Paper Citation Record · LEDGER

Fingerprinting Text-to-Image Diffusion Models via Collapsed Generation

As of 21 August 2026, this Paper Citation Record lists 47 of 47 outbound references and 0 inbound Pith citation observations for arXiv:2608.11732.

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

pith.paper-citation-record.v1
2608.11732 v1

Coverage vector

measured 47 of 47 reference resolution

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Pith citing papers itemized under the disclosed page cap.

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Reference resolution

47 of 47 outbound references displayed

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External citation measurements

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Outbound references

Observation 495276f6-04c6-4c47-b336-261a6639b6e9 · outbound

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

Fingerprinting Text-to-Image Diffusion Models via Collapsed Generation High- resolution image synthesis with latent diffusion models,

Reference 1

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This paper cites Stable diffusion v2.1 and dreamstudio updates,.

Fingerprinting Text-to-Image Diffusion Models via Collapsed Generation Stable diffusion v2.1 and dreamstudio updates,

Reference 2

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Observation 632cff3a-1384-4815-ab36-eb589d5bddb1 · outbound

This paper cites Decidiffusion 1.0,.

Fingerprinting Text-to-Image Diffusion Models via Collapsed Generation Decidiffusion 1.0,

Reference 3

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Observation c84bf545-57f2-45f7-994e-3f631746be2c · outbound

This paper cites Hunyuan-DiT: A Powerful Multi-Resolution Diffusion Transformer with Fine-Grained Chinese Understanding.

Fingerprinting Text-to-Image Diffusion Models via Collapsed Generation Hunyuan-DiT: A Powerful Multi-Resolution Diffusion Transformer with Fine-Grained Chinese Understanding

Reference 4

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This paper cites Pixart-$\alpha$: Fast training of diffusion transformer for photorealistic text-to-image synthesis,.

Fingerprinting Text-to-Image Diffusion Models via Collapsed Generation Pixart-$\alpha$: Fast training of diffusion transformer for photorealistic text-to-image synthesis,

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Observation d452d13e-99bb-474b-a967-e2682ea3bdfc · outbound

This paper cites A comprehensive defense framework against model extraction attacks,.

Fingerprinting Text-to-Image Diffusion Models via Collapsed Generation A comprehensive defense framework against model extraction attacks,

Reference 6

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Observation 0b894018-6d14-4574-b23c-f6f3c54d2a09 · outbound

This paper cites Megex: Data-free model extrac- tion attack against gradient-based explainable ai,.

Fingerprinting Text-to-Image Diffusion Models via Collapsed Generation Megex: Data-free model extrac- tion attack against gradient-based explainable ai,

Reference 7

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Observation 0c1f15a4-ec02-4c2a-96ff-2e1d5af1867f · outbound

This paper cites A Recipe for Watermarking Diffusion Models.

Fingerprinting Text-to-Image Diffusion Models via Collapsed Generation A Recipe for Watermarking Diffusion Models

Reference 8

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Observation 34c7cd81-4183-4a7c-8522-6b9391f21c6a · outbound

This paper cites The stable signature: Rooting watermarks in latent diffusion models,.

Fingerprinting Text-to-Image Diffusion Models via Collapsed Generation The stable signature: Rooting watermarks in latent diffusion models,

Reference 9

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Observation 3f36070e-fcd7-4869-8262-a4c2e1d3518b · outbound

This paper cites Watermarking Diffusion Model.

Fingerprinting Text-to-Image Diffusion Models via Collapsed Generation Watermarking Diffusion Model

Reference 10

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Observation 200a1b8b-7835-4eef-91bc-d58d38e0dfcc · outbound

This paper cites Huref: Human-readable fingerprint for large language models,.

Fingerprinting Text-to-Image Diffusion Models via Collapsed Generation Huref: Human-readable fingerprint for large language models,

Reference 11

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Observation 760474cb-22e6-471e-aa05-1da93f472926 · outbound

This paper cites One Prompt to Verify Your Models: Black-Box Text-to-Image Models Verification via Non-Transferable Adversarial Attacks.

Fingerprinting Text-to-Image Diffusion Models via Collapsed Generation One Prompt to Verify Your Models: Black-Box Text-to-Image Models Verification via Non-Transferable Adversarial Attacks

Reference 12

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Observation 7d0f59b2-813d-4bbf-9ddb-51d259e5d0ca · outbound

This paper cites Fingerprinting Denoising Diffusion Probabilistic Models,.

