Paper Citation Record · LEDGER

IntroStyle: Training-Free Introspective Style Attribution using Diffusion Features

As of 17 August 2026, this Paper Citation Record lists 49 of 49 outbound references and 1 inbound Pith citation observation for arXiv:2412.14432.

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

pith.paper-citation-record.v1
2412.14432 v2

Coverage vector

measured 49 of 49 reference resolution

Typed states for the displayed outbound observations.

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measured 50 of 50 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-17T06:30:58.91139+00:00

measured 1 of 1 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-08-15T18:14:51.841346Z

measured 0 of 1 external citation measurements

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

Source: pith, observed 2026-08-15T18:14:55.812755Z

Reference resolution

49 of 49 outbound references displayed

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External citation measurements

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Outbound references

Observation 2d769659-d9a4-4419-8c31-f7be2fc22a1e · outbound

This paper cites Improving image generation with better captions.

IntroStyle: Training-Free Introspective Style Attribution using Diffusion Features Improving image generation with better captions

Reference 1

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Observation 2ea462f3-f4bf-4a5c-b349-c6b0de0c6ee9 · outbound

This paper cites Extracting training data from diffu- sion models.

IntroStyle: Training-Free Introspective Style Attribution using Diffusion Features Extracting training data from diffu- sion models

Reference 2

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Observation bdcfec45-02cf-42b8-af0f-5d01b5b58526 · outbound

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

IntroStyle: Training-Free Introspective Style Attribution using Diffusion Features Emerg- ing properties in self-supervised vision transformers

Reference 3

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Observation e66a7ed4-399b-413b-a2d3-f0aee965c7d8 · outbound

This paper cites Image style classification based on learnt deep correlation features.

IntroStyle: Training-Free Introspective Style Attribution using Diffusion Features Image style classification based on learnt deep correlation features

Reference 4

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Observation 33c25364-0582-4f0c-a8e6-c2802fa1a0f4 · outbound

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

IntroStyle: Training-Free Introspective Style Attribution using Diffusion Features Style injec- tion in diffusion: A training-free approach for adapting large- scale diffusion models for style transfer

Reference 5

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Observation 809561e3-711e-4ad3-bf38-561635e135da · outbound

This paper cites AI art and the problem of consent.

IntroStyle: Training-Free Introspective Style Attribution using Diffusion Features AI art and the problem of consent

Reference 6

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Observation 7e7f0c96-3bc5-4ea1-807b-c67b186787a7 · outbound

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

IntroStyle: Training-Free Introspective Style Attribution using Diffusion Features An Image is Worth One Word: Personalizing Text-to-Image Generation using Textual Inversion

Reference 7

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Observation 3f63bc4f-2a0f-422e-9760-0893368515a0 · outbound

This paper cites Im- age style transfer using convolutional neural networks.

IntroStyle: Training-Free Introspective Style Attribution using Diffusion Features Im- age style transfer using convolutional neural networks

Reference 8

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Observation 970ffd5e-02d3-4367-b36c-59b235a89538 · outbound

This paper cites Midjourney founder admits to using a ’hun- dred million’ images without consent.

IntroStyle: Training-Free Introspective Style Attribution using Diffusion Features Midjourney founder admits to using a ’hun- dred million’ images without consent

Reference 9

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Observation ea806d07-5d70-4edb-8b55-88bdbb99fb9e · outbound

This paper cites Momentum Contrast for Unsupervised Visual Representation Learning.

IntroStyle: Training-Free Introspective Style Attribution using Diffusion Features Momentum Contrast for Unsupervised Visual Representation Learning

Reference 10

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Source-reported events for the cited work

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Observation 4db55033-046c-43c6-8d21-6414f1f70414 · outbound

This paper cites What does the rise of AI mean for the future of art? The Sydney Morning Herald , 2022.

