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Paper Citation Record · LEDGER

Few-step Flow for 3D Generation via Marginal-Data Transport Distillation

As of 21 August 2026, this Paper Citation Record lists 94 of 94 outbound references and 0 inbound Pith citation observations for arXiv:2509.04406.

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

pith.paper-citation-record.v1
2509.04406 v1

Coverage vector

measured 94 of 94 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links, observed 2026-08-05T10:19:33.908823Z

measured 94 of 94 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

94 of 94 outbound references displayed

  • verified exact6
  • verified fuzzy20
  • unresolved68
  • parse uncertain0
  • malformed identifier0
  • metadata mismatch0

External citation measurements

No source-named external measurement is stored.

Outbound references

Observation 34a48f19-71ee-4ff3-8a80-1cd2d84c7d64 · outbound

This paper cites Re-imagine the Negative Prompt Algorithm: Transform 2D Diffusion into 3D, alleviate Janus problem and Beyond.

Few-step Flow for 3D Generation via Marginal-Data Transport Distillation Re-imagine the Negative Prompt Algorithm: Transform 2D Diffusion into 3D, alleviate Janus problem and Beyond

Reference 1

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source=pdf_text observed=2026-08-05T10:19:33.512710Z digest=sha256:bff726bb20542f2b78f1f5a3675d27557d3baa1b14ee87c0d154b7f5f58334b7

Observation db9b50ad-1427-40b8-91ca-6aaf2dd31eca · outbound

This paper cites DreamAvatar: Text-and-Shape Guided 3D Human Avatar Generation via Diffusion Models.

Few-step Flow for 3D Generation via Marginal-Data Transport Distillation DreamAvatar: Text-and-Shape Guided 3D Human Avatar Generation via Diffusion Models

Reference 2

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local_arxiv, observed 2026-08-05T10:19:34.473659Z

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

source=pdf_text observed=2026-08-05T10:19:33.516592Z digest=sha256:081c5db659463b02eeba6f9e013661bbb06dbafc9d3ed1863ea0e9252898f5b0

Observation a60d2b1e-88a0-47fd-9031-112619568ff5 · outbound

This paper cites Mode regularized generative adversarial networks.

Few-step Flow for 3D Generation via Marginal-Data Transport Distillation Mode regularized generative adversarial networks

Reference 3

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source=pdf_text observed=2026-08-05T10:19:33.519753Z digest=sha256:1cadd9dfd76087ec42019084b72daf782458b53d5dd4061828cb65a49148f6e3

Observation 6c8dfeae-e0d6-466e-9b20-2f96e3731b83 · outbound

This paper cites Mar-3d: Progressive masked auto-regressor for high-resolution 3d generation.

Few-step Flow for 3D Generation via Marginal-Data Transport Distillation Mar-3d: Progressive masked auto-regressor for high-resolution 3d generation

Reference 4

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source=pdf_text observed=2026-08-05T10:19:33.522569Z digest=sha256:49da78197962b6283748ec8053fbcf55749a9babe617b5b7b15f1027e675f300

Observation a6605fb3-43be-4093-bfdc-a1c4eef65b67 · outbound

This paper cites Fantasia3D: Disentangling Geometry and Appearance for High-quality Text-to-3D Content Creation.

Few-step Flow for 3D Generation via Marginal-Data Transport Distillation Fantasia3D: Disentangling Geometry and Appearance for High-quality Text-to-3D Content Creation

Reference 5

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source=pdf_text observed=2026-08-05T10:19:33.525623Z digest=sha256:4486150c4396767ef6bdaf62ddd9d2b1d53fc1daa0990135c39e78913877b966

Observation 8b59bb04-c9f2-4f47-939d-42c6059dbad5 · outbound

This paper cites Dora: Sampling and benchmarking for 3d shape varia- tional auto-encoders.

Few-step Flow for 3D Generation via Marginal-Data Transport Distillation Dora: Sampling and benchmarking for 3d shape varia- tional auto-encoders

Reference 6

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source=pdf_text observed=2026-08-05T10:19:33.528685Z digest=sha256:2ac7ac782062be05bd5b5cc4a279ad063f99bb09a41a20c04f2b94d71df634d5

Observation 7985db70-203d-4131-9aed-ea1765dfaba3 · outbound

This paper cites Sar3d: Autoregressive 3d object genera- tion and understanding via multi-scale 3d vqvae.

Few-step Flow for 3D Generation via Marginal-Data Transport Distillation Sar3d: Autoregressive 3d object genera- tion and understanding via multi-scale 3d vqvae

Reference 7

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source=pdf_text observed=2026-08-05T10:19:33.531659Z digest=sha256:43eee31ad33ab3dcfdea7ce15264d63f0b12ac1069dd482f78731d9776c2a1f3

Observation bafa8341-d93f-4d3d-b90d-e7a2a8b3f1cf · outbound

This paper cites Text-to-3D using Gaussian Splatting.

Few-step Flow for 3D Generation via Marginal-Data Transport Distillation Text-to-3D using Gaussian Splatting

Reference 8

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source=pdf_text observed=2026-08-05T10:19:33.534815Z digest=sha256:c15cb752bdf419d42f9c92ad8ec6dbab784dac6f2eecc8d17ed05121905aaca3

Observation 4f140fd7-92f6-4061-a9f2-a73392ae7a94 · outbound

This paper cites 3dtopia-xl: Scaling high- quality 3d asset generation via primitive diffusion.

Few-step Flow for 3D Generation via Marginal-Data Transport Distillation 3dtopia-xl: Scaling high- quality 3d asset generation via primitive diffusion

Reference 9

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source=pdf_text observed=2026-08-05T10:19:33.538226Z digest=sha256:734614b40671c6941a3e0df3c3017306729c42985858431f8b8d0e0c33a456c8

Observation fbf4cfec-59d6-4537-9f7c-fc9fcc5a333d · outbound

This paper cites Abo: Dataset and benchmarks for real-world 3d object understand- ing.

Few-step Flow for 3D Generation via Marginal-Data Transport Distillation Abo: Dataset and benchmarks for real-world 3d object understand- ing

Reference 10

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source=pdf_text observed=2026-08-05T10:19:33.541098Z digest=sha256:b0afb62f101adc28e5f47a7aeb4dd6550c6fdacfa58f8f0c2ad9437fdc294aef

Observation 1a4141d8-32ee-4f84-a08a-3351528d5e9a · outbound

This paper cites Objaverse: A universe of annotated 3d objects.

Few-step Flow for 3D Generation via Marginal-Data Transport Distillation Objaverse: A universe of annotated 3d objects

Reference 11

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source=pdf_text observed=2026-08-05T10:19:33.543971Z digest=sha256:06f2781467fe9fb67ff33690ebb23fa2e904a86ab9612b8ad3ecef2cad5b0c4f

Observation 3e80c4cb-4b4e-41f1-9e32-84443dbb60bb · outbound

This paper cites 3d-future: 3d fur- niture shape with texture.