Fingerprinting Text-to-Image Diffusion Models via Collapsed Generation Fingerprinting Denoising Diffusion Probabilistic Models,

Reference 13

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Observation 89a364a2-6a47-4da7-8868-ec8a2b542d30 · outbound

This paper cites Diffip: Representation fingerprints for robust ip protection of diffusion models,.

Fingerprinting Text-to-Image Diffusion Models via Collapsed Generation Diffip: Representation fingerprints for robust ip protection of diffusion models,

Reference 14

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Observation b385ccc4-b11f-4886-8d3a-dace1fb6d808 · outbound

This paper cites Extracting training data from diffusion models,.

Fingerprinting Text-to-Image Diffusion Models via Collapsed Generation Extracting training data from diffusion models,

Reference 15

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Observation f7424c73-7793-4b1b-b15f-317774c07c43 · outbound

This paper cites Finding nemo: Localizing neurons responsible for memorization in diffusion models,.

Fingerprinting Text-to-Image Diffusion Models via Collapsed Generation Finding nemo: Localizing neurons responsible for memorization in diffusion models,

Reference 16

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Observation ba4e907c-feb3-488e-b237-62c928a6c410 · outbound

This paper cites Understanding and Mitigating Copying in Diffusion Models,.

Fingerprinting Text-to-Image Diffusion Models via Collapsed Generation Understanding and Mitigating Copying in Diffusion Models,

Reference 17

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Observation 5185654a-686b-4393-8de9-43d16ab18451 · outbound

This paper cites Detecting, Explaining, and Mit- igating Memorization in Diffusion Models,.

Fingerprinting Text-to-Image Diffusion Models via Collapsed Generation Detecting, Explaining, and Mit- igating Memorization in Diffusion Models,

Reference 18

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Observation 89e583df-3479-4dfd-acd7-6bd2d41b252f · outbound

This paper cites Embedding watermarks into deep neural networks,.

Fingerprinting Text-to-Image Diffusion Models via Collapsed Generation Embedding watermarks into deep neural networks,

Reference 19

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This paper cites Turning your weakness into a strength: Watermarking deep neural networks by backdooring,.

Fingerprinting Text-to-Image Diffusion Models via Collapsed Generation Turning your weakness into a strength: Watermarking deep neural networks by backdooring,

Reference 20

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Observation 814a6ccc-4707-459a-a2ba-8af210b0329e · outbound

This paper cites Deepsigns: A generic watermarking framework for ip protection of deep learning models,.

Fingerprinting Text-to-Image Diffusion Models via Collapsed Generation Deepsigns: A generic watermarking framework for ip protection of deep learning models,

Reference 21

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Observation 15e77288-9f75-47fc-a2d0-fb78901df95b · outbound

This paper cites Deep Neural Network Fingerprinting by Conferrable Adversarial Examples.

Fingerprinting Text-to-Image Diffusion Models via Collapsed Generation Deep Neural Network Fingerprinting by Conferrable Adversarial Examples

Reference 22

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This paper cites Ipguard: Protecting intellectual property of deep neural networks via fingerprinting the classification boundary,.

Fingerprinting Text-to-Image Diffusion Models via Collapsed Generation Ipguard: Protecting intellectual property of deep neural networks via fingerprinting the classification boundary,

Reference 23

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Observation 789e8088-38dd-4a4e-8fd4-1e72a58b1871 · outbound

This paper cites A dnn fingerprint for non- repudiable model ownership identification and piracy detection,.

Fingerprinting Text-to-Image Diffusion Models via Collapsed Generation A dnn fingerprint for non- repudiable model ownership identification and piracy detection,

Reference 24

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Observation b674e45e-aaaa-4c3a-81a9-5f46833822a2 · outbound

This paper cites A Watermark-Conditioned Diffusion Model for IP Protection.

Fingerprinting Text-to-Image Diffusion Models via Collapsed Generation A Watermark-Conditioned Diffusion Model for IP Protection

Reference 25

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Observation 67743ddc-3351-4d80-9f37-26cdfe4fd5f7 · outbound

This paper cites SleeperMark: Towards Robust Watermark against Fine-Tuning Text-to-image Diffusion Models.

Fingerprinting Text-to-Image Diffusion Models via Collapsed Generation SleeperMark: Towards Robust Watermark against Fine-Tuning Text-to-image Diffusion Models

Reference 26

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Observation 2d426600-2b23-4b40-96ae-1d57cdb29281 · outbound

This paper cites Diffusion Art or Digital Forgery? Investigating Data Replication in Diffusion Models,.

