6 citations · 10 across the 4 of their papers we have counts for
4 papers
Better Pre-Training by Reducing Representation Confusion
Haojie Zhang, Mingfei Liang, Ruobing Xie +3
In this work, we revisit the Transformer-based pre-trained language models and identify two different types of information confusion in position encoding and model representations,…
Multi-granularity Item-based Contrastive Recommendation
Ruobing Xie, Zhijie Qiu, Bo Zhang +1
Contrastive learning (CL) has shown its power in recommendation. However, most CL-based recommendation models build their CL tasks merely focusing on the user's aspects, ignoring t…
Improving Accuracy and Diversity in Matching of Recommendation with Diversified Preference Network
Ruobing Xie, Qi Liu, Shukai Liu +4
Recently, real-world recommendation systems need to deal with millions of candidates. It is extremely challenging to conduct sophisticated end-to-end algorithms on the entire corpu…
Beyond Clicks: Modeling Multi-Relational Item Graph for Session-Based Target Behavior Prediction
Wen Wang, Wei Zhang, Shukai Liu +4
Session-based target behavior prediction aims to predict the next item to be interacted with specific behavior types (e.g., clicking). Although existing methods for session-based b…