Emotional intelligence in large language models (LLMs) is of great importance in Natural
Language Processing. However, the previous research mainly focus on basic sentiment …

Humor, deeply rooted in societal meanings and cultural details, poses a unique challenge
for machines. While advances have been made in natural language processing, real-world …

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

This paper analyzes conventional and deep learning methods for eliminating
electromagnetic interference (EMI) in MRI systems. We compare traditional analytical and …

Prompt engineering, as an efficient and effective way to leverage Large Language Models
(LLM), has drawn a lot of attention from the research community. The existing research …

In the era of social media video platforms, popular``hot-comments''play a crucial role in
attracting user impressions of short-form videos, making them vital for marketing and …

Time roots in applying language models for biomedical applications: models are trained on
historical data and will be deployed for new or future data, which may vary from training …

Emotion cognition in large language models (LLMs) is crucial for enhancing performance
across various applications, such as social media, human-computer interaction, and mental …

The advent of clinical language models integrated into electronic health records (EHR) for
clinical decision support has marked a significant advancement, leveraging the depth of …