Affective computing is a rapidly growing multidisciplinary field that encompasses computer
science, engineering, psychology, neuroscience, and other related disciplines. Although the …

Emotions are an inherent part of human interactions, and consequently, it is imperative to
develop AI systems that understand and recognize human emotions. During a conversation …

The task of Emotion-Cause Pair Extraction (ECPE) aims to extract all potential clause-pairs
of emotions and their corresponding causes in a document. Unlike the more well-studied …

Text-based emotion prediction is an important task in the field of affective computing. Most
prior work has been restricted to predicting emotions corresponding to a few high-level …

In Emotion Recognition in Conversations (ERC), the emotions of target utterances are
closely dependent on their context. Therefore, existing works train the model to generate the …

More than a decade has passed since the development of FearNot!, an application
designed to help children deal with bullying through role-playing with virtual characters. It …

As an important task in emotion analysis, Multimodal Emotion-Cause Pair Extraction in
conversations (MECPE) aims to extract all the emotion-cause utterance pairs from a …

Emotion detection is a critical technology extensively employed in diverse fields. While the
incorporation of commonsense knowledge has proven beneficial for existing emotion …

Instruction tuned large language models (LLMs), such as ChatGPT, demonstrate remarkable
performance in a wide range of tasks. Despite numerous recent studies that examine the …

Abstract Emotion Recognition in Conversations (ERC) is an important and active research
area. Recent work has shown the benefits of using multiple modalities (eg, text, audio, and …