325 citations · 1.4k across the 89 of their papers we have counts for
16 papers · 1 filter
Go From the General to the Particular: Multi-Domain Translation with Domain Transformation Networks
Yong Wang, Longyue Wang, Shuming Shi +2
The key challenge of multi-domain translation lies in simultaneously encoding both the general knowledge shared across domains and the particular knowledge distinctive to each doma…
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…
EmpDG: Multiresolution Interactive Empathetic Dialogue Generation
Qintong Li, Hongshen Chen, Zhaochun Ren +3
A humanized dialogue system is expected to generate empathetic replies, which should be sensitive to the users' expressed emotion. The task of empathetic dialogue generation is pro…
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…
Towards Better Modeling Hierarchical Structure for Self-Attention with Ordered Neurons
Jie Hao, Xing Wang, Shuming Shi +2
Recent studies have shown that a hybrid of self-attention networks (SANs) and recurrent neural networks (RNNs) outperforms both individual architectures, while not much is known ab…
Self-Attention with Structural Position Representations
Xing Wang, Zhaopeng Tu, Longyue Wang +1
Although self-attention networks (SANs) have advanced the state-of-the-art on various NLP tasks, one criticism of SANs is their ability of encoding positions of input words (Shaw e…
One Model to Learn Both: Zero Pronoun Prediction and Translation
Longyue Wang, Zhaopeng Tu, Xing Wang +1
Zero pronouns (ZPs) are frequently omitted in pro-drop languages, but should be recalled in non-pro-drop languages. This discourse phenomenon poses a significant challenge for mach…
Exploiting Sentential Context for Neural Machine Translation
Xing Wang, Zhaopeng Tu, Longyue Wang +1
In this work, we present novel approaches to exploit sentential context for neural machine translation (NMT). Specifically, we first show that a shallow sentential context extracte…
Assessing the Ability of Self-Attention Networks to Learn Word Order
Baosong Yang, Longyue Wang, Derek F. Wong +2
Self-attention networks (SAN) have attracted a lot of interests due to their high parallelization and strong performance on a variety of NLP tasks, e.g. machine translation. Due to…
Convolutional Self-Attention Networks
Baosong Yang, Longyue Wang, Derek Wong +2
Self-attention networks (SANs) have drawn increasing interest due to their high parallelization in computation and flexibility in modeling dependencies. SANs can be further enhance…
Information Aggregation for Multi-Head Attention with Routing-by-Agreement
Jian Li, Baosong Yang, Zi-Yi Dou +3
Multi-head attention is appealing for its ability to jointly extract different types of information from multiple representation subspaces. Concerning the information aggregation,…
Modeling Recurrence for Transformer
Jie Hao, Xing Wang, Baosong Yang +3
Recently, the Transformer model that is based solely on attention mechanisms, has advanced the state-of-the-art on various machine translation tasks. However, recent studies reveal…
Dynamic Past and Future for Neural Machine Translation
Zaixiang Zheng, Shujian Huang, Zhaopeng Tu +2
Previous studies have shown that neural machine translation (NMT) models can benefit from explicitly modeling translated (Past) and untranslated (Future) to groups of translated an…
Dynamic Layer Aggregation for Neural Machine Translation with Routing-by-Agreement
Zi-Yi Dou, Zhaopeng Tu, Xing Wang +3
With the promising progress of deep neural networks, layer aggregation has been used to fuse information across layers in various fields, such as computer vision and machine transl…
Context-Aware Self-Attention Networks
Baosong Yang, Jian Li, Derek Wong +3
Self-attention model have shown its flexibility in parallel computation and the effectiveness on modeling both long- and short-term dependencies. However, it calculates the depende…