Paper Citation Record · LEDGER

Leveraging Diffusion Models for Stylization using Multiple Style Images

As of 12 August 2026, this Paper Citation Record lists 47 of 47 outbound references and 0 inbound Pith citation observations for arXiv:2508.12784.

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

pith.paper-citation-record.v1
2508.12784 v1

Coverage vector

measured 47 of 47 reference resolution

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Source: paper_references, paper_reference_links, observed 2026-08-05T19:22:18.515446Z

measured 47 of 47 standing notices

One-hop event checks from named stored sources.

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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

47 of 47 outbound references displayed

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External citation measurements

No source-named external measurement is stored.

Outbound references

Observation f38e36eb-20d3-4059-b56c-40ba39896714 · outbound

This paper cites Emerg- ing properties in self-supervised vision transformers, 2021.

Leveraging Diffusion Models for Stylization using Multiple Style Images Emerg- ing properties in self-supervised vision transformers, 2021

Reference 1

Resolution: verified fuzzy; raw_fallback, observed 2026-08-05T19:22:26.110478Z

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Observation e351c182-8854-4ee9-8926-935ca6cf7746 · outbound

This paper cites Artistic style transfer with internal-external learning and contrastive learning.

Leveraging Diffusion Models for Stylization using Multiple Style Images Artistic style transfer with internal-external learning and contrastive learning

Reference 2

Resolution: verified fuzzy; raw_fallback, observed 2026-08-05T19:22:25.948321Z

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Observation 353d5771-3d45-4cb7-8809-3cc65395bb8b · outbound

This paper cites Pixart-α: Fast training of dif- fusion transformer for photorealistic text-to-image synthesis,.

Leveraging Diffusion Models for Stylization using Multiple Style Images Pixart-α: Fast training of dif- fusion transformer for photorealistic text-to-image synthesis,

Reference 3

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Observation 8668364b-0e44-4775-a641-01384514acb7 · outbound

This paper cites Pixart- σ: Weak-to-strong training of diffu- sion transformer for 4k text-to-image generation, 2024.

Leveraging Diffusion Models for Stylization using Multiple Style Images Pixart- σ: Weak-to-strong training of diffu- sion transformer for 4k text-to-image generation, 2024

Reference 4

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Observation b29a2ac0-5285-4393-99bd-25aff9e69b00 · outbound

This paper cites Style Injection in Diffusion: A Training-free Approach for Adapting Large-scale Diffusion Models for Style Transfer.

Leveraging Diffusion Models for Stylization using Multiple Style Images Style Injection in Diffusion: A Training-free Approach for Adapting Large-scale Diffusion Models for Style Transfer

Reference 5

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Observation 0eba500d-e1a6-49bd-9237-47b6fd49defd · outbound

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

Leveraging Diffusion Models for Stylization using Multiple Style Images Style injec- tion in diffusion: A training-free approach for adapting large- scale diffusion models for style transfer

Reference 6

Resolution: verified fuzzy; raw_fallback, observed 2026-08-05T19:22:25.626346Z

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Observation 9ef1ee8e-2acb-4164-b2b0-7d5e512de50c · outbound

This paper cites Arbitrary Video Style Transfer via Multi-Channel Correlation.

Leveraging Diffusion Models for Stylization using Multiple Style Images Arbitrary Video Style Transfer via Multi-Channel Correlation

Reference 7

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Observation a2058e05-846e-4bc3-ba21-f6ecc54c4543 · outbound

This paper cites Stytr 2: Image style transfer with transformers, 2022.

Leveraging Diffusion Models for Stylization using Multiple Style Images Stytr 2: Image style transfer with transformers, 2022

Reference 8

Resolution: verified fuzzy; raw_fallback, observed 2026-08-05T19:22:25.505815Z

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Observation 7333771b-56a2-4a6b-8df9-8a31cf9c911a · outbound

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

Leveraging Diffusion Models for Stylization using Multiple Style Images Implicit style-content separation using b-lora,

Reference 9

Resolution: verified fuzzy; raw_fallback, observed 2026-08-05T19:22:25.358584Z

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Observation 15881a59-b086-4e72-aee2-a545d7b9b014 · outbound

This paper cites Gatys, Alexander S.

Leveraging Diffusion Models for Stylization using Multiple Style Images Gatys, Alexander S

Reference 10

Resolution: verified fuzzy; raw_fallback, observed 2026-08-05T19:22:25.189328Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-11T06:34:44.6726+00:00.

Observation b36411dd-fa33-4258-870b-e01ee48c387d · outbound

This paper cites Style aligned image generation via shared atten- tion, 2024.

