collaborators

5 papers

cs.AI2026

POLAR-Bench: A Diagnostic Benchmark for Privacy-Utility Trade-offs in LLM Agents

Qiaoyuan Zheng, Yiqu Yang, Qi Gao +1

LLM agents increasingly have access to private user data and act on the user's behalf when interacting with third-party systems. The user defines what may and must not be shared, a…

cs.CL2026

Evolving Interactive Diagnostic Agents in a Virtual Clinical Environment

Pengcheng Qiu, Chaoyi Wu, Junwei Liu +11

We present a framework for training large language models (LLMs) as diagnostic agents with reinforcement learning, enabling them to manage multi-turn interactive diagnostic process…

cs.CL2026

End-to-End Agentic RAG System Training for Traceable Diagnostic Reasoning

Qiaoyu Zheng, Yuze Sun, Chaoyi Wu +8

The integration of Large Language Models (LLMs) into healthcare is constrained by knowledge limitations, hallucinations, and a disconnect from Evidence-Based Medicine (EBM). While…

cs.CV2025

How Well Can Modern LLMs Act as Agent Cores in Radiology Environments?

Qiaoyu Zheng, Chaoyi Wu, Pengcheng Qiu +4

We introduce RadA-BenchPlat, an evaluation platform that benchmarks the performance of large language models (LLMs) act as agent cores in radiology environments using 2,200 radiolo…

cs.CV2025

M^3Builder: A Multi-Agent System for Automated Machine Learning in Medical Imaging

Jinghao Feng, Qiaoyu Zheng, Chaoyi Wu +4

Agentic AI systems have gained significant attention for their ability to autonomously perform complex tasks. However, their reliance on well-prepared tools limits their applicabil…