Few-step Flow for 3D Generation via Marginal-Data Transport Distillation 3d-future: 3d fur- niture shape with texture

Reference 12

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source=pdf_text observed=2026-08-05T10:19:33.547018Z digest=sha256:12ce7cc4b917674f433f96e6788605718773fdbbc122737d79e922b3f3473c5f

Observation 05a20579-0395-4424-a0ec-1cc604d3b0d8 · outbound

This paper cites Get3d: A generative model of high quality 3d tex- tured shapes learned from images.

Few-step Flow for 3D Generation via Marginal-Data Transport Distillation Get3d: A generative model of high quality 3d tex- tured shapes learned from images

Reference 13

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source=pdf_text observed=2026-08-05T10:19:33.549873Z digest=sha256:e255cbd67a225d05d63ae29ee4c9b8594bb6b30f038264c30aac3ac1c20e9ce8

Observation 6b0a67c4-5d8e-43c4-bf59-e55f445e9539 · outbound

This paper cites Mean Flows for One-step Generative Modeling.

Few-step Flow for 3D Generation via Marginal-Data Transport Distillation Mean Flows for One-step Generative Modeling

Reference 14

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source=pdf_text observed=2026-08-05T10:19:33.552444Z digest=sha256:cc265bcb8d1c0bbf749044c9dfc525b8c6f508e4dda402055ff3b2ac48a3181e

Observation da547425-f58e-40af-bc7b-c6146af9416a · outbound

This paper cites Generative adversarial networks.

Few-step Flow for 3D Generation via Marginal-Data Transport Distillation Generative adversarial networks

Reference 15

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source=pdf_text observed=2026-08-05T10:19:33.555406Z digest=sha256:c9e39b1eec3b98d06ceceeb351e1f4b0648100c26819c8da1c60281f0ade0ff7

Observation 1848a56f-31e9-4497-9a5b-d1d3eb987847 · outbound

This paper cites 3DGen: Triplane Latent Diffusion for Textured Mesh Generation.

Few-step Flow for 3D Generation via Marginal-Data Transport Distillation 3DGen: Triplane Latent Diffusion for Textured Mesh Generation

Reference 16

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source=pdf_text observed=2026-08-05T10:19:33.558089Z digest=sha256:2c69a96f3986185a386210adff24576df74e3440290b4c5c280cd8486dc56d38

Observation 3131a337-5cd3-42a7-886b-fc055dcf8849 · outbound

This paper cites Classifier-Free Diffusion Guidance.

Few-step Flow for 3D Generation via Marginal-Data Transport Distillation Classifier-Free Diffusion Guidance

Reference 17

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source=pdf_text observed=2026-08-05T10:19:33.561319Z digest=sha256:43fb7de94cec5938f1a82c6480232a6454b0fa42e87bef8aced728ac4949b92a

Observation 8a0e865c-6ef8-4c10-b637-59012d4b09dc · outbound

This paper cites Denoising diffu- sion probabilistic models.

Few-step Flow for 3D Generation via Marginal-Data Transport Distillation Denoising diffu- sion probabilistic models

Reference 18

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source=pdf_text observed=2026-08-05T10:19:33.564274Z digest=sha256:348db26d0ed574c8d8e6062f6e44f7b0f11ca48c9a8fa65a33122af36651d0a1

Observation f031f7f0-6c37-412f-8a14-94d88c294ac9 · outbound

This paper cites LRM: Large Reconstruction Model for Single Image to 3D.

Few-step Flow for 3D Generation via Marginal-Data Transport Distillation LRM: Large Reconstruction Model for Single Image to 3D

Reference 19

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source=pdf_text observed=2026-08-05T10:19:33.567018Z digest=sha256:16a768d2dbcd81cd5d1b31bc87e32f90bdd9d7e5ea5f4a52936fdaf109131de9

Observation 2201341c-3404-49db-b3f0-34ad60798b10 · outbound

This paper cites DreamWaltz: Make a Scene with Complex 3D Animatable Avatars.

Few-step Flow for 3D Generation via Marginal-Data Transport Distillation DreamWaltz: Make a Scene with Complex 3D Animatable Avatars

Reference 20

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

source=pdf_text observed=2026-08-05T10:19:33.570384Z digest=sha256:dbd12dd5517c583df7b5dfabf672806c3fd440d7e9201ce8eaf5dd476c9db2e3

Observation 8ae132ce-9844-43d3-b52e-71980265d9ff · outbound

This paper cites TeCH: Text-guided Reconstruction of Lifelike Clothed Humans.

Few-step Flow for 3D Generation via Marginal-Data Transport Distillation TeCH: Text-guided Reconstruction of Lifelike Clothed Humans

Reference 21

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local_arxiv, observed 2026-08-05T10:19:34.393389Z

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=2026-08-05T10:19:33.573400Z digest=sha256:adc7da3550d06ae6450d59094fa455a557eb7529f108437352d479e87738bdeb

Observation 9f94c856-816c-4847-8e8f-bbf80d3c9220 · outbound

This paper cites Zero-shot text-guided object gen- eration with dream fields.

Few-step Flow for 3D Generation via Marginal-Data Transport Distillation Zero-shot text-guided object gen- eration with dream fields

Reference 22

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source=pdf_text observed=2026-08-05T10:19:33.576836Z digest=sha256:e9d1657c5aeb9b81ffc506e22b5e5a75bc8e96dddef8c9e780c0de4500df06ba

Observation a0283d5a-c2cd-475a-83ef-29c91f9eaf60 · outbound

This paper cites AvatarCraft: Transforming Text into Neural Human Avatars with Parameterized Shape and Pose Control.

Few-step Flow for 3D Generation via Marginal-Data Transport Distillation AvatarCraft: Transforming Text into Neural Human Avatars with Parameterized Shape and Pose Control

Reference 23

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local_arxiv, observed 2026-08-05T10:19:34.381480Z

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

source=pdf_text observed=2026-08-05T10:19:33.580653Z digest=sha256:f2f396571b4d738556cf71caf099d1c8872645976de06117daaff17bb8bd5ffa

Observation 2e109972-30d0-432c-9d9b-1d7a8c081747 · outbound

This paper cites Shap-E: Generating Conditional 3D Implicit Functions.

Few-step Flow for 3D Generation via Marginal-Data Transport Distillation Shap-E: Generating Conditional 3D Implicit Functions

Reference 24

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source=pdf_text observed=2026-08-05T10:19:33.584539Z digest=sha256:d71f64ef88c87e6656db1a7424941817b2ef616ba079806de1475aede63c3415

Observation 6b12b4f3-94f3-4800-b289-f1608afea3e3 · outbound

This paper cites 3d gaussian splatting for real-time radiance field rendering.

