User-generated content on various Internet platforms is growing explosively, and contains
valuable information that helps decision-making. However, extracting this information …

Mainstream approaches for unsupervised domain adaptation (UDA) learn domain-invariant
representations to narrow the domain shift, which are empirically effective but theoretically …

Cross-domain sentiment classification aims to address the lack of massive amounts of
labeled data. It demands to predict sentiment polarity on a target domain utilizing a classifier …

Cross-domain sentiment analysis has achieved promising results with the help of pre-
trained language models. As GPT-3 appears, prompt tuning has been widely explored to …

Abstract Distantly-Supervised Named Entity Recognition (DS-NER) effectively alleviates the
data scarcity problem in NER by automatically generating training samples. Unfortunately …

Cross-domain emotion classification aims to leverage useful information in a source domain
to help predict emotion polarity in a target domain in a unsupervised or semi-supervised …

Text style transfer without parallel data has achieved some practical success. However, in
the scenario where less data is available, these methods may yield poor performance. In this …