Instruct: Identify the main and secondary category of Arxiv papers based on the titles and abstracts
Query: Relation Extraction using Explicit Context Conditioning   Relation Extraction (RE) aims to label relations between groups of marked
entities in raw text. Most current RE models learn context-aware
representations of the target entities that are then used to establish relation
between them. This works well for intra-sentence RE and we call them
first-order relations. However, this methodology can sometimes fail to capture
complex and long dependencies. To address this, we hypothesize that at times
two target entities can be explicitly connected via a context token. We refer
to such indirect relations as second-order relations and describe an efficient
implementation for computing them. These second-order relation scores are then
combined with first-order relation scores. Our empirical results show that the
proposed method leads to state-of-the-art performance over two biomedical
datasets.

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The categories of this paper are: adap-org
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The categories of this paper are: plasm-ph
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The categories of this paper are: funct-an
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The categories of this paper are: nucl-th
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The categories of this paper are: dg-ga
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The categories of this paper are: atom-ph
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The categories of this paper are: physics
35
The categories of this paper are: mtrl-th
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The categories of this paper are: nucl-ex
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The categories of this paper are: chao-dyn
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The categories of this paper are: q-alg
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The categories of this paper are: ao-sci
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The categories of this paper are: acc-phys
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The categories of this paper are: econ
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The categories of this paper are: cmp-lg
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The categories of this paper are: math