Paper Citation Record · LEDGER

Fast LiDAR Data Generation with Rectified Flows

As of 20 August 2026, this Paper Citation Record lists 34 of 34 outbound references and 0 inbound Pith citation observations for arXiv:2412.02241.

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

pith.paper-citation-record.v1
2412.02241 v2

Coverage vector

measured 34 of 34 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links, observed 2026-08-11T23:45:59.462594Z

measured 34 of 34 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-19T06:32:44.657259+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

34 of 34 outbound references displayed

verified exact0
verified fuzzy32
unresolved2
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External citation measurements

No source-named external measurement is stored.

Outbound references

Observation dc587c41-c988-4efa-91b2-61036cef7044 · outbound

This paper cites Deep generative modeling of LiDAR data,.

Fast LiDAR Data Generation with Rectified Flows Deep generative modeling of LiDAR data,

Reference 1

Resolution: verified fuzzy; raw_fallback, observed 2026-08-11T23:45:59.770482Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

Observation fef28f48-efd9-4082-b26b-2b6235b542b6 · outbound

This paper cites Learning to drop points for Li- DAR scan synthesis,.

Fast LiDAR Data Generation with Rectified Flows Learning to drop points for Li- DAR scan synthesis,

Reference 2

Resolution: verified fuzzy; raw_fallback, observed 2026-08-11T23:45:59.762052Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

Observation d33b4b0d-1e53-4233-99d4-7dce1d9eca1c · outbound

This paper cites Generative range imaging for learning scene priors of 3D LiDAR data,.

Fast LiDAR Data Generation with Rectified Flows Generative range imaging for learning scene priors of 3D LiDAR data,

Reference 3

Resolution: verified fuzzy; raw_fallback, observed 2026-08-11T23:45:59.753683Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

Observation 694f4a6b-643b-4bed-bb4b-ccbc11b49ce8 · outbound

This paper cites LiDAR data synthesis with denois- ing diffusion probabilistic models,.

Fast LiDAR Data Generation with Rectified Flows LiDAR data synthesis with denois- ing diffusion probabilistic models,

Reference 4

Resolution: verified fuzzy; raw_fallback, observed 2026-08-11T23:45:59.744805Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

Observation 3c511238-a94d-475c-8e1e-929d62c87c51 · outbound

This paper cites Learning to generate realistic LiDAR point clouds,.

Fast LiDAR Data Generation with Rectified Flows Learning to generate realistic LiDAR point clouds,

Reference 5

Resolution: verified fuzzy; raw_fallback, observed 2026-08-11T23:45:59.735964Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

Observation 16d6bacb-adb4-4cb1-bd40-0e5e53747f20 · outbound

This paper cites Towards realistic scene generation with LiDAR diffusion models,.

Fast LiDAR Data Generation with Rectified Flows Towards realistic scene generation with LiDAR diffusion models,

Reference 6

Resolution: verified fuzzy; raw_fallback, observed 2026-08-11T23:45:59.727934Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

Observation 8f463441-4084-4782-93ec-46335d2e7439 · outbound

This paper cites Learning compact representations for lidar completion and generation,.

Fast LiDAR Data Generation with Rectified Flows Learning compact representations for lidar completion and generation,

Reference 7

Resolution: verified fuzzy; raw_fallback, observed 2026-08-11T23:45:59.720260Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

Observation f8ab6a73-fcbb-43ac-b091-5e18500fc037 · outbound

This paper cites RangeLDM: Fast realistic LiDAR point cloud generation,.

Fast LiDAR Data Generation with Rectified Flows RangeLDM: Fast realistic LiDAR point cloud generation,

Reference 8

Resolution: verified fuzzy; raw_fallback, observed 2026-08-11T23:45:59.712597Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

Observation 1fbbcf03-62b4-4306-865d-80ca316b84d9 · outbound

This paper cites Deep gen- erative modelling: A comparative review of V AEs, GANs, normalizing flows, energy-based and autoregressive models,.

Fast LiDAR Data Generation with Rectified Flows Deep gen- erative modelling: A comparative review of V AEs, GANs, normalizing flows, energy-based and autoregressive models,

Reference 9

Resolution: verified fuzzy; raw_fallback, observed 2026-08-11T23:45:59.704644Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

Observation f7bd371d-03cc-44d1-a649-f3402b576aab · outbound

This paper cites Score-based generative modeling through stochastic differential equations,.

