Preprint Open access
G$^2$PTQ: Improving LLM Post-Training Quantization with Generalized Gradient Compensation
Post-training quantization (PTQ) is a practical approach to reducing the memory and computational footprint of large language models (LLMs) without retraining. GPTQ-based methods have become the de facto standard, yet they suffer from two complementary limitations. Methods with local, layer-wise objectives lack global …