7 citations · 15 across the 5 of their papers we have counts for
5 papers
Improving Neural Machine Translation by Bidirectional Training
Liang Ding, Di Wu, Dacheng Tao
We present a simple and effective pretraining strategy -- bidirectional training (BiT) for neural machine translation. Specifically, we bidirectionally update the model parameters…
The USYD-JD Speech Translation System for IWSLT 2021
Liang Ding, Di Wu, Dacheng Tao
This paper describes the University of Sydney& JD's joint submission of the IWSLT 2021 low resource speech translation task. We participated in the Swahili-English direction and go…
Bridging the Gap Between Clean Data Training and Real-World Inference for Spoken Language Understanding
Di Wu, Yiren Chen, Liang Ding +1
Spoken language understanding (SLU) system usually consists of various pipeline components, where each component heavily relies on the results of its upstream ones. For example, In…
Context-Aware Cross-Attention for Non-Autoregressive Translation
Liang Ding, Longyue Wang, Di Wu +2
Non-autoregressive translation (NAT) significantly accelerates the inference process by predicting the entire target sequence. However, due to the lack of target dependency modelli…
SlotRefine: A Fast Non-Autoregressive Model for Joint Intent Detection and Slot Filling
Di Wu, Liang Ding, Fan Lu +1
Slot filling and intent detection are two main tasks in spoken language understanding (SLU) system. In this paper, we propose a novel non-autoregressive model named SlotRefine for…