Leveraging Diffusion Models for Stylization using Multiple Style Images Style aligned image generation via shared atten- tion, 2024

Reference 11

Resolution: verified fuzzy; raw_fallback, observed 2026-08-05T19:22:25.025926Z

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Observation c3a98225-b9b5-49c5-828b-8a20e8d1e5f6 · outbound

This paper cites LoRA: Low-Rank Adaptation of Large Language Models.

Leveraging Diffusion Models for Stylization using Multiple Style Images LoRA: Low-Rank Adaptation of Large Language Models

Reference 12

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Observation dd25344b-a279-47c7-8991-4dc5a101b158 · outbound

This paper cites Arbitrary style transfer in real-time with adaptive instance normalization.

Leveraging Diffusion Models for Stylization using Multiple Style Images Arbitrary style transfer in real-time with adaptive instance normalization

Reference 13

Resolution: verified fuzzy; raw_fallback, observed 2026-08-05T19:22:24.908766Z

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Observation 077b7c0c-df18-4f2c-96bc-ec4be11939f6 · outbound

This paper cites Style mixer: Semantic-aware multi-style transfer network.

Leveraging Diffusion Models for Stylization using Multiple Style Images Style mixer: Semantic-aware multi-style transfer network

Reference 14

Resolution: verified fuzzy; raw_fallback, observed 2026-08-05T19:22:24.789329Z

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Observation ee66c153-64d6-4855-8d0e-b5c1a8152110 · outbound

This paper cites Neural style transfer: A review.

Leveraging Diffusion Models for Stylization using Multiple Style Images Neural style transfer: A review

Reference 15

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Observation 2dc66cfe-9777-440a-9975-85e1ff57707c · outbound

This paper cites In the light of feature distributions: moment matching for Neural Style Transfer.

Leveraging Diffusion Models for Stylization using Multiple Style Images In the light of feature distributions: moment matching for Neural Style Transfer

Reference 16

Resolution: verified exact; local_arxiv, observed 2026-08-05T19:22:19.610226Z

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Observation 100474b8-5e88-49f0-a4f9-e15e653b8ba7 · outbound

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

Leveraging Diffusion Models for Stylization using Multiple Style Images A style-based generator architecture for generative adversarial networks

Reference 17

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Observation fb9597a6-f281-43bd-93f8-58566d5baaf7 · outbound

This paper cites Training generative adver- sarial networks with limited data.

Leveraging Diffusion Models for Stylization using Multiple Style Images Training generative adver- sarial networks with limited data

Reference 18

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Observation dc69edb7-3e0b-4d9a-8fc5-1bf297c26237 · outbound

This paper cites Neural neighbor style transfer, 2022.

Leveraging Diffusion Models for Stylization using Multiple Style Images Neural neighbor style transfer, 2022

Reference 19

Resolution: verified fuzzy; raw_fallback, observed 2026-08-05T19:22:24.359092Z

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Observation 5e6a93dc-955f-40d4-955c-ab43fdcc4614 · outbound

This paper cites Multi-concept customization of text-to-image diffusion, 2022.

Leveraging Diffusion Models for Stylization using Multiple Style Images Multi-concept customization of text-to-image diffusion, 2022

Reference 20

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Observation e01b4d0f-55a2-4f26-b16e-2762d7da5b03 · outbound

This paper cites Universal Style Transfer via Feature Transforms.

Leveraging Diffusion Models for Stylization using Multiple Style Images Universal Style Transfer via Feature Transforms

Reference 21

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Observation 4b58f0d7-16f5-4f13-98b2-d5b758636718 · outbound

This paper cites AdaAttN: Revisit Attention Mechanism in Arbitrary Neural Style Transfer.

Leveraging Diffusion Models for Stylization using Multiple Style Images AdaAttN: Revisit Attention Mechanism in Arbitrary Neural Style Transfer

Reference 22

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Observation bb029c95-9967-4704-9b68-0a343e171dfe · outbound

This paper cites Multiple style transfer via variational autoencoder.

Leveraging Diffusion Models for Stylization using Multiple Style Images Multiple style transfer via variational autoencoder

Reference 23

Resolution: verified fuzzy; raw_fallback, observed 2026-08-05T19:22:24.042517Z

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Observation 9cbf08ed-f67e-4cb9-9d8c-46ddffb89791 · outbound

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Leveraging Diffusion Models for Stylization using Multiple Style Images Unresolved cited work

Reference 24

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Observation 8aac0caa-1d20-41e7-95b7-cbce65d4769d · outbound

This paper cites Consistent Style Transfer.

