86 citations · 129 across the 6 of their papers we have counts for
6 papers
Nonlinearity-Aware LoRA: Structured Gate Adaptation under Low-Rank Constraints
Shuai Yuan, Sudong Cai, Bingzhi Chen +4
Low-rank adaptation (LoRA) is commonly viewed as an update-space approximation to full fine-tuning, yet this view is incomplete for self-gated Transformer feed-forward networks. In…
Cross Modal Fine-Grained Alignment via Granularity-Aware and Region-Uncertain Modeling
Jiale Liu, Haoming Zhou, Yishu Liu +2
Fine-grained image-text alignment is a pivotal challenge in multimodal learning, underpinning key applications such as visual question answering, image captioning, and vision-langu…
Cause-Effect Driven Optimization for Robust Medical Visual Question Answering with Language Biases
Huanjia Zhu, Yishu Liu, Xiaozhao Fang +2
Existing Medical Visual Question Answering (Med-VQA) models often suffer from language biases, where spurious correlations between question types and answer categories are inadvert…
Enhancing Few-Shot Classification without Forgetting through Multi-Level Contrastive Constraints
Bingzhi Chen, Haoming Zhou, Yishu Liu +3
Most recent few-shot learning approaches are based on meta-learning with episodic training. However, prior studies encounter two crucial problems: (1) \textit{the presence of induc…
TransAttUnet: Multi-level Attention-guided U-Net with Transformer for Medical Image Segmentation
Bingzhi Chen, Yishu Liu, Zheng Zhang +2
Accurate segmentation of organs or lesions from medical images is crucial for reliable diagnosis of diseases and organ morphometry. In recent years, convolutional encoder-decoder s…
DS-TransUNet:Dual Swin Transformer U-Net for Medical Image Segmentation
Ailiang Lin, Bingzhi Chen, Jiayu Xu +2
Automatic medical image segmentation has made great progress benefit from the development of deep learning. However, most existing methods are based on convolutional neural network…