416 citations · 729 across the 10 of their papers we have counts for
31 papers
ViKL: A Mammography Interpretation Framework via Multimodal Aggregation of Visual-knowledge-linguistic Features
Xin Wei, Yaling Tao, Changde Du +3
Mammography is the primary imaging tool for breast cancer diagnosis. Despite significant strides in applying deep learning to interpret mammography images, efforts that focus predo…
Uncertainty Estimation of Large Language Models in Medical Question Answering
Jiaxin Wu, Yizhou Yu, Hong-Yu Zhou
Large Language Models (LLMs) show promise for natural language generation in healthcare, but risk hallucinating factually incorrect information. Deploying LLMs for medical question…
Cross-Dimensional Medical Self-Supervised Representation Learning Based on a Pseudo-3D Transformation
Fei Gao, Siwen Wang, Fandong Zhang +5
Medical image analysis suffers from a shortage of data, whether annotated or not. This becomes even more pronounced when it comes to 3D medical images. Self-Supervised Learning (SS…
OVER-NAV: Elevating Iterative Vision-and-Language Navigation with Open-Vocabulary Detection and StructurEd Representation
Ganlong Zhao, Guanbin Li, Weikai Chen +1
Recent advances in Iterative Vision-and-Language Navigation (IVLN) introduce a more meaningful and practical paradigm of VLN by maintaining the agent's memory across tours of scene…
DreamDA: Generative Data Augmentation with Diffusion Models
Yunxiang Fu, Chaoqi Chen, Yu Qiao +1
The acquisition of large-scale, high-quality data is a resource-intensive and time-consuming endeavor. Compared to conventional Data Augmentation (DA) techniques (e.g. cropping and…
RegionGPT: Towards Region Understanding Vision Language Model
Qiushan Guo, Shalini De Mello, Hongxu Yin +5
Vision language models (VLMs) have experienced rapid advancements through the integration of large language models (LLMs) with image-text pairs, yet they struggle with detailed reg…