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Paper Citation Record · LEDGER

Data-Efficient Point Cloud Semantic Segmentation Pipeline for Unimproved Roads

As of 22 August 2026, this Paper Citation Record lists 23 of 23 outbound references and 0 inbound Pith citation observations for arXiv:2508.20135.

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

pith.paper-citation-record.v1
2508.20135 v1

Coverage vector

measured 23 of 23 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links, observed 2026-08-15T16:58:51.203361Z

measured 23 of 23 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-21T06:32:19.484+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

23 of 23 outbound references displayed

  • verified exact0
  • verified fuzzy21
  • unresolved2
  • parse uncertain0
  • malformed identifier0
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External citation measurements

No source-named external measurement is stored.

Outbound references

Observation 27d6f3b6-a246-4b66-a69b-ccd5c15823df · outbound

This paper cites Scalability in Percep- tion for Autonomous Driving: Waymo Open Dataset,.

Data-Efficient Point Cloud Semantic Segmentation Pipeline for Unimproved Roads Scalability in Percep- tion for Autonomous Driving: Waymo Open Dataset,

Reference 1

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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.

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Observation 9a69ae10-fe12-4c82-bb8a-fd53dc26ee73 · outbound

This paper cites SemanticKITTI: A Dataset for Semantic Scene Under- standing of LiDAR Sequences,.

Data-Efficient Point Cloud Semantic Segmentation Pipeline for Unimproved Roads SemanticKITTI: A Dataset for Semantic Scene Under- standing of LiDAR Sequences,

Reference 2

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raw_fallback, observed 2026-08-15T16:58:51.488303Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.

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Observation 7a23baeb-e002-4d34-b2c2-3409993f34ff · outbound

This paper cites A Closer Look at Few-shot Classification,.

Data-Efficient Point Cloud Semantic Segmentation Pipeline for Unimproved Roads A Closer Look at Few-shot Classification,

Reference 3

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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.

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Observation b42991f8-3453-4168-aa88-cc165f9522a7 · outbound

This paper cites Prototypical Networks for Few- shot Learning,.

Data-Efficient Point Cloud Semantic Segmentation Pipeline for Unimproved Roads Prototypical Networks for Few- shot Learning,

Reference 4

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raw_fallback, observed 2026-08-15T16:58:51.459578Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.

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Observation 965d770d-6cfc-4a5c-bd83-2ec7b19e782c · outbound

This paper cites SimpleShot: Revisiting Nearest-Neighbor Classification for Few-Shot Learning.

Data-Efficient Point Cloud Semantic Segmentation Pipeline for Unimproved Roads SimpleShot: Revisiting Nearest-Neighbor Classification for Few-Shot Learning

Reference 5

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no resolver link, observed 2026-08-15T16:58:51.135242Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-15T16:58:51.135242Z digest=sha256:b103fe4ab21794daa3cb1cd32cfb2c8dc68c1c9a613af14e0338f1625c988bf2

Observation 9c2af06f-a6cc-48ce-815f-7c3da991def3 · outbound

This paper cites Self- Supervised Learning For Few-Shot Image Classification,.

Data-Efficient Point Cloud Semantic Segmentation Pipeline for Unimproved Roads Self- Supervised Learning For Few-Shot Image Classification,

Reference 6

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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.

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Observation a4babfe5-6505-4d23-b7be-bd10c42ea3e9 · outbound

This paper cites Pushing the Limits of Simple Pipelines for Few-Shot Learning: External Data and Fine-Tuning Make a Difference,.

Data-Efficient Point Cloud Semantic Segmentation Pipeline for Unimproved Roads Pushing the Limits of Simple Pipelines for Few-Shot Learning: External Data and Fine-Tuning Make a Difference,

Reference 7

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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.

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Observation 5ca124a7-4f27-49f6-b251-fa134aeea0f4 · outbound

This paper cites Re- thinking Few-Shot Image Classification: a Good Embedding Is All You Need?,.

Data-Efficient Point Cloud Semantic Segmentation Pipeline for Unimproved Roads Re- thinking Few-Shot Image Classification: a Good Embedding Is All You Need?,

Reference 8

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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.

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Observation 744ed32f-c871-4998-9549-6670dbff5240 · outbound

This paper cites PANet: Few-shot image semantic segmentation with prototype alignment,.

Data-Efficient Point Cloud Semantic Segmentation Pipeline for Unimproved Roads PANet: Few-shot image semantic segmentation with prototype alignment,

Reference 9

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raw_fallback, observed 2026-08-15T16:58:51.411266Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.

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Observation 42e2f43b-6fea-486c-a96f-ba75ae918350 · outbound

This paper cites GPr-Net: Geometric Prototypical Network for Point Cloud Few-Shot Learning,.

Data-Efficient Point Cloud Semantic Segmentation Pipeline for Unimproved Roads GPr-Net: Geometric Prototypical Network for Point Cloud Few-Shot Learning,

Reference 10

Resolution
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raw_fallback, observed 2026-08-15T16:58:51.398713Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.

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Observation ebff2f4b-4f03-4bde-843b-965439468629 · outbound

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

Data-Efficient Point Cloud Semantic Segmentation Pipeline for Unimproved Roads 3d shapenets: A deep representation for volumetric shapes,

Reference 11

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no resolver link, observed 2026-08-15T16:58:51.158670Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

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Observation e5d2176c-0b2c-436d-80e7-ab82dcaf5afa · outbound

This paper cites A Closer Look at Few-Shot 3D Point Cloud Classification,.

