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Paper Citation Record · LEDGER

A Continuous-Time Consistency Model for 3D Point Cloud Generation

As of 7 August 2026, this Paper Citation Record lists 55 of 55 outbound references and 0 inbound Pith citation observations for arXiv:2509.01492.

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

pith.paper-citation-record.v1
2509.01492 v1

Coverage vector

measured 55 of 55 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links, observed 2026-08-05T12:43:37.993951Z

measured 55 of 55 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-07T06:34:17.273281+00:00

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

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

Source: cited_works

Reference resolution

55 of 55 outbound references displayed

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  • verified fuzzy24
  • unresolved26
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External citation measurements

No source-named external measurement is stored.

Outbound references

Observation 17b0fd63-5019-4494-84c0-3ad8dd3fafa5 · outbound

This paper cites Learning representations and generative models for 3d point clouds.

A Continuous-Time Consistency Model for 3D Point Cloud Generation Learning representations and generative models for 3d point clouds

Reference 1

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Observation c386105c-18a7-4460-b7de-9d7d9cf77b92 · outbound

This paper cites How to build a consistency model: Learning flow maps via self-distillation.

A Continuous-Time Consistency Model for 3D Point Cloud Generation How to build a consistency model: Learning flow maps via self-distillation

Reference 2

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Observation 8398d99b-32db-4581-aadb-e5240975dd26 · outbound

This paper cites Learning gradient fields for shape generation.

A Continuous-Time Consistency Model for 3D Point Cloud Generation Learning gradient fields for shape generation

Reference 3

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Observation b5b762cf-4bf3-44ef-bfe6-db3c8e9fe52d · outbound

This paper cites ShapeNet: An Information-Rich 3D Model Repository.

A Continuous-Time Consistency Model for 3D Point Cloud Generation ShapeNet: An Information-Rich 3D Model Repository

Reference 4

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Observation c1f47107-9e01-4157-972b-3683c92d7c98 · outbound

This paper cites Sana-sprint: One-step diffusion with continuous-time consistency distillation.

A Continuous-Time Consistency Model for 3D Point Cloud Generation Sana-sprint: One-step diffusion with continuous-time consistency distillation

Reference 5

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Observation 629d3e42-00dc-4ad0-8187-62b186a79427 · outbound

This paper cites Convergence Of Consistency Model With Multistep Sampling Under General Data Assumptions.

A Continuous-Time Consistency Model for 3D Point Cloud Generation Convergence Of Consistency Model With Multistep Sampling Under General Data Assumptions

Reference 6

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Observation ff8072be-53b3-4d3f-bbcd-f62107582bac · outbound

This paper cites Improved Training Technique for Latent Consistency Models.

A Continuous-Time Consistency Model for 3D Point Cloud Generation Improved Training Technique for Latent Consistency Models

Reference 7

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Observation c1190d93-62e9-4bd1-a5ce-e260ae8ddbd5 · outbound

This paper cites Multi-scale latent point consistency models for 3d shape generation.

A Continuous-Time Consistency Model for 3D Point Cloud Generation Multi-scale latent point consistency models for 3d shape generation

Reference 8

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Observation e92fa9ce-002e-4e68-b218-4883d9db1b77 · outbound

This paper cites A point set generation network for 3d object reconstruction from a single image.

A Continuous-Time Consistency Model for 3D Point Cloud Generation A point set generation network for 3d object reconstruction from a single image

Reference 9

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Observation 604f8cdb-2f2d-48a5-8405-06092d35cd37 · outbound

This paper cites Towards an MLOps Architecture for XAI in Industrial Applications.

A Continuous-Time Consistency Model for 3D Point Cloud Generation Towards an MLOps Architecture for XAI in Industrial Applications

Reference 10

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Observation 213ce1dc-a743-46ff-85a5-148f4f87e75e · outbound

This paper cites Point cloud diffusion models for automatic implant generation.

A Continuous-Time Consistency Model for 3D Point Cloud Generation Point cloud diffusion models for automatic implant generation

Reference 11

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Observation 58474512-516e-414b-bcff-7907dc0816ed · outbound

This paper cites Multistep Consistency Models.

A Continuous-Time Consistency Model for 3D Point Cloud Generation Multistep Consistency Models

Reference 12

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Observation 4c67e665-5bb6-48c7-b8bf-24f7ee12b3e4 · outbound

This paper cites Denoising diffusion probabilistic models.

