This report presents a study on the emotional dialogue capability of ChatGPT, an advanced
language model developed by OpenAI. The study evaluates the performance of ChatGPT on …

Emotion Cause Extraction Field (ECEF) focuses on the cause that triggers an emotion in a
document. Traditional ECEF aims to extract the cause based on a given emotion while …

Capturing complex contextual dependencies plays a vital role in Emotion Recognition in
Conversations (ERC). Previous studies have predominantly focused on speaker-aware …

The ability to understand emotions is an essential component of human-like artificial
intelligence, as emotions greatly influence human cognition, decision making, and social …

Abstract Emotion Cause Triplet Extraction in Conversations (ECTEC) aims to simultaneously
extract emotion utterances, emotion categories, and cause utterances from conversations …

As an emerging research topic in natural language processing community, emotion
recognition in multi-party conversations has attained increasing interest. Previous …

Multi-Modal Emotion Recognition in Conversations (MMERC) is an increasingly active
research field that leverages multi-modal signals to understand the feelings behind each …

Emotion cause extraction in conversations, the task of recognizing and extracting the causes
behind the emotions in a conversation, is a new and under-explored task. It was previously …

The multimodal emotion-cause pair extraction (MECPE) task aims to detect the emotions,
causes, and emotion-cause pairs from multimodal conversations. Existing methods for this …

Abstract The Causal Emotion Entailment (CEE) task aims to extract all potential pairs of
emotions and corresponding causes from the unannotated emotion document in the …