3 citations · 7 across the 10 of their papers we have counts for
7 papers · 1 filter
Forging a Dynamic Memory: Retrieval-Guided Continual Learning for Generalist Medical Foundation Models
Zizhi Chen, Yizhen Gao, Minghao Han +4
Multimodal biomedical Vision-Language Models (VLMs) exhibit immense potential in the field of Continual Learning (CL). However, they confront a core dilemma: how to preserve fine-g…
Improving Multimodal Sentiment Analysis via Modality Optimization and Dynamic Primary Modality Selection
Dingkang Yang, Mingcheng Li, Xuecheng Wu +5
Multimodal Sentiment Analysis (MSA) aims to predict sentiment from language, acoustic, and visual data in videos. However, imbalanced unimodal performance often leads to suboptimal…
MMARD: Improving the Min-Max Optimization Process in Adversarial Robustness Distillation
Yuzheng Wang, Zhaoyu Chen, Dingkang Yang +2
Adversarial Robustness Distillation (ARD) is a promising task to boost the robustness of small-capacity models with the guidance of the pre-trained robust teacher. The ARD can be s…
Large Vision-Language Models as Emotion Recognizers in Context Awareness
Yuxuan Lei, Dingkang Yang, Zhaoyu Chen +3
Context-aware emotion recognition (CAER) is a complex and significant task that requires perceiving emotions from various contextual cues. Previous approaches primarily focus on de…
Towards Context-Aware Emotion Recognition Debiasing from a Causal Demystification Perspective via De-confounded Training
Dingkang Yang, Kun Yang, Haopeng Kuang +3
Understanding emotions from diverse contexts has received widespread attention in computer vision communities. The core philosophy of Context-Aware Emotion Recognition (CAER) is to…
Self-Cooperation Knowledge Distillation for Novel Class Discovery
Yuzheng Wang, Zhaoyu Chen, Dingkang Yang +2
Novel Class Discovery (NCD) aims to discover unknown and novel classes in an unlabeled set by leveraging knowledge already learned about known classes. Existing works focus on inst…
De-confounded Data-free Knowledge Distillation for Handling Distribution Shifts
Yuzheng Wang, Dingkang Yang, Zhaoyu Chen +5
Data-Free Knowledge Distillation (DFKD) is a promising task to train high-performance small models to enhance actual deployment without relying on the original training data. Exist…