Few-step Flow for 3D Generation via Marginal-Data Transport Distillation 3d gaussian splatting for real-time radiance field rendering

Reference 25

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source=pdf_text observed=2026-08-05T10:19:33.588822Z digest=sha256:dc8c4f53f3c1e61b5f44fa2b352c285137abc5131e24f748fc1db75ede0b440c

Observation 440cc822-f3e4-49d5-adf8-057d23aa3bf5 · outbound

This paper cites Chang, and Manolis Savva.

Few-step Flow for 3D Generation via Marginal-Data Transport Distillation Chang, and Manolis Savva

Reference 26

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source=pdf_text observed=2026-08-05T10:19:33.591490Z digest=sha256:9f94ac92cce6efb4c6826fba3a663429a333a22437e70d8267e16282235b31ab

Observation 8bd78198-dd7e-47e9-bf1c-cc8beefd24fa · outbound

This paper cites Auto-Encoding Variational Bayes.

Few-step Flow for 3D Generation via Marginal-Data Transport Distillation Auto-Encoding Variational Bayes

Reference 27

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source=pdf_text observed=2026-08-05T10:19:33.594120Z digest=sha256:98940431c0286c7535c36faa7bdf5e5ec2fa874f56768e31aae7caa409d7209c

Observation 59608df7-5cd3-4354-b799-387166d0aba9 · outbound

This paper cites Unleashing Vecset Diffusion Model for Fast Shape Generation.

Few-step Flow for 3D Generation via Marginal-Data Transport Distillation Unleashing Vecset Diffusion Model for Fast Shape Generation

Reference 28

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source=pdf_text observed=2026-08-05T10:19:33.597295Z digest=sha256:20cb5ff4e2c3e3fc284398d39af97e76ee7a905d75502519f2782ec1afb75e14

Observation c8393487-b963-4631-9812-3e76d407ee41 · outbound

This paper cites Ln3diff: Scalable latent neural fields diffusion for speedy 3d generation.

Few-step Flow for 3D Generation via Marginal-Data Transport Distillation Ln3diff: Scalable latent neural fields diffusion for speedy 3d generation

Reference 29

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raw_fallback, observed 2026-08-05T10:19:34.672467Z

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=2026-08-05T10:19:33.600660Z digest=sha256:78e2e8b243d2f2a844f7291c7ad7cf726af7f2ffdf60f4eda55950feb8f2edbd

Observation 038c1733-af7e-40d5-a109-74aabd8d7f20 · outbound

This paper cites Tango: Text-driven photorealistic and robust 3d stylization via lighting decom- position.

Few-step Flow for 3D Generation via Marginal-Data Transport Distillation Tango: Text-driven photorealistic and robust 3d stylization via lighting decom- position

Reference 30

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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=2026-08-05T10:19:33.603813Z digest=sha256:82ece1442e8b9034369a8beb1eab8b5ce414d89c35eb44c3882b0911b5deaa07

Observation 0ddb0615-2f1c-484c-9399-0fa098f3419d · outbound

This paper cites Instant3D: Fast Text-to-3D with Sparse-View Generation and Large Reconstruction Model.

Few-step Flow for 3D Generation via Marginal-Data Transport Distillation Instant3D: Fast Text-to-3D with Sparse-View Generation and Large Reconstruction Model

Reference 31

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source=pdf_text observed=2026-08-05T10:19:33.606924Z digest=sha256:7bf28bec7a65c8f7b7b4a0c46bff87130c405aee95d929f311250a61398a08d8

Observation 633dba49-5468-4ef6-ae9c-2f2dfbbeeced · outbound

This paper cites SweetDreamer: Aligning Geometric Priors in 2D Diffusion for Consistent Text-to-3D.

Few-step Flow for 3D Generation via Marginal-Data Transport Distillation SweetDreamer: Aligning Geometric Priors in 2D Diffusion for Consistent Text-to-3D

Reference 32

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source=pdf_text observed=2026-08-05T10:19:33.610205Z digest=sha256:11429225d7a42f75e76eaf62f7bf0aad41c246b7871a56a62be2f1b7989035e0

Observation f2aa7b3d-b375-4388-a54c-e622585c38cf · outbound

This paper cites CraftsMan3D: High-fidelity Mesh Generation with 3D Native Generation and Interactive Geometry Refiner.

Few-step Flow for 3D Generation via Marginal-Data Transport Distillation CraftsMan3D: High-fidelity Mesh Generation with 3D Native Generation and Interactive Geometry Refiner

Reference 33

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source=pdf_text observed=2026-08-05T10:19:33.722347Z digest=sha256:374b3cc9f2c7b62db966e54667de58d6375bce05836248c11dae005377ab8faa

Observation 26604d30-27ff-448b-bee7-a043560e4913 · outbound

This paper cites Step1X-3D: Towards High-Fidelity and Controllable Generation of Textured 3D Assets.

Few-step Flow for 3D Generation via Marginal-Data Transport Distillation Step1X-3D: Towards High-Fidelity and Controllable Generation of Textured 3D Assets

Reference 34

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source=pdf_text observed=2026-08-05T10:19:33.725928Z digest=sha256:6e80ef4589ae4c3108e8a4b5eda7cfb6218b9023304a97f92648110f065efd48

Observation 9816e1b5-3391-458b-a828-cbac66b59b08 · outbound

This paper cites Luciddreamer: Towards high-fidelity text-to-3d generation via interval score match- ing, 2023.

Few-step Flow for 3D Generation via Marginal-Data Transport Distillation Luciddreamer: Towards high-fidelity text-to-3d generation via interval score match- ing, 2023

Reference 35

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raw_fallback, observed 2026-08-05T10:19:34.654157Z

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=2026-08-05T10:19:33.729122Z digest=sha256:cab6cb7d72b7c0373de06b259782fb67817043ddaa57182dabb3667d259c9b9e

Observation eb413350-a8ea-4e8d-89ad-af15368a605d · outbound

This paper cites Magic3d: High-resolution text-to-3d content creation.

Few-step Flow for 3D Generation via Marginal-Data Transport Distillation Magic3d: High-resolution text-to-3d content creation

Reference 36

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raw_fallback, observed 2026-08-05T10:19:34.645403Z

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=2026-08-05T10:19:33.732115Z digest=sha256:73e70f232355651d1b7ea57a3a0a0b4462f7b23c8f57cad70096ec781d696bd7

Observation 01402e0a-e2ec-4b2b-a768-b4fd83679992 · outbound

This paper cites Flow Matching for Generative Modeling.

