Structured 3D Latents Are Surprisingly Powerful: Unleashing Generalizable Style with 2D Diffusion | Paper Citation Record

Observation 4e4311b9-6a31-4df6-be0b-07a4aa468f9b · outbound

This paper cites Denoising diffusion probabilistic models.Advances in neural information processing systems, 33:6840–6851.

Structured 3D Latents Are Surprisingly Powerful: Unleashing Generalizable Style with 2D Diffusion Denoising diffusion probabilistic models.Advances in neural information processing systems, 33:6840–6851

Reference 1

Resolution: verified fuzzy; raw_fallback, observed 2026-05-26T06:46:53.833284Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.

Observation 69e03fae-4712-4e45-ba38-c237cadd90ff · outbound

This paper cites Denoising Diffusion Implicit Models.

Structured 3D Latents Are Surprisingly Powerful: Unleashing Generalizable Style with 2D Diffusion Denoising Diffusion Implicit Models

Reference 2

Resolution: verified exact; local_arxiv, observed 2026-05-11T17:16:07.486096Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.

Observation 6cab9232-e022-470b-8ef5-ca2ba1837e73 · outbound

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

Structured 3D Latents Are Surprisingly Powerful: Unleashing Generalizable Style with 2D Diffusion High- resolution image synthesis with latent diffusion models

Reference 3

Resolution: verified fuzzy; raw_fallback, observed 2026-05-26T06:46:53.837929Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.

Observation 06cc9dc1-dbff-4100-8a45-3134216c3728 · outbound

This paper cites Advances in 3D Generation: A Survey.

Structured 3D Latents Are Surprisingly Powerful: Unleashing Generalizable Style with 2D Diffusion Advances in 3D Generation: A Survey

Reference 4

Resolution: verified exact; arxiv_id, observed 2026-05-11T17:16:07.490761Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.

Observation 1ec442c6-cf99-4b50-b9ea-d3ed5b4e175d · outbound

This paper cites Combo- verse: Compositional 3d assets creation using spatially-aware diffusion guidance.

Structured 3D Latents Are Surprisingly Powerful: Unleashing Generalizable Style with 2D Diffusion Combo- verse: Compositional 3d assets creation using spatially-aware diffusion guidance

Reference 5

Resolution: verified fuzzy; raw_fallback, observed 2026-05-26T06:46:53.844981Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.

Observation 5256c2f8-f1f5-401a-b80d-b1a36356cac5 · outbound

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

Structured 3D Latents Are Surprisingly Powerful: Unleashing Generalizable Style with 2D Diffusion DreamFusion: Text-to-3D using 2D Diffusion

Reference 6

Resolution: verified exact; local_arxiv, observed 2026-05-11T17:16:07.480252Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.

Observation 65fa0f13-2260-4942-a8e1-480fae02a5ff · outbound

This paper cites Zero-1-to-3: Zero-shot one image to 3d object.

Structured 3D Latents Are Surprisingly Powerful: Unleashing Generalizable Style with 2D Diffusion Zero-1-to-3: Zero-shot one image to 3d object

Reference 7

Resolution: verified fuzzy; raw_fallback, observed 2026-05-26T06:46:53.850787Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.

Observation 0acd6511-5c3d-455d-897f-abb086c1127b · outbound

This paper cites Structured 3d latents for scalable and versatile 3d generation.

Structured 3D Latents Are Surprisingly Powerful: Unleashing Generalizable Style with 2D Diffusion Structured 3d latents for scalable and versatile 3d generation

Reference 8

Resolution: verified fuzzy; raw_fallback, observed 2026-05-26T06:46:53.621910Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.

Observation f31aeb58-47f9-4a06-a3e9-e6bc1ff5cd54 · outbound

This paper cites arXiv preprint arXiv:2509.25079 , year=.

Structured 3D Latents Are Surprisingly Powerful: Unleashing Generalizable Style with 2D Diffusion arXiv preprint arXiv:2509.25079 , year=

Reference 9

Resolution: verified exact; arxiv_id, observed 2026-05-11T17:16:07.537731Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.

