Instruct: Identify the main and secondary category of Arxiv papers based on the titles and abstracts
Query: Controlling Text Complexity in Neural Machine Translation   This work introduces a machine translation task where the output is aimed at
audiences of different levels of target language proficiency. We collect a high
quality dataset of news articles available in English and Spanish, written for
diverse grade levels and propose a method to align segments across comparable
bilingual articles. The resulting dataset makes it possible to train multi-task
sequence-to-sequence models that translate Spanish into English targeted at an
easier reading grade level than the original Spanish. We show that these
multi-task models outperform pipeline approaches that translate and simplify
text independently.

15
The categories of this paper are: nucl-ex
31
The categories of this paper are: ao-sci
4
The categories of this paper are: cond-mat
6
The categories of this paper are: astro-ph
0
The categories of this paper are: hep-ph
17
The categories of this paper are: q-fin
13
The categories of this paper are: quant-ph
5
The categories of this paper are: gr-qc
23
The categories of this paper are: solv-int
14
The categories of this paper are: math-ph
28
The categories of this paper are: alg-geom
11
The categories of this paper are: hep-lat
34
The categories of this paper are: chem-ph
2
The categories of this paper are: math
32
The categories of this paper are: atom-ph
26
The categories of this paper are: bayes-an