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cs.AI2026
MEA: A Reward-Driven Multi-Agent System for Faithful Model Explanations
Yuyang Cheng, Raghav Kaushik Ravi, Srivarshinee Sridhar +3
Recent years have seen the employment of a plethora of machine learning (ML) models in high-stakes domains, but they remain largely opaque to the practitioners who act on their pre…
cs.AI2026
The Clinician's Veto: Navigating Trust, Liability, and Uncertainty in Autonomous AI Prescribing
Eileanor LaRocco, Sarah Tan, Adarsh Subbaswamy +4
Autonomous AI systems are transitioning from advisory roles to autonomous ones for medication prescriptions. Recent U.S. bill H.R. 238 and Utah's prescription-renewal pilot program…
cs.AI2026
CURE-Med: Curriculum-Informed Reinforcement Learning for Multilingual Medical Reasoning
Eric Onyame, Akash Ghosh, Subhadip Baidya +3
While large language models (LLMs) have shown to perform well on monolingual mathematical and commonsense reasoning, they remain unreliable for multilingual medical reasoning appli…