Observation 2f29fe39-966e-46fa-91df-f41d7d3dd28e · outbound

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

Structured 3D Latents Are Surprisingly Powerful: Unleashing Generalizable Style with 2D Diffusion Hunyuan3D 2.0: Scaling Diffusion Models for High Resolution Textured 3D Assets Generation

Reference 10

Resolution: verified exact; arxiv_id, observed 2026-05-11T17:16:07.589765Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.

Observation 7010f48d-ccb3-48af-886e-ceb1cda24131 · outbound

This paper cites Style injection in diffusion: A training-free approach for adapting large-scale diffusion models for style transfer.

Structured 3D Latents Are Surprisingly Powerful: Unleashing Generalizable Style with 2D Diffusion Style injection in diffusion: A training-free approach for adapting large-scale diffusion models for style transfer

Reference 11

Resolution: verified fuzzy; raw_fallback, observed 2026-05-26T06:46:53.636352Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.

Observation 40e50a74-66ab-4ca2-877c-ec0cd7b64e8d · outbound

This paper cites Z*: Zero-shot style transfer via attention reweighting.

Structured 3D Latents Are Surprisingly Powerful: Unleashing Generalizable Style with 2D Diffusion Z*: Zero-shot style transfer via attention reweighting

Reference 12

Resolution: verified fuzzy; raw_fallback, observed 2026-05-26T06:46:53.573630Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.

Observation 8862b5c6-f1a2-42ed-be9f-a558ed93c6c2 · outbound

This paper cites Unziplora: Separating content and style from a single image.

Structured 3D Latents Are Surprisingly Powerful: Unleashing Generalizable Style with 2D Diffusion Unziplora: Separating content and style from a single image

Reference 13

Resolution: verified fuzzy; raw_fallback, observed 2026-05-26T06:46:53.819726Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.

Observation 41f20892-f034-43c8-a60a-4c2b34f670a2 · outbound

This paper cites Stylediffusion: Controllable disentangled style transfer via diffusion models.

Structured 3D Latents Are Surprisingly Powerful: Unleashing Generalizable Style with 2D Diffusion Stylediffusion: Controllable disentangled style transfer via diffusion models

Reference 14

Resolution: verified fuzzy; raw_fallback, observed 2026-05-26T06:46:53.805761Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.

Observation 881c1a70-c24b-497e-a7e3-40c85f297fd5 · outbound

This paper cites Stylessp: Sampling start- point enhancement for training-free diffusion-based method for style transfer.

Structured 3D Latents Are Surprisingly Powerful: Unleashing Generalizable Style with 2D Diffusion Stylessp: Sampling start- point enhancement for training-free diffusion-based method for style transfer

Reference 15

Resolution: verified fuzzy; raw_fallback, observed 2026-05-26T06:46:53.578481Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.

Observation 603b76df-bdf3-4357-8066-8ea1cb5b8c26 · outbound

This paper cites Attention distillation: A unified approach to visual characteristics transfer.

Structured 3D Latents Are Surprisingly Powerful: Unleashing Generalizable Style with 2D Diffusion Attention distillation: A unified approach to visual characteristics transfer

Reference 16

Resolution: verified fuzzy; raw_fallback, observed 2026-05-26T06:46:53.789265Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.

Observation 0cfafc93-1349-495f-9f4e-09e67dff429c · outbound

This paper cites Stylesculptor: Zero-shot style-controllable 3d asset generation with texture-geometry dual guidance.

Structured 3D Latents Are Surprisingly Powerful: Unleashing Generalizable Style with 2D Diffusion Stylesculptor: Zero-shot style-controllable 3d asset generation with texture-geometry dual guidance

Reference 17

Resolution: verified fuzzy; raw_fallback, observed 2026-05-26T06:46:53.797719Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.

Observation 82500e42-218e-493a-bc87-aabda73bbba8 · outbound

This paper cites Morphany3d: Unleashing the power of structured latent in 3d morphing.

