Generating Diverse Translation with Perturbed kNN-MT

arXiv:2402.09344v1 Announce Type: new
Abstract: Generating multiple translation candidates would enable users to choose the one that satisfies their needs. Although there has been work on diversified generation, there exists room for improving the diversity mainly because the previous methods do not address the overcorrection problem -- the model underestimates a prediction that is largely different from the training data, even if that prediction is likely. This paper proposes methods that generate more diverse translations by introducing perturbed k-nearest neighbor …

abstract arxiv cs.cl diverse diversity knn multiple prediction room translation type work