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QUASAR: Lowering the Loss Floor of Quantization-Aware Training with Loss-Aware Reconstruction
As large language model inference shifts toward lower precision, post-training quantization (PTQ) becomes increasingly brittle, making quantization-aware training (QAT) essential for preserving model quality. However, QAT has a structural mismatch: gradient updates are applied to latent full-precisi
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