Structured 3D Latents Are Surprisingly Powerful: Unleashing Generalizable Style with 2D Diffusion Morphany3d: Unleashing the power of structured latent in 3d morphing

Reference 18

Resolution: verified exact; arxiv_id, observed 2026-05-11T17:16:07.548924Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.

Observation 71593de9-6da9-4b4d-81f6-4fa07bfc1569 · outbound

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

Structured 3D Latents Are Surprisingly Powerful: Unleashing Generalizable Style with 2D Diffusion 3d gaussian splatting for real-time radiance field rendering.ACM Trans

Reference 19

Resolution: verified fuzzy; raw_fallback, observed 2026-05-26T06:46:53.782115Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.

Observation c709634f-f797-4c18-a8f3-94dc18314fae · outbound

This paper cites Generative adversarial nets.Advances in neural information processing systems, 27.

Structured 3D Latents Are Surprisingly Powerful: Unleashing Generalizable Style with 2D Diffusion Generative adversarial nets.Advances in neural information processing systems, 27

Reference 20

Resolution: verified fuzzy; raw_fallback, observed 2026-05-26T06:46:53.774345Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.

Observation 665ce830-249a-474f-8fdc-fd91c42215c9 · outbound

This paper cites A style-based generator architecture for generative adversarial networks.

Structured 3D Latents Are Surprisingly Powerful: Unleashing Generalizable Style with 2D Diffusion A style-based generator architecture for generative adversarial networks

Reference 21

Resolution: verified fuzzy; raw_fallback, observed 2026-05-26T06:46:53.812414Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.

Observation cf51f5ae-ecb1-4706-a76c-b559e17b469b · outbound

This paper cites Analyzing and improving the image quality of stylegan.

Structured 3D Latents Are Surprisingly Powerful: Unleashing Generalizable Style with 2D Diffusion Analyzing and improving the image quality of stylegan

Reference 22

Resolution: verified fuzzy; raw_fallback, observed 2026-05-26T06:46:53.825657Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.

Observation feab9fcb-b06a-4798-9a9b-71697365be0c · outbound

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

Structured 3D Latents Are Surprisingly Powerful: Unleashing Generalizable Style with 2D Diffusion Score-Based Generative Modeling through Stochastic Differential Equations

Reference 23

Resolution: verified exact; local_arxiv, observed 2026-05-11T17:16:07.509130Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.

Observation 4ca0ab87-7283-4f18-a27d-344999ee7f53 · outbound

This paper cites Photorealistic text-to-image diffusion models with deep language understanding.Advances in neural information processing systems, 35:36479–36494.

Structured 3D Latents Are Surprisingly Powerful: Unleashing Generalizable Style with 2D Diffusion Photorealistic text-to-image diffusion models with deep language understanding.Advances in neural information processing systems, 35:36479–36494

Reference 24

Resolution: verified fuzzy; raw_fallback, observed 2026-05-26T06:46:53.724630Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.

Observation 8b216937-c8f3-4607-8814-2d8f500265b3 · outbound

This paper cites SDXL: Improving Latent Diffusion Models for High-Resolution Image Synthesis.

Structured 3D Latents Are Surprisingly Powerful: Unleashing Generalizable Style with 2D Diffusion SDXL: Improving Latent Diffusion Models for High-Resolution Image Synthesis

Reference 25

Resolution: verified exact; local_arxiv, observed 2026-05-11T17:16:07.564975Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.

Observation 55bf4aca-ad2c-4f2b-9cee-6d6480ea0c81 · outbound

This paper cites Flow Matching for Generative Modeling.

Structured 3D Latents Are Surprisingly Powerful: Unleashing Generalizable Style with 2D Diffusion Flow Matching for Generative Modeling

Reference 26

Resolution: verified exact; local_arxiv, observed 2026-05-11T17:16:07.533360Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.

Observation 7342f6a8-73fd-4e6c-9233-89b808752757 · outbound

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

Structured 3D Latents Are Surprisingly Powerful: Unleashing Generalizable Style with 2D Diffusion Flow Straight and Fast: Learning to Generate and Transfer Data with Rectified Flow

Reference 27

Resolution: verified exact; local_arxiv, observed 2026-05-11T17:16:07.497350Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.

