Transformer architectures are highly expressive because they use self-attention
mechanisms to encode long-range dependencies in the input sequences. In this paper, we …

Recently, transformer-based pretrained language models have demonstrated stellar
performance in natural language understanding (NLU) tasks. For example, bidirectional …

This paper proposes a hybrid deep learning emotion classification system (HDECS), a
hybrid multimodal deep learning system designed for emotion classification in a specific …

Relation Extraction (RE) aims to predict the correct relation between two entities from the
given sentence. To obtain the proper relation in Relation Extraction (RE), it is significant to …

As the number of language models has increased, various benchmarks have been
suggested to assess the proficiency of the models in natural language understanding …

Natural language processing refers to the ability of computers to understand text and spoken
words similar to humans. Recently, various machine learning techniques have been used to …

Since understanding a user's request has become a critical task for the artificial intelligence
speakers, capturing intents and finding correct slots along with corresponding slot value is …

Before starting any construction work, providing workers with awareness about past similar
accident cases is effective in preventing mishaps. Based on construction accident reports …

The think-aloud protocol is a valuable tool for investigating readers' cognitive processes
during reading. However, its reliance on experienced human evaluators poses challenges …

Inference plays a key role in reading comprehension. However, assessing inference in
reading is a complex process that relies on the judgment of trained experts. In this study, we …