\[\begin{gathered}
\mathcal{V}^c=\underset{v\in\mathcal{V}}{\text{Top-}k}\bigg\{
\sum_{x_{in}\in\mathcal{D}_{train}^c}{
\log{P_\theta\Big(
\text{[MASK]}=v|\mathcal{T}(x_{in})
\Big)}
}
\bigg\}, \\
\text{where }\mathcal{D}_{train}^c\subset\mathcal{D}_{train}\text{ is the subset of all examples of class }c.
\end{gathered}\]
Prompt Generation
\[\begin{aligned}
(x_1,y)&\Rightarrow\text{<}p_1\text{>}\mathcal{M}(y)\text{<}p_2\text{>}\text{<}x_1\text{>} \\
(x_1,y)&\Rightarrow\text{<}x_1\text{>}\text{<}p_1\text{>}\mathcal{M}(y)\text{<}p_2\text{>} \\
(x_1,x_2,y)&\Rightarrow\text{<}x_1\text{>}\text{<}p_1\text{>}\mathcal{M}(y)\text{<}p_2\text{>}\text{<}x_2\text{>}
\end{aligned}\]
\[\begin{gathered}
(\text{"Best pizza I ever had."},positive)\Rightarrow\text{"Best pizza I ever had. It was }great\text{ !"}
\end{gathered}\]
\[\begin{gathered}
\hat{\mathcal{T}}=\underset{\mathcal{T}\in\text{T}}{\text{argmax}}{
\sum_{x_{in},y\in\mathcal{D}_{train}}{
\log{
P_\theta\Big(
\text{[MASK]}=\mathcal{M}(y)|\mathcal{T}(x_{in})
\Big)
}
}
}
\end{gathered}\]