Fine-tuning pre-trained Neural Machine Translation (NMT) models is the dominant approach for adapting to new languages and domains.
this highlights a key strength of the approach: by varying adapter capacity it is possi-ble to adapt the same model to domains of varying complexity and amounts of data.