41 citations · 146 across the 20 of their papers we have counts for
33 papers · 1 filter
Glancing Future for Simultaneous Machine Translation
Shoutao Guo, Shaolei Zhang, Yang Feng
Simultaneous machine translation (SiMT) outputs translation while reading the source sentence. Unlike conventional sequence-to-sequence (seq2seq) training, existing SiMT methods ad…
Improving Zero-Shot Multilingual Translation with Universal Representations and Cross-Mappings
Shuhao Gu, Yang Feng
The many-to-many multilingual neural machine translation can translate between language pairs unseen during training, i.e., zero-shot translation. Improving zero-shot translation r…
Guiding Teacher Forcing with Seer Forcing for Neural Machine Translation
Yang Feng, Shuhao Gu, Dengji Guo +2
Although teacher forcing has become the main training paradigm for neural machine translation, it usually makes predictions only conditioned on past information, and hence lacks gl…
GTM: A Generative Triple-Wise Model for Conversational Question Generation
Lei Shen, Fandong Meng, Jinchao Zhang +2
Generating some appealing questions in open-domain conversations is an effective way to improve human-machine interactions and lead the topic to a broader or deeper direction. To a…
Addressing Inquiries about History: An Efficient and Practical Framework for Evaluating Open-domain Chatbot Consistency
Zekang Li, Jinchao Zhang, Zhengcong Fei +2
A good open-domain chatbot should avoid presenting contradictory responses about facts or opinions in a conversational session, known as its consistency capacity. However, evaluati…
Conversations Are Not Flat: Modeling the Dynamic Information Flow across Dialogue Utterances
Zekang Li, Jinchao Zhang, Zhengcong Fei +2
Nowadays, open-domain dialogue models can generate acceptable responses according to the historical context based on the large-scale pre-trained language models. However, they gene…