372 citations · 862 across the 46 of their papers we have counts for
10 papers · 1 filter
Importance-Aware Learning for Neural Headline Editing
Qingyang Wu, Lei Li, Hao Zhou +2
Many social media news writers are not professionally trained. Therefore, social media platforms have to hire professional editors to adjust amateur headlines to attract more reade…
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…
Kernelized Bayesian Softmax for Text Generation
Ning Miao, Hao Zhou, Chengqi Zhao +2
Neural models for text generation require a softmax layer with proper token embeddings during the decoding phase. Most existing approaches adopt single point embedding for each tok…
Rethinking Text Attribute Transfer: A Lexical Analysis
Yao Fu, Hao Zhou, Jiaze Chen +1
Text attribute transfer is modifying certain linguistic attributes (e.g. sentiment, style, authorship, etc.) of a sentence and transforming them from one type to another. In this p…
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…
Towards Making the Most of BERT in Neural Machine Translation
Jiacheng Yang, Mingxuan Wang, Hao Zhou +4
GPT-2 and BERT demonstrate the effectiveness of using pre-trained language models (LMs) on various natural language processing tasks. However, LM fine-tuning often suffers from cat…