3: Sim- pler, Faster, Stronger

Reference 6

Resolution: unresolved; no resolver link, observed 2026-08-10T14:52:30.372639Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 5f32731c-7974-403b-af6d-8b3d64bcca57 · outbound

This paper cites BLAINDER—A Blender AI Add- On for Generation of Semantically Labeled Depth-Sensing Data.

Synthetic LiDAR Data Generation and Deterministic Downsampling for Point Cloud Classification on the Edge BLAINDER—A Blender AI Add- On for Generation of Semantically Labeled Depth-Sensing Data

Reference 7

Resolution: malformed identifier; raw_fallback, observed 2026-08-10T14:52:31.532918Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.

Observation 445d9a98-3300-4310-a99f-48d21b71fb99 · outbound

This paper cites Adaptive Hierarchical Down-Sampling for Point Cloud Classification.

Synthetic LiDAR Data Generation and Deterministic Downsampling for Point Cloud Classification on the Edge Adaptive Hierarchical Down-Sampling for Point Cloud Classification

Reference 8

Resolution: metadata mismatch; local_arxiv, observed 2026-08-10T14:52:30.870964Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.

Observation 9f8dd62b-fc8b-4bac-8b5d-285303d70a7f · outbound

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

Synthetic LiDAR Data Generation and Deterministic Downsampling for Point Cloud Classification on the Edge PointNet: Deep Learning on Point Sets for 3D Classification and Segmentation

Reference 9

Resolution: unresolved; no resolver link, observed 2026-08-10T14:52:30.384241Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation d22eadf1-88a4-4570-941f-78d2c8702744 · outbound

This paper cites Visualizing Global Explanations of Point Cloud DNNs.

Synthetic LiDAR Data Generation and Deterministic Downsampling for Point Cloud Classification on the Edge Visualizing Global Explanations of Point Cloud DNNs

Reference 10

Resolution: unresolved; no resolver link, observed 2026-08-10T14:52:30.388451Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 9629ef41-c786-4c83-884b-63be391f9df6 · outbound

This paper cites Survey of Nearest Neighbor Techniques.

Synthetic LiDAR Data Generation and Deterministic Downsampling for Point Cloud Classification on the Edge Survey of Nearest Neighbor Techniques

Reference 11

Resolution: unresolved; no resolver link, observed 2026-08-10T14:52:30.392133Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 91088e3b-4976-4cdf-a050-b01158dece03 · outbound

This paper cites SemanticKITTI: A Dataset for Semantic Scene Understanding of LiDAR Sequences.

Synthetic LiDAR Data Generation and Deterministic Downsampling for Point Cloud Classification on the Edge SemanticKITTI: A Dataset for Semantic Scene Understanding of LiDAR Sequences

Reference 12

Resolution: unresolved; no resolver link, observed 2026-08-10T14:52:30.396547Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation a7e9acd2-3bd6-430c-83ea-42729f360c40 · outbound

This paper cites Point Cloud Classification with ModelNet40: What is left?.

Synthetic LiDAR Data Generation and Deterministic Downsampling for Point Cloud Classification on the Edge Point Cloud Classification with ModelNet40: What is left?

Reference 13

Resolution: verified fuzzy; raw_fallback, observed 2026-08-10T14:52:31.519059Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.

Observation 1c6baac9-49bb-486f-a330-172972653903 · outbound

This paper cites Enhancing 3D Point Cloud Classification with ModelNet-R and Point-SkipNet.

Synthetic LiDAR Data Generation and Deterministic Downsampling for Point Cloud Classification on the Edge Enhancing 3D Point Cloud Classification with ModelNet-R and Point-SkipNet

Reference 14

Resolution: metadata mismatch; local_arxiv, observed 2026-08-10T14:52:30.822787Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.

Observation 604c150b-1bea-4d5a-b0c1-f67f147106ff · outbound

This paper cites Advancements in Point Cloud Data Augmentation for Deep Learning: A Survey.

Synthetic LiDAR Data Generation and Deterministic Downsampling for Point Cloud Classification on the Edge Advancements in Point Cloud Data Augmentation for Deep Learning: A Survey

Reference 15

Resolution: malformed identifier; local_arxiv, observed 2026-08-10T14:52:31.099043Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.

Observation 507c8c2e-78e4-4bcc-91a4-32d99516abfd · outbound

This paper cites PointCutMix: Regularization Strategy for Point Cloud Classification.

Synthetic LiDAR Data Generation and Deterministic Downsampling for Point Cloud Classification on the Edge PointCutMix: Regularization Strategy for Point Cloud Classification

Reference 16

Resolution: metadata mismatch; local_arxiv, observed 2026-08-10T14:52:30.805655Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.

