Instruct: Identify the main and secondary category of Arxiv papers based on the titles and abstracts
Query: Do Multi-Lingual Pre-trained Language Models Reveal Consistent Token
  Attributions in Different Languages?   During the past several years, a surge of multi-lingual Pre-trained Language
Models (PLMs) has been proposed to achieve state-of-the-art performance in many
cross-lingual downstream tasks. However, the understanding of why multi-lingual
PLMs perform well is still an open domain. For example, it is unclear whether
multi-Lingual PLMs reveal consistent token attributions in different languages.
To address this, in this paper, we propose a Cross-lingual Consistency of Token
Attributions (CCTA) evaluation framework. Extensive experiments in three
downstream tasks demonstrate that multi-lingual PLMs assign significantly
different attributions to multi-lingual synonyms. Moreover, we have the
following observations: 1) the Spanish achieves the most consistent token
attributions in different languages when it is used for training PLMs; 2) the
consistency of token attributions strongly correlates with performance in
downstream tasks.

14
The categories of this paper are: math-ph
20
The categories of this paper are: acc-phys
0
The categories of this paper are: hep-ph
19
The categories of this paper are: eess
10
The categories of this paper are: q-bio
7
The categories of this paper are: hep-th
35
The categories of this paper are: mtrl-th
30
The categories of this paper are: q-alg
34
The categories of this paper are: chem-ph
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The categories of this paper are: q-fin
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The categories of this paper are: adap-org
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The categories of this paper are: econ
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The categories of this paper are: nlin
24
The categories of this paper are: dg-ga
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The categories of this paper are: astro-ph
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The categories of this paper are: nucl-th