Explainable Multimodal Aspect-Based Sentiment Analysis with Dependency-guided Large Language Model
This paper reformulates MABSA as a generative and explainable task, proposing a unified framework that simultaneously predicts aspect-level sentiment and generates natural language explanations and proposes a dependency-syntax-guided sentiment cue strategy.