Papers by Amine M. Aboussalah

1 papers
GeLoRA: Geometric Adaptive Ranks For Efficient LoRA Fine-tuning (2025.findings-emnlp)

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Challenge: Existing adaptive LoRA methods lack a theoretical foundation to guide this trade-off optimally.
Approach: They propose a principled approach that estimates the intrinsic dimensionality of hidden data representations to adaptively select LoRA ranks.
Outcome: Experiments show that GeLoRA outperforms adaptive LoRA methods by up to +1.0% .

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