Instruct: Identify the main and secondary category of Arxiv papers based on the titles and abstracts
Query: Cross-Lingual Transfer Learning for Complex Word Identification   Complex Word Identification (CWI) is a task centered on detecting
hard-to-understand words, or groups of words, in texts from different areas of
expertise. The purpose of CWI is to highlight problematic structures that
non-native speakers would usually find difficult to understand. Our approach
uses zero-shot, one-shot, and few-shot learning techniques, alongside
state-of-the-art solutions for Natural Language Processing (NLP) tasks (i.e.,
Transformers). Our aim is to provide evidence that the proposed models can
learn the characteristics of complex words in a multilingual environment by
relying on the CWI shared task 2018 dataset available for four different
languages (i.e., English, German, Spanish, and also French). Our approach
surpasses state-of-the-art cross-lingual results in terms of macro F1-score on
English (0.774), German (0.782), and Spanish (0.734) languages, for the
zero-shot learning scenario. At the same time, our model also outperforms the
state-of-the-art monolingual result for German (0.795 macro F1-score).

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The categories of this paper are: hep-ex
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The categories of this paper are: nucl-ex
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The categories of this paper are: acc-phys
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The categories of this paper are: alg-geom
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The categories of this paper are: dg-ga
7
The categories of this paper are: hep-th
32
The categories of this paper are: atom-ph
29
The categories of this paper are: funct-an
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The categories of this paper are: bayes-an
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The categories of this paper are: mtrl-th
34
The categories of this paper are: chem-ph
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The categories of this paper are: econ
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The categories of this paper are: q-fin
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The categories of this paper are: supr-con
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The categories of this paper are: chao-dyn
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The categories of this paper are: astro-ph