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RubricsTree transforms the evaluation landscape for personal health agents, achieving expert alignment and significant performance gains while addressing the scalability challenge in clinical deployment.
Generalization in LLMs hinges on training reward saturation dynamics, with reasoning faithfulness emerging as a critical predictor of success under weak supervision.
