Instruct: Identify the main and secondary category of Arxiv papers based on the titles and abstracts
Query: Adversarial Token Attacks on Vision Transformers   Vision transformers rely on a patch token based self attention mechanism, in
contrast to convolutional networks. We investigate fundamental differences
between these two families of models, by designing a block sparsity based
adversarial token attack. We probe and analyze transformer as well as
convolutional models with token attacks of varying patch sizes. We infer that
transformer models are more sensitive to token attacks than convolutional
models, with ResNets outperforming Transformer models by up to $\sim30\%$ in
robust accuracy for single token attacks.

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The categories of this paper are: q-fin
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The categories of this paper are: atom-ph
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The categories of this paper are: bayes-an
7
The categories of this paper are: hep-th
31
The categories of this paper are: ao-sci
36
The categories of this paper are: cmp-lg
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The categories of this paper are: chao-dyn
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The categories of this paper are: comp-gas
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The categories of this paper are: quant-ph
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The categories of this paper are: nucl-ex
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The categories of this paper are: nlin
20
The categories of this paper are: acc-phys
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The categories of this paper are: math
34
The categories of this paper are: chem-ph
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The categories of this paper are: stat
3
The categories of this paper are: physics