Anti-Persona: Disrupting Unauthorized Identity Binding and Recognition in Personalized Vision--Language Models

arXiv:2610.01944 · cs.CV · Submitted 2026-10-01 · Read on arXiv

cs.CV

Submitted: 2026-10-01

Updated: 2026-10-01

Code: https://github.com/iabh1shekbasu/anti-persona

Terminology

• Personalization — 37× in this paper · explained in 2 episodes
• Alignment — 9× in this paper · explained in 1 episode
• Fidelity — 9× in this paper · explained in 2 episodes
• Robustness — 8× in this paper · explained in 5 episodes
• Diffusion Model — 5× in this paper · explained in 8 episodes
• Diffusion Models — 5× in this paper · explained in 6 episodes
• Generative Model — 4× in this paper · explained in 2 episodes
• Ablation — 3× in this paper · explained in 1 episode
• Adversarial Examples — 3× in this paper · explained in 2 episodes
• CVF International Conference on Computer Vision — 3× in this paper
• Conference on Computer Vision and Pattern Recognition — 3× in this paper
• Embeddings — 3× in this paper · explained in 2 episodes
• Generative Models — 3× in this paper · explained in 2 episodes
• Adversarial Attacks — 2× in this paper · explained in 1 episode
• Benchmark — 2× in this paper · explained in 2 episodes
• Ablation Studies — 1× in this paper · explained in 1 episode
• Access Regimes — 1× in this paper · explained in 1 episode
• Cosine Similarity — 1× in this paper · explained in 3 episodes
• Generalization — 1× in this paper · explained in 13 episodes
• Instruction Tuning — 1× in this paper · explained in 2 episodes

Sources

• Online-PVLM: Advancing Personalized VLMs with Online Concept Learning
• An Image is Worth One Word: Personalizing Text-to-Image Generation using Textual Inversion
• Explaining and Harnessing Adversarial Examples
• Mist: Towards Improved Adversarial Examples for Diffusion Models
• Adversarial Example Does Good: Preventing Painting Imitation from Diffusion Models via Adversarial Examples
• Towards Deep Learning Models Resistant to Adversarial Attacks
• Personalized Large Vision-Language Models
• Raising the Cost of Malicious AI-Powered Image Editing
• Evaluating Adversarial Protections for Diffusion Personalization: A Comprehensive Study
• Targeted Attack Improves Protection against Unauthorized Diffusion Customization

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