Instruct: Identify the main and secondary category of Arxiv papers based on the titles and abstracts
Query: Why not be Versatile? Applications of the SGNMT Decoder for Machine
  Translation   SGNMT is a decoding platform for machine translation which allows paring
various modern neural models of translation with different kinds of constraints
and symbolic models. In this paper, we describe three use cases in which SGNMT
is currently playing an active role: (1) teaching as SGNMT is being used for
course work and student theses in the MPhil in Machine Learning, Speech and
Language Technology at the University of Cambridge, (2) research as most of the
research work of the Cambridge MT group is based on SGNMT, and (3) technology
transfer as we show how SGNMT is helping to transfer research findings from the
laboratory to the industry, eg. into a product of SDL plc.

23
The categories of this paper are: solv-int
24
The categories of this paper are: dg-ga
9
The categories of this paper are: nlin
12
The categories of this paper are: nucl-th
28
The categories of this paper are: alg-geom
25
The categories of this paper are: patt-sol
7
The categories of this paper are: hep-th
33
The categories of this paper are: plasm-ph
0
The categories of this paper are: hep-ph
37
The categories of this paper are: supr-con
35
The categories of this paper are: mtrl-th
31
The categories of this paper are: ao-sci
22
The categories of this paper are: chao-dyn
5
The categories of this paper are: gr-qc
14
The categories of this paper are: math-ph
32
The categories of this paper are: atom-ph