← All parts of this equation

Equation 4 · Part 8 · The Benchmarks That Don't Need the Image

subtraction

MG=Sv−Swv,ML=max⁡(0, Swv−St)MG = S_v - S_{wv}, \qquad ML = \max(0,\ S_{wv} - S_t)
subtraction

What this part means

Subtract the following term or group from the preceding one. A leading minus marks a negative quantity.

Its job in the formula

Subtract the following term or group from the preceding one. A leading minus marks a negative quantity.

The passage around this formula

The first is measurement-time ablation : take an already-trained system, rerun the exact same benchmark items with one channel removed at inference, and compare. This is what the original VQA paper did with its question-only baseline [ 1 ] , and it is what a 2024 audit of vision-language benchmarks did formally, by defining two paired metrics from three separately measured accuracies. Let SvS_v be a model’s accuracy on a benchmark with the image present, SwvS_{wv} its accuracy on the same items with the image withheld, and StS_t the accuracy of that same model’s underlying text-only language backbone, evaluated on its own before any multimodal training touched it. The audit’s two metrics are then…

Read this part in the article →

Learn the underlying idea

Addition combines quantities; subtraction measures the signed difference between them. Parentheses show what is combined before the rest of the expression is evaluated.

Open the illustrated addition and subtraction in an equation guide →

Sources cited in the surrounding passage

These citations provide research context; check each source for the exact claim it supports.