SleeperMark: Towards Robust Watermark against Fine-Tuning Text-to-image Diffusion Models | Paper Citation Record

Observation 8006f36d-74cd-4e15-a4d5-7fb4acc59bb1 · outbound

This paper cites Waves: Bench- marking the robustness of image watermarks.

SleeperMark: Towards Robust Watermark against Fine-Tuning Text-to-image Diffusion Models Waves: Bench- marking the robustness of image watermarks

Reference 1

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Observation 51227024-5ffe-4cfa-9d1f-7fd4c96f7863 · outbound

This paper cites Wasserstein generative adversarial networks.

SleeperMark: Towards Robust Watermark against Fine-Tuning Text-to-image Diffusion Models Wasserstein generative adversarial networks

Reference 2

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This paper cites DeepFloyd IF: a novel state-of- the-art open-source text-to-image model with a high degree of photorealism and language understanding.

SleeperMark: Towards Robust Watermark against Fine-Tuning Text-to-image Diffusion Models DeepFloyd IF: a novel state-of- the-art open-source text-to-image model with a high degree of photorealism and language understanding

Reference 3

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Observation 91ed3c07-272a-4d7f-992b-642e3846a0de · outbound

This paper cites eDiff-I: Text-to-Image Diffusion Models with an Ensemble of Expert Denoisers.

SleeperMark: Towards Robust Watermark against Fine-Tuning Text-to-image Diffusion Models eDiff-I: Text-to-Image Diffusion Models with an Ensemble of Expert Denoisers

Reference 4

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Observation 589a19ce-50f0-42b6-b0f2-b488861b54e2 · outbound

This paper cites Improving image generation with better captions.

SleeperMark: Towards Robust Watermark against Fine-Tuning Text-to-image Diffusion Models Improving image generation with better captions

Reference 5

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Observation d25fd948-f579-4e03-8275-b472b108602d · outbound

This paper cites Betker, G.

SleeperMark: Towards Robust Watermark against Fine-Tuning Text-to-image Diffusion Models Betker, G

Reference 6

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Observation 9bcfcedc-496a-4dd0-a828-d896d0a5376c · outbound

This paper cites A computational approach to edge detection.

SleeperMark: Towards Robust Watermark against Fine-Tuning Text-to-image Diffusion Models A computational approach to edge detection

Reference 7

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Observation 369e78b6-24ff-41ca-872b-754d03337838 · outbound

This paper cites Naruto blip captions.

SleeperMark: Towards Robust Watermark against Fine-Tuning Text-to-image Diffusion Models Naruto blip captions

Reference 8

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Observation 65b47c9c-f98d-4003-8e85-f9a521fbeb4a · outbound

This paper cites WMAdapter: Adding WaterMark Control to Latent Diffusion Models.

SleeperMark: Towards Robust Watermark against Fine-Tuning Text-to-image Diffusion Models WMAdapter: Adding WaterMark Control to Latent Diffusion Models

Reference 9

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Observation 8cfaa314-a4fd-4099-8131-b21a66ea8067 · outbound

This paper cites Insider threats to cloud computing: Directions for new research challenges.

SleeperMark: Towards Robust Watermark against Fine-Tuning Text-to-image Diffusion Models Insider threats to cloud computing: Directions for new research challenges

Reference 10

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Observation cd7bfec8-2c81-448a-8ab1-c923a010b971 · outbound

This paper cites https://civitai.com/models/22354/clearvae.

SleeperMark: Towards Robust Watermark against Fine-Tuning Text-to-image Diffusion Models https://civitai.com/models/22354/clearvae

Reference 11

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Observation 889f2883-8173-4643-82ea-e103ef6e0567 · outbound

This paper cites DiffusionShield: A Watermark for Copyright Protection against Generative Diffusion Models.

SleeperMark: Towards Robust Watermark against Fine-Tuning Text-to-image Diffusion Models DiffusionShield: A Watermark for Copyright Protection against Generative Diffusion Models

Reference 12

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Observation 752263ce-993e-4689-a148-6af900e88b27 · outbound

This paper cites PreGIP: Watermarking the Pretraining of Graph Neural Networks for Deep Intellectual Property Protection.

SleeperMark: Towards Robust Watermark against Fine-Tuning Text-to-image Diffusion Models PreGIP: Watermarking the Pretraining of Graph Neural Networks for Deep Intellectual Property Protection

Reference 13

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Observation a986dad8-796f-4336-a9b0-8986281e302f · outbound

This paper cites Diffusion models beat gans on image synthesis.