IntroStyle: Training-Free Introspective Style Attribution using Diffusion Features What does the rise of AI mean for the future of art? The Sydney Morning Herald , 2022

Reference 11

Resolution: verified fuzzy; raw_fallback, observed 2026-08-11T12:18:20.073813Z

Source-reported events for the cited work

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Observation 94840988-1595-4001-84ff-788206aa3b44 · outbound

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

IntroStyle: Training-Free Introspective Style Attribution using Diffusion Features Arbitrary style transfer in real-time with adaptive instance normalization

Reference 12

Resolution: verified fuzzy; raw_fallback, observed 2026-08-11T12:18:20.052853Z

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Observation da2481a7-e610-436b-8e18-9f75ef134d5d · outbound

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

IntroStyle: Training-Free Introspective Style Attribution using Diffusion Features A style-based generator architecture for generative adversarial networks

Reference 13

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Observation 8000b6f2-d92a-4833-b954-8b59ec7cbfb3 · outbound

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

IntroStyle: Training-Free Introspective Style Attribution using Diffusion Features Multi-concept customization of text-to-image diffusion

Reference 14

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Observation d80a6b46-69c9-46b6-9fec-9d14d7b245dc · outbound

This paper cites Greg rutkowski was removed from stable diffusion, but ai artists brought him back.

IntroStyle: Training-Free Introspective Style Attribution using Diffusion Features Greg rutkowski was removed from stable diffusion, but ai artists brought him back

Reference 15

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Observation 988b7c74-54bd-4a6c-878c-cc0f939c543d · outbound

This paper cites Cosmo: Content-style modulation for image retrieval with text feed- back.

IntroStyle: Training-Free Introspective Style Attribution using Diffusion Features Cosmo: Content-style modulation for image retrieval with text feed- back

Reference 16

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Source-reported events for the cited work

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Observation c02b2436-4819-4424-b3b6-cf66aa2f8b6d · outbound

This paper cites Parrot captions teach clip to spot text.

IntroStyle: Training-Free Introspective Style Attribution using Diffusion Features Parrot captions teach clip to spot text

Reference 17

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Source-reported events for the cited work

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Observation 2434087e-2929-4013-98cd-d47316ea2fb2 · outbound

This paper cites Stgan: A unified selec- tive transfer network for arbitrary image attribute editing.

IntroStyle: Training-Free Introspective Style Attribution using Diffusion Features Stgan: A unified selec- tive transfer network for arbitrary image attribute editing

Reference 18

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Source-reported events for the cited work

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Observation f52f2016-a7d2-4ca9-a8e4-6d37060e61a4 · outbound

This paper cites Deep photo style transfer.

IntroStyle: Training-Free Introspective Style Attribution using Diffusion Features Deep photo style transfer

Reference 19

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Observation 1a96e18f-08f0-4557-aba5-2d01165f816c · outbound

This paper cites Null-text inversion for editing real im- ages using guided diffusion models.

IntroStyle: Training-Free Introspective Style Attribution using Diffusion Features Null-text inversion for editing real im- ages using guided diffusion models

Reference 20

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Observation 0485f4b0-3a23-48d0-b788-4b6aad96c34a · outbound

This paper cites Diffusion Models Beat GANs on Image Classification.

IntroStyle: Training-Free Introspective Style Attribution using Diffusion Features Diffusion Models Beat GANs on Image Classification

Reference 21

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Observation d9d5a91e-7610-4810-a8c3-bb8d762219d1 · outbound

This paper cites Do text-free diffusion models learn discriminative visual representations? In European Conference on Com- puter Vision, pages 253–272.

IntroStyle: Training-Free Introspective Style Attribution using Diffusion Features Do text-free diffusion models learn discriminative visual representations? In European Conference on Com- puter Vision, pages 253–272

Reference 22

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Observation 75390e3e-9bcf-4bce-bed7-f9e8c07fce68 · outbound

This paper cites Chatgpt, 2024.

IntroStyle: Training-Free Introspective Style Attribution using Diffusion Features Chatgpt, 2024

Reference 23

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Observation f4445130-3a01-4842-a772-a1d38397b574 · outbound

This paper cites Moment matching for multi-source domain adaptation.

IntroStyle: Training-Free Introspective Style Attribution using Diffusion Features Moment matching for multi-source domain adaptation

Reference 24

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Source-reported events for the cited work

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Observation 6d8a70cd-eb92-425a-816d-6ed6d52df03b · outbound

This paper cites Concept arithmetics for circumventing concept inhibition in diffusion models.

IntroStyle: Training-Free Introspective Style Attribution using Diffusion Features Concept arithmetics for circumventing concept inhibition in diffusion models

Reference 25

Resolution: verified fuzzy; raw_fallback, observed 2026-08-11T12:18:19.838450Z

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Observation 1139f215-ee2c-4a6a-97da-e7134658e1e0 · outbound

This paper cites A self-supervised descriptor for image copy detection.

