Instruct: Identify the main and secondary category of Arxiv papers based on the titles and abstracts
Query: Input Prioritization for Testing Neural Networks   Deep neural networks (DNNs) are increasingly being adopted for sensing and
control functions in a variety of safety and mission-critical systems such as
self-driving cars, autonomous air vehicles, medical diagnostics, and industrial
robotics. Failures of such systems can lead to loss of life or property, which
necessitates stringent verification and validation for providing high
assurance. Though formal verification approaches are being investigated,
testing remains the primary technique for assessing the dependability of such
systems. Due to the nature of the tasks handled by DNNs, the cost of obtaining
test oracle data---the expected output, a.k.a. label, for a given input---is
high, which significantly impacts the amount and quality of testing that can be
performed. Thus, prioritizing input data for testing DNNs in meaningful ways to
reduce the cost of labeling can go a long way in increasing testing efficacy.
This paper proposes using gauges of the DNN's sentiment derived from the
computation performed by the model, as a means to identify inputs that are
likely to reveal weaknesses. We empirically assessed the efficacy of three such
sentiment measures for prioritization---confidence, uncertainty, and
surprise---and compare their effectiveness in terms of their fault-revealing
capability and retraining effectiveness. The results indicate that sentiment
measures can effectively flag inputs that expose unacceptable DNN behavior. For
MNIST models, the average percentage of inputs correctly flagged ranged from
88% to 94.8%.

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The categories of this paper are: mtrl-th
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The categories of this paper are: hep-th
11
The categories of this paper are: hep-lat
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The categories of this paper are: cmp-lg
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The categories of this paper are: q-fin
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The categories of this paper are: alg-geom
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The categories of this paper are: acc-phys
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The categories of this paper are: q-alg
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The categories of this paper are: math-ph
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The categories of this paper are: hep-ph
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The categories of this paper are: astro-ph
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The categories of this paper are: hep-ex
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The categories of this paper are: eess
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The categories of this paper are: plasm-ph
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The categories of this paper are: nlin
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The categories of this paper are: econ