SleeperMark: Towards Robust Watermark against Fine-Tuning Text-to-image Diffusion Models Diffusion models beat gans on image synthesis

Reference 14

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Observation e9166b7c-7335-4596-bdf3-70ca00c54e14 · outbound

This paper cites Scaling recti- fied flow transformers for high-resolution image synthesis.

SleeperMark: Towards Robust Watermark against Fine-Tuning Text-to-image Diffusion Models Scaling recti- fied flow transformers for high-resolution image synthesis

Reference 15

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Observation 73b6c8c0-1ea1-4fbd-b988-da269ccc4573 · outbound

This paper cites train text to image lora.py.

SleeperMark: Towards Robust Watermark against Fine-Tuning Text-to-image Diffusion Models train text to image lora.py

Reference 16

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Observation c222f9d9-89c0-496a-9537-6551597fb0e0 · outbound

This paper cites Diffusers dreambooth example.

SleeperMark: Towards Robust Watermark against Fine-Tuning Text-to-image Diffusion Models Diffusers dreambooth example

Reference 17

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Observation 17066fad-80ae-404c-8965-d43a9834dc7c · outbound

This paper cites Wide flat minimum watermarking for robust ownership ver- ification of gans.

SleeperMark: Towards Robust Watermark against Fine-Tuning Text-to-image Diffusion Models Wide flat minimum watermarking for robust ownership ver- ification of gans

Reference 18

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Observation 208e4ecf-aa7b-46dd-b4d9-23b547e4c4fa · outbound

This paper cites AquaLoRA: Toward White-box Protection for Customized Stable Diffusion Models via Watermark LoRA.

SleeperMark: Towards Robust Watermark against Fine-Tuning Text-to-image Diffusion Models AquaLoRA: Toward White-box Protection for Customized Stable Diffusion Models via Watermark LoRA

Reference 19

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Observation 33cefc2f-66c6-4907-8005-3960a3fb6483 · outbound

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

SleeperMark: Towards Robust Watermark against Fine-Tuning Text-to-image Diffusion Models The stable signature: Rooting watermarks in latent diffusion models

Reference 20

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Observation b4d6708a-9de4-495a-82c1-044fe36e1af6 · outbound

This paper cites DreamSim: Learning New Dimensions of Human Visual Similarity using Synthetic Data.

SleeperMark: Towards Robust Watermark against Fine-Tuning Text-to-image Diffusion Models DreamSim: Learning New Dimensions of Human Visual Similarity using Synthetic Data

Reference 21

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Observation 633e587b-13d7-412a-b100-ad75a002f3c1 · outbound

This paper cites Watermarking plms on classification tasks by combining contrastive learning with weight perturbation.

SleeperMark: Towards Robust Watermark against Fine-Tuning Text-to-image Diffusion Models Watermarking plms on classification tasks by combining contrastive learning with weight perturbation

Reference 22

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Observation 73ce2db0-6c49-4800-963a-a6d7841a849e · outbound

This paper cites Vec- tor quantized diffusion model for text-to-image synthesis.

SleeperMark: Towards Robust Watermark against Fine-Tuning Text-to-image Diffusion Models Vec- tor quantized diffusion model for text-to-image synthesis

Reference 23

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Observation 1e3f3c79-52e1-4cfb-ad69-b5465dc41dcd · outbound

This paper cites Stable diffusion prompts dataset.

SleeperMark: Towards Robust Watermark against Fine-Tuning Text-to-image Diffusion Models Stable diffusion prompts dataset

Reference 24

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Observation ba14a169-6f09-4cb5-bfad-54d6aedbb9d9 · outbound

This paper cites Classifier-Free Diffusion Guidance.

SleeperMark: Towards Robust Watermark against Fine-Tuning Text-to-image Diffusion Models Classifier-Free Diffusion Guidance

Reference 25

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Observation a5ff4d7f-0fa9-49fe-8a1f-c2a6f67d1028 · outbound

This paper cites Denoising dif- fusion probabilistic models.

