Instruct: Identify the main and secondary category of Arxiv papers based on the titles and abstracts
Query: An Exploratory Analysis of Multilingual Word-Level Quality Estimation
  with Cross-Lingual Transformers   Most studies on word-level Quality Estimation (QE) of machine translation
focus on language-specific models. The obvious disadvantages of these
approaches are the need for labelled data for each language pair and the high
cost required to maintain several language-specific models. To overcome these
problems, we explore different approaches to multilingual, word-level QE. We
show that these QE models perform on par with the current language-specific
models. In the cases of zero-shot and few-shot QE, we demonstrate that it is
possible to accurately predict word-level quality for any given new language
pair from models trained on other language pairs. Our findings suggest that the
word-level QE models based on powerful pre-trained transformers that we propose
in this paper generalise well across languages, making them more useful in
real-world scenarios.

6
The categories of this paper are: astro-ph
29
The categories of this paper are: funct-an
22
The categories of this paper are: chao-dyn
26
The categories of this paper are: bayes-an
3
The categories of this paper are: physics
21
The categories of this paper are: adap-org
0
The categories of this paper are: hep-ph
12
The categories of this paper are: nucl-th
24
The categories of this paper are: dg-ga
2
The categories of this paper are: math
27
The categories of this paper are: comp-gas
9
The categories of this paper are: nlin
10
The categories of this paper are: q-bio
7
The categories of this paper are: hep-th
37
The categories of this paper are: supr-con
33
The categories of this paper are: plasm-ph