Instruct: Identify the main and secondary category of Arxiv papers based on the titles and abstracts
Query: SNU_IDS at SemEval-2018 Task 12: Sentence Encoder with Contextualized
  Vectors for Argument Reasoning Comprehension   We present a novel neural architecture for the Argument Reasoning
Comprehension task of SemEval 2018. It is a simple neural network consisting of
three parts, collectively judging whether the logic built on a set of given
sentences (a claim, reason, and warrant) is plausible or not. The model
utilizes contextualized word vectors pre-trained on large machine translation
(MT) datasets as a form of transfer learning, which can help to mitigate the
lack of training data. Quantitative analysis shows that simply leveraging LSTMs
trained on MT datasets outperforms several baselines and non-transferred
models, achieving accuracies of about 70% on the development set and about 60%
on the test set.

16
The categories of this paper are: stat
22
The categories of this paper are: chao-dyn
0
The categories of this paper are: hep-ph
31
The categories of this paper are: ao-sci
13
The categories of this paper are: quant-ph
28
The categories of this paper are: alg-geom
24
The categories of this paper are: dg-ga
30
The categories of this paper are: q-alg
10
The categories of this paper are: q-bio
18
The categories of this paper are: econ
6
The categories of this paper are: astro-ph
33
The categories of this paper are: plasm-ph
8
The categories of this paper are: hep-ex
19
The categories of this paper are: eess
11
The categories of this paper are: hep-lat
15
The categories of this paper are: nucl-ex