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Equation 1 · Part 2 · A History of How We Learned to Evaluate AI Agents

Symbol t

SGLUE=19∑t=19st,S_{\mathrm{GLUE}} = \frac{1}{9}\sum_{t=1}^{9} s_t,
tt

What this part means

t appears in the bound of this sum. The bound states where the repeated operation starts, ends, or which values it includes.

Its job in the formula

t appears in the bound of this sum. The bound states where the repeated operation starts, ends, or which values it includes.

The passage around this formula

Wang and colleagues then generalized the single-turn approach across tasks rather than within one, arguing that for language understanding “to be maximally useful, both practically and as a scientific object of study, it must be general: it must be able to process language in a way that is not exclusively tailored to any one specific task or dataset” [ 4 ] . GLUE bundled nine separate tasks — grammatical acceptability, sentiment, paraphrase and similarity judgments, and several varieties of natural-language inference — behind one leaderboard number. That number is worth writing out, because the arithmetic embeds an assumption the field would later revisit: SGLUE=19∑t=19stS_{\mathrm{GLUE}} = \frac{1}{9}\sum_{t=1}^{9} s_t. an unweighted…

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A variable is a named place for a value. Its letter is a local label: x can mean position in one formula and a data point in another.

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Sources cited in the surrounding passage

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