Representation and Reference Selection in Training-Free Synthetic Image Attribution

arXiv:2607.12052 · cs.CV, cs.AI, cs.CR · Submitted 2026-07-13 · Read on arXiv

Meiling Li, Pietro Bongini, Benedetta Tondi, Mauro Barni

cs.CV, cs.AI, cs.CR

Submitted: 2026-07-13

Comments: 6 pages, 5 figures, 4 tables

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

Terminology

• Accuracy — 25× in this paper · explained in 1 episode
• Aggregation — 9× in this paper · explained in 1 episode
• Abstraction — 6× in this paper · explained in 1 episode
• Alignment — 5× in this paper · explained in 1 episode
• Semantic Alignment — 5× in this paper · explained in 3 episodes
• Embeddings — 3× in this paper · explained in 2 episodes
• Robustness — 3× in this paper · explained in 5 episodes
• Trace — 3× in this paper · explained in 2 episodes
• Benchmark — 2× in this paper · explained in 2 episodes
• Transformer — 2× in this paper · explained in 2 episodes
• alpha — 2× in this paper · explained in 1 episode
• Ablation — 1× in this paper · explained in 1 episode
• Adaptation — 1× in this paper · explained in 1 episode
• Clustering — 1× in this paper · explained in 2 episodes
• Core — 1× in this paper · explained in 2 episodes
• Cosine Similarity — 1× in this paper · explained in 3 episodes
• Fine-Tuning — 1× in this paper · explained in 5 episodes
• Instruction Tuning — 1× in this paper · explained in 2 episodes
• Model-Agnostic — 1× in this paper · explained in 2 episodes

Sources

• Who Made This? Fake Detection and Source Attribution with Diffusion Features
• Training-free Source Attribution of AI-generated Images via Resynthesis
• Learning to Disentangle GAN Fingerprint for Fake Image Attribution
• On Attribution of Deepfakes

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