Affective computing, which aims to recognize, interpret, and understand human emotions,
provides benefits in healthcare, such as improving patient care and enhancing doctor …

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

The emergence of social media has made the spread of misinformation easier. In the
financial domain, the accuracy of information is crucial for various aspects of financial …

The global rise in mental disorders, particularly in workplaces, necessitated innovative and
scalable solutions for delivering therapy. Large Language Model (LLM)-based mental health …

The internet has brought both benefits and harms to society. A prime example of the latter is
misinformation, including conspiracy theories, which flood the web. Recent advances in …

Multimodal Multi-Label Emotion Recognition (MMER) aims to identify one or more emotion
categories expressed by an utterance of a speaker. Despite obtaining promising results …

Sentiment analysis and emotion detection are critical research areas in natural language
processing (NLP), offering benefits to numerous downstream tasks. Despite the widespread …

Multi-modal sarcasm detection (MSD) presents a formidable and intricate endeavor. Despite
strides made by extant models, two principal hurdles persist: Firstly, prevailing …

Context-aware emotion recognition (CAER) is a complex and significant task that requires
perceiving emotions from various contextual cues. Previous approaches primarily focus on …

Human emotions are often not expressed directly, but regulated according to internal
processes and social display rules. For affective computing systems, an understanding of …