Semi-supervised text classification (SSTC) has gained increasing attention due to its ability
to leverage unlabeled data. However, existing approaches based on pseudo-labeling suffer …

In the realm of semi-supervised graph learning, pseudo-labeling is a pivotal strategy to
utilize both labeled and unlabeled nodes for model training. Currently, confidence score is …

Unsupervised domain adaptation (UDA) is a pivotal form in machine learning to extend the
in-domain model to the distinctive target domains where the data distributions differ. Most …

Understanding what leads to emotions during large-scale crises is important as it can
provide groundings for expressed emotions and subsequently improve the understanding of …

The debate surrounding gun control and gun regulation in the United States has intensified
in the wake of numerous mass shooting events. As perspectives on this matter vary, it …

We describe our models for the Pragmatic Tagging of Peer Reviews Shared Task at the 10th
Workshop on Argument Mining at EMNLP-2023. We trained multiple sentence classification …

Active learning is an iterative labeling process that is used to obtain a small labeled subset,
despite the absence of labeled data, thereby enabling to train a model for supervised tasks …

With the increasing importance of user data privacy, it is crucial for individuals to understand
how companies handle their information. While considerable research has been conducted …

In recent years, social media platforms have become increasingly popular, with comment
sections serving as essential spaces to express and discuss opinions and share information …