Observation a84e26de-e568-4316-9adb-c28c25499a25 · outbound

This paper cites Efficient geometry- aware 3d generative adversarial networks.

Structured 3D Latents Are Surprisingly Powerful: Unleashing Generalizable Style with 2D Diffusion Efficient geometry- aware 3d generative adversarial networks

Reference 28

Resolution: verified fuzzy; raw_fallback, observed 2026-05-26T06:46:53.583702Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.

Observation 8689c763-2d11-4949-85b1-7fe92150160a · outbound

This paper cites Gram: Generative radiance manifolds for 3d-aware image generation.

Structured 3D Latents Are Surprisingly Powerful: Unleashing Generalizable Style with 2D Diffusion Gram: Generative radiance manifolds for 3d-aware image generation

Reference 29

Resolution: verified fuzzy; raw_fallback, observed 2026-05-26T06:46:53.730822Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.

Observation 1bd70ed9-2855-4280-ae23-9a26f71e262a · outbound

This paper cites Get3d: A generative model of high quality 3d textured shapes learned from images.Advances in neural information processing systems, 35:31841–31854.

Structured 3D Latents Are Surprisingly Powerful: Unleashing Generalizable Style with 2D Diffusion Get3d: A generative model of high quality 3d textured shapes learned from images.Advances in neural information processing systems, 35:31841–31854

Reference 30

Resolution: verified fuzzy; raw_fallback, observed 2026-05-26T06:46:53.749610Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.

Observation ad88d819-72a0-45a4-a32e-a4cbe69728fd · outbound

This paper cites Sdf-stylegan: implicit sdf-based stylegan for 3d shape generation.

Structured 3D Latents Are Surprisingly Powerful: Unleashing Generalizable Style with 2D Diffusion Sdf-stylegan: implicit sdf-based stylegan for 3d shape generation

Reference 31

Resolution: verified fuzzy; raw_fallback, observed 2026-05-26T06:46:53.597354Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.

Observation 8d34ecbe-cb5a-4024-88c2-8f3566fd2037 · outbound

This paper cites Lucid- dreamer: Towards high-fidelity text-to-3d generation via interval score matching.

Structured 3D Latents Are Surprisingly Powerful: Unleashing Generalizable Style with 2D Diffusion Lucid- dreamer: Towards high-fidelity text-to-3d generation via interval score matching

Reference 32

Resolution: verified fuzzy; raw_fallback, observed 2026-05-26T06:46:53.711977Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.

Observation bcc4bdcc-7384-460e-b6e2-961d1eb1ecf9 · outbound

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

Structured 3D Latents Are Surprisingly Powerful: Unleashing Generalizable Style with 2D Diffusion DreamGaussian: Generative Gaussian Splatting for Efficient 3D Content Creation

Reference 33

Resolution: verified exact; arxiv_id, observed 2026-05-16T10:18:06.729150Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.

Observation f0388f59-4c2b-482a-a6fd-f8000d7cd4e3 · outbound

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

Structured 3D Latents Are Surprisingly Powerful: Unleashing Generalizable Style with 2D Diffusion Magic3d: High-resolution text-to-3d content creation

Reference 34

Resolution: verified fuzzy; raw_fallback, observed 2026-05-26T06:46:53.588339Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.

Observation 4885037f-48ea-4e67-a75d-2825d8a821fc · outbound

This paper cites Make-it-3d: High-fidelity 3d creation from a single image with diffusion prior.

Structured 3D Latents Are Surprisingly Powerful: Unleashing Generalizable Style with 2D Diffusion Make-it-3d: High-fidelity 3d creation from a single image with diffusion prior

Reference 35

Resolution: verified fuzzy; raw_fallback, observed 2026-05-26T06:46:53.704950Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.

Observation 7e1a0c3e-e522-4edc-9c74-a48bd07b068c · outbound

This paper cites Pro- lificdreamer: High-fidelity and diverse text-to-3d generation with variational score distillation.

