QUASAR: How Saliency-Weighted Reconstruction Closes the Loss Floor Gap in LLM Quantization-Aware Training
Researchers introduced QUASAR, a method that lowers the loss floor gap in quantization-aware training (QAT) for large language models by adding a saliency-weighted reconstruction step. The approach reduces held-out KL di…