Author

Yang Gao

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#artificial intelligence Preprint Sep 2026

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. · 0 citations

#artificial intelligence Apr 2026

Understanding and Enforcing Weight Disentanglement in Task Arithmetic

This paper first proves that TFS is a sufficient condition for weight disentanglement, and finds that TFS also gives rise to an observable geometric consequence: weight vector orthogonality, which positions TFS as the common cause for both the desired functional outcome and a measurable geometric property.

Shan Liu, Yuehan Yin, Lei Wang et al. · arXiv.org · 3 citations