Data-Efficient Point Cloud Semantic Segmentation Pipeline for Unimproved Roads A Closer Look at Few-Shot 3D Point Cloud Classification,

Reference 12

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verified fuzzy
raw_fallback, observed 2026-08-15T16:58:51.379109Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.

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Observation c21da4b8-f312-4b67-8abb-bddd385062e8 · outbound

This paper cites Unified 3D Segmenter As Prototypical Classifiers,.

Data-Efficient Point Cloud Semantic Segmentation Pipeline for Unimproved Roads Unified 3D Segmenter As Prototypical Classifiers,

Reference 13

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raw_fallback, observed 2026-08-15T16:58:51.367914Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.

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Observation 03eb9316-53a8-42fe-820a-dc3dc45867cc · outbound

This paper cites ProtoSeg: A Prototype-Based Point Cloud Instance Segmentation Method,.

Data-Efficient Point Cloud Semantic Segmentation Pipeline for Unimproved Roads ProtoSeg: A Prototype-Based Point Cloud Instance Segmentation Method,

Reference 14

Resolution
verified fuzzy
raw_fallback, observed 2026-08-15T16:58:51.356334Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.

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Observation be8b90ff-51a4-4fc3-8e5e-00ff1682dfae · outbound

This paper cites Few-shot 3D Point Cloud Semantic Segmentation,.

Data-Efficient Point Cloud Semantic Segmentation Pipeline for Unimproved Roads Few-shot 3D Point Cloud Semantic Segmentation,

Reference 15

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raw_fallback, observed 2026-08-15T16:58:51.344417Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.

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Observation aa1c6911-505a-4106-8a3b-099884fa077e · outbound

This paper cites Towards Large-Scale 3D Representation Learning with Multi-Dataset Point Prompt Training,.

Data-Efficient Point Cloud Semantic Segmentation Pipeline for Unimproved Roads Towards Large-Scale 3D Representation Learning with Multi-Dataset Point Prompt Training,

Reference 16

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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.

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Observation 63fd0bb7-be22-4b4a-890a-33d667f9dd7b · outbound

This paper cites Point Transformer V3: Simpler, Faster, Stronger,.

Data-Efficient Point Cloud Semantic Segmentation Pipeline for Unimproved Roads Point Transformer V3: Simpler, Faster, Stronger,

Reference 17

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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.

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Observation 7dca7a56-b8f8-415a-a100-46e37ced76c0 · outbound

This paper cites Manifold Mixup: Better Representations by Interpolat- ing Hidden States,.

Data-Efficient Point Cloud Semantic Segmentation Pipeline for Unimproved Roads Manifold Mixup: Better Representations by Interpolat- ing Hidden States,

Reference 18

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raw_fallback, observed 2026-08-15T16:58:51.309560Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.

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Observation 249593b8-99b1-436e-8835-9dca47f93e7a · outbound

This paper cites Charting the Right Manifold: Manifold Mixup for Few-shot Learning,.

Data-Efficient Point Cloud Semantic Segmentation Pipeline for Unimproved Roads Charting the Right Manifold: Manifold Mixup for Few-shot Learning,

Reference 19

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raw_fallback, observed 2026-08-15T16:58:51.297250Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.

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Observation 3b8c5fcd-bae0-4dfe-9064-c52471cf9706 · outbound

This paper cites PointMixup: Augmentation for Point Clouds,.

Data-Efficient Point Cloud Semantic Segmentation Pipeline for Unimproved Roads PointMixup: Augmentation for Point Clouds,

Reference 20

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raw_fallback, observed 2026-08-15T16:58:51.285826Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.

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Observation e3d20ac1-30b9-4721-8991-c02b37faafed · outbound

This paper cites SimpliMix: A Sim- plified Manifold Mixup for Few-shot Point Cloud Classification,.

Data-Efficient Point Cloud Semantic Segmentation Pipeline for Unimproved Roads SimpliMix: A Sim- plified Manifold Mixup for Few-shot Point Cloud Classification,

Reference 21

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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.

source=pdf_text observed=2026-08-15T16:58:51.195474Z digest=sha256:c11f3a12b85e7aa620e60abd4fd63a4c39c14e36254949ce285571720b8774df

Observation b56a060a-7393-4828-9253-1b506e68201a · outbound

This paper cites FRNet: Frustum-Range Networks for Scalable LiDAR Segmentation,.

Data-Efficient Point Cloud Semantic Segmentation Pipeline for Unimproved Roads FRNet: Frustum-Range Networks for Scalable LiDAR Segmentation,

Reference 22

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raw_fallback, observed 2026-08-15T16:58:51.260361Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.

source=pdf_text observed=2026-08-15T16:58:51.199587Z digest=sha256:4942ecde2c3d2f5b910c30a21e351a3828480a98c0e42b08ef0919778bbd3f2f

Observation 5ef6863d-1ac8-416b-821a-a488860d370b · outbound

This paper cites PointNeXt: Revisiting PointNet++ with Improved Training and Scaling Strategies,.

Data-Efficient Point Cloud Semantic Segmentation Pipeline for Unimproved Roads PointNeXt: Revisiting PointNet++ with Improved Training and Scaling Strategies,

Reference 23

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raw_fallback, observed 2026-08-15T16:58:51.248318Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.

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Pith citing papers

No inbound Pith citation observations are available.