28 citations · 88 across the 11 of their papers we have counts for
16 papers
Data Rejuvenation: Exploiting Inactive Training Examples for Neural Machine Translation
Wenxiang Jiao, Xing Wang, Shilin He +3
Large-scale training datasets lie at the core of the recent success of neural machine translation (NMT) models. However, the complex patterns and potential noises in the large-scal…
How Does Selective Mechanism Improve Self-Attention Networks?
Xinwei Geng, Longyue Wang, Xing Wang +3
Self-attention networks (SANs) with selective mechanism has produced substantial improvements in various NLP tasks by concentrating on a subset of input words. However, the underly…
Assessing the Bilingual Knowledge Learned by Neural Machine Translation Models
Shilin He, Xing Wang, Shuming Shi +2
Machine translation (MT) systems translate text between different languages by automatically learning in-depth knowledge of bilingual lexicons, grammar and semantics from the train…
Neuron Interaction Based Representation Composition for Neural Machine Translation
Jian Li, Xing Wang, Baosong Yang +3
Recent NLP studies reveal that substantial linguistic information can be attributed to single neurons, i.e., individual dimensions of the representation vectors. We hypothesize tha…
Towards Understanding Neural Machine Translation with Word Importance
Shilin He, Zhaopeng Tu, Xing Wang +3
Although neural machine translation (NMT) has advanced the state-of-the-art on various language pairs, the interpretability of NMT remains unsatisfactory. In this work, we propose…
Multi-Granularity Self-Attention for Neural Machine Translation
Jie Hao, Xing Wang, Shuming Shi +2
Current state-of-the-art neural machine translation (NMT) uses a deep multi-head self-attention network with no explicit phrase information. However, prior work on statistical mach…