Instruct: Identify the main and secondary category of Arxiv papers based on the titles and abstracts
Query: An Information-Theoretic Explanation for the Adversarial Fragility of AI
  Classifiers   We present a simple hypothesis about a compression property of artificial
intelligence (AI) classifiers and present theoretical arguments to show that
this hypothesis successfully accounts for the observed fragility of AI
classifiers to small adversarial perturbations. We also propose a new method
for detecting when small input perturbations cause classifier errors, and show
theoretical guarantees for the performance of this detection method. We present
experimental results with a voice recognition system to demonstrate this
method. The ideas in this paper are motivated by a simple analogy between AI
classifiers and the standard Shannon model of a communication system.

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The categories of this paper are: cond-mat
20
The categories of this paper are: acc-phys
32
The categories of this paper are: atom-ph
35
The categories of this paper are: mtrl-th
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The categories of this paper are: astro-ph
30
The categories of this paper are: q-alg
22
The categories of this paper are: chao-dyn
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The categories of this paper are: physics
34
The categories of this paper are: chem-ph
28
The categories of this paper are: alg-geom
31
The categories of this paper are: ao-sci
12
The categories of this paper are: nucl-th
18
The categories of this paper are: econ
10
The categories of this paper are: q-bio
25
The categories of this paper are: patt-sol
26
The categories of this paper are: bayes-an