Instruct: Identify the main and secondary category of Arxiv papers based on the titles and abstracts
Query: Personalized Machine Translation: Preserving Original Author Traits   The language that we produce reflects our personality, and various personal
and demographic characteristics can be detected in natural language texts. We
focus on one particular personal trait of the author, gender, and study how it
is manifested in original texts and in translations. We show that author's
gender has a powerful, clear signal in originals texts, but this signal is
obfuscated in human and machine translation. We then propose simple
domain-adaptation techniques that help retain the original gender traits in the
translation, without harming the quality of the translation, thereby creating
more personalized machine translation systems.

21
The categories of this paper are: adap-org
32
The categories of this paper are: atom-ph
37
The categories of this paper are: supr-con
10
The categories of this paper are: q-bio
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
3
The categories of this paper are: physics
12
The categories of this paper are: nucl-th
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
22
The categories of this paper are: chao-dyn
33
The categories of this paper are: plasm-ph
8
The categories of this paper are: hep-ex
20
The categories of this paper are: acc-phys