Author

Jiaye Teng

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#machine learning Preprint Oct 2026

A Fine-Grained Analysis of the LoRA Fine-Tuning Landscape with Implications for Data Selection

Low-Rank Adaptation (LoRA) has become a standard approach for parameter-efficient fine-tuning, yet a fundamental practical question remains unresolved: how should the adapter rank be chosen? An overly small rank may lead to a poorly conditioned optimization landscape, whereas an unnecessarily large rank sacrifices the...

Bo-Wen Zhang, Chang-Rui Fang, Xin-Song Ma et al. · 0 citations

#artificial intelligence Preprint Sep 2026

Normalize-Then-Precondition: A Hierarchical Approach to Marginal Scale and Interaction Geometry for LLM Training

NormPre is developed with NormPre-G and NormPre-L adopting global and localized spectral preconditioning, grounded in spectral-norm steepest descent and a regularized formulation followed by leading mode selection, respectively, to enable large-scale training.

Zi-Xuan Gong, Ze-Yu Gan, Jia-Ye Teng et al. · 0 citations

Jul 2026

Hyperball May Not Be a Free Lunch

An angular effective learning rate is derived that accounts for the parameter-update angle, parameter norm, and update norm, and shows that the conventional norm-based measure is a special case under parameter-update orthogonality.

Yihao Xiao, Jialong Sun, Zitian Gao et al. · arXiv.org · 3 citations