Author

Ze-Yu Gan

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#artificial intelligence Preprint Sep 2026

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

Matrix optimizers have emerged as a promising direction, with Muon standing out as a prominent design. Revisiting Muon through its full-Gram representation, we observe that it jointly processes marginal-scale and interaction information. This opens an alternative way to organize geometric information hierarchically, mo...

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

#artificial intelligence Preprint Sep 2026

Harness Evolution as Learning: Approximation, Generalization, and Optimization Limits of Self-Improving Personal Agents

As the capabilities of large language models (LLMs) continue to advance, increasing attention is turning to how to translate their abilities into useful behavior. Personal agents bring this question into everyday settings, where models are expected to serve individual users and continually adapt to their preferences. W...

Ze-Yu Gan, Zi-Xuan Gong, Yong Liu · 0 citations

#artificial intelligence Jun 2026

Statistical Priors for Implicit Preferences: Decoupling Skill Selection as a Local Harness in Personal Agents

A novel architecture that strictly decouples statistical preference learning from semantic intent parsing is explored, which achieves the lowest cumulative regret and highest test accuracy, significantly outperforming traditional memory-augmented agents.

Ze-Yu Gan, Huayi Tang, Yong Liu · arXiv.org · 2 citations