SleeperMark: Towards Robust Watermark against Fine-Tuning Text-to-image Diffusion Models Denoising dif- fusion probabilistic models

Reference 26

Resolution: verified fuzzy; raw_fallback, observed 2026-08-11T21:18:44.533681Z

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Observation 1169ae50-7732-46c0-a4d5-02cd0e4e4a6e · outbound

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

SleeperMark: Towards Robust Watermark against Fine-Tuning Text-to-image Diffusion Models LoRA: Low-Rank Adaptation of Large Language Models

Reference 27

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Observation 03cad6c1-5a15-4332-9af5-883c72bf5e68 · outbound

This paper cites On the Trustworthiness of Generative Foundation Models: Guideline, Assessment, and Perspective.

SleeperMark: Towards Robust Watermark against Fine-Tuning Text-to-image Diffusion Models On the Trustworthiness of Generative Foundation Models: Guideline, Assessment, and Perspective

Reference 28

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Observation 9ed198d7-47ff-40b4-958c-9c725088df2f · outbound

This paper cites Security issues in cloud com- puting and countermeasures.

SleeperMark: Towards Robust Watermark against Fine-Tuning Text-to-image Diffusion Models Security issues in cloud com- puting and countermeasures

Reference 29

Resolution: verified fuzzy; raw_fallback, observed 2026-08-11T21:18:44.504766Z

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Observation 41b43d46-7304-4e0e-bc6f-70fbad93b554 · outbound

This paper cites Elucidating the design space of diffusion-based generative models.

SleeperMark: Towards Robust Watermark against Fine-Tuning Text-to-image Diffusion Models Elucidating the design space of diffusion-based generative models

Reference 30

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Observation 6c01d489-a24f-4719-889e-0d81d56d4413 · outbound

This paper cites Wouaf: Weight modulation for user attri- bution and fingerprinting in text-to-image diffusion models.

SleeperMark: Towards Robust Watermark against Fine-Tuning Text-to-image Diffusion Models Wouaf: Weight modulation for user attri- bution and fingerprinting in text-to-image diffusion models

Reference 31

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Observation 03d93ad6-b803-4be1-83f2-099dcbd7b273 · outbound

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

SleeperMark: Towards Robust Watermark against Fine-Tuning Text-to-image Diffusion Models Multi-concept customization of text-to-image diffusion

Reference 32

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Observation df0eb3c2-ed17-4d0b-845f-b2407df2221b · outbound

This paper cites Evaluating the robustness of trigger set-based watermarks embedded in deep neural networks.IEEE Trans- actions on Dependable and Secure Computing, 20(4):3434– 3448, 2022.

SleeperMark: Towards Robust Watermark against Fine-Tuning Text-to-image Diffusion Models Evaluating the robustness of trigger set-based watermarks embedded in deep neural networks.IEEE Trans- actions on Dependable and Secure Computing, 20(4):3434– 3448, 2022

Reference 33

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Observation 200f411e-1e20-41fd-8610-3459230bcdeb · outbound

This paper cites DiffuseTrace: A Transparent and Flexible Watermarking Scheme for Latent Diffusion Model.

SleeperMark: Towards Robust Watermark against Fine-Tuning Text-to-image Diffusion Models DiffuseTrace: A Transparent and Flexible Watermarking Scheme for Latent Diffusion Model

Reference 34

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Observation 8a38f0d8-6b5e-4e5d-94eb-651262837726 · outbound

This paper cites Light the night: A multi-condition diffusion framework for unpaired low-light enhancement in autonomous driving.

SleeperMark: Towards Robust Watermark against Fine-Tuning Text-to-image Diffusion Models Light the night: A multi-condition diffusion framework for unpaired low-light enhancement in autonomous driving

Reference 35

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Observation da7ef56b-9cfa-4831-8999-2f89af0dcd34 · outbound

This paper cites Plmmark: A secure and robust black-box watermarking framework for pre-trained language models.

SleeperMark: Towards Robust Watermark against Fine-Tuning Text-to-image Diffusion Models Plmmark: A secure and robust black-box watermarking framework for pre-trained language models

Reference 36

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Observation bb50c7f7-7f31-4e3d-855c-37a979edd6c2 · outbound

This paper cites A survey of deep neural network watermarking techniques.

SleeperMark: Towards Robust Watermark against Fine-Tuning Text-to-image Diffusion Models A survey of deep neural network watermarking techniques

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Observation b541d97c-39fb-4a6f-80e0-b1afd4ae8eb3 · outbound

This paper cites Gligen: Open-set grounded text-to-image generation.

