Author

Xingyu Dang

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#machine learning Preprint Oct 2026

The Best Optimizer Depends on Batch Size

A plethora of new adaptive optimizers are designed to efficiently estimate and use minibatch gradient statistics to shape parameter updates, but they are typically benchmarked at a single batch size. Hyperparameter scaling rules promise to preserve performance as batch size and gradient noise change, suggesting that th...

Xing-Yu Dang, Kai-Yue Wen, Sadhika Malladi · 0 citations

Preprint Aug 2026

Learning What to Remember: Test-Time Training via Context Distillation

This work proposes TTCD, a TTT framework that introduces a self-supervised objective for allocating limited memory capacity for future use, and focuses on an in-place variant: In-Place TTCD, which uses the existing MLP parameters as the fast weights.

Zi-Xuan Wang, Xingyu Dang, Ruiming Zhu et al. · 0 citations