Ahmed Agiza

MTLoRA: Low-Rank Adaptation Approach for Efficient Multi-Task Learning

Adapting models pre-trained on large-scale datasets to a variety of downstream tasks is a common strategy in deep learning. Consequently parameter-efficient fine-tuning methods have emerged as a promising way to adapt pre-trained models to different tasks while training only a minimal number of para…