Fast LiDAR Data Generation with Rectified Flows Score-based generative modeling through stochastic differential equations,

Reference 10

Resolution: verified fuzzy; raw_fallback, observed 2026-08-11T23:45:59.696012Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

Observation 3c2b8b45-715d-494e-8fb4-1ad4b4818cf0 · outbound

This paper cites Scalable diffusion models with transform- ers,.

Fast LiDAR Data Generation with Rectified Flows Scalable diffusion models with transform- ers,

Reference 11

Resolution: verified fuzzy; raw_fallback, observed 2026-08-11T23:45:59.687321Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

Observation 9db14b38-ad89-48c2-ae42-a2698bc26413 · outbound

This paper cites Flow straight and fast: Learning to generate and transfer data with rectified flow,.

Fast LiDAR Data Generation with Rectified Flows Flow straight and fast: Learning to generate and transfer data with rectified flow,

Reference 12

Resolution: verified fuzzy; raw_fallback, observed 2026-08-11T23:45:59.678668Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

Observation b3344cf2-fb52-439c-9899-66bafa3b0a6b · outbound

This paper cites Improving the training of rectified flows,.

Fast LiDAR Data Generation with Rectified Flows Improving the training of rectified flows,

Reference 13

Resolution: verified fuzzy; raw_fallback, observed 2026-08-11T23:45:59.670049Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

Observation 4c596747-f35a-48cc-9341-d99820935961 · outbound

This paper cites Flow matching for generative modeling,.

Fast LiDAR Data Generation with Rectified Flows Flow matching for generative modeling,

Reference 14

Resolution: verified fuzzy; raw_fallback, observed 2026-08-11T23:45:59.661136Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

Observation 7bb820a3-1ef8-4493-8ef3-ee0b4336a030 · outbound

This paper cites Improving and generalizing flow- based generative models with minibatch optimal transport,.

Fast LiDAR Data Generation with Rectified Flows Improving and generalizing flow- based generative models with minibatch optimal transport,

Reference 15

Resolution: verified fuzzy; raw_fallback, observed 2026-08-11T23:45:59.652625Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

Observation 8873c2df-949f-442c-acee-4b534a507517 · outbound

This paper cites Scalable high-resolution pixel-space image synthesis with hourglass diffusion transformers,.

Fast LiDAR Data Generation with Rectified Flows Scalable high-resolution pixel-space image synthesis with hourglass diffusion transformers,

Reference 16

Resolution: verified fuzzy; raw_fallback, observed 2026-08-11T23:45:59.643803Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

Observation 33444011-1f3b-4f10-b0de-4674a815b680 · outbound

This paper cites KITTI-360: A novel dataset and benchmarks for urban scene understanding in 2D and 3D,.

Fast LiDAR Data Generation with Rectified Flows KITTI-360: A novel dataset and benchmarks for urban scene understanding in 2D and 3D,

Reference 17

Resolution: verified fuzzy; raw_fallback, observed 2026-08-11T23:45:59.634965Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

Observation 66baf039-deb8-4d41-93de-77155c39fabe · outbound

This paper cites Auto-encoding variational bayes,.

Fast LiDAR Data Generation with Rectified Flows Auto-encoding variational bayes,

Reference 18

Resolution: verified fuzzy; raw_fallback, observed 2026-08-11T23:45:59.626327Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

Observation a1c23ebb-89fe-4364-89c2-fc04246f2d22 · outbound

This paper cites Neural discrete representation learning,.

Fast LiDAR Data Generation with Rectified Flows Neural discrete representation learning,

Reference 19

Resolution: verified fuzzy; raw_fallback, observed 2026-08-11T23:45:59.618692Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

Observation e69e16dd-3a7a-4dab-a833-bd5b121ad117 · outbound

This paper cites Generative adversarial nets,.

Fast LiDAR Data Generation with Rectified Flows Generative adversarial nets,

Reference 20

Resolution: verified fuzzy; raw_fallback, observed 2026-08-11T23:45:59.610634Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

Observation 1b9b03dd-7746-4a22-93a6-c63ded189530 · outbound

This paper cites Generative modeling by estimating gradients of the data distribution,.

Fast LiDAR Data Generation with Rectified Flows Generative modeling by estimating gradients of the data distribution,

Reference 21

Resolution: verified fuzzy; raw_fallback, observed 2026-08-11T23:45:59.601988Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

Observation 6fd400ec-6dc6-4a35-92ca-b8256d0267ae · outbound

This paper cites Improved techniques for training score-based generative models,.

Fast LiDAR Data Generation with Rectified Flows Improved techniques for training score-based generative models,

Reference 22

Resolution: verified fuzzy; raw_fallback, observed 2026-08-11T23:45:59.592517Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

Observation d7935316-7eab-4b3d-9768-9a4ada8c8c0a · outbound

This paper cites Denoising diffusion probabilistic models,.

