Progressive Class Semantic Matching for Semi-supervised Text Classification. (arXiv:2205.10189v1 [cs.CL])

Semi-supervised learning is a promising way to reduce the annotation cost for
text-classification. Combining with pre-trained language models (PLMs), e.g.,
BERT, recent semi-supervised learning methods achieved impressive performance.
In this work, we further investigate the marriage between semi-supervised
learning and a pre-trained language model. Unlike existing approaches that
utilize PLMs only for model parameter initialization, we explore the inherent
topic matching capability inside PLMs for building a more powerful
semi-supervised learning approach. Specifically, we propose a joint
semi-supervised learning process …

arxiv classification semantic semi-supervised text text classification