IntroStyle: Training-Free Introspective Style Attribution using Diffusion Features A self-supervised descriptor for image copy detection

Reference 26

Resolution: verified fuzzy; raw_fallback, observed 2026-08-11T12:18:19.820517Z

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Observation f2a3f041-7e74-4e8d-b44c-05475161d28d · outbound

This paper cites Learning transferable visual models from natural language supervi- 9 sion.

IntroStyle: Training-Free Introspective Style Attribution using Diffusion Features Learning transferable visual models from natural language supervi- 9 sion

Reference 27

Resolution: verified fuzzy; raw_fallback, observed 2026-08-11T12:18:19.802598Z

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Observation 09a29250-1e37-46a1-8ab3-6ba5535a6fe1 · outbound

This paper cites Hierarchical Text-Conditional Image Generation with CLIP Latents.

IntroStyle: Training-Free Introspective Style Attribution using Diffusion Features Hierarchical Text-Conditional Image Generation with CLIP Latents

Reference 28

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Observation 7b62e0f5-6bc2-4d8d-9577-c6589ad9ff2d · outbound

This paper cites Generative ad- versarial text to image synthesis.

IntroStyle: Training-Free Introspective Style Attribution using Diffusion Features Generative ad- versarial text to image synthesis

Reference 29

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Observation 2197eec3-43cf-4dc5-bd29-9c363f358a3a · outbound

This paper cites Ai-created images lose US copyrights in test of new technology.

IntroStyle: Training-Free Introspective Style Attribution using Diffusion Features Ai-created images lose US copyrights in test of new technology

Reference 30

Resolution: verified fuzzy; raw_fallback, observed 2026-08-11T12:18:19.762275Z

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Observation b3f42454-47b3-4b64-9402-bee1f19813db · outbound

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

IntroStyle: Training-Free Introspective Style Attribution using Diffusion Features High-resolution image synthesis with latent diffusion models

Reference 31

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Observation 6e2cec2a-73e6-4788-a81d-50670ae758de · outbound

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

IntroStyle: Training-Free Introspective Style Attribution using Diffusion Features Aladin: All layer adaptive instance normalization for fine- grained style similarity

Reference 32

Resolution: verified fuzzy; raw_fallback, observed 2026-08-11T12:18:19.732135Z

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Observation fb185bd2-084d-4f4d-a2ed-56bd25b251a2 · outbound

This paper cites Photorealistic text-to-image diffusion models with deep language understanding.

IntroStyle: Training-Free Introspective Style Attribution using Diffusion Features Photorealistic text-to-image diffusion models with deep language understanding

Reference 33

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Observation 2e7904b7-5268-4527-820e-3d4111b0df14 · outbound

This paper cites Large-scale Classification of Fine-Art Paintings: Learning The Right Metric on The Right Feature.

IntroStyle: Training-Free Introspective Style Attribution using Diffusion Features Large-scale Classification of Fine-Art Paintings: Learning The Right Metric on The Right Feature

Reference 34

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Observation ad6bf6ba-a700-4fc7-9872-892abbf3d4c7 · outbound

This paper cites Laion-5b: An open large-scale dataset for training next generation image-text models.

IntroStyle: Training-Free Introspective Style Attribution using Diffusion Features Laion-5b: An open large-scale dataset for training next generation image-text models

Reference 35

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Observation d6cb8bf8-7820-4fa4-8f32-12914aaaefe4 · outbound

This paper cites Glaze: Protecting artists from style mimicry by {Text-to-Image} models.

IntroStyle: Training-Free Introspective Style Attribution using Diffusion Features Glaze: Protecting artists from style mimicry by {Text-to-Image} models

Reference 36

Resolution: verified fuzzy; raw_fallback, observed 2026-08-11T12:18:19.682590Z

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Observation 4a8cec15-d57f-4f82-b242-6a660c0e7659 · outbound

This paper cites Alchemist: Parametric control of material proper- ties with diffusion models.

IntroStyle: Training-Free Introspective Style Attribution using Diffusion Features Alchemist: Parametric control of material proper- ties with diffusion models

Reference 37

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Observation 5b3bdce5-169a-4460-a797-44bbc2f6dc16 · outbound

This paper cites Investigating style similarity in diffusion models.

