AIBullisharXiv – CS AI · 8h ago7/10
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LiftQuant: Continuous Bit-Width LLM via Dimensional Lifting and Projection
Researchers introduce LiftQuant, a novel quantization framework enabling continuous bit-width control for Large Language Models by lifting weights into higher-dimensional space and projecting them back via 1-bit lattices. The approach bridges the gap between rigid integer bit-widths and real-world deployment constraints, allowing a 70B LLM to compress to 2.4 bits while maintaining hardware efficiency and outperforming existing 2-bit quantization methods.