SleeperMark: Towards Robust Watermark against Fine-Tuning Text-to-image Diffusion Models Gligen: Open-set grounded text-to-image generation

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Resolution: verified fuzzy; raw_fallback, observed 2026-08-11T21:18:43.860243Z

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Observation c6cb07f0-5f32-4a47-9186-35e36ea4219b · outbound

This paper cites Hunyuan-dit: A powerful multi-resolution diffusion trans- former with fine-grained chinese understanding, 2024.

SleeperMark: Towards Robust Watermark against Fine-Tuning Text-to-image Diffusion Models Hunyuan-dit: A powerful multi-resolution diffusion trans- former with fine-grained chinese understanding, 2024

Reference 39

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Observation 5e76d652-1b12-4d88-9a3f-b7865a48346d · outbound

This paper cites Microsoft coco: Common objects in context.

SleeperMark: Towards Robust Watermark against Fine-Tuning Text-to-image Diffusion Models Microsoft coco: Common objects in context

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Observation 8d6dc5f9-265d-43c0-9c53-f96a5926ae86 · outbound

This paper cites Lazy Layers to Make Fine-Tuned Diffusion Models More Traceable.

SleeperMark: Towards Robust Watermark against Fine-Tuning Text-to-image Diffusion Models Lazy Layers to Make Fine-Tuned Diffusion Models More Traceable

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Observation 442317b1-9f86-43c7-81f1-bfd0a8da9855 · outbound

This paper cites Pseudo Numerical Methods for Diffusion Models on Manifolds.

SleeperMark: Towards Robust Watermark against Fine-Tuning Text-to-image Diffusion Models Pseudo Numerical Methods for Diffusion Models on Manifolds

Reference 42

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Observation db0dc3ce-043a-46a8-ade8-353b7de1bb10 · outbound

This paper cites Watermarking Diffusion Model.

SleeperMark: Towards Robust Watermark against Fine-Tuning Text-to-image Diffusion Models Watermarking Diffusion Model

Reference 43

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Observation e5b7be6c-57c3-43b8-90cc-6be02dd29362 · outbound

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

SleeperMark: Towards Robust Watermark against Fine-Tuning Text-to-image Diffusion Models Dpm-solver: A fast ode solver for diffusion probabilistic model sampling in around 10 steps

Reference 44

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Observation e623b735-0b4b-4f79-a34b-c68ac82b44d7 · outbound

This paper cites Countering language drift with seeded iterated learning.

SleeperMark: Towards Robust Watermark against Fine-Tuning Text-to-image Diffusion Models Countering language drift with seeded iterated learning

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Resolution: verified fuzzy; raw_fallback, observed 2026-08-11T21:18:43.706202Z

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Observation cef33bb5-6068-4875-8ad4-83e62d58c7d1 · outbound

This paper cites Understanding diffusion models: A unified per- spective, 2022.

SleeperMark: Towards Robust Watermark against Fine-Tuning Text-to-image Diffusion Models Understanding diffusion models: A unified per- spective, 2022

Reference 46

Resolution: verified fuzzy; raw_fallback, observed 2026-08-11T21:18:43.630780Z

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Observation 5c61e516-5807-4c4c-898a-ecd463114a25 · outbound

This paper cites A robustness- assured white-box watermark in neural networks.

SleeperMark: Towards Robust Watermark against Fine-Tuning Text-to-image Diffusion Models A robustness- assured white-box watermark in neural networks

Reference 47

Resolution: verified fuzzy; raw_fallback, observed 2026-08-11T21:18:43.484757Z

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Observation 8a2e9c3e-d9b4-4408-99d8-ebeb78b6f691 · outbound

This paper cites Ssl-wm: A black-box watermarking approach for encoders pre-trained by self-supervised learning, 2024.

SleeperMark: Towards Robust Watermark against Fine-Tuning Text-to-image Diffusion Models Ssl-wm: A black-box watermarking approach for encoders pre-trained by self-supervised learning, 2024

Reference 48

Resolution: verified fuzzy; raw_fallback, observed 2026-08-11T21:18:43.319108Z

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Observation b4d1c1df-d189-4fa6-9f4f-3470c324c729 · outbound

This paper cites Latent Watermark: Inject and Detect Watermarks in Latent Diffusion Space.

SleeperMark: Towards Robust Watermark against Fine-Tuning Text-to-image Diffusion Models Latent Watermark: Inject and Detect Watermarks in Latent Diffusion Space

Reference 49

Resolution: verified exact; local_arxiv, observed 2026-08-11T21:18:40.423991Z

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Observation 9be8d57a-c55c-46d3-9cef-ffcb5f0796f4 · outbound

This paper cites Midjourney home page.

