9 papers
Beyond Few-Step Inference: Accelerating Video Diffusion Transformer Model Serving with Inter-Request Caching Reuse
Hao Liu, Ye Huang, Chenghuan Huang +5
Video Diffusion Transformer (DiT) models are a dominant approach for high-quality video generation but suffer from high inference cost due to iterative denoising. Existing caching…
UniSurgSAM: A Unified Promptable Model for Reliable Surgical Video Segmentation
Haofeng Liu, Ziyue Wang, Alex Y. W. Kong +6
Surgical video segmentation is fundamental to computer-assisted surgery. In practice, surgeons need to dynamically specify targets throughout extended procedures, using heterogeneo…
SurgFed: Language-guided Multi-Task Federated Learning for Surgical Video Understanding
Zheng Fang, Ziwei Niu, Ziyue Wang +5
Surgical scene Multi-Task Federated Learning (MTFL) is essential for robot-assisted minimally invasive surgery (RAS) but remains underexplored in surgical video understanding due t…
SurGo-R1: Benchmarking and Modeling Contextual Reasoning for Operative Zone in Surgical Video
Guanyi Qin, Xiaozhen Wang, Zhu Zhuo +7
Minimally invasive surgery has dramatically improved patient operative outcomes, yet identifying safe operative zones remains challenging in critical phases, requiring surgeons to…
SurgSLOT: Segment Anything in Surgical Videos via Semantic Long-term Tracking
Haofeng Liu, Ziyue Wang, Sudhanshu Mishra +8
Surgical scene understanding demands temporally consistent tracking of instruments and tissues. For clinical use, such tracking should generalize to new centers and procedure types…
CARES: Collaborative Agentic Reasoning for Error Detection in Surgery
Chang Han Low, Zhu Zhuo, Ziyue Wang +11
Robotic-assisted surgery (RAS) introduces complex challenges that current surgical error detection methods struggle to address effectively due to limited training data and methodol…