Afshin Bozorgpour

MaLViL slashes memory usage by 83x while achieving state-of-the-art accuracy in medical image segmentation.

Achieve state-of-the-art medical image segmentation accuracy with a linear-time transformer decoder that overcomes the limitations of standard linear attention by subtracting complementary attention paths to amplify relevant context.