3 citations · 6 across the 5 of their papers we have counts for
5 papers
Identifying Untrustworthy Samples: Data Filtering for Open-domain Dialogues with Bayesian Optimization
Lei Shen, Haolan Zhan, Xin Shen +3
Being able to reply with a related, fluent, and informative response is an indispensable requirement for building high-quality conversational agents. In order to generate better re…
Probing Product Description Generation via Posterior Distillation
Haolan Zhan, Hainan Zhang, Hongshen Chen +5
In product description generation (PDG), the user-cared aspect is critical for the recommendation system, which can not only improve user's experiences but also obtain more clicks.…
Learning to Select Context in a Hierarchical and Global Perspective for Open-domain Dialogue Generation
Lei Shen, Haolan Zhan, Xin Shen +1
Open-domain multi-turn conversations mainly have three features, which are hierarchical semantic structure, redundant information, and long-term dependency. Grounded on these, sele…
User-Inspired Posterior Network for Recommendation Reason Generation
Haolan Zhan, Hainan Zhang, Hongshen Chen +4
Recommendation reason generation, aiming at showing the selling points of products for customers, plays a vital role in attracting customers' attention as well as improving user ex…
Modeling Semantic Relationship in Multi-turn Conversations with Hierarchical Latent Variables
Lei Shen, Yang Feng, Haolan Zhan
Multi-turn conversations consist of complex semantic structures, and it is still a challenge to generate coherent and diverse responses given previous utterances. It's practical th…