8 citations · 17 across the 22 of their papers we have counts for
10 papers · 1 filter
AGMixup: Adaptive Graph Mixup for Semi-supervised Node Classification
Weigang Lu, Ziyu Guan, Wei Zhao +4
Mixup is a data augmentation technique that enhances model generalization by interpolating between data points using a mixing ratio in the image domain. Recently, the concept o…
Joint Input and Output Coordination for Class-Incremental Learning
Shuai Wang, Yibing Zhan, Yong Luo +4
Incremental learning is nontrivial due to severe catastrophic forgetting. Although storing a small amount of data on old tasks during incremental learning is a feasible solution, c…
Semantics-Oriented Multitask Learning for DeepFake Detection: A Joint Embedding Approach
Mian Zou, Baosheng Yu, Yibing Zhan +2
In recent years, the multimedia forensics and security community has seen remarkable progress in multitask learning for DeepFake (i.e., face forgery) detection. The prevailing appr…
Harnessing the Power of MLLMs for Transferable Text-to-Image Person ReID
Wentao Tan, Changxing Ding, Jiayu Jiang +3
Text-to-image person re-identification (ReID) retrieves pedestrian images according to textual descriptions. Manually annotating textual descriptions is time-consuming, restricting…
Semantic Contextualization of Face Forgery: A New Definition, Dataset, and Detection Method
Mian Zou, Baosheng Yu, Yibing Zhan +2
In recent years, deep learning has greatly streamlined the process of manipulating photographic face images. Aware of the potential dangers, researchers have developed various tool…
Towards Training A Chinese Large Language Model for Anesthesiology
Zhonghai Wang, Jie Jiang, Yibing Zhan +8
Medical large language models (LLMs) have gained popularity recently due to their significant practical utility. However, most existing research focuses on general medicine, and th…
Affective Computing for Healthcare: Recent Trends, Applications, Challenges, and Beyond
Yuanyuan Liu, Ke Wang, Lin Wei +4
Affective computing, which aims to recognize, interpret, and understand human emotions, provides benefits in healthcare, such as improving patient care and enhancing doctor-patient…
Healthcare Copilot: Eliciting the Power of General LLMs for Medical Consultation
Zhiyao Ren, Yibing Zhan, Baosheng Yu +2
The copilot framework, which aims to enhance and tailor large language models (LLMs) for specific complex tasks without requiring fine-tuning, is gaining increasing attention from…
Towards Alleviating Text-to-Image Retrieval Hallucination for CLIP in Zero-shot Learning
Hanyao Wang, Yibing Zhan, Liu Liu +3
Pretrained cross-modal models, for instance, the most representative CLIP, have recently led to a boom in using pre-trained models for cross-modal zero-shot tasks, considering the…
Large Language Models as an Indirect Reasoner: Contrapositive and Contradiction for Automated Reasoning
Yanfang Zhang, Yiliu Sun, Yibing Zhan +3
Recently, increasing attention has been focused on improving the ability of Large Language Models (LLMs) to perform complex reasoning. Advanced methods, such as Chain-of-Thought (C…