A rubric-based controlled comparison of frontier language models on expert-authored clinical reasoning tasks

arXiv:2607.02175 · cs.AI, cs.LG · Submitted 2026-07-02 · Read on arXiv

cs.AI, cs.LG

Submitted: 2026-07-02

Updated: 2026-09-23

Terminology

• Benchmark — 14× in this paper · explained in 2 episodes
• Accuracy — 5× in this paper · explained in 1 episode
• Calibration — 4× in this paper · explained in 7 episodes
• Resource Constraints — 2× in this paper · explained in 3 episodes
• Alignment — 1× in this paper · explained in 1 episode
• Consistency — 1× in this paper · explained in 3 episodes
• Failure Modes — 1× in this paper · explained in 3 episodes
• Failure Taxonomy — 1× in this paper · explained in 2 episodes
• LLM-as-a-Judge — 1× in this paper · explained in 3 episodes
• Multimodal Reasoning — 1× in this paper · explained in 5 episodes
• Reinforcement Learning — 1× in this paper · explained in 4 episodes
• Reward Hacking — 1× in this paper · explained in 8 episodes
• Scaffolding — 1× in this paper · explained in 3 episodes
• Verifiable Rewards — 1× in this paper · explained in 2 episodes

Sources

• Rubrics as Rewards: Reinforcement Learning Beyond Verifiable Domains
• OpenRubrics: Towards Scalable Synthetic Rubric Generation for Reward Modeling and LLM Alignment
• ER-Reason: A Benchmark Dataset for LLM Clinical Reasoning in the Emergency Room
• Advancing Conversational Diagnostic AI with Multimodal Reasoning

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