The process of creating high-quality labeled data is crucial for training machine-learning
models, but it can be a time-consuming and labor-intensive process. Moreover, manual …

Text augmentation is a popular technique in natural language processing (NLP) that has
been shown to improve the performance of various downstream tasks. The goal of text …

Abstract Counterfactually-Augmented Data (CAD)–minimal editing of sentences to flip the
corresponding labels–has the potential to improve the Out-Of-Distribution (OOD) …

Utilizing information systems is very useful in the current era. Digitizing administration in the
Village is beneficial in the service process to the public. This is seen as a change in service …

Explainability, which is the degree to which an interested stakeholder can understand the
key factors that led to a data-driven model's decision, has been considered an essential …

Background In the domain of natural language processing (NLP), the development and
success of advanced language models are predominantly anchored in the richness of …

Recent surveys on data augmentation for natural language processing have reported
different techniques and advancements in the field. Several frameworks, tools, and …

The automated scoring of student essays is now recognized as a significant development in
both the research and practice of educational testing. The majority of the published studies …

One of the factors that determine the effectiveness of deep learning models for sentiment
analysis is the availability of high-quality training data. Data augmentation is a strategy to …

With the increased use of social networks, spreading propaganda has become more
accessible, making developing propaganda detection methods crucial. However, only some …