3 citations · 7 across the 10 of their papers we have counts for
10 papers
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…
Improving Factuality in Large Language Models via Decoding-Time Hallucinatory and Truthful Comparators
Dingkang Yang, Dongling Xiao, Jinjie Wei +4
Despite their remarkable capabilities, Large Language Models (LLMs) are prone to generate responses that contradict verifiable facts, i.e., unfaithful hallucination content. Existi…
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…
Debiased Multimodal Understanding for Human Language Sequences
Zhi Xu, Dingkang Yang, Mingcheng Li +5
Human multimodal language understanding (MLU) is an indispensable component of expression analysis (e.g., sentiment or humor) from heterogeneous modalities, including visual postur…
Towards Multimodal Sentiment Analysis Debiasing via Bias Purification
Dingkang Yang, Mingcheng Li, Dongling Xiao +7
Multimodal Sentiment Analysis (MSA) aims to understand human intentions by integrating emotion-related clues from diverse modalities, such as visual, language, and audio. Unfortuna…