IntroStyle: Training-Free Introspective Style Attribution using Diffusion Features Investigating style similarity in diffusion models

Reference 38

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Observation 8cbff3d2-c808-46b3-8f73-f3d6c9e23f14 · outbound

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

IntroStyle: Training-Free Introspective Style Attribution using Diffusion Features Score-Based Generative Modeling through Stochastic Differential Equations

Reference 39

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This paper cites Emergent correspondence from image diffusion.

IntroStyle: Training-Free Introspective Style Attribution using Diffusion Features Emergent correspondence from image diffusion

Reference 40

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Observation d31741da-e298-452c-8e5c-f9ef855c48da · outbound

This paper cites Diffuse attend and segment: Un- supervised zero-shot segmentation using stable diffusion.

IntroStyle: Training-Free Introspective Style Attribution using Diffusion Features Diffuse attend and segment: Un- supervised zero-shot segmentation using stable diffusion

Reference 41

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Observation a65401d3-cb2b-449b-854b-9759649bfc1d · outbound

This paper cites P+: Extended textual conditioning in text-to- image generation.

IntroStyle: Training-Free Introspective Style Attribution using Diffusion Features P+: Extended textual conditioning in text-to- image generation

Reference 42

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Observation 0798c1c8-61ba-4ac0-8d3c-064df91340b8 · outbound

This paper cites Evaluating data attribution for text-to-image models.

IntroStyle: Training-Free Introspective Style Attribution using Diffusion Features Evaluating data attribution for text-to-image models

Reference 43

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Observation e24f3b83-5d18-48ef-8fdb-3e99d9dcbd77 · outbound

This paper cites Data Attribution for Text-to-Image Models by Unlearning Synthesized Images.

IntroStyle: Training-Free Introspective Style Attribution using Diffusion Features Data Attribution for Text-to-Image Models by Unlearning Synthesized Images

Reference 44

Resolution: verified exact; local_arxiv, observed 2026-08-11T12:18:19.235940Z

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Observation c777f176-5a97-4494-a268-0521a5024d43 · outbound

This paper cites Denoising diffusion autoencoders are unified self-supervised learners.

IntroStyle: Training-Free Introspective Style Attribution using Diffusion Features Denoising diffusion autoencoders are unified self-supervised learners

Reference 45

Resolution: verified fuzzy; raw_fallback, observed 2026-08-11T12:18:19.551171Z

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Observation 186476a8-e45f-485b-a63b-01b8878e65b4 · outbound

This paper cites Representation Alignment for Generation: Training Diffusion Transformers Is Easier Than You Think.

IntroStyle: Training-Free Introspective Style Attribution using Diffusion Features Representation Alignment for Generation: Training Diffusion Transformers Is Easier Than You Think

Reference 46

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This paper cites Stack- gan: Text to photo-realistic image synthesis with stacked generative adversarial networks.

IntroStyle: Training-Free Introspective Style Attribution using Diffusion Features Stack- gan: Text to photo-realistic image synthesis with stacked generative adversarial networks

Reference 47

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Source-reported events for the cited work

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Observation 0d4de6f3-d0ed-45f8-a391-abbe3d586516 · outbound

This paper cites Style transfer via image component analysis.

IntroStyle: Training-Free Introspective Style Attribution using Diffusion Features Style transfer via image component analysis

Reference 48

Resolution: verified fuzzy; raw_fallback, observed 2026-08-11T12:18:19.521025Z

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Observation fbf27259-770a-4b08-9fb2-c9a7908ee556 · outbound

This paper cites style” prompt and used 2 of their paintings to generate “semantic.

IntroStyle: Training-Free Introspective Style Attribution using Diffusion Features style” prompt and used 2 of their paintings to generate “semantic

Reference 49

Resolution: verified fuzzy; raw_fallback, observed 2026-08-11T12:18:19.502426Z

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Pith citing papers

Observation badc0ae5-e040-4f88-9ce6-405c87a535fa · inbound

Identifying Prompted Artist Names from Generated Images cites this paper.

Identifying Prompted Artist Names from Generated Images IntroStyle: Training-Free Introspective Style Attribution using Diffusion Features

Reference 38

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Source-reported events for the cited work

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