Author

Tian-Yu He

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#machine learning Preprint Sep 2026

Looped Transformers as Optimizers

Looped Transformers provide a parameter-efficient approach to depth scaling by repeatedly applying shared Transformer blocks. Recent reasoning models have likewise highlighted the value of scaling test-time computation through longer computation trajectories. However, the principles for designing effective loop transit...

Yu-Long Huang, Chen Jiang, Zhan-Peng Zhou et al. · 0 citations

#machine learning Preprint Sep 2026

HyperTransfer: Understanding the Equivalence between Base Optimizer and Hyperball

HyperTransfer is proposed, which constructs a Hyperball optimizer that reproduces the dynamics of a target Base Optimizer using only its initialization and learning-rate schedule, without running the target optimizer itself, to extend the framework to non-scale-invariant networks.

Jinghui Yuan, Hong-Tao Zhang, Jade Zou et al. · 0 citations