SleeperMark: Towards Robust Watermark against Fine-Tuning Text-to-image Diffusion Models Midjourney home page

Reference 50

Resolution: verified fuzzy; raw_fallback, observed 2026-08-11T21:18:43.274755Z

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Observation 282d69b6-c8be-4b85-80c4-1949623c8cec · outbound

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

SleeperMark: Towards Robust Watermark against Fine-Tuning Text-to-image Diffusion Models A Watermark-Conditioned Diffusion Model for IP Protection

Reference 51

Resolution: unresolved; no resolver link, observed 2026-08-11T21:18:38.039923Z

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Observation 5cfed399-5ae6-41d9-88b9-3aee3ad07340 · outbound

This paper cites T2i-adapter: Learning adapters to dig out more controllable ability for text-to-image diffusion models.

SleeperMark: Towards Robust Watermark against Fine-Tuning Text-to-image Diffusion Models T2i-adapter: Learning adapters to dig out more controllable ability for text-to-image diffusion models

Reference 52

Resolution: verified fuzzy; raw_fallback, observed 2026-08-11T21:18:43.184185Z

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 31768643-9b2c-4660-9f61-bc68e221f5ea · outbound

This paper cites GLIDE: Towards Photorealistic Image Generation and Editing with Text-Guided Diffusion Models.

SleeperMark: Towards Robust Watermark against Fine-Tuning Text-to-image Diffusion Models GLIDE: Towards Photorealistic Image Generation and Editing with Text-Guided Diffusion Models

Reference 53

Resolution: unresolved; no resolver link, observed 2026-08-11T21:18:38.109594Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation bde14003-3f46-4bbe-b5a7-1d817b2bd8e2 · outbound

This paper cites Improved denoising diffusion probabilistic models.

SleeperMark: Towards Robust Watermark against Fine-Tuning Text-to-image Diffusion Models Improved denoising diffusion probabilistic models

Reference 54

Resolution: unresolved; no resolver link, observed 2026-08-11T21:18:38.133168Z

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Observation fcf9e44c-e249-47de-a315-4268c5c09f7c · outbound

This paper cites Protecting intellectual property of genera- tive adversarial networks from ambiguity attacks.

SleeperMark: Towards Robust Watermark against Fine-Tuning Text-to-image Diffusion Models Protecting intellectual property of genera- tive adversarial networks from ambiguity attacks

Reference 55

Resolution: verified fuzzy; raw_fallback, observed 2026-08-11T21:18:43.121072Z

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 f13d7ed0-ca01-419a-9977-1c0ae29e66c3 · outbound

This paper cites On aliased resizing and surprising subtleties in gan evaluation.

SleeperMark: Towards Robust Watermark against Fine-Tuning Text-to-image Diffusion Models On aliased resizing and surprising subtleties in gan evaluation

Reference 56

Resolution: unresolved; no resolver link, observed 2026-08-11T21:18:38.234847Z

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Observation a876e54d-985d-40c9-8a8c-e10b59c07bbf · outbound

This paper cites Intellectual Property Protection of Diffusion Models via the Watermark Diffusion Process.

SleeperMark: Towards Robust Watermark against Fine-Tuning Text-to-image Diffusion Models Intellectual Property Protection of Diffusion Models via the Watermark Diffusion Process

Reference 57

Resolution: unresolved; no resolver link, observed 2026-08-11T21:18:38.323261Z

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Observation 67e0f14b-c012-4fc4-afcd-c47920dde34a · outbound

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

SleeperMark: Towards Robust Watermark against Fine-Tuning Text-to-image Diffusion Models SDXL: Improving Latent Diffusion Models for High-Resolution Image Synthesis

Reference 58

Resolution: unresolved; no resolver link, observed 2026-08-11T21:18:38.393603Z

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Observation e2d3df57-5125-4b8d-8831-d0bb4b115ba7 · outbound

This paper cites Spire: Semantic prompt-driven image restoration.

SleeperMark: Towards Robust Watermark against Fine-Tuning Text-to-image Diffusion Models Spire: Semantic prompt-driven image restoration

Reference 59

Resolution: verified fuzzy; raw_fallback, observed 2026-08-11T21:18:42.944346Z

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 6ff0bf71-b04b-40fc-9835-3b02cc3f8cc3 · outbound

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

SleeperMark: Towards Robust Watermark against Fine-Tuning Text-to-image Diffusion Models Learning transferable visual models from natural language supervi- sion

Reference 60

Resolution: unresolved; no resolver link, observed 2026-08-11T21:18:38.453975Z

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Observation 4b7ab6d6-a377-4a08-99db-e2df2301fefc · outbound

This paper cites A dwt, dct and svd based watermarking technique to protect the image piracy.

