Instruct: Identify the main and secondary category of Arxiv papers based on the titles and abstracts
Query: A cost-benefit analysis of cross-lingual transfer methods   An effective method for cross-lingual transfer is to fine-tune a bilingual or
multilingual model on a supervised dataset in one language and evaluating it on
another language in a zero-shot manner. Translating examples at training time
or inference time are also viable alternatives. However, there are costs
associated with these methods that are rarely addressed in the literature. In
this work, we analyze cross-lingual methods in terms of their effectiveness
(e.g., accuracy), development and deployment costs, as well as their latencies
at inference time. Our experiments on three tasks indicate that the best
cross-lingual method is highly task-dependent. Finally, by combining zero-shot
and translation methods, we achieve the state-of-the-art in two of the three
datasets used in this work. Based on these results, we question the need for
manually labeled training data in a target language. Code and translated
datasets are available at https://github.com/unicamp-dl/cross-lingual-analysis

11
The categories of this paper are: hep-lat
24
The categories of this paper are: dg-ga
15
The categories of this paper are: nucl-ex
10
The categories of this paper are: q-bio
30
The categories of this paper are: q-alg
0
The categories of this paper are: hep-ph
2
The categories of this paper are: math
19
The categories of this paper are: eess
9
The categories of this paper are: nlin
31
The categories of this paper are: ao-sci
29
The categories of this paper are: funct-an
33
The categories of this paper are: plasm-ph
7
The categories of this paper are: hep-th
32
The categories of this paper are: atom-ph
22
The categories of this paper are: chao-dyn
37
The categories of this paper are: supr-con