Instruct: Identify the main and secondary category of Arxiv papers based on the titles and abstracts
Query: Neighbors Are Not Strangers: Improving Non-Autoregressive Translation
  under Low-Frequency Lexical Constraints   However, current autoregressive approaches suffer from high latency. In this
paper, we focus on non-autoregressive translation (NAT) for this problem for
its efficiency advantage. We identify that current constrained NAT models,
which are based on iterative editing, do not handle low-frequency constraints
well. To this end, we propose a plug-in algorithm for this line of work, i.e.,
Aligned Constrained Training (ACT), which alleviates this problem by
familiarizing the model with the source-side context of the constraints.
Experiments on the general and domain datasets show that our model improves
over the backbone constrained NAT model in constraint preservation and
translation quality, especially for rare constraints.

16
The categories of this paper are: stat
30
The categories of this paper are: q-alg
17
The categories of this paper are: q-fin
14
The categories of this paper are: math-ph
27
The categories of this paper are: comp-gas
31
The categories of this paper are: ao-sci
13
The categories of this paper are: quant-ph
37
The categories of this paper are: supr-con
29
The categories of this paper are: funct-an
19
The categories of this paper are: eess
26
The categories of this paper are: bayes-an
9
The categories of this paper are: nlin
36
The categories of this paper are: cmp-lg
6
The categories of this paper are: astro-ph
32
The categories of this paper are: atom-ph
35
The categories of this paper are: mtrl-th