SleeperMark: Towards Robust Watermark against Fine-Tuning Text-to-image Diffusion Models A dwt, dct and svd based watermarking technique to protect the image piracy

Reference 61

Resolution: verified exact; local_arxiv, observed 2026-08-11T21:18:40.141471Z

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 19bd03fb-a6b7-4594-aea7-a91d051bfa38 · outbound

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

SleeperMark: Towards Robust Watermark against Fine-Tuning Text-to-image Diffusion Models Hierarchical Text-Conditional Image Generation with CLIP Latents

Reference 62

Resolution: unresolved; no resolver link, observed 2026-08-11T21:18:38.508615Z

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Observation 35fd17df-6789-4eee-8750-0f16392e21a5 · outbound

This paper cites Copyright Protection in Generative AI: A Technical Perspective.

SleeperMark: Towards Robust Watermark against Fine-Tuning Text-to-image Diffusion Models Copyright Protection in Generative AI: A Technical Perspective

Reference 63

Resolution: unresolved; no resolver link, observed 2026-08-11T21:18:38.606550Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation c03b8769-0f98-4c1d-a637-488a9c197de1 · outbound

This paper cites Stable signature.

SleeperMark: Towards Robust Watermark against Fine-Tuning Text-to-image Diffusion Models Stable signature

Reference 64

Resolution: verified fuzzy; raw_fallback, observed 2026-08-11T21:18:42.803139Z

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 8353254c-fe24-4154-b0eb-e1638dc2ded6 · outbound

This paper cites LaWa: Using Latent Space for In-Generation Image Watermarking.

SleeperMark: Towards Robust Watermark against Fine-Tuning Text-to-image Diffusion Models LaWa: Using Latent Space for In-Generation Image Watermarking

Reference 65

Resolution: unresolved; no resolver link, observed 2026-08-11T21:18:38.694638Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 1b599ee1-5810-48eb-bf5f-feca22930fda · outbound

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

SleeperMark: Towards Robust Watermark against Fine-Tuning Text-to-image Diffusion Models High-resolution image synthesis with latent diffusion models

Reference 66

Resolution: unresolved; no resolver link, observed 2026-08-11T21:18:38.711767Z

Source-reported events for the cited work

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Observation 7ad1f4d0-5bd1-4142-87a2-fe355591b3fa · outbound

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

SleeperMark: Towards Robust Watermark against Fine-Tuning Text-to-image Diffusion Models Dreambooth: Fine tuning text-to-image diffusion models for subject-driven generation

Reference 67

Resolution: verified fuzzy; raw_fallback, observed 2026-08-11T21:18:42.694078Z

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 ad4a9277-efa2-4c17-8146-7b69f924a27d · outbound

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

SleeperMark: Towards Robust Watermark against Fine-Tuning Text-to-image Diffusion Models Photorealistic text-to-image diffusion models with deep language understanding

Reference 68

Resolution: unresolved; no resolver link, observed 2026-08-11T21:18:38.847549Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 48b30e34-76d5-4922-b7fe-17d92e98aeae · outbound

This paper cites Image super- resolution via iterative refinement.

SleeperMark: Towards Robust Watermark against Fine-Tuning Text-to-image Diffusion Models Image super- resolution via iterative refinement

Reference 69

Resolution: unresolved; no resolver link, observed 2026-08-11T21:18:38.888386Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 347cb4d1-e848-4488-8489-96e8bb848c7f · outbound

This paper cites https://huggingface.co/stabilityai/sd-vae-ft- mse, 2024.

SleeperMark: Towards Robust Watermark against Fine-Tuning Text-to-image Diffusion Models https://huggingface.co/stabilityai/sd-vae-ft- mse, 2024

Reference 70

Resolution: verified fuzzy; raw_fallback, observed 2026-08-11T21:18:42.549480Z

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 3cd4c5ea-71cb-44d6-89c2-3eac102185e8 · outbound

This paper cites Invisible watermark.

