Instruct: Identify the main and secondary category of Arxiv papers based on the titles and abstracts
Query: Can you tell? SSNet -- a Sagittal Stratum-inspired Neural Network
  Framework for Sentiment Analysis   When people try to understand nuanced language they typically process
multiple input sensor modalities to complete this cognitive task. It turns out
the human brain has even a specialized neuron formation, called sagittal
stratum, to help us understand sarcasm. We use this biological formation as the
inspiration for designing a neural network architecture that combines
predictions of different models on the same text to construct robust, accurate
and computationally efficient classifiers for sentiment analysis and study
several different realizations. Among them, we propose a systematic new
approach to combining multiple predictions based on a dedicated neural network
and develop mathematical analysis of it along with state-of-the-art
experimental results. We also propose a heuristic-hybrid technique for
combining models and back it up with experimental results on a representative
benchmark dataset and comparisons to other methods to show the advantages of
the new approaches.

30
The categories of this paper are: q-alg
11
The categories of this paper are: hep-lat
0
The categories of this paper are: hep-ph
28
The categories of this paper are: alg-geom
29
The categories of this paper are: funct-an
26
The categories of this paper are: bayes-an
3
The categories of this paper are: physics
37
The categories of this paper are: supr-con
25
The categories of this paper are: patt-sol
35
The categories of this paper are: mtrl-th
15
The categories of this paper are: nucl-ex
34
The categories of this paper are: chem-ph
18
The categories of this paper are: econ
19
The categories of this paper are: eess
6
The categories of this paper are: astro-ph
7
The categories of this paper are: hep-th