A mixed-precision post-training quantization method for SAM that allocates bit-widths via an integer quadratic program guided by KL-divergence importance scores and a cross-layer synergy heuristic.
Low-bit quantization of neural networks for efficient inference
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Mix-QSAM: Mixed-Precision Quantization of the Segment Anything Model
A mixed-precision post-training quantization method for SAM that allocates bit-widths via an integer quadratic program guided by KL-divergence importance scores and a cross-layer synergy heuristic.