Few-step Flow for 3D Generation via Marginal-Data Transport Distillation Flow Matching for Generative Modeling

Reference 37

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Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-05T10:19:33.735605Z digest=sha256:f98513af2273920bf0356ca88f3b94fae9ce176196891e88de99b3697aca4ed2

Observation c4f1711b-f6bf-46ba-9b47-7a5ae5ee21f0 · outbound

This paper cites Zero-1-to-3: Zero-shot One Image to 3D Object.

Few-step Flow for 3D Generation via Marginal-Data Transport Distillation Zero-1-to-3: Zero-shot One Image to 3D Object

Reference 38

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Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-05T10:19:33.738879Z digest=sha256:58f2e339dcb0d3837bbedb75d730e48a39fcd50ce2609b374e9632709ca57857

Observation a5f26574-97c6-4c9b-a1b6-9c23ee903be3 · outbound

This paper cites Flow Straight and Fast: Learning to Generate and Transfer Data with Rectified Flow.

Few-step Flow for 3D Generation via Marginal-Data Transport Distillation Flow Straight and Fast: Learning to Generate and Transfer Data with Rectified Flow

Reference 39

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Source-reported events for the cited work

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source=pdf_text observed=2026-08-05T10:19:33.742399Z digest=sha256:a17aa46bb5044acd7214aabaabc6897dc0c2e460128ad34203f1ad5175ae5b65

Observation 7f17e841-1e7e-4cf4-8595-387e65b880bb · outbound

This paper cites SyncDreamer: Generating Multiview-consistent Images from a Single-view Image.

Few-step Flow for 3D Generation via Marginal-Data Transport Distillation SyncDreamer: Generating Multiview-consistent Images from a Single-view Image

Reference 40

Resolution
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no resolver link, observed 2026-08-05T10:19:33.745455Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-05T10:19:33.745455Z digest=sha256:079ba66ac27887aa33da1b5a8282b3f305be1f25e4bdb16f4726cb2f539b949a

Observation 3b1b9dc2-a0d1-4b0c-8c1d-b48323b3c068 · outbound

This paper cites Wonder3D: Single Image to 3D using Cross-Domain Diffusion.

Few-step Flow for 3D Generation via Marginal-Data Transport Distillation Wonder3D: Single Image to 3D using Cross-Domain Diffusion

Reference 41

Resolution
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no resolver link, observed 2026-08-05T10:19:33.748711Z

Source-reported events for the cited work

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source=pdf_text observed=2026-08-05T10:19:33.748711Z digest=sha256:15490230eb950a45be3886396df6b1720586304876f7b76afa7fbb9724acbc53

Observation 811d2edb-06e0-48af-807d-25c8f53d96b1 · outbound

This paper cites Decoupled Weight Decay Regularization.

Few-step Flow for 3D Generation via Marginal-Data Transport Distillation Decoupled Weight Decay Regularization

Reference 42

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no resolver link, observed 2026-08-05T10:19:33.751778Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-05T10:19:33.751778Z digest=sha256:5eee75644f992ada55d6a0863239f22a3549c1229d4e1bd329a227d9f528acbb

Observation 982f071e-6695-4b5b-a6f9-0f22b8e4ada2 · outbound

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

Few-step Flow for 3D Generation via Marginal-Data Transport Distillation Simplifying, Stabilizing and Scaling Continuous-Time Consistency Models

Reference 43

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no resolver link, observed 2026-08-05T10:19:33.754772Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-05T10:19:33.754772Z digest=sha256:675561ad09a36e7c4232a43356c93159d1f642e2865aa142386a20abe7d55297

Observation fbc72df0-22a7-4778-b398-c577fd342bbc · outbound

This paper cites Dpm-solver: A fast ode solver for diffusion probabilistic model sampling in around 10 steps.

Few-step Flow for 3D Generation via Marginal-Data Transport Distillation Dpm-solver: A fast ode solver for diffusion probabilistic model sampling in around 10 steps

Reference 44

Resolution
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no resolver link, observed 2026-08-05T10:19:33.757757Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-05T10:19:33.757757Z digest=sha256:5a69da028233caa551fe8ecd5a7d03e9a02d628ecdc54c99baa0ce4cc1397836

Observation bdf71d1b-3f08-45b1-b315-75be77c2d741 · outbound

This paper cites Don’t blame the elbo! a linear vae perspective on posterior collapse.

Few-step Flow for 3D Generation via Marginal-Data Transport Distillation Don’t blame the elbo! a linear vae perspective on posterior collapse

Reference 45

Resolution
verified fuzzy
raw_fallback, observed 2026-08-05T10:19:34.630646Z

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=2026-08-05T10:19:33.760681Z digest=sha256:2182347c17b1f3844d0adff415a7f83a314aa7a7377baf435c8a73c726e91319

Observation 1e79499c-0625-403f-8a25-d554ed59e746 · outbound

This paper cites Scalable 3D Captioning with Pretrained Models.

Few-step Flow for 3D Generation via Marginal-Data Transport Distillation Scalable 3D Captioning with Pretrained Models

Reference 46

Resolution
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no resolver link, observed 2026-08-05T10:19:33.763390Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-05T10:19:33.763390Z digest=sha256:18925007005fd794594c58ca9012ae683c1c69d870ae7cbb4909f235ab18f038

Observation 442dda77-5f24-4246-b4b0-1741ed82669c · outbound

This paper cites GeoDream: Disentangling 2D and Geometric Priors for High-Fidelity and Consistent 3D Generation.

Few-step Flow for 3D Generation via Marginal-Data Transport Distillation GeoDream: Disentangling 2D and Geometric Priors for High-Fidelity and Consistent 3D Generation

Reference 47

Resolution
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no resolver link, observed 2026-08-05T10:19:33.766260Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-05T10:19:33.766260Z digest=sha256:09efcca26e448ce1c117ec35855db06cd0024e6bbb7e661d8269097a1744acc6

Observation 01fbb1df-09f9-4c75-a5e2-e6fcd044d72e · outbound

This paper cites Latent-nerf for shape-guided generation of 3d shapes and textures.

Few-step Flow for 3D Generation via Marginal-Data Transport Distillation Latent-nerf for shape-guided generation of 3d shapes and textures

Reference 48

Resolution
verified fuzzy
raw_fallback, observed 2026-08-05T10:19:34.621909Z

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=2026-08-05T10:19:33.769331Z digest=sha256:68b038dc6a2082dba3825e806957704080e57bae4bc69b5ef8b9543ac04986ab

Observation 2f20be34-9eeb-4737-b0b6-a7c30c2c3f1c · outbound

This paper cites Text2mesh: Text-driven neural stylization for meshes.

