3 accepted papers
Multimodal Sentiment Analysis (MSA) aims to integrate textual, acoustic, and visual information to predict sentiment polarity. With the emergence of Large Language Models (LLMs), existing studies commonly employ learnable queries to compress audio-visual representations and feed them as soft prompts
Automatic depression detection provides cues for early clinical intervention by clinicians. Clinical interviews for depression detection involve dialogues centered around multiple themes. Existing studies primarily design end-to-end neural network models to capture the hierarchical structure of clin…
Human multimodal sentiment analysis is a challenging task that devotes to extract and integrate information from multiple resources, such as language, acoustic and visual information. Recently, multimodal adaptation gate (MAG), an attachment to transformer-based pre-trained language representation m…