93 citations · 132 across the 10 of their papers we have counts for
5 papers · 1 filter
Group-wise Contrastive Learning for Neural Dialogue Generation
Hengyi Cai, Hongshen Chen, Yonghao Song +4
Neural dialogue response generation has gained much popularity in recent years. Maximum Likelihood Estimation (MLE) objective is widely adopted in existing dialogue model learning.…
Data Manipulation: Towards Effective Instance Learning for Neural Dialogue Generation via Learning to Augment and Reweight
Hengyi Cai, Hongshen Chen, Yonghao Song +3
Current state-of-the-art neural dialogue models learn from human conversations following the data-driven paradigm. As such, a reliable training corpus is the crux of building a rob…
Learning from Easy to Complex: Adaptive Multi-curricula Learning for Neural Dialogue Generation
Hengyi Cai, Hongshen Chen, Cheng Zhang +5
Current state-of-the-art neural dialogue systems are mainly data-driven and are trained on human-generated responses. However, due to the subjectivity and open-ended nature of huma…
Adaptive Parameterization for Neural Dialogue Generation
Hengyi Cai, Hongshen Chen, Cheng Zhang +3
Neural conversation systems generate responses based on the sequence-to-sequence (SEQ2SEQ) paradigm. Typically, the model is equipped with a single set of learned parameters to gen…
KNPTC: Knowledge and Neural Machine Translation Powered Chinese Pinyin Typo Correction
Hengyi Cai, Xingguang Ji, Yonghao Song +4
Chinese pinyin input methods are very important for Chinese language processing. Actually, users may make typos inevitably when they input pinyin. Moreover, pinyin typo correction…