Assessment and evaluation have long been critical challenges in artificial intelligence (AI)
and natural language processing (NLP). However, traditional methods, whether matching …

Large Language Models (LLMs) have shown impressive performance in natural language
tasks, but their outputs can exhibit undesirable attributes or biases. Existing methods for …

Facial affective behavior analysis (FABA) is crucial for understanding human mental states
from images. However, traditional approaches primarily deploy models to discriminate …

Accurate stock market predictions following earnings reports are crucial for investors.
Traditional methods, particularly classical machine learning models, struggle with these …

Recent advancements in large language models (LLMs) have achieved promising
performances across various applications. Nonetheless, the ongoing challenge of …

In recent years, the rapid advancement of Large Language Models (LLMs) has transformed
the landscape of scientific research, offering unprecedented support across various stages …

Gastrointestinal (GI) tract disorders, ranging from benign polyps to aggressive forms of
cancer, pose significant health challenges globally. Early detection and precise …

The explainability of recommender systems has attracted significant attention in academia
and industry. Many efforts have been made for explainable recommendations, yet …

As Large Language Models (LLMs) are increasingly deployed to handle various natural
language processing (NLP) tasks, concerns regarding the potential negative societal …

This research explores the integration of deep learning and large language models in
speech recognition to improve accuracy and handle complex contexts. Deep neural network …