collaborators

9 papers

cs.CV2026

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…

cs.CV2026

MedPruner: Training-Free Hierarchical Token Pruning for Efficient 3D Medical Image Understanding in Vision-Language Models

Shengyuan Liu, Zanting Ye, Yunrui Lin +6

While specialized Medical Vision-Language Models (VLMs) have achieved remarkable success in interpreting 2D and 3D medical modalities, their deployment for 3D volumetric data remai…

cs.SE2026

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…

q-bio.QM2026

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…

cs.CV2026

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…

cs.CV2026

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…