QASA: Quality-Aware Semantic Augmentation for Robust Multimodal Sentiment Analysis 事件

QASA: Quality-Aware Semantic Augmentation for Robust Multimodal Sentiment Analysis arXiv:2601.06870v2 Announce Type: replace-cross Abstract: Multimodal large language models have demonstrated strong ability in capturing semantic representations for multimodal sentiment analysis. Their capacity to learn stable and generalizable multimodal features is limited, however, by the scarcity of high-quality training data. To address this, we propose QASA (Quality-Aware Semantic Augmentation), which uses