3 papers
cs.CL2022
One Reference Is Not Enough: Diverse Distillation with Reference Selection for Non-Autoregressive Translation
Chenze Shao, Xuanfu Wu, Yang Feng
Non-autoregressive neural machine translation (NAT) suffers from the multi-modality problem: the source sentence may have multiple correct translations, but the loss function is ca…
cs.CL2021
Mixup Decoding for Diverse Machine Translation
Jicheng Li, Pengzhi Gao, Xuanfu Wu +4
Diverse machine translation aims at generating various target language translations for a given source language sentence. Leveraging the linear relationship in the sentence latent…
cs.CL2020
Generating Diverse Translation from Model Distribution with Dropout
Xuanfu Wu, Yang Feng, Chenze Shao
Despite the improvement of translation quality, neural machine translation (NMT) often suffers from the lack of diversity in its generation. In this paper, we propose to generate d…