Instruct: Identify the main and secondary category of Arxiv papers based on the titles and abstracts
Query: N24News: A New Dataset for Multimodal News Classification   Current news datasets merely focus on text features on the news and rarely
leverage the feature of images, excluding numerous essential features for news
classification. In this paper, we propose a new dataset, N24News, which is
generated from New York Times with 24 categories and contains both text and
image information in each news. We use a multitask multimodal method and the
experimental results show multimodal news classification performs better than
text-only news classification. Depending on the length of the text, the
classification accuracy can be increased by up to 8.11%. Our research reveals
the relationship between the performance of a multimodal classifier and its
sub-classifiers, and also the possible improvements when applying multimodal in
news classification. N24News is shown to have great potential to prompt the
multimodal news studies.

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The categories of this paper are: nucl-th
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The categories of this paper are: eess
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The categories of this paper are: q-fin
11
The categories of this paper are: hep-lat
9
The categories of this paper are: nlin
36
The categories of this paper are: cmp-lg
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The categories of this paper are: adap-org
16
The categories of this paper are: stat
20
The categories of this paper are: acc-phys
4
The categories of this paper are: cond-mat
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The categories of this paper are: bayes-an
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The categories of this paper are: hep-th
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The categories of this paper are: plasm-ph
10
The categories of this paper are: q-bio
37
The categories of this paper are: supr-con
23
The categories of this paper are: solv-int