Instruct: Identify the main and secondary category of Arxiv papers based on the titles and abstracts
Query: A Comparative Study of Word Embeddings for Reading Comprehension   The focus of past machine learning research for Reading Comprehension tasks
has been primarily on the design of novel deep learning architectures. Here we
show that seemingly minor choices made on (1) the use of pre-trained word
embeddings, and (2) the representation of out-of-vocabulary tokens at test
time, can turn out to have a larger impact than architectural choices on the
final performance. We systematically explore several options for these choices,
and provide recommendations to researchers working in this area.

28
The categories of this paper are: alg-geom
8
The categories of this paper are: hep-ex
36
The categories of this paper are: cmp-lg
18
The categories of this paper are: econ
19
The categories of this paper are: eess
9
The categories of this paper are: nlin
17
The categories of this paper are: q-fin
32
The categories of this paper are: atom-ph
6
The categories of this paper are: astro-ph
35
The categories of this paper are: mtrl-th
14
The categories of this paper are: math-ph
21
The categories of this paper are: adap-org
24
The categories of this paper are: dg-ga
4
The categories of this paper are: cond-mat
22
The categories of this paper are: chao-dyn
23
The categories of this paper are: solv-int