1 citations · 1 across the 3 of their papers we have counts for
3 papers
eess.IV2025
Exposing and Mitigating Calibration Biases and Demographic Unfairness in MLLM Few-Shot In-Context Learning for Medical Image Classification
Xing Shen, Justin Szeto, Mingyang Li +2
Multimodal large language models (MLLMs) have enormous potential to perform few-shot in-context learning in the context of medical image analysis. However, safe deployment of these…
cs.MM2024★ 1 cited
Early Joint Learning of Emotion Information Makes MultiModal Model Understand You Better
Mengying Ge, Mingyang Li, Dongkai Tang +7
In this paper, we present our solutions for emotion recognition in the sub-challenges of Multimodal Emotion Recognition Challenge (MER2024). To mitigate the modal competition issue…
cs.CV2024
Video Emotion Open-vocabulary Recognition Based on Multimodal Large Language Model
Mengying Ge, Dongkai Tang, Mingyang Li
Multimodal emotion recognition is a task of great concern. However, traditional data sets are based on fixed labels, resulting in models that often focus on main emotions and ignor…