3 accepted papers
Large Language Models (LLMs) have shown promising in-context learning abilities. However, conventional In-Context Learning (ICL) approaches are often impeded by length limitations of transformer architecture, which pose challenges when attempting to effectively integrate supervision from a substanti…
Recently, Transformer has been demonstrating promising performance in many NLP tasks and showing a trend of replacing Recurrent Neural Network (RNN). Meanwhile, less attention is drawn to Convolutional Neural Network (CNN) due to its weak ability in capturing sequential and long-distance dependencie…
Emotion recognition from speech is a challenging task. Recent advances in deep learning have led bi-directional recurrent neural network (Bi-RNN) and attention mechanism as a standard method for speech emotion recognition, extracting and attending multi-modal features - audio and text, and then fusi…