Papers by Qiao Zhuang

2 papers
Beyond Benchmarks: A Capability-Based Maturity Model for Systematic AI Integration in Hospitals (2026.findings-acl)

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Challenge: Current Large Language Models (LLMs) excel in standardized tests focused on medical knowledge recall, but not in real-world healthcare scenarios.
Approach: They propose a "capability-based hospital AI Maturity Model" framework that categorizes capabilities into distinct maturity levels . medical artificial intelligence is currently at a critical transition stage from technical verification to deep clinical integration .
Outcome: The proposed model provides a clear, stepwise evolutionary path for hospitals from foundational infrastructure construction to ubiquitous intelligence.
On-the-Fly VLA Adaptation via Test-Time Reinforcement Learning (2026.acl-long)

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Challenge: Existing vision-language-action models are unsuitable for simulated or physical-world deployments . current methods fail when confronted with inherent real-world dynamic variability.
Approach: They propose a test-time reinforcement learning framework that enables on-the-fly policy adaptation during inference.
Outcome: Empirical results show that the proposed framework improves adaptability, stability and task success in dynamic, previously unseen scenarios.

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