5 papers
QASA: Quality-Aware Semantic Augmentation for Robust Multimodal Sentiment Analysis
Jiazhang Liang, Jianheng Dai, Miaosen Luo +2
Multimodal large language models have demonstrated strong ability in capturing semantic representations for multimodal sentiment analysis. Their capacity to learn stable and genera…
SmartPhotoCrafter: Unified Reasoning, Generation and Optimization for Automatic Photographic Image Editing
Ying Zeng, Miaosen Luo, Guangyuan Li +10
Traditional photographic image editing typically requires users to possess sufficient aesthetic understanding to provide appropriate instructions for adjusting image quality and ca…
C2F-Thinker: Coarse-to-Fine Reasoning with Hint-Guided Reinforcement Learning for Multimodal Sentiment Analysis
Miaosen Luo, Zhenhao Yang, Jieshen Long +3
Multimodal sentiment analysis aims to integrate textual, acoustic, and visual information for deep emotional understanding. Despite the progress of multimodal large language models…
Multimodal Large Language Models for End-to-End Affective Computing: Benchmarking and Boosting with Generative Knowledge Prompting
Miaosen Luo, Jiesen Long, Zequn Li +3
Multimodal Affective Computing (MAC) aims to recognize and interpret human emotions by integrating information from diverse modalities such as text, video, and audio. Recent advanc…
Towards Explainable Fusion and Balanced Learning in Multimodal Sentiment Analysis
Miaosen Luo, Yuncheng Jiang, Sijie Mai
Multimodal Sentiment Analysis (MSA) faces two critical challenges: the lack of interpretability in the decision logic of multimodal fusion and modality imbalance caused by disparit…