Unveiling Multimodal Sentiment Analysis Biases with Counterfactual Inference

The author presents a Multimodal Counterfactual Inference Sentiment (MCIS) framework to address harmful biases in Multimodal Sentiment Analysis, focusing on label and context biases. By leveraging causal inference and counterfactual intuition, MCIS aims to improve model performance by purifying biases.