SleeperMark: Towards Robust Watermark against Fine-Tuning Text-to-image Diffusion Models Invisible watermark

Reference 71

Resolution: verified fuzzy; raw_fallback, observed 2026-08-11T21:18:42.348291Z

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 3f1cdd02-c81f-4972-a752-877a4b2534d1 · outbound

This paper cites Jpeg-resistant adversarial im- ages.

SleeperMark: Towards Robust Watermark against Fine-Tuning Text-to-image Diffusion Models Jpeg-resistant adversarial im- ages

Reference 72

Resolution: verified fuzzy; raw_fallback, observed 2026-08-11T21:18:42.196134Z

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 ec71a325-8a18-4d67-b3e6-a07fe2a21a31 · outbound

This paper cites Denoising Diffusion Implicit Models.

SleeperMark: Towards Robust Watermark against Fine-Tuning Text-to-image Diffusion Models Denoising Diffusion Implicit Models

Reference 73

Resolution: unresolved; no resolver link, observed 2026-08-11T21:18:38.985830Z

Source-reported events for the cited work

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Observation 2ea3be15-4f28-424a-a769-683dbc9bfc79 · outbound

This paper cites Generative modeling by esti- mating gradients of the data distribution.

SleeperMark: Towards Robust Watermark against Fine-Tuning Text-to-image Diffusion Models Generative modeling by esti- mating gradients of the data distribution

Reference 74

Resolution: unresolved; no resolver link, observed 2026-08-11T21:18:39.008813Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 673bbd10-242e-4cbf-9c11-8fa0c7f8f60e · outbound

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

SleeperMark: Towards Robust Watermark against Fine-Tuning Text-to-image Diffusion Models Score-Based Generative Modeling through Stochastic Differential Equations

Reference 75

Resolution: unresolved; no resolver link, observed 2026-08-11T21:18:39.065386Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 6e8e0a5f-d739-4491-ab80-1283a8b850ea · outbound

This paper cites Stegastamp: Invisible hyperlinks in physical photographs.

SleeperMark: Towards Robust Watermark against Fine-Tuning Text-to-image Diffusion Models Stegastamp: Invisible hyperlinks in physical photographs

Reference 76

Resolution: verified fuzzy; raw_fallback, observed 2026-08-11T21:18:42.101930Z

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 a50d3e16-21b3-444b-aa95-98003cef1c39 · outbound

This paper cites Common sense guide to mitigating insider threats.

SleeperMark: Towards Robust Watermark against Fine-Tuning Text-to-image Diffusion Models Common sense guide to mitigating insider threats

Reference 77

Resolution: verified fuzzy; raw_fallback, observed 2026-08-11T21:18:42.027051Z

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 d3b28d43-9611-4fdc-9c2f-11091efc4a31 · outbound

This paper cites Bovik, H.R.

SleeperMark: Towards Robust Watermark against Fine-Tuning Text-to-image Diffusion Models Bovik, H.R

Reference 78

Resolution: unresolved; no resolver link, observed 2026-08-11T21:18:39.154821Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 9358764a-dcfd-4a65-92eb-1a2cab0aee33 · outbound

This paper cites Malware detection in cloud comput- ing infrastructures.

SleeperMark: Towards Robust Watermark against Fine-Tuning Text-to-image Diffusion Models Malware detection in cloud comput- ing infrastructures

Reference 79

Resolution: verified fuzzy; raw_fallback, observed 2026-08-11T21:18:41.844856Z

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 bb0de50c-91a9-4afb-bbed-a9475d17dc9f · outbound

This paper cites Tree-rings watermarks: Invisible fingerprints for diffusion images.

SleeperMark: Towards Robust Watermark against Fine-Tuning Text-to-image Diffusion Models Tree-rings watermarks: Invisible fingerprints for diffusion images

Reference 80

Resolution: verified fuzzy; raw_fallback, observed 2026-08-11T21:18:41.648773Z

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 cc71bc2d-e9c9-462a-8871-d57cc3d906cb · outbound

This paper cites Flexible and secure watermarking for latent diffusion model.

SleeperMark: Towards Robust Watermark against Fine-Tuning Text-to-image Diffusion Models Flexible and secure watermarking for latent diffusion model

Reference 81

Resolution: verified fuzzy; raw_fallback, observed 2026-08-11T21:18:41.560581Z

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 cebc46bb-0c8b-4481-86a2-35fc07c2cbda · outbound

This paper cites Diffusion models: A comprehensive survey of methods and applications, 2024.

