What FID Hides: Detecting, Ranking, and Diagnosing Deviations in Generative Evaluation

arXiv:2608.24881 · stat.ML, cs.LG · Submitted 2026-08-25 · Read on arXiv

stat.ML, cs.LG

Submitted: 2026-08-25

Updated: 2026-08-25

Terminology

• Calibration — 17× in this paper · explained in 7 episodes
• Generative Model — 14× in this paper · explained in 2 episodes
• Generative Models — 13× in this paper · explained in 2 episodes
• Accuracy — 12× in this paper · explained in 1 episode
• Fidelity — 9× in this paper · explained in 2 episodes
• Aggregation — 8× in this paper · explained in 1 episode
• Embeddings — 8× in this paper · explained in 2 episodes
• Transformer — 7× in this paper · explained in 2 episodes
• Conference on Computer Vision and Pattern Recognition — 5× in this paper
• Robustness — 5× in this paper · explained in 5 episodes
• Trace — 4× in this paper · explained in 2 episodes
• International Conference on Learning Representations — 3× in this paper
• Ablation — 2× in this paper · explained in 1 episode
• Diffusion Model — 2× in this paper · explained in 8 episodes
• Homogeneity — 2× in this paper · explained in 2 episodes
• International Conference on Computer Vision — 2× in this paper
• Z-resolved Integrated Diagnostic — 2× in this paper
• Diffusion Models — 1× in this paper · explained in 6 episodes
• Graph Construction — 1× in this paper · explained in 3 episodes
• In European Conference on Computer Vision — 1× in this paper
• Mode Collapse — 1× in this paper · explained in 2 episodes
• Nash Equilibrium — 1× in this paper · explained in 2 episodes
• Sample Efficiency — 1× in this paper · explained in 4 episodes
• Wasserstein Distance — 1× in this paper · explained in 4 episodes

Sources

• MIND: Monge Inception Distance for Generative Models Evaluation
• Classifier-Free Diffusion Guidance
• Compound Frechet Inception Distance for Quality Assessment of GAN Created Images
• Assessing the Distributional Fidelity of Synthetic Chest X-rays using the Embedded Characteristic Score

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