Structured 3D Latents Are Surprisingly Powerful: Unleashing Generalizable Style with 2D Diffusion Pro- lificdreamer: High-fidelity and diverse text-to-3d generation with variational score distillation

Reference 36

Resolution: verified fuzzy; raw_fallback, observed 2026-05-26T06:46:53.718738Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.

Observation 4aaae185-4a96-4a0e-a9f4-6030857f231e · outbound

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

Structured 3D Latents Are Surprisingly Powerful: Unleashing Generalizable Style with 2D Diffusion Instant3D: Fast Text-to-3D with Sparse-View Generation and Large Reconstruction Model

Reference 37

Resolution: verified exact; arxiv_id, observed 2026-05-11T17:16:07.504113Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.

Observation 991c110d-aa72-4c8e-a317-88ca15d1d470 · outbound

This paper cites One-2-3-45++: Fast single image to 3d objects with consistent multi-view generation and 3d diffusion.

Structured 3D Latents Are Surprisingly Powerful: Unleashing Generalizable Style with 2D Diffusion One-2-3-45++: Fast single image to 3d objects with consistent multi-view generation and 3d diffusion

Reference 38

Resolution: verified fuzzy; raw_fallback, observed 2026-05-26T06:46:53.742568Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.

Observation ca22d1aa-abe7-4aa9-9a11-e7e641f61492 · outbound

This paper cites Wonder3d: Single image to 3d using cross-domain diffusion.

Structured 3D Latents Are Surprisingly Powerful: Unleashing Generalizable Style with 2D Diffusion Wonder3d: Single image to 3d using cross-domain diffusion

Reference 39

Resolution: verified fuzzy; raw_fallback, observed 2026-05-26T06:46:53.763387Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.

Observation eca24e43-f4e3-4af8-8490-6207d17808bd · outbound

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

Structured 3D Latents Are Surprisingly Powerful: Unleashing Generalizable Style with 2D Diffusion MVDream: Multi-view Diffusion for 3D Generation

Reference 40

Resolution: verified exact; arxiv_id, observed 2026-05-15T08:36:20.266102Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.

Observation b363ba5e-ffa5-47fe-b3f3-bb39b0f05b41 · outbound

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

Structured 3D Latents Are Surprisingly Powerful: Unleashing Generalizable Style with 2D Diffusion LRM: Large Reconstruction Model for Single Image to 3D

Reference 41

Resolution: verified exact; arxiv_id, observed 2026-05-15T10:11:00.998012Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.

Observation 214b1505-1db5-4d06-a9a4-de1b2f166704 · outbound

This paper cites Autodecoding latent 3d diffusion models.Advances in Neural Information Processing Systems, 36:67021–67047.

Structured 3D Latents Are Surprisingly Powerful: Unleashing Generalizable Style with 2D Diffusion Autodecoding latent 3d diffusion models.Advances in Neural Information Processing Systems, 36:67021–67047

Reference 42

Resolution: verified fuzzy; raw_fallback, observed 2026-05-26T06:46:53.592800Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.

Observation 7715c2ad-f5a2-4cee-875d-ae1673be69ae · outbound

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

Structured 3D Latents Are Surprisingly Powerful: Unleashing Generalizable Style with 2D Diffusion 3dtopia-xl: Scaling high-quality 3d asset generation via primitive diffusion

Reference 43

Resolution: verified fuzzy; raw_fallback, observed 2026-05-26T06:46:53.687760Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.

Observation d3f0f5c5-5144-4e34-a80c-043393ce28a9 · outbound

This paper cites Ln3diff++: Scalable latent neural fields diffusion for speedy 3d generation.IEEE Transactions on Pattern Analysis and Machine Intelligence.

Structured 3D Latents Are Surprisingly Powerful: Unleashing Generalizable Style with 2D Diffusion Ln3diff++: Scalable latent neural fields diffusion for speedy 3d generation.IEEE Transactions on Pattern Analysis and Machine Intelligence

Reference 44

Resolution: verified fuzzy; raw_fallback, observed 2026-05-26T06:46:53.616676Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.

