9 citations · 30 across the 12 of their papers we have counts for
12 papers
PostAlign: Multimodal Grounding as a Corrective Lens for MLLMs
Yixuan Wu, Yang Zhang, Jian Wu +2
Multimodal Large Language Models (MLLMs) excel in vision-language tasks, such as image captioning and visual question answering. However, they often suffer from over-reliance on sp…
TeleOR: Real-time Telemedicine System for Full-Scene Operating Room
Yixuan Wu, Kaiyuan Hu, Qian Shao +3
The advent of telemedicine represents a transformative development in leveraging technology to extend the reach of specialized medical expertise to remote surgeries, a field where…
Multi-Modal CLIP-Informed Protein Editing
Mingze Yin, Hanjing Zhou, Yiheng Zhu +8
Proteins govern most biological functions essential for life, but achieving controllable protein discovery and optimization remains challenging. Recently, machine learning-assisted…
PoCo: A Self-Supervised Approach via Polar Transformation Based Progressive Contrastive Learning for Ophthalmic Disease Diagnosis
Jinhong Wang, Tingting Chen, Jintai Chen +5
Automatic ophthalmic disease diagnosis on fundus images is important in clinical practice. However, due to complex fundus textures and limited annotated data, developing an effecti…
DetToolChain: A New Prompting Paradigm to Unleash Detection Ability of MLLM
Yixuan Wu, Yizhou Wang, Shixiang Tang +5
We present DetToolChain, a novel prompting paradigm, to unleash the zero-shot object detection ability of multimodal large language models (MLLMs), such as GPT-4V and Gemini. Our a…
AI-Enhanced Virtual Reality in Medicine: A Comprehensive Survey
Yixuan Wu, Kaiyuan Hu, Danny Z. Chen +1
With the rapid advance of computer graphics and artificial intelligence technologies, the ways we interact with the world have undergone a transformative shift. Virtual Reality (VR…
Hulk: A Universal Knowledge Translator for Human-Centric Tasks
Yizhou Wang, Yixuan Wu, Weizhen He +8
Human-centric perception tasks, e.g., pedestrian detection, skeleton-based action recognition, and pose estimation, have wide industrial applications, such as metaverse and sports…
OneSeg: Self-learning and One-shot Learning based Single-slice Annotation for 3D Medical Image Segmentation
Yixuan Wu, Bo Zheng, Jintai Chen +2
As deep learning methods continue to improve medical image segmentation performance, data annotation is still a big bottleneck due to the labor-intensive and time-consuming burden…
GCL: Gradient-Guided Contrastive Learning for Medical Image Segmentation with Multi-Perspective Meta Labels
Yixuan Wu, Jintai Chen, Jiahuan Yan +3
Since annotating medical images for segmentation tasks commonly incurs expensive costs, it is highly desirable to design an annotation-efficient method to alleviate the annotation…
MolHF: A Hierarchical Normalizing Flow for Molecular Graph Generation
Yiheng Zhu, Zhenqiu Ouyang, Ben Liao +5
Molecular de novo design is a critical yet challenging task in scientific fields, aiming to design novel molecular structures with desired property profiles. Significant progress h…
T2G-Former: Organizing Tabular Features into Relation Graphs Promotes Heterogeneous Feature Interaction
Jiahuan Yan, Jintai Chen, Yixuan Wu +2
Recent development of deep neural networks (DNNs) for tabular learning has largely benefited from the capability of DNNs for automatic feature interaction. However, the heterogenei…
D-Former: A U-shaped Dilated Transformer for 3D Medical Image Segmentation
Yixuan Wu, Kuanlun Liao, Jintai Chen +4
Computer-aided medical image segmentation has been applied widely in diagnosis and treatment to obtain clinically useful information of shapes and volumes of target organs and tiss…