Observation 7eb89b5e-9a30-41a6-a8f8-3dfc6ebb4135 · outbound

This paper cites Benchmarking Robustness of 3D Point Cloud Recognition Against Common Corruptions.

Synthetic LiDAR Data Generation and Deterministic Downsampling for Point Cloud Classification on the Edge Benchmarking Robustness of 3D Point Cloud Recognition Against Common Corruptions

Reference 17

Resolution: unresolved; no resolver link, observed 2026-08-10T14:52:30.415971Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 54b59db2-72fb-4b5c-ba0c-4f21972dffb2 · outbound

This paper cites Virtual Sparse Convolution for Multimodal 3D Object Detection.

Synthetic LiDAR Data Generation and Deterministic Downsampling for Point Cloud Classification on the Edge Virtual Sparse Convolution for Multimodal 3D Object Detection

Reference 18

Resolution: metadata mismatch; local_arxiv, observed 2026-08-10T14:52:30.777900Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.

Observation b5fca164-6995-47a9-afcb-7ec6fb6f966d · outbound

This paper cites Deep Learning on 3D Semantic Segmentation: A Detailed Review.

Synthetic LiDAR Data Generation and Deterministic Downsampling for Point Cloud Classification on the Edge Deep Learning on 3D Semantic Segmentation: A Detailed Review

Reference 19

Resolution: verified exact; local_arxiv, observed 2026-08-10T14:52:31.082864Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.

Observation c8a0c254-101c-4e26-8473-c506930302cc · outbound

This paper cites Point Cloud Based Scene Segmentation: A Survey.

Synthetic LiDAR Data Generation and Deterministic Downsampling for Point Cloud Classification on the Edge Point Cloud Based Scene Segmentation: A Survey

Reference 20

Resolution: unresolved; no resolver link, observed 2026-08-10T14:52:30.427748Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 972d4c3b-076d-4cc0-89bd-20600008e16d · outbound

This paper cites SqueezeSeg: Convolutional Neural Nets with Recurrent CRF for Real-Time Road-Object Segmentation from 3D LiDAR Point Cloud.

Synthetic LiDAR Data Generation and Deterministic Downsampling for Point Cloud Classification on the Edge SqueezeSeg: Convolutional Neural Nets with Recurrent CRF for Real-Time Road-Object Segmentation from 3D LiDAR Point Cloud

Reference 21

Resolution: unresolved; no resolver link, observed 2026-08-10T14:52:30.431589Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation f044d6ea-8259-4604-b14a-c88308400ee1 · outbound

This paper cites SqueezeSegV2: Improved Model Structure and Unsupervised Domain Adaptation for Road-Object Segmentation from a LiDAR Point Cloud.

Synthetic LiDAR Data Generation and Deterministic Downsampling for Point Cloud Classification on the Edge SqueezeSegV2: Improved Model Structure and Unsupervised Domain Adaptation for Road-Object Segmentation from a LiDAR Point Cloud

Reference 22

Resolution: unresolved; no resolver link, observed 2026-08-10T14:52:30.435423Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation aa1744df-5d38-4ff2-8d7e-bca3e0683f6d · outbound

This paper cites 3D-MiniNet: Learning a 2D Representation from Point Clouds for Fast and Efficient 3D LIDAR Semantic Segmentation.

Synthetic LiDAR Data Generation and Deterministic Downsampling for Point Cloud Classification on the Edge 3D-MiniNet: Learning a 2D Representation from Point Clouds for Fast and Efficient 3D LIDAR Semantic Segmentation

Reference 23

Resolution: metadata mismatch; local_arxiv, observed 2026-08-10T14:52:30.730413Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.

Observation 7d2a61c7-3d07-472c-b131-c473d5cb611c · outbound

This paper cites Learning Semantic Seg- mentation of Large-Scale Point Clouds With Random Sampling.

Synthetic LiDAR Data Generation and Deterministic Downsampling for Point Cloud Classification on the Edge Learning Semantic Seg- mentation of Large-Scale Point Clouds With Random Sampling

Reference 24

Resolution: unresolved; no resolver link, observed 2026-08-10T14:52:30.443119Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 3f0471cc-c0e9-4662-95f1-16ecfd4d51b9 · outbound

This paper cites Deep Learning-based 3D Point Cloud Classification: A Systematic Survey and Outlook.

