Instruct: Identify the main and secondary category of Arxiv papers based on the titles and abstracts
Query: Tracking Typological Traits of Uralic Languages in Distributed Language
  Representations   Although linguistic typology has a long history, computational approaches
have only recently gained popularity. The use of distributed representations in
computational linguistics has also become increasingly popular. A recent
development is to learn distributed representations of language, such that
typologically similar languages are spatially close to one another. Although
empirical successes have been shown for such language representations, they
have not been subjected to much typological probing. In this paper, we first
look at whether this type of language representations are empirically useful
for model transfer between Uralic languages in deep neural networks. We then
investigate which typological features are encoded in these representations by
attempting to predict features in the World Atlas of Language Structures, at
various stages of fine-tuning of the representations. We focus on Uralic
languages, and find that some typological traits can be automatically inferred
with accuracies well above a strong baseline.

9
The categories of this paper are: nlin
3
The categories of this paper are: physics
15
The categories of this paper are: nucl-ex
27
The categories of this paper are: comp-gas
4
The categories of this paper are: cond-mat
6
The categories of this paper are: astro-ph
31
The categories of this paper are: ao-sci
11
The categories of this paper are: hep-lat
21
The categories of this paper are: adap-org
18
The categories of this paper are: econ
14
The categories of this paper are: math-ph
8
The categories of this paper are: hep-ex
16
The categories of this paper are: stat
26
The categories of this paper are: bayes-an
29
The categories of this paper are: funct-an
20
The categories of this paper are: acc-phys