9 citations · 10 across the 3 of their papers we have counts for
7 papers
An Architecture for Web 3.0 and the Emergence of Spontaneous Time Order
Hengjin Cai, Tianqi Cai
In this study, we proposed an architecture for Web 3.0, which is based on the hashed interactions among user nodes that can transform bilateral trusts into collective time order, w…
Pre-trained Language Model based Ranking in Baidu Search
Lixin Zou, Shengqiang Zhang, Hengyi Cai +8
As the heart of a search engine, the ranking system plays a crucial role in satisfying users' information demands. More recently, neural rankers fine-tuned from pre-trained languag…
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…