Synthetic LiDAR Data Generation and Deterministic Downsampling for Point Cloud Classification on the Edge Deep Learning-based 3D Point Cloud Classification: A Systematic Survey and Outlook

Reference 25

Resolution: verified exact; local_arxiv, observed 2026-08-10T14:52:30.983434Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.

Observation 115e790f-70a5-4cda-aa1f-f24726cfc3bf · outbound

This paper cites Searching Efficient 3D Architectures with Sparse Point-Voxel Convo- lution.

Synthetic LiDAR Data Generation and Deterministic Downsampling for Point Cloud Classification on the Edge Searching Efficient 3D Architectures with Sparse Point-Voxel Convo- lution

Reference 26

Resolution: malformed identifier; no resolver link, observed 2026-08-10T14:52:30.450713Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 9044497e-3912-42bf-8888-f6290de6a386 · outbound

This paper cites PointNet++: Deep Hierarchical Feature Learning on Point Sets in a Metric Space.

Synthetic LiDAR Data Generation and Deterministic Downsampling for Point Cloud Classification on the Edge PointNet++: Deep Hierarchical Feature Learning on Point Sets in a Metric Space

Reference 27

Resolution: unresolved; no resolver link, observed 2026-08-10T14:52:30.454684Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 953162b0-f3c2-437f-acbe-eea4431a5937 · outbound

This paper cites Dynamic Graph CNN for Learning on Point Clouds.

Synthetic LiDAR Data Generation and Deterministic Downsampling for Point Cloud Classification on the Edge Dynamic Graph CNN for Learning on Point Clouds

Reference 28

Resolution: unresolved; no resolver link, observed 2026-08-10T14:52:30.458722Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation bc3c581e-bb20-4027-8904-7bb94cfd236c · outbound

This paper cites arXiv:2303.16570 [cs.CV].

Synthetic LiDAR Data Generation and Deterministic Downsampling for Point Cloud Classification on the Edge arXiv:2303.16570 [cs.CV]

Reference 29

Resolution: verified exact; doi, observed 2026-08-10T14:52:30.682753Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.

Observation 022bce74-091d-4915-b113-51aa1cb61fc1 · outbound

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

Synthetic LiDAR Data Generation and Deterministic Downsampling for Point Cloud Classification on the Edge Point-GN: A Non-Parametric Network Using Gaussian Positional Encoding for Point Cloud Classification

Reference 30

Resolution: unresolved; no resolver link, observed 2026-08-10T14:52:30.466429Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation c2dee2bc-f6d6-4fd3-b67a-a5c5c917c79e · outbound

This paper cites PointCloud Saliency Maps.

Synthetic LiDAR Data Generation and Deterministic Downsampling for Point Cloud Classification on the Edge PointCloud Saliency Maps

Reference 31

Resolution: unresolved; no resolver link, observed 2026-08-10T14:52:30.470527Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 2a5c17e0-8345-4230-810e-bcea96e214bb · outbound

This paper cites Fast and Simple Explainability for Point Cloud Networks.

Synthetic LiDAR Data Generation and Deterministic Downsampling for Point Cloud Classification on the Edge Fast and Simple Explainability for Point Cloud Networks

Reference 32

Resolution: unresolved; no resolver link, observed 2026-08-10T14:52:30.474484Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 81f9da7a-b891-4001-b707-ac28cc5ead40 · outbound

This paper cites Surrogate Model-Based Explainability Methods for Point Cloud NNs.

Synthetic LiDAR Data Generation and Deterministic Downsampling for Point Cloud Classification on the Edge Surrogate Model-Based Explainability Methods for Point Cloud NNs

Reference 33

Resolution: metadata mismatch; local_arxiv, observed 2026-08-10T14:52:30.523062Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.

Observation eea66295-4d21-4cc4-b2e7-a8f327d171bf · outbound

This paper cites Characterizing Deep Neural Networks on Edge Computing Systems for Object Classification in 3D Point Clouds.

Synthetic LiDAR Data Generation and Deterministic Downsampling for Point Cloud Classification on the Edge Characterizing Deep Neural Networks on Edge Computing Systems for Object Classification in 3D Point Clouds

Reference 34

Resolution: metadata mismatch; raw_fallback, observed 2026-08-10T14:52:30.965827Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.

Observation 6b672ad3-07f5-411d-83ad-267351ed5900 · outbound

This paper cites Meyer and S.

Synthetic LiDAR Data Generation and Deterministic Downsampling for Point Cloud Classification on the Edge Meyer and S

Reference 35

Resolution: verified fuzzy; raw_fallback, observed 2026-08-10T14:52:31.506523Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.

Pith citing papers

No inbound Pith citation observations are available.