5 citations · 7 across the 3 of their papers we have counts for
4 papers
Curriculum Learning for Dense Retrieval Distillation
Hansi Zeng, Hamed Zamani, Vishwa Vinay
Recent work has shown that more effective dense retrieval models can be obtained by distilling ranking knowledge from an existing base re-ranking model. In this paper, we propose a…
Understanding the Effectiveness of Reviews in E-commerce Top-N Recommendation
Zhichao Xu, Hansi Zeng, Qingyao Ai
Modern E-commerce websites contain heterogeneous sources of information, such as numerical ratings, textual reviews and images. These information can be utilized to assist recommen…
A Zero Attentive Relevance Matching Networkfor Review Modeling in Recommendation System
Hansi Zeng, Zhichao Xu, Qingyao Ai
User and item reviews are valuable for the construction of recommender systems. In general, existing review-based methods for recommendation can be broadly categorized into two gro…
A Hierarchical Self-attentive Convolution Network for Review Modeling in Recommendation Systems
Hansi Zeng, Qingyao Ai
Using reviews to learn user and item representations is important for recommender system. Current review based methods can be divided into two categories: (1) the Convolution Neura…