6 papers
GRCF: Two-Stage Groupwise Ranking and Calibration Framework for Multimodal Sentiment Analysis
Manning Gao, Leheng Zhang, Shiqin Han +3
Most Multimodal Sentiment Analysis research has focused on point-wise regression. While straightforward, this approach is sensitive to label noise and neglects whether one sample i…
Beyond Cosine Similarity: Magnitude-Aware CLIP for No-Reference Image Quality Assessment
Zhicheng Liao, Dongxu Wu, Zhenshan Shi +5
Recent efforts have repurposed the Contrastive Language-Image Pre-training (CLIP) model for No-Reference Image Quality Assessment (NR-IQA) by measuring the cosine similarity betwee…
Towards Minimal Causal Representations for Human Multimodal Language Understanding
Menghua Jiang, Yuncheng Jiang, Haifeng Hu +1
Human Multimodal Language Understanding (MLU) aims to infer human intentions by integrating related cues from heterogeneous modalities. Existing works predominantly follow a ``lear…
Uncertainty-Aware Collaborative System of Large and Small Models for Multimodal Sentiment Analysis
Shiqin Han, Manning Gao, Menghua Jiang +3
Multimodal Large Language Models (MLLMs) have notably enhanced the performance of Multimodal Sentiment Analysis (MSA), yet their massive parameter scale leads to excessive resource…
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…