Deep neural classifiers trained with cross-entropy loss (CE loss) often
...
Etremely Weakly Supervised Text Classification (XWS-TC) refers to text
c...
We explore the use of large language models (LLMs) for zero-shot semanti...
Multilingual transformer language models have recently attracted much
at...
Manually annotating datasets requires domain experts to read through man...
Weakly supervised text classification methods typically train a deep neu...
Existing text classification methods mainly focus on a fixed label set,
...
Backdoor attack introduces artificial vulnerabilities into the model by
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Hashtag annotation for microblog posts has been recently formulated as a...
In this paper, we explore to conduct text classification with extremely ...
Hierarchical classification is supervised multi-class classification pro...
Review score prediction of text reviews has recently gained a lot of
att...
We present a feature vector formation technique for documents - Sparse
C...