QUASAR: How Saliency-Weighted Reconstruction Closes the Loss Floor Gap in LLM Quantization-Aware Training

QUASAR: How Saliency-Weighted Reconstruction Closes the Loss Floor Gap in LLM Quantization-Aware Training Quantization is one of the most practical tools in the LLM deployment toolkit. Shrinking a model from 16-bit to 4-bit or even 2-bit precision can cut memory requirements by 4–8×, making it p...

Source: [Dev.to](https://dev.to/prabhakar_chaudhary_7afe4/quasar-how-saliency-weighted-reconstruction-closes-the-loss-floor-gap-in-llm-quantization-aware-5akb)