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

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 …

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

Multimodal affective computing (MAC) has garnered increasing attention due to its broad
applications in analyzing human behaviors and intentions, especially in text-dominated …

This paper presents our winning submission to Subtask 2 of SemEval 2024 Task 3 on
multimodal emotion cause analysis in conversations. We propose a novel Multimodal …

Emotion recognition in conversations (ERC) has wide applications in medical care, human-
computer interaction, and other fields. Unlike the general task of emotion analysis, humans …

Reasoning, a crucial aspect of NLP research, has not been adequately addressed by
prevailing models including Large Language Model. Conversation reasoning, as a critical …

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 …

The aspect term extraction (ATE) task aims to extract aspect terms describing a part or an
attribute of a product from review sentences. Most existing works rely on either general or …

Emotion-cause pair extraction (ECPE) is an extraction task aiming to simultaneously identify
the emotions and causes from the text without emotion annotations. Let ci and cj represent …