Learning Normal Diffusion Dynamics for Backdoor Defense in Text-to-Image Models

arXiv:2609.39548 · cs.CV, cs.AI, cs.CR · Submitted 2026-09-30 · Read on arXiv

cs.CV, cs.AI, cs.CR

Submitted: 2026-09-30

Updated: 2026-09-30

Terminology

• Diffusion Model — 38× in this paper · explained in 8 episodes
• Diffusion Models — 35× in this paper · explained in 6 episodes
• Generalizability — 9× in this paper · explained in 6 episodes
• Attention Entropy — 6× in this paper · explained in 2 episodes
• Consistency — 5× in this paper · explained in 3 episodes
• Ablation — 4× in this paper · explained in 1 episode
• Latent Representation — 4× in this paper · explained in 2 episodes
• Normal Diffusion Dynamics Learning — 4× in this paper
• Ablation study — 3× in this paper · explained in 1 episode
• Accuracy — 3× in this paper · explained in 1 episode
• Generative AI — 3× in this paper · explained in 2 episodes
• Latent Diffusion Model — 3× in this paper · explained in 2 episodes
• Latent Diffusion Models — 3× in this paper · explained in 2 episodes
• Transformer — 3× in this paper · explained in 2 episodes
• Cosine Similarity — 2× in this paper · explained in 3 episodes
• Fine-Tuning — 2× in this paper · explained in 5 episodes
• Regularization — 2× in this paper · explained in 3 episodes
• Unified Framework — 2× in this paper · explained in 5 episodes
• Ablation Studies — 1× in this paper · explained in 1 episode
• Adversarial Attacks — 1× in this paper · explained in 1 episode
• Adversarial Defense — 1× in this paper · explained in 1 episode
• Aggregation — 1× in this paper · explained in 1 episode
• Alignment — 1× in this paper · explained in 1 episode
• Anisotropy — 1× in this paper · explained in 3 episodes
• Bit-Flip Attacks — 1× in this paper · explained in 2 episodes
• Core — 1× in this paper · explained in 2 episodes
• Exposure Bias — 1× in this paper · explained in 2 episodes
• Generalization — 1× in this paper · explained in 13 episodes
• Generative Model — 1× in this paper · explained in 2 episodes
• Generative Modeling — 1× in this paper · explained in 3 episodes
• Generative Models — 1× in this paper · explained in 2 episodes
• Joint Attention — 1× in this paper · explained in 2 episodes
• Rectified Flow — 1× in this paper · explained in 3 episodes
• Redundancy — 1× in this paper · explained in 2 episodes
• Robustness — 1× in this paper · explained in 5 episodes
• Trace — 1× in this paper · explained in 2 episodes
• Verification — 1× in this paper · explained in 2 episodes

Sources

• Do System Prompts Leave Behavioral Fingerprints? A Large-Scale Empirical Study of Clone Detection via Output Similarity
• Bit-Flip Attacks on Vision-Language-Action Models: Action-Decoding Architecture Shapes the Vulnerability
• PathMark: Protecting Intellectual Property of Mixture-of-Expert LLMs via Path Watermarks
• BadNets: Identifying Vulnerabilities in the Machine Learning Model Supply Chain
• Dual Inversion for Text-to-Image Diffusion Models: From Both Prompt and Noise Perspectives

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