Few-step Flow for 3D Generation via Marginal-Data Transport Distillation Text2mesh: Text-driven neural stylization for meshes

Reference 49

Resolution
verified fuzzy
raw_fallback, observed 2026-08-05T10:19:34.612833Z

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=2026-08-05T10:19:33.772482Z digest=sha256:f146ba1c79fdabaf24499280aa5710c22cc663ea10c319ce607cbe04e437ef71

Observation 1afd68d9-491f-4502-abf1-50e398c946f8 · outbound

This paper cites Nerf: Representing scenes as neural radiance fields for view syn- thesis.

Few-step Flow for 3D Generation via Marginal-Data Transport Distillation Nerf: Representing scenes as neural radiance fields for view syn- thesis

Reference 50

Resolution
verified fuzzy
raw_fallback, observed 2026-08-05T10:19:34.604102Z

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=2026-08-05T10:19:33.775249Z digest=sha256:389ed288f90dfeff1bb97efc3094638491105242dece3148d67f03f8f8845066

Observation 37836102-fc66-467e-ba32-03d1a008c673 · outbound

This paper cites Point-E: A System for Generating 3D Point Clouds from Complex Prompts.

Few-step Flow for 3D Generation via Marginal-Data Transport Distillation Point-E: A System for Generating 3D Point Clouds from Complex Prompts

Reference 51

Resolution
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no resolver link, observed 2026-08-05T10:19:33.778150Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-05T10:19:33.778150Z digest=sha256:49663cbc7594c43f370c1821ed29fbe74c6c3c4d9c2b2212fb374f743eaaa12a

Observation cacfc7a6-d690-43e2-add9-221696bdfd3b · outbound

This paper cites DINOv2: Learning Robust Visual Features without Supervision.

Few-step Flow for 3D Generation via Marginal-Data Transport Distillation DINOv2: Learning Robust Visual Features without Supervision

Reference 52

Resolution
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no resolver link, observed 2026-08-05T10:19:33.781161Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-05T10:19:33.781161Z digest=sha256:c3f17ceee8c6509bf64f45634ab9510702329bb70b9e74f5559bc83821a60e94

Observation ac1f58cc-ce2d-4cb2-b2c0-5abdb4d8de73 · outbound

This paper cites Chasing Consistency in Text-to-3D Generation from a Single Image.

Few-step Flow for 3D Generation via Marginal-Data Transport Distillation Chasing Consistency in Text-to-3D Generation from a Single Image

Reference 53

Resolution
verified exact
local_arxiv, observed 2026-08-05T10:19:34.213821Z

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=2026-08-05T10:19:33.784109Z digest=sha256:fcbeedd5bfde91d86df80a04a767d6e156fc6545d1e7dfa25460f5d71c06d1b8

Observation 20afbd73-0be1-43f3-a0f5-8a07625afa47 · outbound

This paper cites DreamFusion: Text-to-3D using 2D Diffusion.

Few-step Flow for 3D Generation via Marginal-Data Transport Distillation DreamFusion: Text-to-3D using 2D Diffusion

Reference 54

Resolution
unresolved
no resolver link, observed 2026-08-05T10:19:33.787049Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-05T10:19:33.787049Z digest=sha256:beb64fec261fa015b9287fa89bf86d5fe7f85ced49c3ce3c90d0411372e58ed1

Observation 40d3ae9d-b474-4cf5-a828-dadb76d8f354 · outbound

This paper cites Richdreamer: A generalizable normal-depth diffusion model for detail richness in text-to- 3d.

Few-step Flow for 3D Generation via Marginal-Data Transport Distillation Richdreamer: A generalizable normal-depth diffusion model for detail richness in text-to- 3d

Reference 55

Resolution
verified fuzzy
raw_fallback, observed 2026-08-05T10:19:34.594832Z

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=2026-08-05T10:19:33.790039Z digest=sha256:b61906384545afed50ef215d0365aef0d49adeb49c532db17757cbae9408ce50

Observation 4dd8d22b-5f5f-4f2c-96c2-3c383b0bd9cd · outbound

This paper cites DreamBooth3D: Subject-Driven Text-to-3D Generation.

Few-step Flow for 3D Generation via Marginal-Data Transport Distillation DreamBooth3D: Subject-Driven Text-to-3D Generation

Reference 56

Resolution
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no resolver link, observed 2026-08-05T10:19:33.792826Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-05T10:19:33.792826Z digest=sha256:12bb1ff3d67a6966e0ef7796ba3007d775db1847457e1ad9b665f07b6953ec7e

Observation 34a5be65-78c7-40dd-9b96-8004f7205139 · outbound

This paper cites Stochastic backpropagation and approximate inference in deep generative models.

Few-step Flow for 3D Generation via Marginal-Data Transport Distillation Stochastic backpropagation and approximate inference in deep generative models

Reference 57

Resolution
verified fuzzy
raw_fallback, observed 2026-08-05T10:19:34.585745Z

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=2026-08-05T10:19:33.795949Z digest=sha256:123205dd389893048fefe9dd2eb31cd4cac7a4e35f773e40083da5224ee51548

Observation 90737e8d-874b-48dc-86b3-3673295d5f09 · outbound

This paper cites High-resolution image syn- thesis with latent diffusion models.

Few-step Flow for 3D Generation via Marginal-Data Transport Distillation High-resolution image syn- thesis with latent diffusion models

Reference 58

Resolution
verified fuzzy
raw_fallback, observed 2026-08-05T10:19:34.576877Z

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=2026-08-05T10:19:33.799114Z digest=sha256:b690a5695ae838cdf30486b5a0c73431f778b6a497162e6d07c2e69f713c4d1b

Observation a2c2eb4a-8d7c-4139-9649-7925acd0c736 · outbound

This paper cites DITTO-NeRF: Diffusion-based Iterative Text To Omni-directional 3D Model.

Few-step Flow for 3D Generation via Marginal-Data Transport Distillation DITTO-NeRF: Diffusion-based Iterative Text To Omni-directional 3D Model

Reference 59

Resolution
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no resolver link, observed 2026-08-05T10:19:33.801899Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-05T10:19:33.801899Z digest=sha256:bdf244c9eb6847111cabaedfde0f8dc8c7825a03ab1d40e744f78920724bc50c

Observation 6b4eaf80-8340-4825-9c44-0009635524c1 · outbound

This paper cites Let 2D Diffusion Model Know 3D-Consistency for Robust Text-to-3D Generation.

Few-step Flow for 3D Generation via Marginal-Data Transport Distillation Let 2D Diffusion Model Know 3D-Consistency for Robust Text-to-3D Generation

Reference 60

Resolution
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no resolver link, observed 2026-08-05T10:19:33.806246Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-05T10:19:33.806246Z digest=sha256:db393bbcd3d37e565d89856d060115c2a2da9c6ce74d5de0ac088d950934e5c5

Observation f6d49770-c054-4d9b-a2cd-3294f9bfb071 · outbound

This paper cites Gamba: Marry Gaussian Splatting with Mamba for single view 3D reconstruction.