A Continuous-Time Consistency Model for 3D Point Cloud Generation Denoising diffusion probabilistic models

Reference 13

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Observation e54916b1-b4fd-430c-ac84-fdcb833a768c · outbound

This paper cites Design automation: A conditional vae approach to 3d object generation under conditions.

A Continuous-Time Consistency Model for 3D Point Cloud Generation Design automation: A conditional vae approach to 3d object generation under conditions

Reference 14

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Observation 60eb5d37-1089-4d74-bcad-3938b8f9601a · outbound

This paper cites Not-So-Optimal Transport Flows for 3D Point Cloud Generation.

A Continuous-Time Consistency Model for 3D Point Cloud Generation Not-So-Optimal Transport Flows for 3D Point Cloud Generation

Reference 15

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Observation 90c350ba-f7fd-4121-9c40-fa3f721b5602 · outbound

This paper cites Progressive point cloud deconvolution generation network.

A Continuous-Time Consistency Model for 3D Point Cloud Generation Progressive point cloud deconvolution generation network

Reference 16

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Observation a8fcc853-576f-40a2-bdbe-eed5906edf84 · outbound

This paper cites Progressive point cloud deconvolution generation network.

A Continuous-Time Consistency Model for 3D Point Cloud Generation Progressive point cloud deconvolution generation network

Reference 17

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Observation 34ce6c03-6063-4b69-ae8f-5dd52aeb72e3 · outbound

This paper cites Consistency Diffusion Models for Single-Image 3D Reconstruction with Priors.

A Continuous-Time Consistency Model for 3D Point Cloud Generation Consistency Diffusion Models for Single-Image 3D Reconstruction with Priors

Reference 18

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Observation f31bda9f-ac2e-4806-abfe-26ad589e1217 · outbound

This paper cites Softflow: Probabilistic framework for normalizing flow on manifolds.

A Continuous-Time Consistency Model for 3D Point Cloud Generation Softflow: Probabilistic framework for normalizing flow on manifolds

Reference 19

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Observation b0df4866-b3ee-48cf-bdcf-109727c06b7c · outbound

This paper cites Setvae: Learning hierarchical composition for generative modeling of set-structured data.

A Continuous-Time Consistency Model for 3D Point Cloud Generation Setvae: Learning hierarchical composition for generative modeling of set-structured data

Reference 20

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Observation 549e57d2-5f51-4998-bf56-4f35b8efd0f0 · outbound

This paper cites Adam: A Method for Stochastic Optimization.

A Continuous-Time Consistency Model for 3D Point Cloud Generation Adam: A Method for Stochastic Optimization

Reference 21

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Observation 7c716688-5ed6-4aab-a878-ab4b43b16e52 · outbound

This paper cites Discrete point flow networks for efficient point cloud generation.

A Continuous-Time Consistency Model for 3D Point Cloud Generation Discrete point flow networks for efficient point cloud generation

Reference 22

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Observation 3ff38092-e808-42f3-82fd-1c7e8ad78d82 · outbound

This paper cites Sp-gan: Sphere-guided 3d shape generation and manipula- tion.

A Continuous-Time Consistency Model for 3D Point Cloud Generation Sp-gan: Sphere-guided 3d shape generation and manipula- tion

Reference 23

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Observation 8f2a0486-55ab-4f5e-9135-93d0ce4bd96d · outbound

This paper cites Generalized deep 3d shape prior via part-discretized diffusion process.

A Continuous-Time Consistency Model for 3D Point Cloud Generation Generalized deep 3d shape prior via part-discretized diffusion process

Reference 24

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Observation 2ea36f1f-195f-4e42-b1ba-f06c02d16241 · outbound

This paper cites Flow Matching for Generative Modeling.

A Continuous-Time Consistency Model for 3D Point Cloud Generation Flow Matching for Generative Modeling

Reference 25

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Observation b1e0da13-e053-4f03-bd26-0f6fcd30ec2c · outbound

This paper cites Treegan: Syntax-aware sequence generation with generative adversarial networks.

A Continuous-Time Consistency Model for 3D Point Cloud Generation Treegan: Syntax-aware sequence generation with generative adversarial networks

Reference 26

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Observation e66623ea-f63e-40c0-9a60-f33447ac5c9c · outbound

This paper cites MeshDiffusion: Score-based Generative 3D Mesh Modeling.

A Continuous-Time Consistency Model for 3D Point Cloud Generation MeshDiffusion: Score-based Generative 3D Mesh Modeling

Reference 27

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Observation 2e1902f2-1508-4b32-8aa0-f09e74c0aab9 · outbound

This paper cites Point-voxel cnn for efficient 3d deep learning.