Observation 580f219c-3650-4c74-86ec-037044b5ef8e · outbound

This paper cites IP-Adapter: Text Compatible Image Prompt Adapter for Text-to-Image Diffusion Models.

Structured 3D Latents Are Surprisingly Powerful: Unleashing Generalizable Style with 2D Diffusion IP-Adapter: Text Compatible Image Prompt Adapter for Text-to-Image Diffusion Models

Reference 45

Resolution: verified exact; local_arxiv, observed 2026-05-11T17:16:07.571138Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.

Observation 304281d3-657f-43c0-bd60-be5344653c28 · outbound

This paper cites Deadiff: An efficient stylization diffusion model with disentangled representations.

Structured 3D Latents Are Surprisingly Powerful: Unleashing Generalizable Style with 2D Diffusion Deadiff: An efficient stylization diffusion model with disentangled representations

Reference 46

Resolution: verified fuzzy; raw_fallback, observed 2026-05-26T06:46:53.602368Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.

Observation 8a53d635-567b-4cd7-8fe1-7a350ac3b9ee · outbound

This paper cites Styletokenizer: Defining image style by a single instance for controlling diffusion models.

Structured 3D Latents Are Surprisingly Powerful: Unleashing Generalizable Style with 2D Diffusion Styletokenizer: Defining image style by a single instance for controlling diffusion models

Reference 47

Resolution: verified fuzzy; raw_fallback, observed 2026-05-26T06:46:53.683016Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.

Observation a43e54da-33f5-4c38-9f4d-b1ac2991d559 · outbound

This paper cites Stylestudio: Text-driven style transfer with selective control of style elements.

Structured 3D Latents Are Surprisingly Powerful: Unleashing Generalizable Style with 2D Diffusion Stylestudio: Text-driven style transfer with selective control of style elements

Reference 48

Resolution: verified fuzzy; raw_fallback, observed 2026-05-26T06:46:53.694060Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.

Observation 3c29a946-1800-4a52-8218-116beb899932 · outbound

This paper cites Customizing text-to-image models with a single image pair.

Structured 3D Latents Are Surprisingly Powerful: Unleashing Generalizable Style with 2D Diffusion Customizing text-to-image models with a single image pair

Reference 49

Resolution: verified fuzzy; raw_fallback, observed 2026-05-26T06:46:53.737230Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.

Observation b41a9eab-58d3-414c-87be-eea294ebd55f · outbound

This paper cites Sigstyle: Signature style transfer via personalized text-to-image models.

Structured 3D Latents Are Surprisingly Powerful: Unleashing Generalizable Style with 2D Diffusion Sigstyle: Signature style transfer via personalized text-to-image models

Reference 50

Resolution: verified fuzzy; raw_fallback, observed 2026-05-26T06:46:53.611474Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.

Observation 805eb004-9913-4538-ac95-41df6d58bf08 · outbound

This paper cites Omnistyle: Filtering high quality style transfer data at scale.

Structured 3D Latents Are Surprisingly Powerful: Unleashing Generalizable Style with 2D Diffusion Omnistyle: Filtering high quality style transfer data at scale

Reference 51

Resolution: verified fuzzy; raw_fallback, observed 2026-05-26T06:46:53.672739Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.

Observation 4dcc0474-6f88-4ebf-a6d4-9fc45c7cf62a · outbound

This paper cites An Image is Worth One Word: Personalizing Text-to-Image Generation using Textual Inversion.

Structured 3D Latents Are Surprisingly Powerful: Unleashing Generalizable Style with 2D Diffusion An Image is Worth One Word: Personalizing Text-to-Image Generation using Textual Inversion

Reference 52

Resolution: verified exact; arxiv_id, observed 2026-05-11T18:08:55.677650Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.

Observation a7563a2f-3bfe-4c27-ad5f-1da85d428429 · outbound

This paper cites Inversion-based style transfer with diffusion models.

Structured 3D Latents Are Surprisingly Powerful: Unleashing Generalizable Style with 2D Diffusion Inversion-based style transfer with diffusion models

Reference 53

Resolution: verified fuzzy; raw_fallback, observed 2026-05-26T06:46:53.606959Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.

