Instruct: Identify the main and secondary category of Arxiv papers based on the titles and abstracts
Query: A Joint Model for Definition Extraction with Syntactic Connection and
  Semantic Consistency   Definition Extraction (DE) is one of the well-known topics in Information
Extraction that aims to identify terms and their corresponding definitions in
unstructured texts. This task can be formalized either as a sentence
classification task (i.e., containing term-definition pairs or not) or a
sequential labeling task (i.e., identifying the boundaries of the terms and
definitions). The previous works for DE have only focused on one of the two
approaches, failing to model the inter-dependencies between the two tasks. In
this work, we propose a novel model for DE that simultaneously performs the two
tasks in a single framework to benefit from their inter-dependencies. Our model
features deep learning architectures to exploit the global structures of the
input sentences as well as the semantic consistencies between the terms and the
definitions, thereby improving the quality of the representation vectors for
DE. Besides the joint inference between sentence classification and sequential
labeling, the proposed model is fundamentally different from the prior work for
DE in that the prior work has only employed the local structures of the input
sentences (i.e., word-to-word relations), and not yet considered the semantic
consistencies between terms and definitions. In order to implement these novel
ideas, our model presents a multi-task learning framework that employs graph
convolutional neural networks and predicts the dependency paths between the
terms and the definitions. We also seek to enforce the consistency between the
representations of the terms and definitions both globally (i.e., increasing
semantic consistency between the representations of the entire sentences and
the terms/definitions) and locally (i.e., promoting the similarity between the
representations of the terms and the definitions).

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The categories of this paper are: cond-mat
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The categories of this paper are: econ
17
The categories of this paper are: q-fin
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The categories of this paper are: gr-qc
25
The categories of this paper are: patt-sol
3
The categories of this paper are: physics
15
The categories of this paper are: nucl-ex
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The categories of this paper are: math-ph
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The categories of this paper are: adap-org
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The categories of this paper are: nlin
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The categories of this paper are: q-alg
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The categories of this paper are: hep-ph
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The categories of this paper are: ao-sci
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The categories of this paper are: chao-dyn
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The categories of this paper are: nucl-th
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The categories of this paper are: q-bio