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HGA-Quant: Heterogeneity-Aware Quantization for AutoRegressive Visual Generation Models
Recently, AutoRegressive Visual Generation (ARVG) models have emerged as a competitive paradigm for high-quality image synthesis. However, their substantial computational and memory demands make them difficult to deploy on resource-constrained edge devices. Post-Training Quantization (PTQ) provides
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