Instruct: Identify the main and secondary category of Arxiv papers based on the titles and abstracts
Query: Sequence-Based Extractive Summarisation for Scientific Articles   This paper presents the results of research on supervised extractive text
summarisation for scientific articles. We show that a simple sequential tagging
model based only on the text within a document achieves high results against a
simple classification model. Improvements can be achieved through additional
sentence-level features, though these were minimal. Through further analysis,
we show the potential of the sequential model relying on the structure of the
document depending on the academic discipline which the document is from.

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The categories of this paper are: math-ph
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The categories of this paper are: hep-lat
4
The categories of this paper are: cond-mat
6
The categories of this paper are: astro-ph
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The categories of this paper are: nlin
15
The categories of this paper are: nucl-ex
20
The categories of this paper are: acc-phys
29
The categories of this paper are: funct-an
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The categories of this paper are: quant-ph
2
The categories of this paper are: math
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The categories of this paper are: dg-ga
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The categories of this paper are: bayes-an
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The categories of this paper are: mtrl-th
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The categories of this paper are: alg-geom
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The categories of this paper are: atom-ph
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The categories of this paper are: hep-ex