Introduced on day 46
Quality-diversity trade-off
Sampling choices that make each output more typical (lower temperature, truncation, stronger guidance) usually reduce how much of the real variety the set of outputs covers.
In detail
Quality is a property of single samples (do they look realistic?); diversity or coverage is a property of the set (does it reach rare patterns?). Measuring them with separate numbers, such as precision and recall of generated samples, prevents a narrow generator from winning on one realism score. The right operating point depends on the purpose: showcase images versus training-data augmentation.