Instruct: Identify the main and secondary category of Arxiv papers based on the titles and abstracts
Query: Outline Generation: Understanding the Inherent Content Structure of
  Documents   In this paper, we introduce and tackle the Outline Generation (OG) task,
which aims to unveil the inherent content structure of a multi-paragraph
document by identifying its potential sections and generating the corresponding
section headings. Without loss of generality, the OG task can be viewed as a
novel structured summarization task. To generate a sound outline, an ideal OG
model should be able to capture three levels of coherence, namely the coherence
between context paragraphs, that between a section and its heading, and that
between context headings. The first one is the foundation for section
identification, while the latter two are critical for consistent heading
generation. In this work, we formulate the OG task as a hierarchical structured
prediction problem, i.e., to first predict a sequence of section boundaries and
then a sequence of section headings accordingly. We propose a novel
hierarchical structured neural generation model, named HiStGen, for the task.
Our model attempts to capture the three-level coherence via the following ways.
First, we introduce a Markov paragraph dependency mechanism between context
paragraphs for section identification. Second, we employ a section-aware
attention mechanism to ensure the semantic coherence between a section and its
heading. Finally, we leverage a Markov heading dependency mechanism and a
review mechanism between context headings to improve the consistency and
eliminate duplication between section headings. Besides, we build a novel
WIKIOG dataset, a public collection which consists of over 1.75 million
document-outline pairs for research on the OG task. Experimental results on our
benchmark dataset demonstrate that our model can significantly outperform
several state-of-the-art sequential generation models for the OG task.

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The categories of this paper are: physics
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The categories of this paper are: stat
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The categories of this paper are: solv-int
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The categories of this paper are: funct-an
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The categories of this paper are: plasm-ph
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The categories of this paper are: atom-ph
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The categories of this paper are: chem-ph
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The categories of this paper are: eess
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The categories of this paper are: dg-ga
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The categories of this paper are: q-bio
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The categories of this paper are: astro-ph
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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: hep-ex
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The categories of this paper are: q-fin
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The categories of this paper are: nucl-ex