Instruct: Identify the main and secondary category of Arxiv papers based on the titles and abstracts
Query: Cross-Task Instance Representation Interactions and Label Dependencies
  for Joint Information Extraction with Graph Convolutional Networks   Existing works on information extraction (IE) have mainly solved the four
main tasks separately (entity mention recognition, relation extraction, event
trigger detection, and argument extraction), thus failing to benefit from
inter-dependencies between tasks. This paper presents a novel deep learning
model to simultaneously solve the four tasks of IE in a single model (called
FourIE). Compared to few prior work on jointly performing four IE tasks, FourIE
features two novel contributions to capture inter-dependencies between tasks.
First, at the representation level, we introduce an interaction graph between
instances of the four tasks that is used to enrich the prediction
representation for one instance with those from related instances of other
tasks. Second, at the label level, we propose a dependency graph for the
information types in the four IE tasks that captures the connections between
the types expressed in an input sentence. A new regularization mechanism is
introduced to enforce the consistency between the golden and predicted type
dependency graphs to improve representation learning. We show that the proposed
model achieves the state-of-the-art performance for joint IE on both
monolingual and multilingual learning settings with three different languages.

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The categories of this paper are: hep-ph
31
The categories of this paper are: ao-sci
8
The categories of this paper are: hep-ex
32
The categories of this paper are: atom-ph
27
The categories of this paper are: comp-gas
10
The categories of this paper are: q-bio
6
The categories of this paper are: astro-ph
11
The categories of this paper are: hep-lat
26
The categories of this paper are: bayes-an
9
The categories of this paper are: nlin
36
The categories of this paper are: cmp-lg
21
The categories of this paper are: adap-org
17
The categories of this paper are: q-fin
20
The categories of this paper are: acc-phys
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The categories of this paper are: quant-ph
28
The categories of this paper are: alg-geom