Instruct: Identify the main and secondary category of Arxiv papers based on the titles and abstracts
Query: DeepMath - Deep Sequence Models for Premise Selection   We study the effectiveness of neural sequence models for premise selection in
automated theorem proving, one of the main bottlenecks in the formalization of
mathematics. We propose a two stage approach for this task that yields good
results for the premise selection task on the Mizar corpus while avoiding the
hand-engineered features of existing state-of-the-art models. To our knowledge,
this is the first time deep learning has been applied to theorem proving on a
large scale.

29
The categories of this paper are: funct-an
8
The categories of this paper are: hep-ex
3
The categories of this paper are: physics
7
The categories of this paper are: hep-th
35
The categories of this paper are: mtrl-th
5
The categories of this paper are: gr-qc
27
The categories of this paper are: comp-gas
4
The categories of this paper are: cond-mat
10
The categories of this paper are: q-bio
31
The categories of this paper are: ao-sci
24
The categories of this paper are: dg-ga
30
The categories of this paper are: q-alg
21
The categories of this paper are: adap-org
17
The categories of this paper are: q-fin
36
The categories of this paper are: cmp-lg
13
The categories of this paper are: quant-ph