Few-step Flow for 3D Generation via Marginal-Data Transport Distillation Gamba: Marry Gaussian Splatting with Mamba for single view 3D reconstruction

Reference 61

Resolution
unresolved
no resolver link, observed 2026-08-05T10:19:33.809356Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-05T10:19:33.809356Z digest=sha256:6bf399b0c35a5597e325fd34f57c3ae26a5c5a650aaba6a637e2dcff7b81e47a

Observation 5a8b278e-dbb6-4549-9a4c-eb46feb73478 · outbound

This paper cites MVDream: Multi-view Diffusion for 3D Generation.

Few-step Flow for 3D Generation via Marginal-Data Transport Distillation MVDream: Multi-view Diffusion for 3D Generation

Reference 62

Resolution
unresolved
no resolver link, observed 2026-08-05T10:19:33.812405Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-05T10:19:33.812405Z digest=sha256:02b9312e7e661ecd3932a98b07b392a9e60bb29191acb24d34d27277f08c90a5

Observation 336303c0-1d38-4606-8e47-a25cef1f43be · outbound

This paper cites Denoising Diffusion Implicit Models.

Few-step Flow for 3D Generation via Marginal-Data Transport Distillation Denoising Diffusion Implicit Models

Reference 63

Resolution
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no resolver link, observed 2026-08-05T10:19:33.815669Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-05T10:19:33.815669Z digest=sha256:032d0873e55e48d6b881a9125e08f617d2b5d01bc090cf1557e0213b208dc7d6

Observation 4032860b-99e1-4744-8f4d-3c69b3b95b4a · outbound

This paper cites RoomDreamer: Text-Driven 3D Indoor Scene Synthesis with Coherent Geometry and Texture.

Few-step Flow for 3D Generation via Marginal-Data Transport Distillation RoomDreamer: Text-Driven 3D Indoor Scene Synthesis with Coherent Geometry and Texture

Reference 64

Resolution
unresolved
no resolver link, observed 2026-08-05T10:19:33.818637Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-05T10:19:33.818637Z digest=sha256:6e2537c006d8ef5469d9108581efd6f17241bcf99e97464fd4dbfe973223c56b

Observation 7fb86734-5973-49c6-85a3-d3fdab38871d · outbound

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

Few-step Flow for 3D Generation via Marginal-Data Transport Distillation Score-Based Generative Modeling through Stochastic Differential Equations

Reference 65

Resolution
unresolved
no resolver link, observed 2026-08-05T10:19:33.822035Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-05T10:19:33.822035Z digest=sha256:a65ff157f2f94e9b7ea3f3e31db7b9393ff82cc2377ff0a0577d78b99b58015f

Observation 7926981b-82d2-48c6-a2c4-a1a360ba979f · outbound

This paper cites Consistency models.

Few-step Flow for 3D Generation via Marginal-Data Transport Distillation Consistency models

Reference 66

Resolution
verified fuzzy
raw_fallback, observed 2026-08-05T10:19:34.567905Z

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=2026-08-05T10:19:33.825086Z digest=sha256:be15eec591439b120add4fb82087a8baca1ee2f0bb3e9ca6289cf756fc38dd4d

Observation fad5cf87-f012-40a6-ad4e-d4903c7d6cf1 · outbound

This paper cites Veegan: Reducing mode col- lapse in gans using implicit variational learning.

Few-step Flow for 3D Generation via Marginal-Data Transport Distillation Veegan: Reducing mode col- lapse in gans using implicit variational learning

Reference 67

Resolution
verified fuzzy
raw_fallback, observed 2026-08-05T10:19:34.558540Z

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=2026-08-05T10:19:33.827966Z digest=sha256:d392ec77fe52791259980a996f24bce441d5cb2d5772ecb6b513b273098ea024

Observation 43d7029c-9d8b-40be-a127-edac3e8183af · outbound

This paper cites Using shape to categorize: Low-shot learning with an explicit shape bias.

Few-step Flow for 3D Generation via Marginal-Data Transport Distillation Using shape to categorize: Low-shot learning with an explicit shape bias

Reference 68

Resolution
verified fuzzy
raw_fallback, observed 2026-08-05T10:19:34.549247Z

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=2026-08-05T10:19:33.830689Z digest=sha256:95c0b27e46edc7e57ea506fcaabe889b7a9fed3374d5d6fa560def4fd6e5a04f

Observation b22e6652-d253-4ea8-b83d-c68d76d2c3be · outbound

This paper cites DreamCraft3D: Hierarchical 3D Generation with Bootstrapped Diffusion Prior.

Few-step Flow for 3D Generation via Marginal-Data Transport Distillation DreamCraft3D: Hierarchical 3D Generation with Bootstrapped Diffusion Prior

Reference 69

Resolution
unresolved
no resolver link, observed 2026-08-05T10:19:33.833519Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-05T10:19:33.833519Z digest=sha256:80973a3703302dc156e01e5107d33cef0f82c2c17920f8d07e382da3562683f7

Observation cb497c33-c611-489c-ace8-69e3581d6a42 · outbound

This paper cites DreamGaussian: Generative Gaussian Splatting for Efficient 3D Content Creation.

Few-step Flow for 3D Generation via Marginal-Data Transport Distillation DreamGaussian: Generative Gaussian Splatting for Efficient 3D Content Creation

Reference 70

Resolution
unresolved
no resolver link, observed 2026-08-05T10:19:33.836386Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-05T10:19:33.836386Z digest=sha256:795a9a67f4d20b578ec84cebae392664b1b4e9a511c279f57fdbbdc3b8efa2f1

Observation 3597b756-7acc-45ce-9e63-318b9a7506c7 · outbound

This paper cites LGM: Large Multi-View Gaussian Model for High-Resolution 3D Content Creation.

Few-step Flow for 3D Generation via Marginal-Data Transport Distillation LGM: Large Multi-View Gaussian Model for High-Resolution 3D Content Creation

Reference 71

Resolution
unresolved
no resolver link, observed 2026-08-05T10:19:33.839437Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-05T10:19:33.839437Z digest=sha256:c91069bbb0dafdbf4a77e361381135fcc80b4478277dc9c5972df580783b2e39

Observation e9539c96-3904-4038-98c0-f33910b441eb · outbound

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

Few-step Flow for 3D Generation via Marginal-Data Transport Distillation Improving and generalizing flow-based generative models with minibatch optimal transport

Reference 72

Resolution
unresolved
no resolver link, observed 2026-08-05T10:19:33.842417Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-05T10:19:33.842417Z digest=sha256:cb54ef941f1cfc4542af3ac2ff093065ba6f732e9b3d1d0c84a8e85a5d22bd01

Observation 83f3ab9b-ffc7-43f6-8189-e2cc75cb365b · outbound

This paper cites TextMesh: Generation of Realistic 3D Meshes From Text Prompts.

