most citedSurgVLM: A Large Vision-Language Model and Systematic Evaluation Benchmark for Surgical Intelligence

2 citations · 2 across the 7 of their papers we have counts for

collaborators

10 papers

eess.IV2026

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…

cs.RO2026

Instrument-Splatting++: Towards Controllable Surgical Instrument Digital Twin Using Gaussian Splatting

Shuojue Yang, Zijian Wu, Chengjiaao Liao +5

High-quality and controllable digital twins of surgical instruments are critical for Real2Sim in robot-assisted surgery, as they enable realistic simulation, synthetic data generat…

cs.AI2026

Surg: A Spectrum of Large-Scale Multimodal Data and Foundation Models for Surgical Intelligence

Zhitao Zeng, Mengya Xu, Jian Jiang +13

Surgical intelligence has the potential to improve the safety and consistency of surgical care, yet most existing surgical AI frameworks remain task-specific and struggle to genera…

cs.CV2026

3DMedAgent: Unified Perception-to-Understanding for 3D Medical Analysis

Ziyue Wang, Linghan Cai, Chang Han Low +8

3D CT analysis spans a continuum from low-level perception to high-level clinical understanding. Existing 3D-oriented analysis methods adopt either isolated task-specific modeling…

cs.CV2026

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…

cs.MA2025

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…