most citedReCoSa: Detecting the Relevant Contexts with Self-Attention for Multi-turn Dialogue Generation

9 citations · 10 across the 7 of their papers we have counts for

collaborators

7 papers

cs.CL2021

Adaptive Bridge between Training and Inference for Dialogue

Haoran Xu, Hainan Zhang, Yanyan Zou +3

Although exposure bias has been widely studied in some NLP tasks, it faces its unique challenges in dialogue response generation, the representative one-to-various generation scena…

cs.CL2021

FCM: A Fine-grained Comparison Model for Multi-turn Dialogue Reasoning

Xu Wang, Hainan Zhang, Shuai Zhao +5

Despite the success of neural dialogue systems in achieving high performance on the leader-board, they cannot meet users' requirements in practice, due to their poor reasoning skil…

cs.CL2021

Topic-Aware Contrastive Learning for Abstractive Dialogue Summarization

Junpeng Liu, Yanyan Zou, Hainan Zhang +4

Unlike well-structured text, such as news reports and encyclopedia articles, dialogue content often comes from two or more interlocutors, exchanging information with each other. In…

cs.CL20211 cited

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.…

cs.IR2021

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…

cs.CL2019

Neural or Statistical: An Empirical Study on Language Models for Chinese Input Recommendation on Mobile

Hainan Zhang, Yanyan Lan, Jiafeng Guo +2

Chinese input recommendation plays an important role in alleviating human cost in typing Chinese words, especially in the scenario of mobile applications. The fundamental problem i…