Instruct: Identify the main and secondary category of Arxiv papers based on the titles and abstracts
Query: LegalNLP -- Natural Language Processing methods for the Brazilian Legal
  Language   We present and make available pre-trained language models (Phraser, Word2Vec,
Doc2Vec, FastText, and BERT) for the Brazilian legal language, a Python package
with functions to facilitate their use, and a set of demonstrations/tutorials
containing some applications involving them. Given that our material is built
upon legal texts coming from several Brazilian courts, this initiative is
extremely helpful for the Brazilian legal field, which lacks other open and
specific tools and language models. Our main objective is to catalyze the use
of natural language processing tools for legal texts analysis by the Brazilian
industry, government, and academia, providing the necessary tools and
accessible material.

7
The categories of this paper are: hep-th
34
The categories of this paper are: chem-ph
25
The categories of this paper are: patt-sol
5
The categories of this paper are: gr-qc
26
The categories of this paper are: bayes-an
30
The categories of this paper are: q-alg
23
The categories of this paper are: solv-int
27
The categories of this paper are: comp-gas
11
The categories of this paper are: hep-lat
16
The categories of this paper are: stat
20
The categories of this paper are: acc-phys
10
The categories of this paper are: q-bio
9
The categories of this paper are: nlin
35
The categories of this paper are: mtrl-th
19
The categories of this paper are: eess
15
The categories of this paper are: nucl-ex