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A unified framework reveals critical insights into the effectiveness of U-Net, Transformer, and SAM architectures in medical image segmentation, addressing both accuracy and efficiency challenges.
Achieving superior safety alignment with LLMs using only 100 harmful samples, SafeSteer drastically cuts alignment costs while maintaining model performance.
