Instruct: Identify the main and secondary category of Arxiv papers based on the titles and abstracts
Query: Capturing Event Argument Interaction via A Bi-Directional Entity-Level
  Recurrent Decoder   Capturing interactions among event arguments is an essential step towards
robust event argument extraction (EAE). However, existing efforts in this
direction suffer from two limitations: 1) The argument role type information of
contextual entities is mainly utilized as training signals, ignoring the
potential merits of directly adopting it as semantically rich input features;
2) The argument-level sequential semantics, which implies the overall
distribution pattern of argument roles over an event mention, is not well
characterized. To tackle the above two bottlenecks, we formalize EAE as a
Seq2Seq-like learning problem for the first time, where a sentence with a
specific event trigger is mapped to a sequence of event argument roles. A
neural architecture with a novel Bi-directional Entity-level Recurrent Decoder
(BERD) is proposed to generate argument roles by incorporating contextual
entities' argument role predictions, like a word-by-word text generation
process, thereby distinguishing implicit argument distribution patterns within
an event more accurately.

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The categories of this paper are: comp-gas
16
The categories of this paper are: stat
13
The categories of this paper are: quant-ph
4
The categories of this paper are: cond-mat
30
The categories of this paper are: q-alg
9
The categories of this paper are: nlin
37
The categories of this paper are: supr-con
28
The categories of this paper are: alg-geom
11
The categories of this paper are: hep-lat
21
The categories of this paper are: adap-org
19
The categories of this paper are: eess
35
The categories of this paper are: mtrl-th
29
The categories of this paper are: funct-an
0
The categories of this paper are: hep-ph
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The categories of this paper are: solv-int
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The categories of this paper are: chem-ph