SleeperMark: Towards Robust Watermark against Fine-Tuning Text-to-image Diffusion Models Diffusion models: A comprehensive survey of methods and applications, 2024

Reference 82

Resolution: verified fuzzy; raw_fallback, observed 2026-08-11T21:18:41.506582Z

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 fa14bdd0-31d1-4bf7-a688-f978d74bfb55 · outbound

This paper cites Reco: Region-controlled text-to-image genera- tion.

SleeperMark: Towards Robust Watermark against Fine-Tuning Text-to-image Diffusion Models Reco: Region-controlled text-to-image genera- tion

Reference 83

Resolution: unresolved; no resolver link, observed 2026-08-11T21:18:39.314726Z

Source-reported events for the cited work

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Observation 2749fccb-7217-4be5-87ef-070e2873a320 · outbound

This paper cites Text-to-image diffusion models can be easily backdoored through multimodal data poisoning.

SleeperMark: Towards Robust Watermark against Fine-Tuning Text-to-image Diffusion Models Text-to-image diffusion models can be easily backdoored through multimodal data poisoning

Reference 84

Resolution: verified fuzzy; raw_fallback, observed 2026-08-11T21:18:41.402930Z

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 42a84f35-470e-4804-a31b-ef53b6736d22 · outbound

This paper cites Robust Invisible Video Watermarking with Attention.

SleeperMark: Towards Robust Watermark against Fine-Tuning Text-to-image Diffusion Models Robust Invisible Video Watermarking with Attention

Reference 85

Resolution: unresolved; no resolver link, observed 2026-08-11T21:18:39.343740Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation ff8b90d6-8994-4b2a-8395-cba576748d4d · outbound

This paper cites Adding conditional control to text-to-image diffusion models.

SleeperMark: Towards Robust Watermark against Fine-Tuning Text-to-image Diffusion Models Adding conditional control to text-to-image diffusion models

Reference 86

Resolution: verified fuzzy; raw_fallback, observed 2026-08-11T21:18:41.317783Z

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 b6ce5ec5-2d5d-45f6-aa7b-6949589edf44 · outbound

This paper cites The unreasonable effectiveness of deep features as a perceptual metric.

SleeperMark: Towards Robust Watermark against Fine-Tuning Text-to-image Diffusion Models The unreasonable effectiveness of deep features as a perceptual metric

Reference 87

Resolution: unresolved; no resolver link, observed 2026-08-11T21:18:39.376033Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 1555fa7a-488b-4647-8dd2-da743eeb09f2 · outbound

This paper cites Uni-controlnet: All-in-one control to text-to-image diffusion models.

SleeperMark: Towards Robust Watermark against Fine-Tuning Text-to-image Diffusion Models Uni-controlnet: All-in-one control to text-to-image diffusion models

Reference 88

Resolution: unresolved; no resolver link, observed 2026-08-11T21:18:39.385528Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation a2919eb9-89f7-48f3-9c96-48a500af4171 · outbound

This paper cites Unipc: A unified predictor-corrector framework for fast sampling of diffusion models.

SleeperMark: Towards Robust Watermark against Fine-Tuning Text-to-image Diffusion Models Unipc: A unified predictor-corrector framework for fast sampling of diffusion models

Reference 89

Resolution: unresolved; no resolver link, observed 2026-08-11T21:18:39.455785Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 47e8389c-81bc-4962-99ff-b409b7cd2a30 · outbound

This paper cites A Recipe for Watermarking Diffusion Models.

SleeperMark: Towards Robust Watermark against Fine-Tuning Text-to-image Diffusion Models A Recipe for Watermarking Diffusion Models

Reference 90

Resolution: unresolved; no resolver link, observed 2026-08-11T21:18:39.561284Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation c8d8f0dd-5b7b-45f5-a42e-88a42b2bc16c · outbound

This paper cites *[Z]& A dog⋯.

SleeperMark: Towards Robust Watermark against Fine-Tuning Text-to-image Diffusion Models *[Z]& A dog⋯

Reference 91

Resolution: verified fuzzy; raw_fallback, observed 2026-08-11T21:18:41.136857Z

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 b64aaaea-6e75-43bb-a504-9ccb35261a83 · outbound

This paper cites *[Z]&%#{@}Aˆ˜$.

SleeperMark: Towards Robust Watermark against Fine-Tuning Text-to-image Diffusion Models *[Z]&%#{@}Aˆ˜$

Reference 200

Resolution: verified fuzzy; raw_fallback, observed 2026-08-11T21:18:41.119527Z

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.

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