A Continuous-Time Consistency Model for 3D Point Cloud Generation Point-voxel cnn for efficient 3d deep learning

Reference 28

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Observation bbf4a540-0a14-48c2-bab0-0c2f5036f3c4 · outbound

This paper cites Simplifying, Stabilizing and Scaling Continuous-Time Consistency Models.

A Continuous-Time Consistency Model for 3D Point Cloud Generation Simplifying, Stabilizing and Scaling Continuous-Time Consistency Models

Reference 29

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Observation e8fbbf00-7937-4b19-bcb0-0b017b2e1120 · outbound

This paper cites ManiCM: Real-time 3D Diffusion Policy via Consistency Model for Robotic Manipulation.

A Continuous-Time Consistency Model for 3D Point Cloud Generation ManiCM: Real-time 3D Diffusion Policy via Consistency Model for Robotic Manipulation

Reference 30

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Observation dbe059f4-e5fd-406f-8143-3a9633f46e2f · outbound

This paper cites Diffusion probabilistic models for 3d point cloud generation.

A Continuous-Time Consistency Model for 3D Point Cloud Generation Diffusion probabilistic models for 3d point cloud generation

Reference 31

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Source-reported events for the cited work

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Observation 3aacb28b-af60-40b2-9ba5-c4295af6cc51 · outbound

This paper cites Dit-3d: Exploring plain diffusion transformers for 3d shape generation.

A Continuous-Time Consistency Model for 3D Point Cloud Generation Dit-3d: Exploring plain diffusion transformers for 3d shape generation

Reference 32

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Observation ccce8a22-0b63-4237-b38b-4a6df11b1232 · outbound

This paper cites Dit-3d: Exploring plain diffusion transformers for 3d shape generation.

A Continuous-Time Consistency Model for 3D Point Cloud Generation Dit-3d: Exploring plain diffusion transformers for 3d shape generation

Reference 33

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Observation 449b5ef1-ed3d-4697-a102-e0145acce195 · outbound

This paper cites Shape as points: A differentiable poisson solver.

A Continuous-Time Consistency Model for 3D Point Cloud Generation Shape as points: A differentiable poisson solver

Reference 34

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Observation 71fa3079-808a-4828-944c-54a113d4f85c · outbound

This paper cites Convolutional occupancy networks.

A Continuous-Time Consistency Model for 3D Point Cloud Generation Convolutional occupancy networks

Reference 35

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source=pdf_text observed=2026-08-05T12:43:35.163694Z digest=sha256:869b2efb42fc5d23ca16777af300ff762f4b76279f211a9dbaeb31f33df21ff9

Observation 2eff67fa-4ab9-4070-9409-68b7dcae583c · outbound

This paper cites A Generative Neural Network Approach for 3D Multi-Criteria Design Generation and Optimization of an Engine Mount for an Unmanned Air Vehicle.

A Continuous-Time Consistency Model for 3D Point Cloud Generation A Generative Neural Network Approach for 3D Multi-Criteria Design Generation and Optimization of an Engine Mount for an Unmanned Air Vehicle

Reference 36

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verified exact
local_arxiv, observed 2026-08-05T12:43:38.518342Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

source=pdf_text observed=2026-08-05T12:43:35.305965Z digest=sha256:78a37b8a16d8b47b65bbc17a233959e55f5e106bdfa971fad8c3152d6e4381fb

Observation 7c90efbc-2a33-463f-9d05-a10aee93c606 · outbound

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

A Continuous-Time Consistency Model for 3D Point Cloud Generation Pointnet: Deep learning on point sets for 3d classification and segmentation

Reference 37

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no resolver link, observed 2026-08-05T12:43:35.434879Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-05T12:43:35.434879Z digest=sha256:1561d97dc402da0d41e352fdf44285b0a2e47b59655d1a94a7c5f14ce1157db5

Observation 35b60a79-6e54-4aa0-8784-ad5b2d00c791 · outbound

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

A Continuous-Time Consistency Model for 3D Point Cloud Generation Pointnet++: Deep hierarchical feature learning on point sets in a metric space

Reference 38

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no resolver link, observed 2026-08-05T12:43:35.567421Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-05T12:43:35.567421Z digest=sha256:8b6b88a70b39b9dcb118b4986dcb1e7068c2027e82524f476c3b3ae81e0bed65

Observation 75730211-1dc1-40db-bdc2-d5402a0d6a1e · outbound

This paper cites Learning transferable visual models from natural language supervision.

