Instruct: Identify the main and secondary category of Arxiv papers based on the titles and abstracts
Query: Localization of Fake News Detection via Multitask Transfer Learning   The use of the internet as a fast medium of spreading fake news reinforces
the need for computational tools that combat it. Techniques that train fake
news classifiers exist, but they all assume an abundance of resources including
large labeled datasets and expert-curated corpora, which low-resource languages
may not have. In this work, we make two main contributions: First, we alleviate
resource scarcity by constructing the first expertly-curated benchmark dataset
for fake news detection in Filipino, which we call "Fake News Filipino."
Second, we benchmark Transfer Learning (TL) techniques and show that they can
be used to train robust fake news classifiers from little data, achieving 91%
accuracy on our fake news dataset, reducing the error by 14% compared to
established few-shot baselines. Furthermore, lifting ideas from multitask
learning, we show that augmenting transformer-based transfer techniques with
auxiliary language modeling losses improves their performance by adapting to
writing style. Using this, we improve TL performance by 4-6%, achieving an
accuracy of 96% on our best model. Lastly, we show that our method generalizes
well to different types of news articles, including political news,
entertainment news, and opinion articles.

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The categories of this paper are: gr-qc
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The categories of this paper are: nlin
21
The categories of this paper are: adap-org
27
The categories of this paper are: comp-gas
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The categories of this paper are: ao-sci
8
The categories of this paper are: hep-ex
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The categories of this paper are: cond-mat
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The categories of this paper are: quant-ph
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The categories of this paper are: hep-ph
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The categories of this paper are: hep-lat
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The categories of this paper are: alg-geom
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The categories of this paper are: q-bio
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The categories of this paper are: math-ph
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The categories of this paper are: patt-sol
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The categories of this paper are: supr-con
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The categories of this paper are: plasm-ph