Instruct: Identify the main and secondary category of Arxiv papers based on the titles and abstracts
Query: A BERT-based Distractor Generation Scheme with Multi-tasking and
  Negative Answer Training Strategies   In this paper, we investigate the following two limitations for the existing
distractor generation (DG) methods. First, the quality of the existing DG
methods are still far from practical use. There is still room for DG quality
improvement. Second, the existing DG designs are mainly for single distractor
generation. However, for practical MCQ preparation, multiple distractors are
desired. Aiming at these goals, in this paper, we present a new distractor
generation scheme with multi-tasking and negative answer training strategies
for effectively generating \textit{multiple} distractors. The experimental
results show that (1) our model advances the state-of-the-art result from 28.65
to 39.81 (BLEU 1 score) and (2) the generated multiple distractors are diverse
and show strong distracting power for multiple choice question.

23
The categories of this paper are: solv-int
0
The categories of this paper are: hep-ph
5
The categories of this paper are: gr-qc
27
The categories of this paper are: comp-gas
18
The categories of this paper are: econ
33
The categories of this paper are: plasm-ph
11
The categories of this paper are: hep-lat
9
The categories of this paper are: nlin
35
The categories of this paper are: mtrl-th
26
The categories of this paper are: bayes-an
16
The categories of this paper are: stat
28
The categories of this paper are: alg-geom
15
The categories of this paper are: nucl-ex
29
The categories of this paper are: funct-an
8
The categories of this paper are: hep-ex
24
The categories of this paper are: dg-ga