Few-step Flow for 3D Generation via Marginal-Data Transport Distillation TextMesh: Generation of Realistic 3D Meshes From Text Prompts

Reference 73

Resolution
unresolved
no resolver link, observed 2026-08-05T10:19:33.845585Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-05T10:19:33.845585Z digest=sha256:6d401a32328bfc9f868dfe9098c6ae98d3e1f358f59f25db90121f930f1f26b7

Observation 26c06041-a898-4eb7-b265-57a756995b61 · outbound

This paper cites Phased consistency models.

Few-step Flow for 3D Generation via Marginal-Data Transport Distillation Phased consistency models

Reference 74

Resolution
verified fuzzy
raw_fallback, observed 2026-08-05T10:19:34.539570Z

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=2026-08-05T10:19:33.848533Z digest=sha256:8914fde7926ea7d6bf732c39289775a0fd76ed66f738e20677f078edb1d9cfda

Observation bc23e6a7-df4d-4b4e-80bb-99243b8029f0 · outbound

This paper cites Embodiedgen: Towards a generative 3d world engine for embodied intel- ligence, 2025.

Few-step Flow for 3D Generation via Marginal-Data Transport Distillation Embodiedgen: Towards a generative 3d world engine for embodied intel- ligence, 2025

Reference 75

Resolution
verified fuzzy
raw_fallback, observed 2026-08-05T10:19:34.529461Z

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=2026-08-05T10:19:33.851109Z digest=sha256:77a1e9bb9be53fb96414c7cd5d0cfe7f28ba82fa8c432ccc4eaa3e9769631c7e

Observation c8940e9a-229b-43cf-99fe-8934f4f79bc0 · outbound

This paper cites ProlificDreamer: High-Fidelity and Diverse Text-to-3D Generation with Variational Score Distillation.

Few-step Flow for 3D Generation via Marginal-Data Transport Distillation ProlificDreamer: High-Fidelity and Diverse Text-to-3D Generation with Variational Score Distillation

Reference 76

Resolution
unresolved
no resolver link, observed 2026-08-05T10:19:33.853819Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-05T10:19:33.853819Z digest=sha256:164e90c45f2657195d2a0ec1fb0cf6d8a3da40e4355ee609719e333dc908b2f4

Observation d441757d-0e5a-464f-8d6c-721c2876b850 · outbound

This paper cites HD-Fusion: Detailed Text-to-3D Generation Leveraging Multiple Noise Estimation.

Few-step Flow for 3D Generation via Marginal-Data Transport Distillation HD-Fusion: Detailed Text-to-3D Generation Leveraging Multiple Noise Estimation

Reference 77

Resolution
unresolved
no resolver link, observed 2026-08-05T10:19:33.856758Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-05T10:19:33.856758Z digest=sha256:32956b269a57420ec8e11aa8f82b7ccc2111177f7f00c95f56066f8ef5944d7b

Observation 54789b1a-a093-4e36-9027-ff1aa3217edf · outbound

This paper cites Direct3D: Scalable Image-to-3D Generation via 3D Latent Diffusion Transformer.

Few-step Flow for 3D Generation via Marginal-Data Transport Distillation Direct3D: Scalable Image-to-3D Generation via 3D Latent Diffusion Transformer

Reference 78

Resolution
unresolved
no resolver link, observed 2026-08-05T10:19:33.859731Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-05T10:19:33.859731Z digest=sha256:19a44081b60ca35d41b37364e956a1c0ef79f890ed625b57d15e6dfbd371f9f2

Observation 5835f37e-56c0-4d56-a933-ec49754a3f4f · outbound

This paper cites Direct3D-S2: Gigascale 3D Generation Made Easy with Spatial Sparse Attention.

Few-step Flow for 3D Generation via Marginal-Data Transport Distillation Direct3D-S2: Gigascale 3D Generation Made Easy with Spatial Sparse Attention

Reference 79

Resolution
unresolved
no resolver link, observed 2026-08-05T10:19:33.862476Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-05T10:19:33.862476Z digest=sha256:c2af0ea06d9d2fecf7a4b5f46c76c34cf562aa1100ab1fd1ee4a01592f926bc7

Observation 6e6b73df-ca6a-4c0c-ba97-d10e6c9800cc · outbound

This paper cites Inception-v3 for flower classification.

Few-step Flow for 3D Generation via Marginal-Data Transport Distillation Inception-v3 for flower classification

Reference 80

Resolution
verified fuzzy
raw_fallback, observed 2026-08-05T10:19:34.520543Z

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=2026-08-05T10:19:33.865671Z digest=sha256:86c55d5df3a81810e4ea39f63b6391bd358b56bb43e470bf41316d922a222a08

Observation 98be5d64-e1b5-4b06-93e3-441e25476043 · outbound

This paper cites Structured 3D Latents for Scalable and Versatile 3D Generation.

Few-step Flow for 3D Generation via Marginal-Data Transport Distillation Structured 3D Latents for Scalable and Versatile 3D Generation

Reference 81

Resolution
unresolved
no resolver link, observed 2026-08-05T10:19:33.868584Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-05T10:19:33.868584Z digest=sha256:e8db7f428a9395654224a657fc4dbe2b97972ca5e7c5a122caf7700b25d78f08

Observation 14eece61-03dc-45fe-86db-be84d254140f · outbound

This paper cites GRM: Large Gaussian Reconstruction Model for Efficient 3D Reconstruction and Generation.

Few-step Flow for 3D Generation via Marginal-Data Transport Distillation GRM: Large Gaussian Reconstruction Model for Efficient 3D Reconstruction and Generation

Reference 82

Resolution
unresolved
no resolver link, observed 2026-08-05T10:19:33.871843Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-05T10:19:33.871843Z digest=sha256:16ed9f62cc08c8faaec0d3fd2fa34e93cf05585fae55d78342401c036f5a17f5

Observation 5aa51398-c069-44c2-ab2e-44410856b40d · outbound

This paper cites Ulip-2: Towards scal- able multimodal pre-training for 3d understanding.

Few-step Flow for 3D Generation via Marginal-Data Transport Distillation Ulip-2: Towards scal- able multimodal pre-training for 3d understanding

Reference 83

Resolution
verified fuzzy
raw_fallback, observed 2026-08-05T10:19:34.511130Z

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=2026-08-05T10:19:33.875454Z digest=sha256:993652dbf020e95bc1f7f63e3856e203f44ecf5b4614f9416a72d066e2edbce8

Observation 84c7daf7-b97f-4759-b5aa-558a78f05f95 · outbound

This paper cites Hunyuan3D 1.0: A Unified Framework for Text-to-3D and Image-to-3D Generation.

