Recentstudieshaveshownthat the transferability of adversarial examples exists for CNNs, and the same holds true for ViTs.

We use the discrete variablezd,t to represent the topic that thetth word is generated from.

However, these models suffer from quadratic computational cost in the input sequence lengthn to compute pairwise attention in each layer.

Bayesian model evidence gives a clear criteria for such model selection. However, computing model evidence requires integration over the likelihood, which is challenging, particularly when the likelihood is non-closed-form and/or expensive.

Let defined denote conditional (x)= P(y =1|x).

Apart from linguistic transformations, synthesizing among statements usually requires specific synthesis rulesofstatements.