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How to Parameterize Asymmetric Quantization Ranges for Quantization-Aware Training
This paper investigates three different parameterizations of asymmetric uniform quantization for quantization-aware training: (1) scale and offset, (2) minimum and maximum, and (3) beta and gamma.
Oh! We Freeze: Improving Quantized Knowledge Distillation via Signal Propagation Analysis for Large Language Models
Large generative models such as large language models (LLMs) and diffusion models have revolutionized the fields of NLP and computer vision respectively.
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