Text-Routed MoE Model for Multi-Modal Sentiment Analysis

This paper introduces TEXT, a novel model for Multi-modal Sentiment Analysis (MSA) that leverages explanations from Multi-modal Large Language Models (MLLMs) and incorporates temporal alignment. The key contributions are the use of explanations, a temporal alignment block (combining Mamba and temporal cross-attention), and a text-routed sparse mixture-of-experts with gate fusion. The paper claims state-of-the-art performance across multiple datasets, demonstrating the effectiveness of the proposed approach.