Author

Rebekka Burkholz

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#machine learning Preprint Oct 2026

RoSA: Rotational Sparse Adaptation for Memory-Efficient Fine-Tuning

Parameter-efficient fine-tuning (PEFT) reduces the cost of adapting foundation models by focusing training on a small parameter subset. Complementary to this idea, we introduce RoSA (Rotational Sparse Adaptation), which narrows adaptation to a subset of layers at a time. RoSA freezes lower layers close to the input thr...

Muhammad Azeem Lodhi, Chao Zhou, Rebekka Burkholz · 0 citations

#machine learning Preprint Oct 2026

Mind the Drift: Diagonal Linear Networks Under Large Learning Rates

Large learning rates can qualitatively change the trajectory of neural network training, often pushing optimization into regimes far from classical gradient-flow behavior. The Edge of Stability (EoS) offers a valuable lens on the dynamics such learning rates induce. We study corresponding dynamics in diagonal linear ne...

Aniket Sanyal, Tom Jacobs, Rebekka Burkholz · 0 citations