Instruct: Identify the main and secondary category of Arxiv papers based on the titles and abstracts
Query: Lifelong Learning of Hate Speech Classification on Social Media   Existing work on automated hate speech classification assumes that the
dataset is fixed and the classes are pre-defined. However, the amount of data
in social media increases every day, and the hot topics changes rapidly,
requiring the classifiers to be able to continuously adapt to new data without
forgetting the previously learned knowledge. This ability, referred to as
lifelong learning, is crucial for the real-word application of hate speech
classifiers in social media. In this work, we propose lifelong learning of hate
speech classification on social media. To alleviate catastrophic forgetting, we
propose to use Variational Representation Learning (VRL) along with a memory
module based on LB-SOINN (Load-Balancing Self-Organizing Incremental Neural
Network). Experimentally, we show that combining variational representation
learning and the LB-SOINN memory module achieves better performance than the
commonly-used lifelong learning techniques.

17
The categories of this paper are: q-fin
9
The categories of this paper are: nlin
36
The categories of this paper are: cmp-lg
28
The categories of this paper are: alg-geom
11
The categories of this paper are: hep-lat
30
The categories of this paper are: q-alg
32
The categories of this paper are: atom-ph
15
The categories of this paper are: nucl-ex
33
The categories of this paper are: plasm-ph
19
The categories of this paper are: eess
31
The categories of this paper are: ao-sci
37
The categories of this paper are: supr-con
13
The categories of this paper are: quant-ph
12
The categories of this paper are: nucl-th
29
The categories of this paper are: funct-an
7
The categories of this paper are: hep-th