A Single Model Ensemble Framework for Neural Machine Translation using Pivot Translation

ArXi:2502.01182v2 Announce Type: replace Despite the recent remarkable advances in neural machine translation, translation quality for low-resource language pairs remains subpar. Ensembling multiple systems is a widely adopted technique to enhance performance, often accomplished by combining probability distributions. However, previous approaches face the challenge of high computational costs for