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@@ -138,7 +138,7 @@ gradient norm and then apply soft removal on them to mitigate the potential jail
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$$
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\displaystyle
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\begin{aligned}
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x_{1:n}
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\mathtt{Affirmation~Loss}(x_{1:n},\theta)&=-\log P(y|x_{1:n})
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\end{aligned}
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$$
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$$
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\displaystyle
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\begin{aligned}
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x_{1:n} =\mathtt{embed}_\theta(q_{1:n})&\\
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\mathtt{Affirmation~Loss}(x_{1:n},\theta)&=-\log P(y|x_{1:n})
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\end{aligned}
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$$
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