Author

Tuomas P. Oikarinen

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Preprint Jul 2026

Data-Efficient Adaptation of LLMs via Attention Head Reweighting

Experiments on diverse open-source text classification datasets show that AHR can outperform standard baselines like LoRA when learning from limited samples, despite having 200-1000x fewer trainable parameters, as the authors' AHR only modifies ~0.0001% of the model's parameters.

Tuomas P. Oikarinen, Zixiao Chen, Charlotte Siska et al. · 0 citations