Instruct: Identify the main and secondary category of Arxiv papers based on the titles and abstracts
Query: MM-Claims: A Dataset for Multimodal Claim Detection in Social Media   In recent years, the problem of misinformation on the web has become
widespread across languages, countries, and various social media platforms.
Although there has been much work on automated fake news detection, the role of
images and their variety are not well explored. In this paper, we investigate
the roles of image and text at an earlier stage of the fake news detection
pipeline, called claim detection. For this purpose, we introduce a novel
dataset, MM-Claims, which consists of tweets and corresponding images over
three topics: COVID-19, Climate Change and broadly Technology. The dataset
contains roughly 86000 tweets, out of which 3400 are labeled manually by
multiple annotators for the training and evaluation of multimodal models. We
describe the dataset in detail, evaluate strong unimodal and multimodal
baselines, and analyze the potential and drawbacks of current models.

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The categories of this paper are: gr-qc
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The categories of this paper are: solv-int
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The categories of this paper are: stat
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The categories of this paper are: plasm-ph
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The categories of this paper are: dg-ga
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The categories of this paper are: q-alg
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The categories of this paper are: bayes-an
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The categories of this paper are: nucl-th
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The categories of this paper are: nucl-ex
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The categories of this paper are: supr-con
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The categories of this paper are: math
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The categories of this paper are: nlin
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The categories of this paper are: physics
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The categories of this paper are: cond-mat
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The categories of this paper are: cmp-lg
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The categories of this paper are: patt-sol