Instruct: Identify the main and secondary category of Arxiv papers based on the titles and abstracts
Query: UIT-HSE at WNUT-2020 Task 2: Exploiting CT-BERT for Identifying COVID-19
  Information on the Twitter Social Network   Recently, COVID-19 has affected a variety of real-life aspects of the world
and led to dreadful consequences. More and more tweets about COVID-19 has been
shared publicly on Twitter. However, the plurality of those Tweets are
uninformative, which is challenging to build automatic systems to detect the
informative ones for useful AI applications. In this paper, we present our
results at the W-NUT 2020 Shared Task 2: Identification of Informative COVID-19
English Tweets. In particular, we propose our simple but effective approach
using the transformer-based models based on COVID-Twitter-BERT (CT-BERT) with
different fine-tuning techniques. As a result, we achieve the F1-Score of
90.94\% with the third place on the leaderboard of this task which attracted 56
submitted teams in total.

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The categories of this paper are: plasm-ph
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The categories of this paper are: alg-geom
16
The categories of this paper are: stat
5
The categories of this paper are: gr-qc
37
The categories of this paper are: supr-con
23
The categories of this paper are: solv-int
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The categories of this paper are: dg-ga
36
The categories of this paper are: cmp-lg
0
The categories of this paper are: hep-ph
2
The categories of this paper are: math
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The categories of this paper are: atom-ph
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: q-fin
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The categories of this paper are: chao-dyn
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The categories of this paper are: math-ph