2024
Unlocking Parameter-Efficient Fine-Tuning for Low-Resource Language Translation
NAACL 2024findings
Parameter-efficient fine-tuning (PEFT) methods are increasingly vital in adapting large-scale pre-trained language models for diverse tasks, offering a balance between adaptability and computational efficiency. They are important in Low-Resource Language (LRL) Neural Machine Translation (NMT) to enh…