584 citations · 668 across the 8 of their papers we have counts for
8 papers
Answering Ambiguous Questions via Iterative Prompting
Weiwei Sun, Hengyi Cai, Hongshen Chen +4
In open-domain question answering, due to the ambiguity of questions, multiple plausible answers may exist. To provide feasible answers to an ambiguous question, one approach is to…
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…
Posterior-GAN: Towards Informative and Coherent Response Generation with Posterior Generative Adversarial Network
Shaoxiong Feng, Hongshen Chen, Kan Li +1
Neural conversational models learn to generate responses by taking into account the dialog history. These models are typically optimized over the query-response pairs with a maximu…
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…
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…
Explicit State Tracking with Semi-Supervision for Neural Dialogue Generation
Xisen Jin, Wenqiang Lei, Zhaochun Ren +4
The task of dialogue generation aims to automatically provide responses given previous utterances. Tracking dialogue states is an important ingredient in dialogue generation for es…
A Survey on Dialogue Systems: Recent Advances and New Frontiers
Hongshen Chen, Xiaorui Liu, Dawei Yin +1
Dialogue systems have attracted more and more attention. Recent advances on dialogue systems are overwhelmingly contributed by deep learning techniques, which have been employed to…