GPT (Generative Pre-trained Transformer) represents advanced language models that have
significantly reshaped the academic writing landscape. These sophisticated language …

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 …

Due to the lack of historical data, accurate prediction is a great challenge for newly
constructed wind farms (NWFs). How to guarantee satisfactory prediction accuracy with …

Convolutional neural networks have achieved impressive results in areas such as computer
vision tasks. Recently, more complex architectures have been designed that add additional …

Abstract Grammatical Error Correction (GEC) refers to the automatic identification and
amendment of grammatical, spelling, punctuation, and word-positioning errors in …

The sparsity of labelled data is an obstacle to the development of Relation Extraction (RE)
models and the completion of databases in various biomedical areas. While being of high …

Abstract Human Activity Recognition (HAR) has become a significant area of study in the
fields of health, human behavior analysis, the Internet of Things, and human–machine …

Recent advances in machine learning have led to revolutionary breakthroughs in computer
games, image and natural language understanding, and scientific discovery. Foundation …

Speech emotion recognition (SER) is difficult since emotions are complex and dynamic
processes involving multiple dimensions and sub-dimensions. Feature extraction is a …

Contemporary language models heavily rely on large corpora for their training. The larger
the corpus, the better a model can capture various semantic relationships. The issue at hand …