1 citations · 1 across the 8 of their papers we have counts for
8 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…
Claw-Eval-Live: A Live Agent Benchmark for Evolving Real-World Workflows
Chenxin Li, Zhengyang Tang, Mingxin Huang +8
LLM agents are expected to complete end-to-end units of work across software tools, business services, and local workspaces. Yet many agent benchmarks freeze a curated task set at…
Topology-Guided Biomechanical Profiling: A White-Box Framework for Opportunistic Screening of Spinal Instability on Routine CT
Zanting Ye, Xuanbin Wu, Guoqing Zhong +9
Routine oncologic computed tomography (CT) presents an ideal opportunity for screening spinal instability, yet prophylactic stabilization windows are frequently missed due to the c…
MedSAM-Agent: Empowering Interactive Medical Image Segmentation with Multi-turn Agentic Reinforcement Learning
Shengyuan Liu, Liuxin Bao, Qi Yang +6
Medical image segmentation is evolving from task-specific models toward generalizable frameworks. Recent research leverages Multi-modal Large Language Models (MLLMs) as autonomous…
Unveiling and Bridging the Functional Perception Gap in MLLMs: Atomic Visual Alignment and Hierarchical Evaluation via PET-Bench
Zanting Ye, Xiaolong Niu, Xuanbin Wu +14
While Multimodal Large Language Models (MLLMs) have demonstrated remarkable proficiency in tasks such as abnormality detection and report generation for anatomical modalities, thei…