Security-Enhanced Seed-Based Weight Quantization for Large Language Models
Seed-Q is a security-enhanced weight compression framework for LLMs. It optimizes storage by assigning representation budgets differently to sensitive weights, leading to better compression and lower energy use. Crucially, it enhances security by making bit-flip attacks more detectable through fault amplification.