Leveraging Diffusion Models for Stylization using Multiple Style Images Consistent Style Transfer

Reference 25

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Source-reported events for the cited work

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Observation 211fc7dd-00f4-4f72-a5af-a5faa909df67 · outbound

This paper cites Few-shot image generation via cross-domain correspondence.

Leveraging Diffusion Models for Stylization using Multiple Style Images Few-shot image generation via cross-domain correspondence

Reference 26

Resolution: verified fuzzy; raw_fallback, observed 2026-08-05T19:22:23.693474Z

Source-reported events for the cited work

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Observation b1813f2b-2346-467f-acce-8c4efc02002e · outbound

This paper cites Arbitrary Style Transfer with Style-Attentional Networks.

Leveraging Diffusion Models for Stylization using Multiple Style Images Arbitrary Style Transfer with Style-Attentional Networks

Reference 27

Resolution: verified exact; local_arxiv, observed 2026-08-05T19:22:18.898029Z

Source-reported events for the cited work

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Observation bacb1574-1df2-44f3-87ed-71681e981fe4 · outbound

This paper cites Sdxl: Improving latent diffusion models for high-resolution image synthesis, 2023.

Leveraging Diffusion Models for Stylization using Multiple Style Images Sdxl: Improving latent diffusion models for high-resolution image synthesis, 2023

Reference 28

Resolution: verified fuzzy; raw_fallback, observed 2026-08-05T19:22:23.488836Z

Source-reported events for the cited work

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Observation 00d9584e-3eb1-4e7a-a91b-26f31230ee2c · outbound

This paper cites Learning Transferable Visual Models From Natural Language Supervision.

Leveraging Diffusion Models for Stylization using Multiple Style Images Learning Transferable Visual Models From Natural Language Supervision

Reference 29

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Source-reported events for the cited work

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Observation 2bb45f55-806e-45d0-9604-775ef6af99ed · outbound

This paper cites High-resolution image syn- thesis with latent diffusion models, 2022.

Leveraging Diffusion Models for Stylization using Multiple Style Images High-resolution image syn- thesis with latent diffusion models, 2022

Reference 30

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Observation 7c279839-9d86-4db4-a4de-f1533d761954 · outbound

This paper cites Dreambooth: Fine tuning text-to-image diffusion models for subject-driven generation, 2023.

Leveraging Diffusion Models for Stylization using Multiple Style Images Dreambooth: Fine tuning text-to-image diffusion models for subject-driven generation, 2023

Reference 31

Resolution: verified fuzzy; raw_fallback, observed 2026-08-05T19:22:23.167170Z

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Observation 5c859c46-f80f-4f71-a56c-02c39da3dfb9 · outbound

This paper cites Aladin: All layer adaptive instance normalization for fine- grained style similarity, 2021.

Leveraging Diffusion Models for Stylization using Multiple Style Images Aladin: All layer adaptive instance normalization for fine- grained style similarity, 2021

Reference 32

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Observation d111f5d5-6f18-4c50-946c-51a473018c8d · outbound

This paper cites Neat: Neural artistic tracing for beautiful style transfer, 2023.

Leveraging Diffusion Models for Stylization using Multiple Style Images Neat: Neural artistic tracing for beautiful style transfer, 2023

Reference 33

Resolution: verified fuzzy; raw_fallback, observed 2026-08-05T19:22:22.823907Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-11T06:34:44.6726+00:00.

Observation 3c6efbad-ae45-4653-b45c-6f8936d57467 · outbound

This paper cites Aladin-nst: Self-supervised disentangled representation learning of artistic style through neural style transfer, 2023.

Leveraging Diffusion Models for Stylization using Multiple Style Images Aladin-nst: Self-supervised disentangled representation learning of artistic style through neural style transfer, 2023

Reference 34

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Observation dd139ce2-6470-4b69-8e95-d4b12718b330 · outbound

This paper cites Diff-nst: Diffusion interleaving for deformable neural style transfer,.

Leveraging Diffusion Models for Stylization using Multiple Style Images Diff-nst: Diffusion interleaving for deformable neural style transfer,

Reference 35

Resolution: verified fuzzy; raw_fallback, observed 2026-08-05T19:22:22.406301Z

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Observation ef2f54d0-51f8-4a96-b1ec-4a4f7855c534 · outbound

This paper cites Large-scale classifica- tion of fine-art paintings: Learning the right metric on the right feature, 2015.

Leveraging Diffusion Models for Stylization using Multiple Style Images Large-scale classifica- tion of fine-art paintings: Learning the right metric on the right feature, 2015

Reference 36

Resolution: verified fuzzy; raw_fallback, observed 2026-08-05T19:22:22.213011Z

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Observation c36c2eec-5cde-4d5a-86e4-a2ce70580bdc · outbound

This paper cites SinGAN: Learning a Generative Model from a Single Natural Image.