A Continuous-Time Consistency Model for 3D Point Cloud Generation Learning transferable visual models from natural language supervision

Reference 39

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no resolver link, observed 2026-08-05T12:43:35.693094Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-05T12:43:35.693094Z digest=sha256:b6b8fd23e8c410e486b330df84594d7902caa42be1672df1fdff308a165bf939

Observation 39be6238-5342-4d48-b03e-50eb03eb89be · outbound

This paper cites The earth mover’s distance as a metric for image retrieval.

A Continuous-Time Consistency Model for 3D Point Cloud Generation The earth mover’s distance as a metric for image retrieval

Reference 40

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verified fuzzy
raw_fallback, observed 2026-08-05T12:43:40.981836Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

source=pdf_text observed=2026-08-05T12:43:35.841639Z digest=sha256:d14ebb27222634bf34d9307a661bc87051852511b6180782d55ecf73300c82f6

Observation 95c2a88e-b316-4128-8ee4-a1aced0bb1ee · outbound

This paper cites Align Your Flow: Scaling Continuous-Time Flow Map Distillation.

A Continuous-Time Consistency Model for 3D Point Cloud Generation Align Your Flow: Scaling Continuous-Time Flow Map Distillation

Reference 41

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no resolver link, observed 2026-08-05T12:43:35.972155Z

Source-reported events for the cited work

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source=pdf_text observed=2026-08-05T12:43:35.972155Z digest=sha256:85e3e9c485d9d65f19070f30c9f6492af401e9292bdd90088990c371160ff96a

Observation 2d7bc9d1-af26-4680-ad6b-670e7f6ab65d · outbound

This paper cites Progressive Distillation for Fast Sampling of Diffusion Models.

A Continuous-Time Consistency Model for 3D Point Cloud Generation Progressive Distillation for Fast Sampling of Diffusion Models

Reference 42

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no resolver link, observed 2026-08-05T12:43:36.116767Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-05T12:43:36.116767Z digest=sha256:0f0fb1073a06d6f396feb88f8f81df360a9e80264d3bc7e7ee5fd77d479ee1b6

Observation 8bff83a9-5e1e-4e95-ab3b-0c537e27f10b · outbound

This paper cites Denoising Diffusion Implicit Models.

A Continuous-Time Consistency Model for 3D Point Cloud Generation Denoising Diffusion Implicit Models

Reference 43

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no resolver link, observed 2026-08-05T12:43:36.296556Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-05T12:43:36.296556Z digest=sha256:f1543fd0a5951552f2fd3f15e07a5d692e5791f3eca9daa5f1362afdc0f63106

Observation bd1161e5-e2b1-499d-9d23-9a00ee9e14c9 · outbound

This paper cites Improved Techniques for Training Consistency Models.

A Continuous-Time Consistency Model for 3D Point Cloud Generation Improved Techniques for Training Consistency Models

Reference 44

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no resolver link, observed 2026-08-05T12:43:36.465971Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-05T12:43:36.465971Z digest=sha256:5d38c8c39114f452c2e5b0e5060fa679aed9878dd175bb7ba57b2b3be66c78bd

Observation 0f3d9d41-88d1-44cc-af09-1ad894351485 · outbound

This paper cites Consistency Models.

A Continuous-Time Consistency Model for 3D Point Cloud Generation Consistency Models

Reference 45

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no resolver link, observed 2026-08-05T12:43:36.638985Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-05T12:43:36.638985Z digest=sha256:e0cfe7822552dea002f30387b0eedc71fcb8832245332643f14bb3377a26e934

Observation f0edd59b-a736-47fe-9563-19d5db8620d7 · outbound

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

A Continuous-Time Consistency Model for 3D Point Cloud Generation Generative modeling by estimating gradients of the data distribution

Reference 46

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no resolver link, observed 2026-08-05T12:43:36.803265Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-05T12:43:36.803265Z digest=sha256:23624203e7f79c0c0d31c689cf39cb10b07dcf1d97fd1716e03be3f36343f977

Observation 5356e8ae-bd19-4a0c-a47b-f92af8b4154e · outbound

This paper cites Score-Based Generative Modeling through Stochastic Differential Equations.

A Continuous-Time Consistency Model for 3D Point Cloud Generation Score-Based Generative Modeling through Stochastic Differential Equations

Reference 47

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no resolver link, observed 2026-08-05T12:43:36.923750Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-05T12:43:36.923750Z digest=sha256:3b6975937fb4b9a1bda3c75f1396a8e55c999a58e178f86353b1534d9226a91a

Observation 11773128-0740-4f01-9877-f580ef08d97c · outbound

This paper cites Attention is all you need.

