55 citations · 375 across the 77 of their papers we have counts for
11 papers · 1 filter
Acquiring Knowledge from Pre-trained Model to Neural Machine Translation
Rongxiang Weng, Heng Yu, Shujian Huang +2
Pre-training and fine-tuning have achieved great success in the natural language process field. The standard paradigm of exploiting them includes two steps: first, pre-training a m…
Non-autoregressive Transformer by Position Learning
Yu Bao, Hao Zhou, Jiangtao Feng +4
Non-autoregressive models are promising on various text generation tasks. Previous work hardly considers to explicitly model the positions of generated words. However, position mod…
Generating Diverse Translation by Manipulating Multi-Head Attention
Zewei Sun, Shujian Huang, Hao-Ran Wei +2
Transformer model has been widely used on machine translation tasks and obtained state-of-the-art results. In this paper, we report an interesting phenomenon in its encoder-decoder…
Multi-Perspective Inferrer: Reasoning Sentences Relationship from Holistic Perspective
Zhen Cheng, Zaixiang Zheng, Xin-Yu Dai +2
Natural Language Inference (NLI) aims to determine the logic relationships (i.e., entailment, neutral and contradiction) between a pair of premise and hypothesis. Recently, the ali…
A Reinforced Generation of Adversarial Examples for Neural Machine Translation
Wei Zou, Shujian Huang, Jun Xie +2
Neural machine translation systems tend to fail on less decent inputs despite its significant efficacy, which may significantly harm the credibility of this systems-fathoming how a…
Fine-grained Knowledge Fusion for Sequence Labeling Domain Adaptation
Huiyun Yang, Shujian Huang, Xinyu Dai +1
In sequence labeling, previous domain adaptation methods focus on the adaptation from the source domain to the entire target domain without considering the diversity of individual…
Improving Neural Machine Translation with Pre-trained Representation
Rongxiang Weng, Heng Yu, Shujian Huang +2
Monolingual data has been demonstrated to be helpful in improving the translation quality of neural machine translation (NMT). The current methods stay at the usage of word-level k…
Correct-and-Memorize: Learning to Translate from Interactive Revisions
Rongxiang Weng, Hao Zhou, Shujian Huang +3
State-of-the-art machine translation models are still not on par with human translators. Previous work takes human interactions into the neural machine translation process to obtai…
Learning Representation Mapping for Relation Detection in Knowledge Base Question Answering
Peng Wu, Shujian Huang, Rongxiang Weng +4
Relation detection is a core step in many natural language process applications including knowledge base question answering. Previous efforts show that single-fact questions could…
Generating Sentences from Disentangled Syntactic and Semantic Spaces
Yu Bao, Hao Zhou, Shujian Huang +5
Variational auto-encoders (VAEs) are widely used in natural language generation due to the regularization of the latent space. However, generating sentences from the continuous lat…
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…