Fingerprinting Text-to-Image Diffusion Models via Collapsed Generation Diffusion Art or Digital Forgery? Investigating Data Replication in Diffusion Models,

Reference 27

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Observation fb05d9af-66ad-4624-94f5-bcf443be4be2 · outbound

This paper cites A Reproducible Extraction of Training Images from Diffusion Models.

Fingerprinting Text-to-Image Diffusion Models via Collapsed Generation A Reproducible Extraction of Training Images from Diffusion Models

Reference 28

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Observation a46d3251-015f-4304-9308-cacc285ad743 · outbound

This paper cites Understanding and Mitigating Memo- rization in Generative Models via Sharpness of Probability Landscapes,.

Fingerprinting Text-to-Image Diffusion Models via Collapsed Generation Understanding and Mitigating Memo- rization in Generative Models via Sharpness of Probability Landscapes,

Reference 29

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Observation f7d1ddcd-377a-4a3f-9a70-4737a0e9e10c · outbound

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Fingerprinting Text-to-Image Diffusion Models via Collapsed Generation A geometric framework for understanding memorization in generative models,

Reference 30

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This paper cites Memo- rization is localized within a small subspace in diffusion models,.

Fingerprinting Text-to-Image Diffusion Models via Collapsed Generation Memo- rization is localized within a small subspace in diffusion models,

Reference 31

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Observation e29b50ef-d310-4c52-ab37-d45a011403e6 · outbound

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

Fingerprinting Text-to-Image Diffusion Models via Collapsed Generation A self- supervised descriptor for image copy detection,

Reference 32

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Observation 1371fcc8-9ba8-44da-bc28-3a7597d1d98a · outbound

This paper cites Denoising Diffusion Probabilistic Models.

Fingerprinting Text-to-Image Diffusion Models via Collapsed Generation Denoising Diffusion Probabilistic Models

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Fingerprinting Text-to-Image Diffusion Models via Collapsed Generation On the convergence and mode collapse of gan,

Reference 34

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Fingerprinting Text-to-Image Diffusion Models via Collapsed Generation Training diffusion models towards diverse image generation with reinforcement learning,

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Fingerprinting Text-to-Image Diffusion Models via Collapsed Generation Content- based unrestricted adversarial attack,

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Fingerprinting Text-to-Image Diffusion Models via Collapsed Generation SD-NAE: Generating Natural Adversarial Examples with Stable Diffusion

Reference 37

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This paper cites Membership inference on text-to-image diffusion models via conditional likelihood discrepancy,.

Fingerprinting Text-to-Image Diffusion Models via Collapsed Generation Membership inference on text-to-image diffusion models via conditional likelihood discrepancy,

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This paper cites Why diffusion models don’t memorize: The role of implicit dynamical regularization in training,.

Fingerprinting Text-to-Image Diffusion Models via Collapsed Generation Why diffusion models don’t memorize: The role of implicit dynamical regularization in training,

Reference 39

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Fingerprinting Text-to-Image Diffusion Models via Collapsed Generation Scaling rectified flow transformers for high-resolution image synthesis,

Reference 40

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Fingerprinting Text-to-Image Diffusion Models via Collapsed Generation Hugging Face – The AI community building the future

Reference 41

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Fingerprinting Text-to-Image Diffusion Models via Collapsed Generation Deliberate v4,

Reference 42

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Fingerprinting Text-to-Image Diffusion Models via Collapsed Generation Realistic vision v2.0,

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Fingerprinting Text-to-Image Diffusion Models via Collapsed Generation Mistral 7B

Reference 44

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Fingerprinting Text-to-Image Diffusion Models via Collapsed Generation Hard prompts made easy: Gradient-based discrete optimization for prompt tuning and discovery,

Reference 45

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This paper cites Universal and Transferable Adversarial Attacks on Aligned Language Models.

Fingerprinting Text-to-Image Diffusion Models via Collapsed Generation Universal and Transferable Adversarial Attacks on Aligned Language Models

Reference 46

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This paper cites DeepSigns: A Generic Watermarking Framework for IP Protection of Deep Learning Models.

Fingerprinting Text-to-Image Diffusion Models via Collapsed Generation DeepSigns: A Generic Watermarking Framework for IP Protection of Deep Learning Models

Reference 2018

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Pith citing papers

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