4 papers
A Comparative Study in Surgical AI: Potential and Limitations of Data, Compute, and Scaling
Kirill Skobelev, Eric Fithian, Yegor Baranovski +9
Recent Artificial Intelligence (AI) models have matched or exceeded human experts in several benchmarks of biomedical task performance, but surgical benchmarks in particular are of…
A Theoretical Framework for Auxiliary-Loss-Free Load Balancing of Sparse Mixture-of-Experts in Large-Scale AI Models
X. Y. Han, Yuan Zhong
In large-scale AI training, Sparse Mixture-of-Experts (s-MoE) layers enable scaling by activating only a small subset of experts per token. An operational challenge in this design…
SurgPhase: Time efficient pituitary tumor surgery phase recognition via an interactive web platform
Yan Meng, Jack Cook, X. Y. Han +12
Accurate surgical phase recognition is essential for analyzing procedural workflows, supporting intraoperative decision-making, and enabling data-driven improvements in surgical ed…
Enhancing Model Context Protocol (MCP) with Context-Aware Server Collaboration
Meenakshi Amulya Jayanti, X. Y. Han
The Model Context Protocol (MCP) (MCP Community, 2025) has emerged as a widely used framework for enabling LLM-based agents to communicate with external tools and services. The ori…