17 citations · 17 across the 5 of their papers we have counts for
5 papers
Volumetric Radiology AI in the Era of Multimodal Large Language Models
Zanting Ye, Shengyuan Liu, Xin Liu +16
Advances in multimodal large language models (MLLMs) are extending radiological artificial intelligence (AI) beyond task-specific image analysis toward multimodal understanding and…
Towards Autonomous and Auditable Medical Imaging Model Development
Shengyuan Liu, Jia-Xuan Jiang, Boyun Zheng +8
Large language model (LLM) agents are beginning to automate machine learning engineering (MLE) by coupling planning, code execution, debugging, and empirical feedback. Translating…
Synergizing Discriminative Exemplars and Self-Refined Experience for MLLM-based In-Context Learning in Medical Diagnosis
Wenkai Zhao, Zipei Wang, Mengjie Fang +3
General Multimodal Large Language Models (MLLMs) often underperform in capturing domain-specific nuances in medical diagnosis, trailing behind fully supervised baselines. Although…
MLLM-Enhanced Face Forgery Detection: A Vision-Language Fusion Solution
Siran Peng, Zipei Wang, Li Gao +5
Reliable face forgery detection algorithms are crucial for countering the growing threat of deepfake-driven disinformation. Previous research has demonstrated the potential of Mult…
Image Deconvolution with Deep Image and Kernel Priors
Zhunxuan Wang, Zipei Wang, Qiqi Li +1
Image deconvolution is the process of recovering convolutional degraded images, which is always a hard inverse problem because of its mathematically ill-posed property. On the succ…