Fast LiDAR Data Generation with Rectified Flows Denoising diffusion probabilistic models,

Reference 23

Resolution: verified fuzzy; raw_fallback, observed 2026-08-11T23:45:59.583434Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

Observation 04dab777-3e30-4a08-b128-ad88cbd35cdb · outbound

This paper cites Variational diffusion models,.

Fast LiDAR Data Generation with Rectified Flows Variational diffusion models,

Reference 24

Resolution: verified fuzzy; raw_fallback, observed 2026-08-11T23:45:59.574255Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

Observation da8c3174-45a4-468d-adb9-542b59ec0afc · outbound

This paper cites High-resolution image synthesis with latent diffusion models,.

Fast LiDAR Data Generation with Rectified Flows High-resolution image synthesis with latent diffusion models,

Reference 25

Resolution: verified fuzzy; raw_fallback, observed 2026-08-11T23:45:59.565457Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

Observation 24aa2c6a-5f3a-4dc6-b864-d4d3fe936ab4 · outbound

This paper cites Neighborhood attention transformer,.

Fast LiDAR Data Generation with Rectified Flows Neighborhood attention transformer,

Reference 26

Resolution: verified fuzzy; raw_fallback, observed 2026-08-11T23:45:59.556378Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

Observation 6f2c5c89-ebe6-47d0-89dc-87eb9e747de3 · outbound

This paper cites An image is worth 16x16 words: Transformers for image recognition at scale,.

Fast LiDAR Data Generation with Rectified Flows An image is worth 16x16 words: Transformers for image recognition at scale,

Reference 27

Resolution: unresolved; no resolver link, observed 2026-08-11T23:45:59.441256Z

Source-reported events for the cited work

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Observation 1861f891-eda5-4ce5-b8f0-e0528f2a1109 · outbound

This paper cites Photorealistic text-to-image diffusion models with deep lan- guage understanding,.

Fast LiDAR Data Generation with Rectified Flows Photorealistic text-to-image diffusion models with deep lan- guage understanding,

Reference 28

Resolution: verified fuzzy; raw_fallback, observed 2026-08-11T23:45:59.541974Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

Observation 91ad8403-390f-411b-bcb5-4119a69e57fc · outbound

This paper cites TULIP: Transformer for upsampling of LiDAR point clouds,.

Fast LiDAR Data Generation with Rectified Flows TULIP: Transformer for upsampling of LiDAR point clouds,

Reference 29

Resolution: verified fuzzy; raw_fallback, observed 2026-08-11T23:45:59.532351Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

Observation f7a98534-1339-42de-8981-b295af96a2cf · outbound

This paper cites RoFormer: Enhanced Transformer with Rotary Position Embedding.

Fast LiDAR Data Generation with Rectified Flows RoFormer: Enhanced Transformer with Rotary Position Embedding

Reference 30

Resolution: unresolved; no resolver link, observed 2026-08-11T23:45:59.450608Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 62cbbf3f-a790-4c2d-8634-b272ce468c33 · outbound

This paper cites All are worth words: A ViT backbone for diffusion models,.

Fast LiDAR Data Generation with Rectified Flows All are worth words: A ViT backbone for diffusion models,

Reference 31

Resolution: verified fuzzy; raw_fallback, observed 2026-08-11T23:45:59.522996Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

Observation 1d1dd267-7b70-4e48-9f6b-520019bcfad4 · outbound

This paper cites 3D point cloud generative adversarial network based on tree structured graph convolutions,.

Fast LiDAR Data Generation with Rectified Flows 3D point cloud generative adversarial network based on tree structured graph convolutions,

Reference 32

Resolution: verified fuzzy; raw_fallback, observed 2026-08-11T23:45:59.513692Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

Observation 0c20192f-c461-40a7-8867-d68867727576 · outbound

This paper cites torchdiffeq,.

Fast LiDAR Data Generation with Rectified Flows torchdiffeq,

Reference 33

Resolution: verified fuzzy; raw_fallback, observed 2026-08-11T23:45:59.504638Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

Observation 36d9e9db-228e-445e-9441-1630c383d60a · outbound

This paper cites Diffusion models beat gans on image synthesis,.

Fast LiDAR Data Generation with Rectified Flows Diffusion models beat gans on image synthesis,

Reference 34

Resolution: verified fuzzy; raw_fallback, observed 2026-08-11T23:45:59.495055Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

Pith citing papers

No inbound Pith citation observations are available.