activity
20182022
most citedDeep Reinforcement Learning for Page-wise Recommendations

430 citations · 981 across the 16 of their papers we have counts for

collaborators
Showing 2021Show all

8 papers · 1 filter

cs.IR2021

Intelligent Online Selling Point Extraction for E-Commerce Recommendation

Xiaojie Guo, Shugen Wang, Hanqing Zhao +8

In the past decade, automatic product description generation for e-commerce have witnessed significant advancement. As the services provided by e-commerce platforms become diverse,…

cs.CL2021★ 1 cited

Automatic Product Copywriting for E-Commerce

Xueying Zhang, Yanyan Zou, Hainan Zhang +10

Product copywriting is a critical component of e-commerce recommendation platforms. It aims to attract users' interest and improve user experience by highlighting product character…

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.IR2021★ 1 cited

Improving Sequential Recommendation Consistency with Self-Supervised Imitation

Xu Yuan, Hongshen Chen, Yonghao Song +4

Most sequential recommendation models capture the features of consecutive items in a user-item interaction history. Though effective, their representation expressiveness is still h…

cs.CL2021★ 1 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…