The proposed SharpRec, Sharpness-aware Model Merging with Salience Recovery for LLM-based CDSR, a framework designed to lift the performance upper bound of merged models, outperforms state-of-the-art baselines.
Hu-Wei Ji, Jia-Jie Su, Yu-Yuan Li et al.· Proceedings of the 32nd ACM...· 1 citation
This paper introduces universal fairness, a clinically grounded definition that reframes fairness as maximizing subgroup-aware diagnostic performance under attribute-conditioned health disparities, and proposes MAPPE, a training-free minimax prompt optimization framework that theoretically promotes universal fairness.
Jiaming Zhang, Yuyuan Li, Xiaohua Feng et al.· Proceedings of the 32nd ACM...· 0 citations
Large Language Models (LLMs) have shown strong potential in medical applications such as question answering and clinical prediction. % Despite their growing adoption, fairness in LLMs for medicine remains underexplored, largely due to the mismatch between conventional fairness constraints and the clinically meaningful...
Jiaming Zhang, Yuyuan Li, Xiaohua Feng et al.· Proceedings of the 32nd ACM...· 0 citations
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