Observation 0c9e02a1-e240-487d-bd64-06b1e2e1d7b7 · outbound

This paper cites Ziplora: Any subject in any style by effectively merging loras.

Structured 3D Latents Are Surprisingly Powerful: Unleashing Generalizable Style with 2D Diffusion Ziplora: Any subject in any style by effectively merging loras

Reference 54

Resolution: verified fuzzy; raw_fallback, observed 2026-05-26T06:46:53.631582Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.

Observation 683ac824-4788-4db3-9943-c9b818bdc359 · outbound

This paper cites Implicit style-content separation using b-lora.

Structured 3D Latents Are Surprisingly Powerful: Unleashing Generalizable Style with 2D Diffusion Implicit style-content separation using b-lora

Reference 55

Resolution: verified fuzzy; raw_fallback, observed 2026-05-26T06:46:53.667092Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.

Observation 1c5ce354-2d24-4c5d-9d9e-ffe0da2591af · outbound

This paper cites Qr-lora: Efficient and disentangled fine-tuning via qr decomposition for customized generation.

Structured 3D Latents Are Surprisingly Powerful: Unleashing Generalizable Style with 2D Diffusion Qr-lora: Efficient and disentangled fine-tuning via qr decomposition for customized generation

Reference 56

Resolution: verified fuzzy; raw_fallback, observed 2026-05-26T06:46:53.678433Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.

Observation 856377dd-d4b0-43d7-a648-261c4fbb38c8 · outbound

This paper cites Nerf: Representing scenes as neural radiance fields for view synthesis.

Structured 3D Latents Are Surprisingly Powerful: Unleashing Generalizable Style with 2D Diffusion Nerf: Representing scenes as neural radiance fields for view synthesis

Reference 57

Resolution: verified fuzzy; raw_fallback, observed 2026-05-26T06:46:53.699989Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.

Observation 4cc1f19e-23ea-4159-bbd6-602cd77173d3 · outbound

This paper cites Stylerf: Zero-shot 3d style transfer of neural radiance fields.

Structured 3D Latents Are Surprisingly Powerful: Unleashing Generalizable Style with 2D Diffusion Stylerf: Zero-shot 3d style transfer of neural radiance fields

Reference 58

Resolution: verified fuzzy; raw_fallback, observed 2026-05-26T06:46:53.757524Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.

Observation 4ac2c3e1-28d1-4aab-827b-3ce593a0b357 · outbound

This paper cites Unified implicit neural stylization.

Structured 3D Latents Are Surprisingly Powerful: Unleashing Generalizable Style with 2D Diffusion Unified implicit neural stylization

Reference 59

Resolution: verified fuzzy; raw_fallback, observed 2026-05-26T06:46:53.659582Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.

Observation 699b4388-b502-4aaa-9430-5d7dedadb21c · outbound

This paper cites Stylegaussian: Instant 3d style transfer with gaussian splatting.

Structured 3D Latents Are Surprisingly Powerful: Unleashing Generalizable Style with 2D Diffusion Stylegaussian: Instant 3d style transfer with gaussian splatting

Reference 60

Resolution: verified fuzzy; raw_fallback, observed 2026-05-26T06:46:53.645253Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.

Observation 70293aad-45ca-4b3e-b952-420f18b4b2ce · outbound

This paper cites StyleSplat: 3D Object Style Transfer with Gaussian Splatting.

Structured 3D Latents Are Surprisingly Powerful: Unleashing Generalizable Style with 2D Diffusion StyleSplat: 3D Object Style Transfer with Gaussian Splatting

Reference 61

Resolution: verified exact; arxiv_id, observed 2026-05-11T17:16:07.601292Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.

Observation bbca859d-a0fe-4a27-bd32-282f845b8fe5 · outbound

This paper cites Styletex: Style image-guided texture generation for 3d models.ACM Transactions on Graphics (TOG), 43(6):1–14.

