collaborators

5 papers

cs.AI2026

OpenHospital: A Thing-in-itself Arena for Evolving and Benchmarking LLM-based Collective Intelligence

Peigen Liu, Rui Ding, Yuren Mao +7

Large Language Model (LLM)-based Collective Intelligence (CI) presents a promising approach to overcoming the data wall and continuously boosting the capabilities of LLM agents. Ho…

cs.RO2026

From Scanning Guidelines to Action: A Robotic Ultrasound Agent with LLM-Based Reasoning

Yuan Bi, Yiping Zhou, Pei Liu +3

Robotic ultrasound offers advantages over free-hand scanning, including improved reproducibility and reduced operator dependency. In clinical practice, US acquisition relies heavil…

cs.MA2025

Agent-Kernel: A MicroKernel Multi-Agent System Framework for Adaptive Social Simulation Powered by LLMs

Yuren Mao, Peigen Liu, Xinjian Wang +11

Multi-Agent System (MAS) developing frameworks serve as the foundational infrastructure for social simulations powered by Large Language Models (LLMs). However, existing frameworks…

cs.CL2025

scAgent: Universal Single-Cell Annotation via a LLM Agent

Yuren Mao, Yu Mi, Peigen Liu +3

Cell type annotation is critical for understanding cellular heterogeneity. Based on single-cell RNA-seq data and deep learning models, good progress has been made in annotating a f…

cs.CL2025

Large-Small Model Collaboration for Enhancing Edge-Deployed Small Models

Yijiang Fan, Peigen Liu, Yuren Mao +5

Edge devices host domain-specific small language models (SLMs) with limited resources, while private clouds offer larger LLMs. We propose G-Boost, an adaptive edge-cloud framework…