Instruct: Identify the main and secondary category of Arxiv papers based on the titles and abstracts
Query: Exploiting Cross-Sentence Context for Neural Machine Translation   In translation, considering the document as a whole can help to resolve
ambiguities and inconsistencies. In this paper, we propose a cross-sentence
context-aware approach and investigate the influence of historical contextual
information on the performance of neural machine translation (NMT). First, this
history is summarized in a hierarchical way. We then integrate the historical
representation into NMT in two strategies: 1) a warm-start of encoder and
decoder states, and 2) an auxiliary context source for updating decoder states.
Experimental results on a large Chinese-English translation task show that our
approach significantly improves upon a strong attention-based NMT system by up
to +2.1 BLEU points.

12
The categories of this paper are: nucl-th
33
The categories of this paper are: plasm-ph
5
The categories of this paper are: gr-qc
27
The categories of this paper are: comp-gas
37
The categories of this paper are: supr-con
18
The categories of this paper are: econ
30
The categories of this paper are: q-alg
13
The categories of this paper are: quant-ph
10
The categories of this paper are: q-bio
17
The categories of this paper are: q-fin
36
The categories of this paper are: cmp-lg
6
The categories of this paper are: astro-ph
34
The categories of this paper are: chem-ph
2
The categories of this paper are: math
22
The categories of this paper are: chao-dyn
8
The categories of this paper are: hep-ex