1 citations · 3 across the 5 of their papers we have counts for
5 papers
Enabling Explainable Recommendation in E-commerce with LLM-powered Product Knowledge Graph
Menghan Wang, Yuchen Guo, Duanfeng Zhang +4
How to leverage large language model's superior capability in e-commerce recommendation has been a hot topic. In this paper, we propose LLM-PKG, an efficient approach that distills…
Causal Inference Based Single-branch Ensemble Trees For Uplift Modeling
Fanglan Zheng, Menghan Wang, Kun Li +2
In this manuscript (ms), we propose causal inference based single-branch ensemble trees for uplift modeling, namely CIET. Different from standard classification methods for predict…
MP2: A Momentum Contrast Approach for Recommendation with Pointwise and Pairwise Learning
Menghan Wang, Yuchen Guo, Zhenqi Zhao +4
Binary pointwise labels (aka implicit feedback) are heavily leveraged by deep learning based recommendation algorithms nowadays. In this paper we discuss the limited expressiveness…
Learning to Hash Naturally Sorts
Jiaguo Yu, Yuming Shen, Menghan Wang +2
Learning to hash pictures a list-wise sorting problem. Its testing metrics, e.g., mean-average precision, count on a sorted candidate list ordered by pair-wise code similarity. How…
You Never Cluster Alone
Yuming Shen, Ziyi Shen, Menghan Wang +3
Recent advances in self-supervised learning with instance-level contrastive objectives facilitate unsupervised clustering. However, a standalone datum is not perceiving the context…