Instruct: Identify the main and secondary category of Arxiv papers based on the titles and abstracts
Query: Cross-Lingual Text Classification of Transliterated Hindi and Malayalam   Transliteration is very common on social media, but transliterated text is
not adequately handled by modern neural models for various NLP tasks. In this
work, we combine data augmentation approaches with a Teacher-Student training
scheme to address this issue in a cross-lingual transfer setting for
fine-tuning state-of-the-art pre-trained multilingual language models such as
mBERT and XLM-R. We evaluate our method on transliterated Hindi and Malayalam,
also introducing new datasets for benchmarking on real-world scenarios: one on
sentiment classification in transliterated Malayalam, and another on crisis
tweet classification in transliterated Hindi and Malayalam (related to the 2013
North India and 2018 Kerala floods). Our method yielded an average improvement
of +5.6% on mBERT and +4.7% on XLM-R in F1 scores over their strong baselines.

13
The categories of this paper are: quant-ph
0
The categories of this paper are: hep-ph
35
The categories of this paper are: mtrl-th
28
The categories of this paper are: alg-geom
16
The categories of this paper are: stat
32
The categories of this paper are: atom-ph
27
The categories of this paper are: comp-gas
10
The categories of this paper are: q-bio
36
The categories of this paper are: cmp-lg
20
The categories of this paper are: acc-phys
2
The categories of this paper are: math
9
The categories of this paper are: nlin
30
The categories of this paper are: q-alg
7
The categories of this paper are: hep-th
18
The categories of this paper are: econ
37
The categories of this paper are: supr-con