Xiangyi Chu

STLA: Spatiotemporal Lookahead Alignment for Post-Training Quantization

Adaptive rounding techniques in Post-Training Quantization (PTQ) enable the efficient deployment of Large Language Models (LLMs) with low resource and data dependencies. While learning-based rounding methods are accurate yet costly, compensation-based approaches offer a highly efficient alternative.…