Instruct: Identify the main and secondary category of Arxiv papers based on the titles and abstracts
Query: Representations of Syntax [MASK] Useful: Effects of Constituency and
  Dependency Structure in Recursive LSTMs   Sequence-based neural networks show significant sensitivity to syntactic
structure, but they still perform less well on syntactic tasks than tree-based
networks. Such tree-based networks can be provided with a constituency parse, a
dependency parse, or both. We evaluate which of these two representational
schemes more effectively introduces biases for syntactic structure that
increase performance on the subject-verb agreement prediction task. We find
that a constituency-based network generalizes more robustly than a
dependency-based one, and that combining the two types of structure does not
yield further improvement. Finally, we show that the syntactic robustness of
sequential models can be substantially improved by fine-tuning on a small
amount of constructed data, suggesting that data augmentation is a viable
alternative to explicit constituency structure for imparting the syntactic
biases that sequential models are lacking.

9
The categories of this paper are: nlin
35
The categories of this paper are: mtrl-th
28
The categories of this paper are: alg-geom
27
The categories of this paper are: comp-gas
16
The categories of this paper are: stat
23
The categories of this paper are: solv-int
0
The categories of this paper are: hep-ph
25
The categories of this paper are: patt-sol
10
The categories of this paper are: q-bio
34
The categories of this paper are: chem-ph
17
The categories of this paper are: q-fin
37
The categories of this paper are: supr-con
29
The categories of this paper are: funct-an
12
The categories of this paper are: nucl-th
22
The categories of this paper are: chao-dyn
7
The categories of this paper are: hep-th