Instruct: Identify the main and secondary category of Arxiv papers based on the titles and abstracts
Query: Achieving Forgetting Prevention and Knowledge Transfer in Continual
  Learning   Continual learning (CL) learns a sequence of tasks incrementally with the
goal of achieving two main objectives: overcoming catastrophic forgetting (CF)
and encouraging knowledge transfer (KT) across tasks. However, most existing
techniques focus only on overcoming CF and have no mechanism to encourage KT,
and thus do not do well in KT. Although several papers have tried to deal with
both CF and KT, our experiments show that they suffer from serious CF when the
tasks do not have much shared knowledge. Another observation is that most
current CL methods do not use pre-trained models, but it has been shown that
such models can significantly improve the end task performance. For example, in
natural language processing, fine-tuning a BERT-like pre-trained language model
is one of the most effective approaches. However, for CL, this approach suffers
from serious CF. An interesting question is how to make the best use of
pre-trained models for CL. This paper proposes a novel model called CTR to
solve these problems. Our experimental results demonstrate the effectiveness of
CTR

15
The categories of this paper are: nucl-ex
27
The categories of this paper are: comp-gas
33
The categories of this paper are: plasm-ph
28
The categories of this paper are: alg-geom
37
The categories of this paper are: supr-con
6
The categories of this paper are: astro-ph
29
The categories of this paper are: funct-an
13
The categories of this paper are: quant-ph
7
The categories of this paper are: hep-th
8
The categories of this paper are: hep-ex
4
The categories of this paper are: cond-mat
34
The categories of this paper are: chem-ph
23
The categories of this paper are: solv-int
3
The categories of this paper are: physics
31
The categories of this paper are: ao-sci
14
The categories of this paper are: math-ph