Text classification in natural language processing (NLP) is evolving rapidly, particularly with
the surge in transformer-based models, including large language models (LLM). This paper …

Sentiment analysis is essential for comprehending public opinion, particularly when
considering e-commerce and the expansion of online businesses. Early approaches treated …

The rapid advancement of large language models (LLMs) has sparked interest in data
synthesis techniques, aiming to generate diverse and high-quality synthetic datasets …

Affective Computing (AC), integrating computer science, psychology, and cognitive science
knowledge, aims to enable machines to recognize, interpret, and simulate human emotions …

Controlling the text generated by language models and customizing the content has been a
long-standing challenge. Existing prompting techniques proposed in pursuit of providing …

In e-commerce, opinion summarization is the process of condensing the opinions presented
in product reviews. However, the absence of large amounts of supervised datasets presents …

Pre-trained language models based on masked language modeling (MLM) excel in natural
language understanding (NLU) tasks. While fine-tuned MLM-based encoders consistently …

Aspect-based sentiment analysis (ABSA) identifies mentioned aspects and predicts their
associated sentiments in sentences. With the rapid growth of users' online activities, ABSA …

In the current landscape, smartwatches have gained popularity as wearable devices thanks
to their fitness tracking and health monitoring capabilities. However, the abundance of …

The aspect-based sentiment analysis (ABSA) is a standard NLP task with numerous
approaches and benchmarks, where large language models (LLM) represent the current …