RGSQ: Riemannian Geometry-Sensitive Quantization for Large Vision-Language Models
Riemannian Geometry-Sensitive Quantization (RGSQ), which formulates quantization as a reconstruction problem under a unified Fisher-Riemannian metric, enabling standard unimodal PTQ methods to evaluate multimodal quantization error under their original assumptions.
Zhi-Ping Wu, Dong-Dong Ren, Yang Zhou et al.
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