Multimodal emotion recognition is an important research topic in artificial intelligence.
However, due to problems such as complex environments and inaccurate annotations …

This paper introduces an integrated model designed to analyze topics and sentiments in
textual data simultaneously, recognizing their interdependence. By tackling challenges such …

The rapid advancements in large language models (LLMs) have demonstrated their
potential to accelerate scientific discovery, particularly in automating the process of research …

Affective artificial intelligence and multimodal sentiment analysis play critical roles in
designing safe and effective human-computer interactions and are in diverse applications …

Sentiment analysis (SA) is an effective method for determining public opinion. Social media
posts have been the subject of much research, due to the platforms' enormous and …

We introduce VARM, variant relationship matcher strategy, to identify pairs of variant
products in e-commerce catalogs. Traditional definitions of entity resolution are concerned …

E-commerce platforms would benefit from performing sentiment analysis of their customer's
feedback. However, the vast amount of transaction data makes manual sentiment analysis of …

The Multimodal Emotion Recognition (MER 2024) Challenge focuses on recognizing
emotions through the integration of audio, language, and visual signals, driving …

Central banks use monetary policy for maintaining economic stability. To enhance economic
growth, central banks need to understand market sentiment, as it can influence the …

We introduce VARM, variant relationship matcher strategy, to identify pairs of variant
products in e-commerce catalogs. Traditional definitions of entity resolution are concerned …