A Continuous-Time Consistency Model for 3D Point Cloud Generation Attention is all you need

Reference 48

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no resolver link, observed 2026-08-05T12:43:37.067179Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-05T12:43:37.067179Z digest=sha256:6778c726f26a1ae650450848e4e12a7c8ccb571b84b81cb3378abfd8845e5d26

Observation 569d8975-f15b-41f1-8fdc-095ab0a93db8 · outbound

This paper cites Fast point cloud generation with straight flows.

A Continuous-Time Consistency Model for 3D Point Cloud Generation Fast point cloud generation with straight flows

Reference 49

Resolution
verified fuzzy
raw_fallback, observed 2026-08-05T12:43:40.751591Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

source=pdf_text observed=2026-08-05T12:43:37.243913Z digest=sha256:38c4c2fcea5870f53a6e168d9b4fa74fae7f17fe6378c1d8247b47aeb824ebb6

Observation 661a0524-2613-4008-bad9-372f0a1bad26 · outbound

This paper cites Pointflow: 3d point cloud generation with continuous normalizing flows.

A Continuous-Time Consistency Model for 3D Point Cloud Generation Pointflow: 3d point cloud generation with continuous normalizing flows

Reference 50

Resolution
verified fuzzy
raw_fallback, observed 2026-08-05T12:43:40.541675Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

source=pdf_text observed=2026-08-05T12:43:37.395499Z digest=sha256:00e4077d09cdea15c7545344add65ce019029ddb07ca9fe7d82abd610e3ba068

Observation 79cf0cc3-cd70-4ed7-b532-689d79f878d9 · outbound

This paper cites Lion: Latent point diffusion models for 3d shape generation.

A Continuous-Time Consistency Model for 3D Point Cloud Generation Lion: Latent point diffusion models for 3d shape generation

Reference 51

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verified fuzzy
raw_fallback, observed 2026-08-05T12:43:40.359118Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

source=pdf_text observed=2026-08-05T12:43:37.538292Z digest=sha256:31b0c8c665edef3aec90293846dcae0dd95d0ca760805d1f19c0d617ea856942

Observation 069bfdf2-f9cf-441e-a031-c30f9c90bd0d · outbound

This paper cites Learning to Generate 3D Shapes with Generative Cellular Automata.

A Continuous-Time Consistency Model for 3D Point Cloud Generation Learning to Generate 3D Shapes with Generative Cellular Automata

Reference 52

Resolution
verified exact
local_arxiv, observed 2026-08-05T12:43:38.218300Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

source=pdf_text observed=2026-08-05T12:43:37.678002Z digest=sha256:3f1227c3a3be95ef4eeb5779eee89c2e91359a4c6c0f5a31a9facbd4602057fd

Observation 2ad5c0bf-e89e-4584-a9d5-45f94ed16da4 · outbound

This paper cites The unreasonable effectiveness of deep features as a perceptual metric.

A Continuous-Time Consistency Model for 3D Point Cloud Generation The unreasonable effectiveness of deep features as a perceptual metric

Reference 53

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no resolver link, observed 2026-08-05T12:43:37.781788Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-05T12:43:37.781788Z digest=sha256:62c2a25d6336ec35edc093d1cc79a2a4a5574562863bd0ee2e69aa7aef06e346

Observation 4dc98bd8-06b2-45da-8c03-241dfb400481 · outbound

This paper cites Inverse flow and consistency models.

A Continuous-Time Consistency Model for 3D Point Cloud Generation Inverse flow and consistency models

Reference 54

Resolution
verified fuzzy
raw_fallback, observed 2026-08-05T12:43:40.120944Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

source=pdf_text observed=2026-08-05T12:43:37.888988Z digest=sha256:ef13e657de995be38a3c30b9ddfd75c025913f2d6ad32c4c084f5a69a571f65f

Observation eb884961-15ba-4a16-9edb-0874f84bbd35 · outbound

This paper cites 3d shape generation and completion through point-voxel diffusion.

A Continuous-Time Consistency Model for 3D Point Cloud Generation 3d shape generation and completion through point-voxel diffusion

Reference 55

Resolution
verified fuzzy
raw_fallback, observed 2026-08-05T12:43:39.828337Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

source=pdf_text observed=2026-08-05T12:43:37.993951Z digest=sha256:2ec7d3ea8ed7d992259e6c99b05d938ee2a57012df7b43a9696558f75868455c

Pith citing papers

No inbound Pith citation observations are available.