Instruct: Identify the main and secondary category of Arxiv papers based on the titles and abstracts
Query: Enriching Visual with Verbal Explanations for Relational Concepts --
  Combining LIME with Aleph   With the increasing number of deep learning applications, there is a growing
demand for explanations. Visual explanations provide information about which
parts of an image are relevant for a classifier's decision. However,
highlighting of image parts (e.g., an eye) cannot capture the relevance of a
specific feature value for a class (e.g., that the eye is wide open).
Furthermore, highlighting cannot convey whether the classification depends on
the mere presence of parts or on a specific spatial relation between them.
Consequently, we present an approach that is capable of explaining a
classifier's decision in terms of logic rules obtained by the Inductive Logic
Programming system Aleph. The examples and the background knowledge needed for
Aleph are based on the explanation generation method LIME. We demonstrate our
approach with images of a blocksworld domain. First, we show that our approach
is capable of identifying a single relation as important explanatory construct.
Afterwards, we present the more complex relational concept of towers. Finally,
we show how the generated relational rules can be explicitly related with the
input image, resulting in richer explanations.

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The categories of this paper are: physics
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The categories of this paper are: hep-ex
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The categories of this paper are: chao-dyn
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The categories of this paper are: cmp-lg
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The categories of this paper are: nucl-th
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The categories of this paper are: mtrl-th
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The categories of this paper are: nlin
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The categories of this paper are: q-fin
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The categories of this paper are: nucl-ex
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The categories of this paper are: alg-geom
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The categories of this paper are: hep-lat
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The categories of this paper are: astro-ph
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The categories of this paper are: bayes-an
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The categories of this paper are: gr-qc
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The categories of this paper are: comp-gas
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The categories of this paper are: dg-ga