Leveraging Arbitrary Data Sources for AI-Generated Image Detection Without Sacrificing Generalization

arXiv:2603.00717 · cs.CV · Submitted 2026-02-28 · Read on arXiv

cs.CV

Submitted: 2026-02-28

Updated: 2026-10-12

Comments: Accepted to ACM MM 2026

License: http://arxiv.org/licenses/nonexclusive-distrib/1.0/

Terminology

Generalization — 37× in this paper · explained in 13 episodes
Generative Model — 18× in this paper · explained in 2 episodes
Generative Models — 16× in this paper · explained in 2 episodes
Diffusion Model — 14× in this paper · explained in 8 episodes
Consistency — 13× in this paper · explained in 3 episodes
Diffusion Models — 12× in this paper · explained in 6 episodes
Accuracy — 8× in this paper · explained in 1 episode
Robustness — 7× in this paper · explained in 5 episodes
Attribution Consistency Module — 4× in this paper
Fidelity — 4× in this paper · explained in 2 episodes
Latent Space — 4× in this paper · explained in 7 episodes
Trace — 4× in this paper · explained in 2 episodes
Adaptability — 2× in this paper · explained in 1 episode
Reconstruction Error — 2× in this paper · explained in 2 episodes
Transformer — 2× in this paper · explained in 2 episodes
Adam — 1× in this paper · explained in 2 episodes
Adversarial Training — 1× in this paper · explained in 1 episode
Benchmark — 1× in this paper · explained in 2 episodes
Core — 1× in this paper · explained in 2 episodes
Domain Shift — 1× in this paper · explained in 4 episodes
Embeddings — 1× in this paper · explained in 2 episodes
F1 Score — 1× in this paper · explained in 3 episodes
Fine-Tuning — 1× in this paper · explained in 5 episodes
Generative Adversarial Networks (GANs) — 1× in this paper · explained in 3 episodes
Latent Diffusion Model — 1× in this paper · explained in 2 episodes
Latent Diffusion Models — 1× in this paper · explained in 2 episodes
Mode Collapse — 1× in this paper · explained in 2 episodes
Model-Agnostic — 1× in this paper · explained in 2 episodes

Terminology

Sources

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