 The first, HYPE-Time, measures visual perception under adaptive time constraints to determine the minimum length of time (e.g. , 250ms) that model output such as a generated face needs to be visible for people to distinguish it as real or fake. The second, HYPE-Infinity ,  measures human error rate on fake and real images with no time constraints, maintaining stability and drastically reducing time and cost .
<clarity>  The first, HYPE-Time, measures visual perception under adaptive time constraints to determine the minimum length of time (e.g. , 250ms) that model output such as a generated face needs to be visible for people to distinguish it as real or fake. The second, HYPE-Infinity ,  measures human error rate on fake and real images with no time constraints, maintaining stability and drastically reducing time and cost .
 The first, HYPE-Time, measures visual perception under adaptive time constraints to determine the minimum length of time (e.g. , 250ms) , measures human error rate on fake and real images with no time constraints, maintaining stability and drastically reducing time and cost .