arXiv AI August 13, 2026 By Yuanmin Huang, Chen Chen, Geng Hong, Xiaoyu You, Hui Xue, Zhenxing Qian, Mi Zhang, Min Yang

Fingerprinting Text-to-Image Diffusion Models via Collapsed Generation

arXiv:2608. 11732v1 Announce Type: cross Abstract: Proprietary text-to-image diffusion models are increasingly distributed as hosted services and downloadable checkpoints, making their intellectual property (IP) protection an increasingly critical concern when model leakage, copying, or unauthorized fine-tuning is disputed.

Machine-generated by The Flow from the publisher's headline and feed description — not written or checked by a human. The full article lives at arXiv AI.

arXiv Computer Vision

Sep 1

Membership is Ownership: A Robust Ownership Verification Framework for Diffusion Models

arXiv:2608.28929v1 Announce Type: cross Abstract: Large-scale diffusion models have fueled numerous profitable downstream applications for AI-related businesses, including visual editing and content...

By Feng Jiang, Zuobin Xiong, An Huang, Zhipeng Cai, Yingshu Li

diffusion fine-tuning safety

arXiv AI

Jun 12

Reconstructing Template-Memorized Images from Natural Prompts

arXiv:2507. 07947v4 Announce Type: replace-cross Abstract: Recent advances in generative models, such as diffusion models, have raised concerns related to privacy, copyright infringement, and data stewardship.

By Sol Yarkoni, Mahmood Sharif, Roi Livni

diffusion safety

arXiv Machine Learning

Aug 14

Noise as a Probe: Membership Inference Attacks on Diffusion Models Leveraging Initial Noise

arXiv:2601. 21628v2 Announce Type: replace-cross Abstract: Diffusion models have achieved remarkable progress in image generation, but their increasing deployment raises serious concerns about privacy and copyright.

By Puwei Lian, Yujun Cai, Songze Li, Bingkun Bao

diffusion fine-tuning safety

arXiv AI

Sep 23

From Bits to Beliefs: Recoverable Semantic Fingerprints for Black-Box Verification of Large Language Models

arXiv:2609.24084v1 Announce Type: cross Abstract: Open-weight large language models (LLMs) can be copied, modified, and redeployed behind black-box APIs, making post-release ownership verification di...

By Jiaxin Hong, Yuxin Peng, Hongyao Yu, Hao Fang, Shuoyang Sun, Bin Chen

llms fine-tuning efficiency

arXiv AI

Jun 12

Efficient, Robust, and Anti-Collusion Fingerprinting of Image Diffusion Models

arXiv:2606. 12977v1 Announce Type: cross Abstract: Model fingerprinting, embedding user-specific identifiers (fingerprints) into generated outputs, has recently emerged as a popular solution to protect the intellectual property rights (IPR) of generative text-to-image (T2I) models and prevent unauthorized redistribution.

By Jianwei Fei, Yunshu Dai, Zhihua Xia, Xiaochun Cao, Jiantao Zhou, Alessandro Piva, Benedetta Tondi

rag diffusion

arXiv AI

Jul 16

PersGuard: Preventing Malicious Personalization in Text-to-Image Diffusion Models via Model Backdoors

arXiv:2502. 16167v2 Announce Type: replace-cross Abstract: Diffusion models (DMs) have advanced text-to-image (T2I) synthesis, yet their personalization capabilities raise serious privacy and copyright concerns.

By Xinwei Liu, Xiaojun Jia, Yuan Xun, Hua Zhang, Xiaochun Cao

diffusion fine-tuning safety

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Membership is Ownership: A Robust Ownership Verification Framework for Diffusion Models

Reconstructing Template-Memorized Images from Natural Prompts

Noise as a Probe: Membership Inference Attacks on Diffusion Models Leveraging Initial Noise

From Bits to Beliefs: Recoverable Semantic Fingerprints for Black-Box Verification of Large Language Models

Efficient, Robust, and Anti-Collusion Fingerprinting of Image Diffusion Models

PersGuard: Preventing Malicious Personalization in Text-to-Image Diffusion Models via Model Backdoors