Integrates dynamic codebook frequency statistics into a transformer attention module. Fuses semantic image features with latent representations of quantization ...
Abstract: This article proposes a neural network (NN)-based calibration framework via quantization code reconstruction to address the critical limitation of multidimensional NNs (MDNNs) in ...
Vector Post-Training Quantization (VPTQ) is a novel Post-Training Quantization method that leverages Vector Quantization to high accuracy on LLMs at an extremely low bit-width (<2-bit). VPTQ can ...
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