Few-step Flow for 3D Generation via Marginal-Data Transport Distillation Hunyuan3D 1.0: A Unified Framework for Text-to-3D and Image-to-3D Generation

Reference 84

Resolution
unresolved
no resolver link, observed 2026-08-05T10:19:33.878283Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-05T10:19:33.878283Z digest=sha256:9f06adb3edf6aeeb79b4eff746048f2a8ef3b6be28bf36bb6ef81e45924b18dc

Observation 2e256559-b0b8-4169-8d31-6954b3531691 · outbound

This paper cites Hi3DGen: High-fidelity 3D Geometry Generation from Images via Normal Bridging.

Few-step Flow for 3D Generation via Marginal-Data Transport Distillation Hi3DGen: High-fidelity 3D Geometry Generation from Images via Normal Bridging

Reference 85

Resolution
unresolved
no resolver link, observed 2026-08-05T10:19:33.881442Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-05T10:19:33.881442Z digest=sha256:903bfc254b113b7004c110bbb984e98e48e968267c119555714386f077e431cf

Observation 9fbf054a-aad1-48dc-b2d6-f82da30a367b · outbound

This paper cites GaussianDreamer: Fast Generation from Text to 3D Gaussians by Bridging 2D and 3D Diffusion Models.

Few-step Flow for 3D Generation via Marginal-Data Transport Distillation GaussianDreamer: Fast Generation from Text to 3D Gaussians by Bridging 2D and 3D Diffusion Models

Reference 86

Resolution
unresolved
no resolver link, observed 2026-08-05T10:19:33.884740Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-05T10:19:33.884740Z digest=sha256:dcbcb9fa5d85109226208325d9b04f3b95d5f961441ad6fc746432c4d22901e9

Observation e926a17e-7737-4e61-ad2f-ed07c0fbe03b · outbound

This paper cites GaussianDreamerPro: Text to Manipulable 3D Gaussians with Highly Enhanced Quality.

Few-step Flow for 3D Generation via Marginal-Data Transport Distillation GaussianDreamerPro: Text to Manipulable 3D Gaussians with Highly Enhanced Quality

Reference 87

Resolution
unresolved
no resolver link, observed 2026-08-05T10:19:33.888070Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-05T10:19:33.888070Z digest=sha256:eaa4655cbf666c745a3ca686717242ee54f5c3051015a739ccce984a0ea92c7f

Observation 44ea926e-d6b0-4f2b-b834-c051a3b037b4 · outbound

This paper cites AvatarVerse: High-quality & Stable 3D Avatar Creation from Text and Pose.

Few-step Flow for 3D Generation via Marginal-Data Transport Distillation AvatarVerse: High-quality & Stable 3D Avatar Creation from Text and Pose

Reference 88

Resolution
verified exact
local_arxiv, observed 2026-08-05T10:19:33.984826Z

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=2026-08-05T10:19:33.890907Z digest=sha256:49db8e23874daddaee7372f9a6e8d03379b04f69952066899764ab6235b03eb7

Observation 80824e7d-8c2e-47ee-b9f0-953b3732e929 · outbound

This paper cites Gs-lrm: Large recon- struction model for 3d gaussian splatting.

Few-step Flow for 3D Generation via Marginal-Data Transport Distillation Gs-lrm: Large recon- struction model for 3d gaussian splatting

Reference 89

Resolution
verified fuzzy
raw_fallback, observed 2026-08-05T10:19:34.502104Z

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=2026-08-05T10:19:33.894057Z digest=sha256:33e8611c8982ac6f6cde60fdd31e2e9825deb43de6bd9806473223f5356de081

Observation fbb9bf1e-6f6c-40a4-b1b2-f49565fa6dcf · outbound

This paper cites DreamFace: Progressive Generation of Animatable 3D Faces under Text Guidance.

Few-step Flow for 3D Generation via Marginal-Data Transport Distillation DreamFace: Progressive Generation of Animatable 3D Faces under Text Guidance

Reference 90

Resolution
unresolved
no resolver link, observed 2026-08-05T10:19:33.896788Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-05T10:19:33.896788Z digest=sha256:4646e019431d0882bbf21a14ce8d63cbdd4bca6539c356e7fef0ada5807a42ef

Observation 08e79577-8904-4382-9b6c-9915bb3d1594 · outbound

This paper cites Clay: A controllable large-scale generative model for creat- ing high-quality 3d assets.

Few-step Flow for 3D Generation via Marginal-Data Transport Distillation Clay: A controllable large-scale generative model for creat- ing high-quality 3d assets

Reference 91

Resolution
verified fuzzy
raw_fallback, observed 2026-08-05T10:19:34.493059Z

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=2026-08-05T10:19:33.899846Z digest=sha256:8c398b8ad8fd9b2d30e2df2b1485db6a5c0f35cdf44dcd0bb515a5098f426104

Observation 1104c778-0a19-42ab-9d00-e1850f612399 · outbound

This paper cites EfficientDreamer: High-Fidelity and Robust 3D Creation via Orthogonal-view Diffusion Prior.

Few-step Flow for 3D Generation via Marginal-Data Transport Distillation EfficientDreamer: High-Fidelity and Robust 3D Creation via Orthogonal-view Diffusion Prior

Reference 92

Resolution
unresolved
no resolver link, observed 2026-08-05T10:19:33.902593Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-05T10:19:33.902593Z digest=sha256:a4578c40f78c56a1eea2061c3dace3475170ab40685950765ca1ee5abd949c67

Observation 81306fba-e992-4a8f-8678-ba5eefefc454 · outbound

This paper cites Hunyuan3D 2.0: Scaling Diffusion Models for High Resolution Textured 3D Assets Generation.

Few-step Flow for 3D Generation via Marginal-Data Transport Distillation Hunyuan3D 2.0: Scaling Diffusion Models for High Resolution Textured 3D Assets Generation

Reference 93

Resolution
unresolved
no resolver link, observed 2026-08-05T10:19:33.906000Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-05T10:19:33.906000Z digest=sha256:8099dbe6c73affd6f5f1be58741a0c93f9c5e9228d29974f9cbcfebe802b0d35

Observation 624f8378-d926-466c-8af3-5871a372941b · outbound

This paper cites Triplane Meets Gaussian Splatting: Fast and Generalizable Single-View 3D Reconstruction with Transformers.

Few-step Flow for 3D Generation via Marginal-Data Transport Distillation Triplane Meets Gaussian Splatting: Fast and Generalizable Single-View 3D Reconstruction with Transformers

Reference 94

Resolution
unresolved
no resolver link, observed 2026-08-05T10:19:33.908823Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-05T10:19:33.908823Z digest=sha256:faacb7325d4e716150afdd26db22b69ad7b40ba7c417918f4572cd947f3d2f65

Pith citing papers

No inbound Pith citation observations are available.