Instruct: Identify the main and secondary category of Arxiv papers based on the titles and abstracts
Query: Latent Tree Learning with Differentiable Parsers: Shift-Reduce Parsing
  and Chart Parsing   Latent tree learning models represent sentences by composing their words
according to an induced parse tree, all based on a downstream task. These
models often outperform baselines which use (externally provided) syntax trees
to drive the composition order. This work contributes (a) a new latent tree
learning model based on shift-reduce parsing, with competitive downstream
performance and non-trivial induced trees, and (b) an analysis of the trees
learned by our shift-reduce model and by a chart-based model.

5
The categories of this paper are: gr-qc
18
The categories of this paper are: econ
21
The categories of this paper are: adap-org
30
The categories of this paper are: q-alg
32
The categories of this paper are: atom-ph
14
The categories of this paper are: math-ph
0
The categories of this paper are: hep-ph
10
The categories of this paper are: q-bio
36
The categories of this paper are: cmp-lg
3
The categories of this paper are: physics
25
The categories of this paper are: patt-sol
19
The categories of this paper are: eess
17
The categories of this paper are: q-fin
29
The categories of this paper are: funct-an
24
The categories of this paper are: dg-ga
35
The categories of this paper are: mtrl-th