Structured 3D Latents Are Surprisingly Powerful: Unleashing Generalizable Style with 2D Diffusion Styletex: Style image-guided texture generation for 3d models.ACM Transactions on Graphics (TOG), 43(6):1–14

Reference 62

Resolution: verified fuzzy; raw_fallback, observed 2026-05-26T06:46:53.626512Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.

Observation d615b944-3ba3-4d4f-9c4f-6a3bf6f19986 · outbound

This paper cites Texture: Text- guided texturing of 3d shapes.

Structured 3D Latents Are Surprisingly Powerful: Unleashing Generalizable Style with 2D Diffusion Texture: Text- guided texturing of 3d shapes

Reference 63

Resolution: verified fuzzy; raw_fallback, observed 2026-05-26T06:46:53.769184Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.

Observation d754a44d-459f-4709-b752-a38379b1ecb7 · outbound

This paper cites Fix false transparency by noise guided splatting.

Structured 3D Latents Are Surprisingly Powerful: Unleashing Generalizable Style with 2D Diffusion Fix false transparency by noise guided splatting

Reference 64

Resolution: verified exact; arxiv_id, observed 2026-05-11T17:16:07.526492Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.

Observation fd0c8caf-e1fb-4603-a77a-39a92cf6ca12 · outbound

This paper cites Object-Centric 2D Gaussian Splatting: Background Removal and Occlusion-Aware Pruning for Compact Object Models.

Structured 3D Latents Are Surprisingly Powerful: Unleashing Generalizable Style with 2D Diffusion Object-Centric 2D Gaussian Splatting: Background Removal and Occlusion-Aware Pruning for Compact Object Models

Reference 65

Resolution: verified exact; arxiv_id, observed 2026-05-11T17:16:07.520501Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.

Observation 0cea4788-230c-499b-8c6c-b4f08294dff4 · outbound

This paper cites Plenoxels: Radiance fields without neural networks.

Structured 3D Latents Are Surprisingly Powerful: Unleashing Generalizable Style with 2D Diffusion Plenoxels: Radiance fields without neural networks

Reference 66

Resolution: verified fuzzy; raw_fallback, observed 2026-05-26T06:46:53.649927Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.

Observation 97ff181c-3cd4-4f42-92e8-b6c8c6f4c966 · outbound

This paper cites InstantStyle-Plus: Style Transfer with Content-Preserving in Text-to-Image Generation.

Structured 3D Latents Are Surprisingly Powerful: Unleashing Generalizable Style with 2D Diffusion InstantStyle-Plus: Style Transfer with Content-Preserving in Text-to-Image Generation

Reference 67

Resolution: verified exact; arxiv_id, observed 2026-05-11T17:16:07.556942Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.

Observation d7a919bf-05a4-468a-8ec8-4baddfbd8fe7 · outbound

This paper cites Hpsv3: Towards wide-spectrum hu- man preference score.

Structured 3D Latents Are Surprisingly Powerful: Unleashing Generalizable Style with 2D Diffusion Hpsv3: Towards wide-spectrum hu- man preference score

Reference 68

Resolution: verified fuzzy; raw_fallback, observed 2026-05-26T06:46:53.654029Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.

Observation 7ba0857d-1dbf-40ca-9e5b-9b825249f33f · outbound

This paper cites Chatgpt-5.5.https://chatgpt.com/.

Structured 3D Latents Are Surprisingly Powerful: Unleashing Generalizable Style with 2D Diffusion Chatgpt-5.5.https://chatgpt.com/

Reference 69

Resolution: verified fuzzy; raw_fallback, observed 2026-05-26T06:46:53.640924Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.

Observation ea7e78de-a046-4a5d-8df1-0556ee298382 · outbound

This paper cites Qwen3-VL Technical Report.

Structured 3D Latents Are Surprisingly Powerful: Unleashing Generalizable Style with 2D Diffusion Qwen3-VL Technical Report

Reference 70

Resolution: verified exact; local_arxiv, observed 2026-05-11T17:16:07.605357Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.

Coverage vector

Reference resolution

Outbound references

Pith citing papers