Leveraging Diffusion Models for Stylization using Multiple Style Images SinGAN: Learning a Generative Model from a Single Natural Image

Reference 37

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Source-reported events for the cited work

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Observation 40a43ca2-ca93-474b-89e2-b457c1a11827 · outbound

This paper cites Measuring style similarity in diffusion models, 2024.

Leveraging Diffusion Models for Stylization using Multiple Style Images Measuring style similarity in diffusion models, 2024

Reference 38

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Observation ead13272-24c7-4799-863b-93630e1dd4f6 · outbound

This paper cites Instantstyle: Free lunch towards style-preserving in text-to-image generation, 2024.

Leveraging Diffusion Models for Stylization using Multiple Style Images Instantstyle: Free lunch towards style-preserving in text-to-image generation, 2024

Reference 39

Resolution: verified fuzzy; raw_fallback, observed 2026-08-05T19:22:21.812283Z

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Observation 794db54c-f68a-4f36-938b-c50e61f64c73 · outbound

This paper cites Multi-source style transfer via style disen- tanglement network.

Leveraging Diffusion Models for Stylization using Multiple Style Images Multi-source style transfer via style disen- tanglement network

Reference 40

Resolution: verified fuzzy; raw_fallback, observed 2026-08-05T19:22:21.589132Z

Source-reported events for the cited work

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Observation c59f3150-76e2-4172-be2c-1d290835e956 · outbound

This paper cites Wilber, Chen Fang, Hailin Jin, Aaron Hertzmann, John Collomosse, and Serge Belongie.

Leveraging Diffusion Models for Stylization using Multiple Style Images Wilber, Chen Fang, Hailin Jin, Aaron Hertzmann, John Collomosse, and Serge Belongie

Reference 41

Resolution: verified fuzzy; raw_fallback, observed 2026-08-05T19:22:21.335261Z

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Observation dcf263fa-62c3-4057-a77e-c8162f733f9e · outbound

This paper cites Uncovering the disentanglement capability in text- to-image diffusion models, 2022.

Leveraging Diffusion Models for Stylization using Multiple Style Images Uncovering the disentanglement capability in text- to-image diffusion models, 2022

Reference 42

Resolution: verified fuzzy; raw_fallback, observed 2026-08-05T19:22:21.074757Z

Source-reported events for the cited work

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Observation 666650fd-4aee-4f84-b38d-ff39fb53a769 · outbound

This paper cites Ip- adapter: Text compatible image prompt adapter for text-to- image diffusion models, 2023.

Leveraging Diffusion Models for Stylization using Multiple Style Images Ip- adapter: Text compatible image prompt adapter for text-to- image diffusion models, 2023

Reference 43

Resolution: verified fuzzy; raw_fallback, observed 2026-08-05T19:22:20.797927Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-11T06:34:44.6726+00:00.

Observation 78e96f98-a970-472b-8a93-cfef2a23231f · outbound

This paper cites S2wat: Image style transfer via hierarchical vision transformer using strips window attention, 2022.

Leveraging Diffusion Models for Stylization using Multiple Style Images S2wat: Image style transfer via hierarchical vision transformer using strips window attention, 2022

Reference 44

Resolution: verified fuzzy; raw_fallback, observed 2026-08-05T19:22:20.580476Z

Source-reported events for the cited work

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Observation 5ad8f2c2-8bf8-4f04-b3e8-e30e2d624ea7 · outbound

This paper cites Adding Conditional Control to Text-to-Image Diffusion Models.

Leveraging Diffusion Models for Stylization using Multiple Style Images Adding Conditional Control to Text-to-Image Diffusion Models

Reference 45

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Observation dd9949f9-7d7d-43e2-a596-57cd2c31253f · outbound

This paper cites Do- main enhanced arbitrary image style transfer via contrastive learning.

Leveraging Diffusion Models for Stylization using Multiple Style Images Do- main enhanced arbitrary image style transfer via contrastive learning

Reference 46

Resolution: verified fuzzy; raw_fallback, observed 2026-08-05T19:22:20.317198Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-11T06:34:44.6726+00:00.

Observation 3733da6f-ef20-45ff-be2f-fc63d3ef9882 · outbound

This paper cites Inversion-based style transfer with diffusion models, 2023.

Leveraging Diffusion Models for Stylization using Multiple Style Images Inversion-based style transfer with diffusion models, 2023

Reference 47

Resolution: verified fuzzy; raw_fallback, observed 2026-08-05T19:22:20.125645Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-11T06:34:44.6726+00:00.

Pith citing papers

No inbound Pith citation observations are available.