5 papers
VentAgent: When LLMs Learn to Breathe -- Multi-Objective Arbitration for ARDS Ventilation
Teqi Hao, Yuxuan Fu, Xiaoyu Tan +4
Mechanical ventilation for Acute Respiratory Distress Syndrome (ARDS) requires balancing competing physiological goals, including oxygenation, lung protection, and acid-base homeos…
Human-in-the-Loop Multi-Agent Ventilator Decision Support with Contextual Bandit Preference Learning
Sijia Li, Xiaoyu Tan, Qixing Wang +7
Ventilator decision support requires sequential decisions that track evolving physiology and disease trajectories while respecting safety boundaries and clinician specific tuning s…
InterveneBench: Benchmarking LLMs for Intervention Reasoning and Causal Study Design in Real Social Systems
Shaojie Shi, Zhengyu Shi, Lingran Zheng +15
Causal inference in social science relies on end-to-end, intervention-centered research-design reasoning grounded in real-world policy interventions, but current benchmarks fail to…
PRISM: Festina Lente Proactivity -- Risk-Sensitive, Uncertainty-Aware Deliberation for Proactive Agents
Yuxuan Fu, Xiaoyu Tan, Teqi Hao +2
Proactive agents must decide not only what to say but also whether and when to intervene. Many current systems rely on brittle heuristics or indiscriminate long reasoning, which of…
Reflective Personalization Optimization: A Post-hoc Rewriting Framework for Black-Box Large Language Models
Teqi Hao, Xioayu Tan, Shaojie Shi +2
The personalization of black-box large language models (LLMs) is a critical yet challenging task. Existing approaches predominantly rely on context injection, where user history is…